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remove outdated dir openbb_sdk
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hjoaquim
141
openbb_sdk/README.md
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141
openbb_sdk/README.md
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@@ -1,141 +0,0 @@
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# Table of contents
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||||
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||||
- [Table of contents](#table-of-contents)
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- [Pre-requisites](#pre-requisites)
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||||
- [Installation](#installation)
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||||
- [API keys](#api-keys)
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||||
- [1. From local file](#1-from-local-file)
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||||
- [2. From runtime](#2-from-runtime)
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- [3. From OpenBB Hub](#3-from-openbb-hub)
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||||
- [Python Usage](#python-usage)
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- [API Usage](#api-usage)
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- [Docker](#docker)
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- [Development](#development)
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## Pre-requisites
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||||
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To install and use the SDK you need:
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||||
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- A fresh virtual environment
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- Python 3.8 or higher
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- API keys for the APIs you want to use
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|
||||
For development you need:
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|
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- Poetry 1.5.1 or higher
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- ruff 0.0.256
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- mypy 1.4.1
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- black
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||||
|
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## Installation
|
||||
|
||||
To install the SDK in a virtual environment from the repo root run:
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```bash
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pip install ./openbb_sdk
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```
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||||
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||||
This will install the SDK and all its dependencies into the site-packages directory of the virtual environment.
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## API keys
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||||
To use your API keys you need to configure them. Here are the 3 options on how to do it:
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||||
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1. From local file
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2. At runtime
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3. From OpenBB Hub
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|
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### 1. From local file
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||||
|
||||
You can specify the keys in the `~/.openbb_sdk/user_settings.json` file.
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||||
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||||
Create this file using the following template and replace the values with your keys:
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||||
```json
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{
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"credentials": {
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"fmp_api_key": "REPLACE_ME",
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||||
"polygon_api_key": "REPLACE_ME",
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||||
"benzinga_api_key": "REPLACE_ME",
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||||
"fred_api_key": "REPLACE_ME"
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||||
}
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}
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```
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### 2. From runtime
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You can also specify your keys at runtime:
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```python
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from openbb import obb
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obb.user.credentials.fmp_api_key = "REPLACE_ME"
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obb.user.credentials.polygon_api_key = "REPLACE_ME"
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```
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|
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### 3. From OpenBB Hub
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|
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You can also load your the keys from the OpenBB Hub.
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|
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```python
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from openbb import obb
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openbb.account.login(username="REPLACE_ME", password="REPLACE_ME")
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```
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## Python Usage
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Import and basic usage:
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```python
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from openbb import obb
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aapl = obb.stocks.load("AAPL")
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df = aapl.to_dataframe()
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df.head()
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```
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## API Usage
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Launch the API with:
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```bash
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uvicorn openbb_core.api.rest_api:app --host 0.0.0.0 --port 8000 --reload
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```
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Navigate to <http://0.0.0.0:8000/docs> to see the swagger API documentation.
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Authorize with the developer credentials: openbb/openbb
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## Docker
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You can use the API through Docker.
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To build the image, from the repo root run:
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```bash
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docker build -f build/docker/api.dockerfile -t openbb-sdk:latest .
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```
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To run this newly-built image:
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```bash
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docker run --rm -p8000:8000 -v ~/.openbb_sdk:/root/.openbb_sdk openbb-sdk:latest
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```
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This will mount the local `~/.openbb_sdk` directory into the Docker container so you can use the API keys from there and it will expose the API on port `8000`.
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## Development
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From the root of the OpenBB Terminal repo, run:
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`poetry install -C ./openbb_sdk`
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When developing a specific extension `cd` into the extension directory and run:
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`pip install -U -e .`
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While we're still developing, it is required to create the static python interface:
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```python
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python -c "import openbb; openbb._rebuild_python_interface()"
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```
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Currently you need to do this before the first launch and every time you install or uninstall a new extension.
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15
openbb_sdk/extensions/README.md
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15
openbb_sdk/extensions/README.md
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@@ -1,15 +0,0 @@
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# Extensions
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All currently supported extensions are listed below.
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| Extension | Description |
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| --- | --- |
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| [Charting](./charting/README.md) | Charting Manager extension for the SDK. |
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| [Crypto](./crypto/README.md) | Access cryptocurrency financial data. |
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| [Economy](./economy/README.md) | Access global macroeconomic data. |
|
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| [Fixed Income](./fixed_income/README.md) | Access central bank decisions, yield curves, government bonds and corporate bonds data. |
|
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| [Forex](./forex/README.md) | Access foreign exchanges, quotes, and forward rates for currency pairs. |
|
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| [News](./news/README.md) | Access news articles. |
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| [Quantitative Analysis](./qa/README.md) | Access to statistical and computational techniques for financial data. |
|
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| [Stocks](./stocks/README.md) | Access historical pricing data, options, sector and industry, and overall due diligence. |
|
||||
| [Technical Analysis](./ta/README.md) | Access tools and techniques for financial market analysis. |
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54
openbb_sdk/extensions/charting/README.md
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54
openbb_sdk/extensions/charting/README.md
vendored
@@ -1,54 +0,0 @@
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# OpenBB Charting extension
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This extension provides a charting library for OpenBB SDK.
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The library includes:
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- a charting infrastructure based on Plotly
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- a set of charting components
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- prebuilt charts for a set of commands that are built-in OpenBB SDK extensions
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## Installation
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To install the extension, run the following command in this folder:
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```bash
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pip install .
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```
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## PyWry dependency on Linux
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The PyWry dependency handles display of interactive charts and tables in a separate window. It is installed automatically with the OpenBB Charting extension.
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||||
When using Linux distributions, the PyWry dependency requires certain dependencies to be installed first.
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||||
- Debian-based / Ubuntu / Mint:
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`sudo apt install libwebkit2gtk-4.0-dev`
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||||
|
||||
- Arch Linux / Manjaro:
|
||||
`sudo pacman -S webkit2gtk`
|
||||
|
||||
- Fedora:
|
||||
`sudo dnf install gtk3-devel webkit2gtk3-devel`
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## Usage
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||||
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To use the extension, run any of the OpenBB SDK endpoints with the `chart` argument set to `True`.
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||||
Here's an example how it would look like in a python interface:
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```python
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from openbb import obb
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||||
stock_data = obb.stocks.load(symbol="TSLA", chart=True)
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||||
```
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|
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This results in a `OBBject` object containing a `chart` attribute, which contains Plotly JSON data.
|
||||
|
||||
In order to display the chart, you need to call the `show()` method:
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```python
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stock_data.show()
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```
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> Note: The `show()` method currently works either in a Jupyter Notebook or in a standalone python script with a PyWry based backend properly initialized.
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@@ -1,6 +0,0 @@
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# flake8: noqa: F401
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from openbb_charting.core.backend import (
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||||
create_backend,
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get_backend,
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)
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||||
from openbb_charting.core.to_chart import to_chart
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||||
@@ -1,46 +0,0 @@
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||||
from inspect import getmembers, isfunction
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||||
from typing import List
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from openbb_charting import charting_router
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||||
from openbb_core.app.router import RouterLoader
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||||
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||||
# refers to the root of the repo, not the root of the extension
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# this script should be run from the root of the repo
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CHARTING_ROUTER = "openbb_sdk/extensions/charting/openbb_charting/charting_router.py"
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def get_routes() -> List[str]:
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router = RouterLoader.from_extensions()
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return [route.path for route in router.api_router.routes] # type: ignore
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||||
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def create_charting_functions_w_routes(routes_to_add: List[str]):
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with open(CHARTING_ROUTER, "a") as f:
|
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for route in routes_to_add:
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||||
original_route = route.replace("_", "/")
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f.write(
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f"""
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|
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def {route}(**kwargs) -> Tuple[OpenBBFigure, Dict[str, Any]]:
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raise NotImplementedError("Command `{original_route}` does not have a charting function")
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||||
"""
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)
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||||
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||||
|
||||
def get_charting_functions() -> List[str]:
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functions = getmembers(charting_router, isfunction)
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if functions:
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return [function[0] for function in functions]
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return []
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|
||||
|
||||
if __name__ == "__main__":
|
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routes = get_routes()
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# format routes to be valid function names
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routes = [route.replace("/", "_")[1:] for route in routes]
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# get functions already in charting_router.py
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known_functions = get_charting_functions()
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# remove known functions from routes
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routes = [route for route in routes if route not in known_functions]
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# create new functions in charting_router.py
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create_charting_functions_w_routes(routes)
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"""Backend for Plotly."""
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import asyncio
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import atexit
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import json
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import os
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import re
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||||
import subprocess
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||||
import sys
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||||
import warnings
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||||
from multiprocessing import current_process
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||||
from pathlib import Path
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||||
from typing import Any, Dict, Optional, Union
|
||||
|
||||
import aiohttp
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import pandas as pd
|
||||
import plotly.graph_objects as go
|
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from openbb_core.app.model.charts.charting_settings import ChartingSettings
|
||||
from packaging import version
|
||||
from reportlab.graphics import renderPDF
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|
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# pylint: disable=C0415
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try:
|
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from pywry import PyWry
|
||||
except ImportError as e:
|
||||
print(f"\033[91m{e}\033[0m")
|
||||
# pylint: disable=C0412
|
||||
from .dummy_backend import DummyBackend
|
||||
|
||||
class PyWry(DummyBackend): # type: ignore
|
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"""Dummy backend for charts."""
|
||||
|
||||
|
||||
from svglib.svglib import svg2rlg
|
||||
|
||||
try:
|
||||
from IPython import get_ipython
|
||||
|
||||
if "IPKernelApp" not in get_ipython().config:
|
||||
raise ImportError("console")
|
||||
if (
|
||||
"parent_header"
|
||||
in get_ipython().kernel._parent_ident # pylint: disable=protected-access
|
||||
):
|
||||
raise ImportError("notebook")
|
||||
except (ImportError, AttributeError):
|
||||
JUPYTER_NOTEBOOK = False
|
||||
else:
|
||||
JUPYTER_NOTEBOOK = True
|
||||
|
||||
PLOTS_CORE_PATH = Path(__file__).parent.resolve()
|
||||
PLOTLYJS_PATH = PLOTS_CORE_PATH / "assets" / "plotly-2.24.2.min.js"
|
||||
BACKEND = None
|
||||
|
||||
|
||||
class Backend(PyWry):
|
||||
"""Custom backend for Plotly."""
|
||||
|
||||
def __new__(cls, *args, **kwargs): # pylint: disable=W0613
|
||||
"""Create a singleton instance of the backend."""
|
||||
if not hasattr(cls, "instance"):
|
||||
cls.instance = super().__new__(cls) # pylint: disable=E1120
|
||||
return cls.instance
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
charting_settings: ChartingSettings,
|
||||
daemon: bool = True,
|
||||
max_retries: int = 30,
|
||||
proc_name: str = "OpenBB Terminal",
|
||||
):
|
||||
self.charting_settings = charting_settings
|
||||
|
||||
has_version = hasattr(PyWry, "__version__")
|
||||
init_kwargs: Dict[str, Any] = dict(daemon=daemon, max_retries=max_retries)
|
||||
|
||||
if has_version and version.parse(PyWry.__version__) >= version.parse("0.4.8"):
|
||||
init_kwargs.update(dict(proc_name=proc_name))
|
||||
|
||||
super().__init__(**init_kwargs)
|
||||
|
||||
self.plotly_html: Path = (PLOTS_CORE_PATH / "plotly.html").resolve()
|
||||
self.table_html: Path = (PLOTS_CORE_PATH / "table.html").resolve()
|
||||
self.isatty = (
|
||||
not JUPYTER_NOTEBOOK
|
||||
and sys.stdin.isatty()
|
||||
and current_process().name == "MainProcess"
|
||||
)
|
||||
if has_version and PyWry.__version__ == "0.0.0":
|
||||
self.isatty = False
|
||||
|
||||
self.WIDTH, self.HEIGHT = 1400, 762
|
||||
self.logged_in: bool = False
|
||||
|
||||
atexit.register(self.close)
|
||||
|
||||
def set_window_dimensions(self):
|
||||
"""Set the window dimensions."""
|
||||
width = self.charting_settings.plot_pywry_width or 1400
|
||||
height = self.charting_settings.plot_pywry_height or 762
|
||||
|
||||
self.WIDTH, self.HEIGHT = int(width), int(height)
|
||||
|
||||
def get_pending(self) -> list:
|
||||
"""Get the pending data that has not been sent to the backend."""
|
||||
# pylint: disable=W0201,E0203
|
||||
pending = self.outgoing + self.init_engine
|
||||
self.outgoing: list = []
|
||||
self.init_engine: list = []
|
||||
return pending
|
||||
|
||||
def get_plotly_html(self) -> Path:
|
||||
"""Get the plotly html file."""
|
||||
self.set_window_dimensions()
|
||||
if self.plotly_html.exists():
|
||||
return self.plotly_html
|
||||
|
||||
warnings.warn(
|
||||
"[bold red]plotly.html file not found, check the path:[/]"
|
||||
f"[green]{PLOTS_CORE_PATH / 'plotly.html'}[/]"
|
||||
)
|
||||
self.max_retries = 0 # pylint: disable=W0201
|
||||
raise FileNotFoundError
|
||||
|
||||
def get_table_html(self) -> Path:
|
||||
"""Get the table html file."""
|
||||
self.set_window_dimensions()
|
||||
if self.table_html.exists():
|
||||
return self.table_html
|
||||
warnings.warn(
|
||||
"[bold red]table.html file not found, check the path:[/]"
|
||||
f"[green]{PLOTS_CORE_PATH / 'table.html'}[/]"
|
||||
)
|
||||
self.max_retries = 0 # pylint: disable=W0201
|
||||
raise FileNotFoundError
|
||||
|
||||
def get_window_icon(self) -> Optional[Path]:
|
||||
"""Get the window icon."""
|
||||
icon_path = PLOTS_CORE_PATH / "assets" / "Terminal_icon.png"
|
||||
if icon_path.exists():
|
||||
return icon_path
|
||||
return None
|
||||
|
||||
def get_json_update(
|
||||
self,
|
||||
cmd_loc: Optional[str] = None,
|
||||
theme: Optional[str] = None,
|
||||
) -> dict:
|
||||
"""Get the json update for the backend."""
|
||||
|
||||
posthog: Dict[str, Any] = dict(collect_logs=self.charting_settings.log_collect)
|
||||
if (
|
||||
self.charting_settings.log_collect
|
||||
and self.charting_settings.user_uuid
|
||||
and not self.logged_in
|
||||
):
|
||||
self.logged_in = True
|
||||
posthog.update(
|
||||
dict(
|
||||
user_id=self.charting_settings.user_uuid,
|
||||
email=self.charting_settings.user_email,
|
||||
)
|
||||
)
|
||||
|
||||
return dict(
|
||||
theme=theme or self.charting_settings.chart_style,
|
||||
log_id=self.charting_settings.app_id,
|
||||
pywry_version=self.__version__,
|
||||
terminal_version=self.charting_settings.version,
|
||||
python_version=self.charting_settings.python_version,
|
||||
posthog=posthog,
|
||||
command_location=cmd_loc,
|
||||
)
|
||||
|
||||
def send_figure(
|
||||
self,
|
||||
fig: go.Figure,
|
||||
export_image: Optional[Union[Path, str]] = "",
|
||||
command_location: Optional[str] = "",
|
||||
):
|
||||
"""Send a Plotly figure to the backend.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
fig : go.Figure
|
||||
Plotly figure to send to backend.
|
||||
export_image : str, optional
|
||||
Path to export image to, by default ""
|
||||
command_location : str, optional
|
||||
Location of the command, by default "".
|
||||
We can use the route here to display it on the chart title.
|
||||
"""
|
||||
self.check_backend()
|
||||
# pylint: disable=C0415
|
||||
|
||||
title = "Interactive Chart"
|
||||
|
||||
fig.layout.title.text = re.sub(
|
||||
r"<[^>]*>", "", fig.layout.title.text if fig.layout.title.text else title
|
||||
)
|
||||
|
||||
fig.layout.height += 69
|
||||
|
||||
if export_image and isinstance(export_image, str):
|
||||
export_image = Path(export_image).resolve()
|
||||
|
||||
json_data = json.loads(fig.to_json())
|
||||
|
||||
json_data.update(self.get_json_update(command_location))
|
||||
|
||||
outgoing = dict(
|
||||
html=self.get_plotly_html(),
|
||||
json_data=json_data,
|
||||
export_image=export_image,
|
||||
**self.get_kwargs(command_location),
|
||||
)
|
||||
self.send_outgoing(outgoing)
|
||||
|
||||
if export_image and isinstance(export_image, Path):
|
||||
self.loop.run_until_complete(self.process_image(export_image))
|
||||
|
||||
async def process_image(self, export_image: Path):
|
||||
"""Check if the image has been exported to the path."""
|
||||
pdf = export_image.suffix == ".pdf"
|
||||
img_path = export_image.resolve()
|
||||
|
||||
checks = 0
|
||||
while not img_path.exists():
|
||||
await asyncio.sleep(0.2)
|
||||
checks += 1
|
||||
if checks > 50:
|
||||
break
|
||||
|
||||
if pdf:
|
||||
img_path = img_path.rename(img_path.with_suffix(".svg"))
|
||||
|
||||
if img_path.exists(): # noqa: SIM102
|
||||
if pdf:
|
||||
drawing = svg2rlg(img_path)
|
||||
img_path.unlink(missing_ok=True)
|
||||
renderPDF.drawToFile(drawing, str(export_image))
|
||||
|
||||
if self.charting_settings.plot_open_export:
|
||||
if sys.platform == "win32":
|
||||
os.startfile(export_image) # nosec: B606
|
||||
else:
|
||||
opener = "open" if sys.platform == "darwin" else "xdg-open"
|
||||
subprocess.check_call([opener, export_image]) # nosec: B603
|
||||
|
||||
def send_table(
|
||||
self,
|
||||
df_table: pd.DataFrame,
|
||||
title: str = "",
|
||||
source: str = "",
|
||||
theme: str = "dark",
|
||||
command_location: Optional[str] = "",
|
||||
):
|
||||
"""Send table data to the backend to be displayed in a table.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
df_table : pd.DataFrame
|
||||
Dataframe to send to backend.
|
||||
title : str, optional
|
||||
Title to display in the window, by default ""
|
||||
source : str, optional
|
||||
Source of the data, by default ""
|
||||
theme : light or dark, optional
|
||||
Theme of the table, by default "light"
|
||||
"""
|
||||
self.check_backend()
|
||||
|
||||
if title:
|
||||
# We remove any html tags and markdown from the title
|
||||
title = re.sub(r"<[^>]*>", "", title)
|
||||
title = re.sub(r"\[\/?[a-z]+\]", "", title)
|
||||
|
||||
# we get the length of each column using the max length of the column
|
||||
# name and the max length of the column values as the column width
|
||||
columnwidth = [
|
||||
max(
|
||||
len(str(df_table[col].name)),
|
||||
df_table[col].astype(str).str.len().max(),
|
||||
)
|
||||
for col in df_table.columns
|
||||
if hasattr(df_table[col], "name") and hasattr(df_table[col], "dtype")
|
||||
]
|
||||
|
||||
# we add a percentage of max to the min column width
|
||||
columnwidth = [
|
||||
int(x + (max(columnwidth) - min(columnwidth)) * 0.2) for x in columnwidth
|
||||
]
|
||||
|
||||
# in case of a very small table we set a min width
|
||||
width = max(int(min(sum(columnwidth) * 9.7, self.WIDTH + 100)), 800)
|
||||
|
||||
json_data = json.loads(df_table.to_json(orient="split", date_format="iso"))
|
||||
json_data.update(
|
||||
dict(
|
||||
title=title,
|
||||
source=source or "",
|
||||
**self.get_json_update(command_location, theme or "dark"),
|
||||
)
|
||||
)
|
||||
|
||||
outgoing = dict(
|
||||
html=self.get_table_html(),
|
||||
json_data=json.dumps(json_data),
|
||||
width=width,
|
||||
height=self.HEIGHT - 100,
|
||||
**self.get_kwargs(command_location),
|
||||
)
|
||||
self.send_outgoing(outgoing)
|
||||
|
||||
def send_url(
|
||||
self,
|
||||
url: str,
|
||||
title: str = "",
|
||||
width: Optional[int] = None,
|
||||
height: Optional[int] = None,
|
||||
):
|
||||
"""Send a URL to the backend to be displayed in a window.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
url : str
|
||||
URL to display in the window.
|
||||
title : str, optional
|
||||
Title to display in the window, by default ""
|
||||
width : int, optional
|
||||
Width of the window, by default 1200
|
||||
height : int, optional
|
||||
Height of the window, by default 800
|
||||
"""
|
||||
self.check_backend()
|
||||
script = f"""
|
||||
<script>
|
||||
window.location.replace("{url}");
|
||||
</script>
|
||||
"""
|
||||
outgoing = dict(
|
||||
html=script,
|
||||
**self.get_kwargs(title),
|
||||
width=width or self.WIDTH,
|
||||
height=height or self.HEIGHT,
|
||||
)
|
||||
self.send_outgoing(outgoing)
|
||||
|
||||
def get_kwargs(self, title: Optional[str] = "") -> dict:
|
||||
"""Get the kwargs for the backend."""
|
||||
return {
|
||||
"title": f"OpenBB - {title}",
|
||||
"icon": self.get_window_icon(),
|
||||
"download_path": str(self.charting_settings.user_exports_directory),
|
||||
}
|
||||
|
||||
def start(self, debug: bool = False, headless: bool = False):
|
||||
"""Start the backend WindowManager process."""
|
||||
if self.isatty:
|
||||
super().start(debug, headless)
|
||||
|
||||
def check_backend(self):
|
||||
"""Override to check if isatty."""
|
||||
if not self.isatty:
|
||||
return None
|
||||
|
||||
message = (
|
||||
"[bold red]PyWry version 0.5.12 or higher is required to use the "
|
||||
"OpenBB Plots backend.[/]\n"
|
||||
"[yellow]Please update pywry with 'pip install pywry --upgrade'[/]"
|
||||
)
|
||||
if not hasattr(PyWry, "__version__"):
|
||||
try:
|
||||
# pylint: disable=C0415
|
||||
from pywry import __version__ as pywry_version
|
||||
except ImportError:
|
||||
self.max_retries = 0
|
||||
return warnings.warn(message)
|
||||
|
||||
PyWry.__version__ = pywry_version # pylint: disable=W0201
|
||||
|
||||
if version.parse(PyWry.__version__) < version.parse("0.5.12"):
|
||||
self.max_retries = 0 # pylint: disable=W0201
|
||||
return warnings.warn(message)
|
||||
|
||||
if version.parse(PyWry.__version__) > version.parse("0.5.12"):
|
||||
return super().check_backend()
|
||||
|
||||
try:
|
||||
return self.loop.run_until_complete(super().check_backend())
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
def close(self, reset: bool = False):
|
||||
"""Close the backend."""
|
||||
if reset:
|
||||
self.max_retries = 50 # pylint: disable=W0201
|
||||
|
||||
super().close()
|
||||
|
||||
async def get_results(self, description: str) -> dict:
|
||||
"""Wait for completion of interactive task and return the data.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
description : str
|
||||
Description of the task to console print while waiting.
|
||||
|
||||
Returns
|
||||
-------
|
||||
dict
|
||||
The data returned from pywry backend.
|
||||
"""
|
||||
warnings.warn(
|
||||
f"[green]{description}[/]\n\n"
|
||||
"[yellow]If the window is closed you can continue by pressing Ctrl+C.[/]"
|
||||
)
|
||||
while True:
|
||||
try:
|
||||
data: dict = self.recv.get(block=False) or {}
|
||||
if data.get("result", False):
|
||||
return json.loads(data["result"])
|
||||
except Exception: # pylint: disable=W0703
|
||||
await asyncio.sleep(0.1)
|
||||
|
||||
await asyncio.sleep(1)
|
||||
|
||||
def call_hub(self, login: bool = True) -> Optional[dict]:
|
||||
"""Call the hub to login or logout.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
login : bool, optional
|
||||
Whether to login or logout, by default True
|
||||
|
||||
Returns
|
||||
-------
|
||||
Optional[dict]
|
||||
The user data if login was successful, None otherwise.
|
||||
"""
|
||||
self.check_backend()
|
||||
endpoint = {True: "login", False: "logout"}[login]
|
||||
|
||||
outgoing = dict(
|
||||
json_data=dict(url=f"https://my.openbb.co/{endpoint}?pywry=true"),
|
||||
**self.get_kwargs(endpoint.title()),
|
||||
width=900,
|
||||
height=800,
|
||||
)
|
||||
self.send_outgoing(outgoing)
|
||||
|
||||
messages_dict = dict(
|
||||
login=dict(
|
||||
message="Welcome to OpenBB Terminal! Please login to continue.",
|
||||
interrupt="Window closed without authentication. Please proceed below.",
|
||||
),
|
||||
logout=dict(
|
||||
message="Sending logout request", interrupt="Please login to continue."
|
||||
),
|
||||
)
|
||||
|
||||
try:
|
||||
return self.loop.run_until_complete(
|
||||
self.get_results(messages_dict[endpoint]["message"])
|
||||
)
|
||||
except KeyboardInterrupt:
|
||||
warnings.warn(f"\n[red]{messages_dict[endpoint]['interrupt']}[/red]")
|
||||
return None
|
||||
|
||||
|
||||
async def download_plotly_js():
|
||||
"""Download or updates plotly.js to the assets folder."""
|
||||
js_filename = PLOTLYJS_PATH.name
|
||||
try:
|
||||
# we use aiohttp to download plotly.js
|
||||
# this is so we don't have to block the main thread
|
||||
async with aiohttp.ClientSession(
|
||||
connector=aiohttp.TCPConnector(verify_ssl=False)
|
||||
) as session:
|
||||
async with session.get(f"https://cdn.plot.ly/{js_filename}") as resp:
|
||||
with open(str(PLOTLYJS_PATH), "wb") as f:
|
||||
while True:
|
||||
chunk = await resp.content.read(1024)
|
||||
if not chunk:
|
||||
break
|
||||
f.write(chunk)
|
||||
|
||||
# We delete the old version of plotly.js
|
||||
for file in (PLOTS_CORE_PATH / "assets").glob("plotly*.js"):
|
||||
if file.name != js_filename:
|
||||
file.unlink(missing_ok=True)
|
||||
|
||||
except Exception as err: # pylint: disable=W0703
|
||||
print(f"Error downloading plotly.js: {err}")
|
||||
|
||||
|
||||
# To avoid having plotly.js in the repo, we download it if it's not present
|
||||
if not PLOTLYJS_PATH.exists() and not JUPYTER_NOTEBOOK:
|
||||
asyncio.run(download_plotly_js())
|
||||
|
||||
|
||||
def create_backend(charting_settings: Optional[ChartingSettings] = None):
|
||||
charting_settings = charting_settings or ChartingSettings()
|
||||
global BACKEND # pylint: disable=W0603 # noqa
|
||||
if BACKEND is None:
|
||||
BACKEND = Backend(charting_settings)
|
||||
|
||||
|
||||
def get_backend() -> Backend:
|
||||
if BACKEND is None:
|
||||
raise ValueError("Backend not created")
|
||||
return BACKEND
|
||||
@@ -1,227 +0,0 @@
|
||||
"""Chart and style helpers for Plotly."""
|
||||
# pylint: disable=C0302,R0902,W3301
|
||||
import json
|
||||
import sys
|
||||
from pathlib import Path
|
||||
from typing import (
|
||||
Any,
|
||||
Dict,
|
||||
List,
|
||||
Optional,
|
||||
Union,
|
||||
)
|
||||
from warnings import warn
|
||||
|
||||
import plotly.graph_objects as go
|
||||
import plotly.io as pio
|
||||
from openbb_charting.core.config.openbb_styles import (
|
||||
PLT_COLORWAY,
|
||||
PLT_DECREASING_COLORWAY,
|
||||
PLT_INCREASING_COLORWAY,
|
||||
)
|
||||
|
||||
|
||||
class ChartStyle:
|
||||
"""The class that helps with handling of style configurations.
|
||||
|
||||
It serves styles for 2 libraries. For `Plotly` this class serves absolute paths
|
||||
to the .pltstyle files. For `Plotly` and `Rich` this class serves custom
|
||||
styles as python dictionaries.
|
||||
"""
|
||||
|
||||
STYLES_REPO = Path(__file__).parent.parent / "styles"
|
||||
user_styles_directory: Path = STYLES_REPO
|
||||
|
||||
plt_styles_available: Dict[str, Path] = {}
|
||||
plt_style: str = "dark"
|
||||
plotly_template: Dict[str, Any] = {}
|
||||
mapbox_style: str = "dark"
|
||||
|
||||
line_color: str = ""
|
||||
up_color: str = ""
|
||||
down_color: str = ""
|
||||
up_colorway: List[str] = []
|
||||
down_colorway: List[str] = []
|
||||
up_color_transparent: str = ""
|
||||
down_color_transparent: str = ""
|
||||
|
||||
line_width: float = 1.5
|
||||
|
||||
initialized: bool = False
|
||||
|
||||
def __new__(cls, *args, **kwargs): # pylint: disable=W0613
|
||||
"""Create a singleton."""
|
||||
if not hasattr(cls, "instance"):
|
||||
cls.instance = super().__new__(cls) # pylint: disable=E1120
|
||||
return cls.instance
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
plt_style: Optional[str] = "",
|
||||
user_styles_directory: Optional[Path] = None,
|
||||
):
|
||||
"""Initialize the class.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
plt_style : `str`, optional
|
||||
The name of the Plotly style to use, by default ""
|
||||
console_style : `str`, optional
|
||||
The name of the Rich style to use, by default ""
|
||||
"""
|
||||
if self.initialized:
|
||||
return
|
||||
|
||||
self.initialized = True
|
||||
self.user_styles_directory = user_styles_directory or self.user_styles_directory
|
||||
self.plt_style = plt_style or self.plt_style
|
||||
self.load_available_styles()
|
||||
self.load_style(plt_style)
|
||||
self.apply_style()
|
||||
|
||||
def apply_style(self, style: Optional[str] = "") -> None:
|
||||
"""Apply the style to the libraries."""
|
||||
style = style or self.plt_style
|
||||
|
||||
if style != self.plt_style:
|
||||
self.load_style(style)
|
||||
|
||||
style = style.lower().replace("light", "white") # type: ignore
|
||||
|
||||
if self.plt_style and self.plotly_template:
|
||||
self.plotly_template.setdefault("layout", {}).setdefault(
|
||||
"mapbox", {}
|
||||
).setdefault("style", "dark")
|
||||
if "tables" in self.plt_styles_available:
|
||||
tables = self.load_json_style(self.plt_styles_available["tables"])
|
||||
pio.templates["openbb_tables"] = go.layout.Template(tables)
|
||||
try:
|
||||
pio.templates["openbb"] = go.layout.Template(self.plotly_template)
|
||||
except ValueError as err:
|
||||
if "plotly.graph_objs.Layout: 'legend2'" in str(err):
|
||||
warn(
|
||||
"[red]Warning: Plotly multiple legends are "
|
||||
"not supported in currently installed version.[/]\n\n"
|
||||
"[yellow]Please update plotly to version >= 5.15.0[/]\n"
|
||||
"[green]pip install plotly --upgrade[/]"
|
||||
)
|
||||
sys.exit(1)
|
||||
|
||||
if style in ["dark", "white"]:
|
||||
pio.templates.default = f"plotly_{style}+openbb"
|
||||
return
|
||||
|
||||
pio.templates.default = "openbb"
|
||||
self.mapbox_style = (
|
||||
self.plotly_template.setdefault("layout", {})
|
||||
.setdefault("mapbox", {})
|
||||
.setdefault("style", "dark")
|
||||
)
|
||||
|
||||
def load_available_styles_from_folder(self, folder: Union[Path, str]) -> None:
|
||||
"""Load custom styles from folder.
|
||||
|
||||
Parses the styles/default and styles/user folders and loads style files.
|
||||
To be recognized files need to follow a naming convention:
|
||||
*.pltstyle - plotly stylesheets
|
||||
*.richstyle.json - rich stylesheets
|
||||
|
||||
Parameters
|
||||
----------
|
||||
folder : str
|
||||
Path to the folder containing the stylesheets
|
||||
"""
|
||||
|
||||
if not isinstance(folder, Path) or not folder.exists():
|
||||
return
|
||||
|
||||
for attr, ext in zip(
|
||||
["plt_styles_available", "console_styles_available"],
|
||||
[".pltstyle.json", ".richstyle.json"],
|
||||
):
|
||||
for file in folder.rglob(f"*{ext}"):
|
||||
getattr(self, attr)[file.name.replace(ext, "")] = file
|
||||
|
||||
def load_available_styles(self) -> None:
|
||||
"""Load custom styles from default and user folders."""
|
||||
self.load_available_styles_from_folder(self.STYLES_REPO)
|
||||
self.load_available_styles_from_folder(self.user_styles_directory)
|
||||
|
||||
def load_json_style(self, file: Path) -> Dict[str, Any]:
|
||||
"""Load style from json file.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
file : Path
|
||||
Path to the file containing the style
|
||||
|
||||
Returns
|
||||
-------
|
||||
Dict[str, Any]
|
||||
Style as a dictionary
|
||||
"""
|
||||
with open(file) as f:
|
||||
return json.load(f)
|
||||
|
||||
def load_style(self, style: Optional[str] = "") -> None:
|
||||
"""Load style from file.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
style : str
|
||||
Name of the style to load
|
||||
"""
|
||||
style = style or self.plt_style
|
||||
|
||||
if style not in self.plt_styles_available:
|
||||
warn(
|
||||
f"[red]Plot Style {style} not found. Using default style.[/red]",
|
||||
)
|
||||
style = "dark"
|
||||
|
||||
self.load_plt_style(style)
|
||||
|
||||
def load_plt_style(self, style: str) -> None:
|
||||
"""Load Plotly style from file.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
style : str
|
||||
Name of the style to load
|
||||
"""
|
||||
self.plt_style = style
|
||||
self.plotly_template = self.load_json_style(self.plt_styles_available[style])
|
||||
line = self.plotly_template.pop("line", {})
|
||||
|
||||
self.up_color = line.get("up_color", "#00ACFF")
|
||||
self.down_color = line.get("down_color", "#FF0000")
|
||||
self.up_color_transparent = line.get(
|
||||
"up_color_transparent", "rgba(0, 170, 255, 0.50)"
|
||||
)
|
||||
self.down_color_transparent = line.get(
|
||||
"down_color_transparent", "rgba(230, 0, 57, 0.50)"
|
||||
)
|
||||
self.line_color = line.get("color", "#ffed00")
|
||||
self.line_width = line.get("width", self.line_width)
|
||||
self.down_colorway = line.get("down_colorway", PLT_DECREASING_COLORWAY)
|
||||
self.up_colorway = line.get("up_colorway", PLT_INCREASING_COLORWAY)
|
||||
|
||||
def get_colors(self, reverse: bool = False) -> list:
|
||||
"""Get colors for the plot.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
reverse : bool, optional
|
||||
Whether to reverse the colors, by default False
|
||||
|
||||
Returns
|
||||
-------
|
||||
list
|
||||
List of colors e.g. ["#00ACFF", "#FF0000"]
|
||||
"""
|
||||
colors = (
|
||||
self.plotly_template.get("layout", {}).get("colorway", PLT_COLORWAY).copy()
|
||||
)
|
||||
if reverse:
|
||||
colors.reverse()
|
||||
return colors
|
||||
@@ -1,271 +0,0 @@
|
||||
from typing import Any, List, Optional
|
||||
|
||||
import pandas as pd
|
||||
|
||||
# Vsurf Plot Settings
|
||||
PLT_3DMESH_COLORSCALE = "Jet"
|
||||
PLT_3DMESH_SCENE = dict(
|
||||
xaxis=dict(
|
||||
backgroundcolor="rgb(94, 94, 94)",
|
||||
gridcolor="white",
|
||||
showbackground=True,
|
||||
zerolinecolor="white",
|
||||
),
|
||||
yaxis=dict(
|
||||
backgroundcolor="rgb(94, 94, 94)",
|
||||
gridcolor="white",
|
||||
showbackground=True,
|
||||
zerolinecolor="white",
|
||||
),
|
||||
zaxis=dict(
|
||||
backgroundcolor="rgb(94, 94, 94)",
|
||||
gridcolor="white",
|
||||
showbackground=True,
|
||||
zerolinecolor="white",
|
||||
),
|
||||
aspectratio=dict(x=1.2, y=1.2, z=0.8),
|
||||
)
|
||||
PLT_3DMESH_HOVERLABEL = dict(bgcolor="gold")
|
||||
|
||||
# Chart Plots Settings
|
||||
PLT_STYLE_TEMPLATE = "plotly_dark"
|
||||
PLT_STYLE_INCREASING = "#00ACFF"
|
||||
PLT_STYLE_DECREASING = "#e4003a"
|
||||
PLT_CANDLESTICKS = dict(
|
||||
increasing=dict(line_color=PLT_STYLE_INCREASING, fillcolor=PLT_STYLE_INCREASING),
|
||||
decreasing=dict(line_color=PLT_STYLE_DECREASING, fillcolor=PLT_STYLE_DECREASING),
|
||||
)
|
||||
PLT_STYLE_INCREASING_GREEN = "#009600"
|
||||
PLT_STYLE_DECREASING_RED = "#c80000"
|
||||
PLT_FONT = dict(family="Fira Code", size=16)
|
||||
PLOTLY_FONT = dict(family="Fira Code", size=18)
|
||||
|
||||
PLT_COLORWAY = [
|
||||
"#ffed00",
|
||||
"#ef7d00",
|
||||
"#e4003a",
|
||||
"#c13246",
|
||||
"#822661",
|
||||
"#48277c",
|
||||
"#005ca9",
|
||||
"#00aaff",
|
||||
"#9b30d9",
|
||||
"#af005f",
|
||||
"#5f00af",
|
||||
"#af87ff",
|
||||
]
|
||||
|
||||
PLT_FIB_COLORWAY: List[Any] = [
|
||||
"rgb(195, 50, 69)", # 0
|
||||
"rgb(130, 38, 96)", # 0.235
|
||||
"rgb(120, 70, 200)", # 0.382
|
||||
"rgb(0, 93, 168)", # 0.5
|
||||
"rgb(173, 0, 95)", # 0.618
|
||||
"rgb(235, 184, 0)", # 0.65 Golden Pocket
|
||||
"rgb(162, 115, 206)", # 1
|
||||
dict(family="Arial Black", size=10), # Fib's Text
|
||||
dict(color="rgb(0, 230, 195)", width=0.9, dash="dash"), # Fib Trendline
|
||||
]
|
||||
|
||||
PLT_INCREASING_COLORWAY = [
|
||||
"rgba(0, 150, 255, 1)",
|
||||
"rgba(0, 170, 255, 0.92)",
|
||||
"rgba(0, 170, 255, 0.90)",
|
||||
"rgba(0, 170, 255, 0.80)",
|
||||
"rgba(0, 170, 255, 0.70)",
|
||||
"rgba(0, 170, 255, 0.60)",
|
||||
"rgba(0, 170, 255, 0.50)",
|
||||
"rgba(0, 170, 255, 0.40)",
|
||||
"rgba(0, 170, 255, 0.34)",
|
||||
"rgba(0, 170, 255, 0.22)",
|
||||
"rgba(0, 170, 255, 0.10)",
|
||||
"rgba(0, 170, 255, 0.05)",
|
||||
]
|
||||
|
||||
PLT_DECREASING_COLORWAY = [
|
||||
"rgba(230, 0, 57, 1)",
|
||||
"rgba(230, 0, 57, 0.92)",
|
||||
"rgba(230, 0, 57, 0.90)",
|
||||
"rgba(230, 0, 57, 0.80)",
|
||||
"rgba(230, 0, 57, 0.70)",
|
||||
"rgba(230, 0, 57, 0.60)",
|
||||
"rgba(230, 0, 57, 0.50)",
|
||||
"rgba(230, 0, 57, 0.40)",
|
||||
"rgba(230, 0, 57, 0.34)",
|
||||
"rgba(230, 0, 57, 0.22)",
|
||||
"rgba(230, 0, 57, 0.10)",
|
||||
"rgba(230, 0, 57, 0.05)",
|
||||
]
|
||||
|
||||
PLT_INCREASING_COLORWAY_GREEN = [
|
||||
"rgba(0, 150, 0, 1)",
|
||||
"rgba(0, 150, 0, 0.92)",
|
||||
"rgba(0, 150, 0, 0.90)",
|
||||
"rgba(0, 150, 0, 0.80)",
|
||||
"rgba(0, 150, 0, 0.70)",
|
||||
"rgba(0, 150, 0, 0.60)",
|
||||
"rgba(0, 150, 0, 0.50)",
|
||||
"rgba(0, 150, 0, 0.40)",
|
||||
"rgba(0, 150, 0, 0.34)",
|
||||
"rgba(0, 150, 0, 0.22)",
|
||||
"rgba(0, 150, 0, 0.10)",
|
||||
"rgba(0, 150, 0, 0.05)",
|
||||
]
|
||||
|
||||
PLT_DECREASING_COLORWAY_RED = [
|
||||
"rgba(200, 0, 0, 1)",
|
||||
"rgba(200, 0, 0, 0.92)",
|
||||
"rgba(200, 0, 0, 0.90)",
|
||||
"rgba(200, 0, 0, 0.80)",
|
||||
"rgba(200, 0, 0, 0.70)",
|
||||
"rgba(200, 0, 0, 0.60)",
|
||||
"rgba(200, 0, 0, 0.50)",
|
||||
"rgba(200, 0, 0, 0.40)",
|
||||
"rgba(200, 0, 0, 0.34)",
|
||||
"rgba(200, 0, 0, 0.22)",
|
||||
"rgba(200, 0, 0, 0.10)",
|
||||
"rgba(200, 0, 0, 0.05)",
|
||||
]
|
||||
|
||||
|
||||
# Table Plots Settings
|
||||
PLT_TBL_HEADER = dict(
|
||||
fill_color="rgb(30, 30, 30)",
|
||||
font_color="white",
|
||||
line_color="#6e6e6e",
|
||||
line_width=1,
|
||||
)
|
||||
PLT_TBL_CELLS = dict(
|
||||
font_color="white",
|
||||
line_color="#6e6e6e",
|
||||
line_width=0,
|
||||
)
|
||||
PLT_TBL_ROW_COLORS = (
|
||||
"#333333",
|
||||
"#242424",
|
||||
)
|
||||
|
||||
|
||||
def de_increasing_color_list(
|
||||
df_column: Optional[pd.DataFrame] = None,
|
||||
text: Optional[str] = None,
|
||||
contains_str: str = "-",
|
||||
increasing_color: str = PLT_STYLE_INCREASING,
|
||||
decreasing_color: str = PLT_STYLE_DECREASING,
|
||||
) -> List[str]:
|
||||
"""Makes a colorlist for decrease/increase if value in df_column
|
||||
contains "{contains_str}" default is "-"
|
||||
|
||||
Parameters
|
||||
----------
|
||||
df_column : pd.DataFrame, optional
|
||||
Dataframe column to create colorlist. by default None
|
||||
text : str, optional
|
||||
Search in a string, by default None
|
||||
contains_str : str, optional
|
||||
Decreasing String to search for in df_column. The default is "-".
|
||||
increasing_color : str, optional
|
||||
Color to use for increasing values. The default is PLT_STYLE_INCREASING.
|
||||
decreasing_color : str, optional
|
||||
Color to use for decreasing values. The default is PLT_STYLE_DECREASING.
|
||||
|
||||
Returns
|
||||
-------
|
||||
List[str]
|
||||
List of colors for df_column
|
||||
"""
|
||||
if df_column is None:
|
||||
colorlist = [decreasing_color if contains_str in text else increasing_color] # type: ignore
|
||||
else:
|
||||
colorlist = [
|
||||
decreasing_color if boolv else increasing_color
|
||||
for boolv in df_column.astype(str).str.contains(contains_str)
|
||||
]
|
||||
return colorlist
|
||||
|
||||
|
||||
PLOTLY_THEME = dict(
|
||||
# Layout
|
||||
layout=dict(
|
||||
colorway=PLT_COLORWAY,
|
||||
font=PLOTLY_FONT,
|
||||
yaxis=dict(
|
||||
side="right",
|
||||
zeroline=True,
|
||||
fixedrange=False,
|
||||
title_standoff=20,
|
||||
nticks=15,
|
||||
showline=True,
|
||||
showgrid=True,
|
||||
),
|
||||
yaxis2=dict(
|
||||
zeroline=False,
|
||||
fixedrange=False,
|
||||
anchor="x",
|
||||
layer="above traces",
|
||||
overlaying="y2",
|
||||
nticks=6,
|
||||
tick0=0.5,
|
||||
title_standoff=10,
|
||||
tickfont=dict(size=15),
|
||||
showline=True,
|
||||
),
|
||||
yaxis3=dict(
|
||||
zeroline=False,
|
||||
fixedrange=False,
|
||||
anchor="x",
|
||||
layer="above traces",
|
||||
overlaying="y3",
|
||||
nticks=6,
|
||||
tick0=0.5,
|
||||
title_standoff=10,
|
||||
tickfont=dict(size=15),
|
||||
showline=True,
|
||||
),
|
||||
yaxis4=dict(
|
||||
zeroline=False,
|
||||
fixedrange=False,
|
||||
anchor="x",
|
||||
layer="above traces",
|
||||
overlaying="y4",
|
||||
nticks=6,
|
||||
tick0=0.5,
|
||||
title_standoff=10,
|
||||
tickfont=dict(size=15),
|
||||
showline=True,
|
||||
),
|
||||
xaxis=dict(
|
||||
showgrid=True,
|
||||
zeroline=True,
|
||||
showline=True,
|
||||
rangeslider=dict(visible=False),
|
||||
tickfont=dict(size=16),
|
||||
title_standoff=20,
|
||||
),
|
||||
legend=dict(
|
||||
yanchor="top",
|
||||
y=0.99,
|
||||
xanchor="left",
|
||||
font_size=15,
|
||||
bgcolor="rgba(0, 0, 0, 0)",
|
||||
x=0.01,
|
||||
),
|
||||
dragmode="pan",
|
||||
hovermode="x",
|
||||
hoverlabel=dict(align="left"),
|
||||
),
|
||||
data=dict(
|
||||
candlestick=[
|
||||
dict(
|
||||
increasing=dict(
|
||||
line=dict(color=PLT_STYLE_INCREASING),
|
||||
fillcolor=PLT_STYLE_INCREASING,
|
||||
),
|
||||
decreasing=dict(
|
||||
line=dict(color=PLT_STYLE_DECREASING),
|
||||
fillcolor=PLT_STYLE_DECREASING,
|
||||
),
|
||||
)
|
||||
]
|
||||
),
|
||||
)
|
||||
@@ -1,77 +0,0 @@
|
||||
import asyncio
|
||||
import warnings
|
||||
from queue import Queue
|
||||
from typing import List
|
||||
|
||||
import dotenv
|
||||
from openbb_core.app.constants import OPENBB_DIRECTORY
|
||||
|
||||
SETTINGS_ENV_FILE = OPENBB_DIRECTORY / ".env"
|
||||
|
||||
pywry_missing = """
|
||||
[red]PyWry is not installed or missing required linux dependencies.[/]
|
||||
|
||||
[yellow]Install PyWry[/]
|
||||
[green]pip install pywry --upgrade[/]
|
||||
|
||||
[yellow]Platform-specific notes[/]
|
||||
Here is the underlying web engine each platform uses you might need to install.
|
||||
|
||||
[green]Linux[/]
|
||||
Pywry uses gtk-rs and its related libraries for window creation and Wry also needs WebKitGTK for WebView.
|
||||
To activate interactive plots/tables in pywry window, please make sure the following packages are installed:
|
||||
|
||||
[yellow]Arch Linux / Manjaro:[/]
|
||||
[green]sudo pacman -S webkit2gtk[/]\n
|
||||
[yellow]Debian / Ubuntu:[/]
|
||||
[green]sudo apt install libwebkit2gtk-4.0-dev[/]\n
|
||||
[yellow]Fedora / CentOS / AlmaLinux:[/]
|
||||
[green]sudo dnf install gtk3-devel webkit2gtk3-devel[/]\r
|
||||
"""
|
||||
|
||||
|
||||
class DummyBackend:
|
||||
"""Dummy class to avoid import errors."""
|
||||
|
||||
__version__ = "0.0.0"
|
||||
|
||||
max_retries = 0
|
||||
outgoing: List[str] = []
|
||||
init_engine: List[str] = []
|
||||
daemon = True
|
||||
debug = False
|
||||
shell = False
|
||||
base = None
|
||||
recv: Queue = Queue()
|
||||
|
||||
def __new__(cls, *args, **kwargs): # pylint: disable=W0613
|
||||
"""Create a singleton instance of the backend."""
|
||||
if not hasattr(cls, "instance"):
|
||||
cls.instance = super().__new__(cls) # pylint: disable=E1120
|
||||
return cls.instance
|
||||
|
||||
def __init__(self, daemon: bool = True, max_retries: int = 30):
|
||||
"""Dummy init to avoid import errors."""
|
||||
self.daemon = daemon
|
||||
self.max_retries = max_retries
|
||||
try:
|
||||
self.loop: asyncio.AbstractEventLoop = asyncio.get_event_loop()
|
||||
except RuntimeError:
|
||||
self.loop = asyncio.new_event_loop()
|
||||
asyncio.set_event_loop(self.loop)
|
||||
|
||||
warnings.warn(pywry_missing)
|
||||
dotenv.set_key(SETTINGS_ENV_FILE, "PLOT_ENABLE_PYWRY", "0")
|
||||
|
||||
def close(self, reset: bool = False): # pylint: disable=W0613
|
||||
pass
|
||||
|
||||
def start(self, debug: bool = False): # pylint: disable=W0613
|
||||
pass
|
||||
|
||||
def send_outgoing(self, outgoing: dict):
|
||||
pass
|
||||
|
||||
async def check_backend(self):
|
||||
"""Dummy check backend method to avoid errors and revert to browser."""
|
||||
raise Exception
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,95 +0,0 @@
|
||||
from typing import List, Optional, Union
|
||||
|
||||
import pandas as pd
|
||||
from openbb_charting.core.openbb_figure import OpenBBFigure
|
||||
|
||||
|
||||
class OpenBBFigureTable(OpenBBFigure):
|
||||
def __init__(
|
||||
self,
|
||||
tabular_data: pd.DataFrame,
|
||||
columnwidth: Optional[List[Union[int, float]]] = None,
|
||||
):
|
||||
super().__init__()
|
||||
self._tabular_data = tabular_data
|
||||
self._columnwidth = columnwidth
|
||||
|
||||
def show(
|
||||
self,
|
||||
show_index: Optional[bool] = True,
|
||||
index_name: Optional[str] = "date",
|
||||
headers: Optional[Union[List[str], pd.Index]] = None,
|
||||
title: Optional[str] = "",
|
||||
source: Optional[str] = "",
|
||||
external: Optional[bool] = False,
|
||||
) -> Optional["OpenBBFigureTable"]:
|
||||
if external:
|
||||
return self
|
||||
|
||||
if not self._backend.isatty:
|
||||
tmp_fig = self.to_table()
|
||||
tmp_fig.show()
|
||||
return None
|
||||
else:
|
||||
# Make a copy of the dataframe to avoid SettingWithCopyWarning
|
||||
df = self._tabular_data.copy()
|
||||
|
||||
show_index = not isinstance(df.index, pd.RangeIndex) and show_index
|
||||
# convert non-str that are not timestamp or int into str
|
||||
# eg) praw.models.reddit.subreddit.Subreddit
|
||||
for col in df.columns:
|
||||
try:
|
||||
if not any(
|
||||
isinstance(df[col].iloc[x], pd.Timestamp)
|
||||
for x in range(min(10, len(df)))
|
||||
):
|
||||
df[col] = pd.to_numeric(df[col], errors="ignore")
|
||||
except (ValueError, TypeError):
|
||||
df[col] = df[col].astype(str)
|
||||
|
||||
def _get_headers(_headers: Union[List[str], pd.Index]) -> List[str]:
|
||||
"""Check if headers are valid and return them."""
|
||||
output = _headers
|
||||
if isinstance(_headers, pd.Index):
|
||||
output = list(_headers)
|
||||
if len(output) != len(df.columns):
|
||||
raise (
|
||||
ValueError(
|
||||
"Length of headers does not match length of DataFrame"
|
||||
)
|
||||
)
|
||||
return output
|
||||
|
||||
df_outgoing = df.copy()
|
||||
# If headers are provided, use them
|
||||
if headers is not None:
|
||||
# We check if headers are valid
|
||||
df_outgoing.columns = _get_headers(headers)
|
||||
|
||||
if show_index and index_name not in df_outgoing.columns:
|
||||
# If index name is provided, we use it
|
||||
df_outgoing.index.name = index_name or "Index"
|
||||
df_outgoing = df_outgoing.reset_index()
|
||||
|
||||
for col in df_outgoing.columns:
|
||||
if col == "":
|
||||
df_outgoing = df_outgoing.rename(columns={col: " "})
|
||||
|
||||
self._backend.send_table(
|
||||
df_table=df_outgoing,
|
||||
title=title,
|
||||
source=source, # type: ignore
|
||||
theme=self._charting_settings.table_style,
|
||||
)
|
||||
|
||||
return None
|
||||
|
||||
def to_table(
|
||||
self,
|
||||
print_index: bool = True,
|
||||
**kwargs,
|
||||
) -> "OpenBBFigure":
|
||||
data = self._tabular_data
|
||||
columnwidth = self._columnwidth
|
||||
|
||||
return super().to_table(data, columnwidth, print_index, **kwargs)
|
||||
File diff suppressed because one or more lines are too long
@@ -1,198 +0,0 @@
|
||||
from typing import Any, Callable, Dict, Iterator, List, Optional, Type
|
||||
|
||||
import pandas as pd
|
||||
|
||||
from .data_classes import ChartIndicators, TAIndicator
|
||||
|
||||
|
||||
def columns_regex(df_ta: pd.DataFrame, name: str) -> List[str]:
|
||||
"""Return columns that match regex name"""
|
||||
column_name = df_ta.filter(regex=rf"{name}(?=[^\d]|$)").columns.tolist()
|
||||
|
||||
return column_name
|
||||
|
||||
|
||||
class Indicator:
|
||||
"""Class for technical indicator."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
func: Callable,
|
||||
name: str = "",
|
||||
**attrs: Any,
|
||||
) -> None:
|
||||
self.func = func
|
||||
self.name = name
|
||||
self.attrs = attrs
|
||||
|
||||
def __call__(self, *args: Any, **kwargs: Any) -> Any:
|
||||
return self.func(*args, **kwargs)
|
||||
|
||||
|
||||
class PluginMeta(type):
|
||||
"""Metaclass for all Plotly plugins."""
|
||||
|
||||
__indicators__: List[Indicator] = []
|
||||
__static_methods__: list = []
|
||||
__ma_mode__: List[str] = []
|
||||
__inchart__: List[str] = []
|
||||
__subplots__: List[str] = []
|
||||
|
||||
def __new__(mcs: Type["PluginMeta"], *args: Any, **kwargs: Any) -> "PluginMeta":
|
||||
name, bases, attrs = args
|
||||
indicators: Dict[str, Indicator] = {}
|
||||
cls_attrs: Dict[str, list] = {
|
||||
"__ma_mode__": [],
|
||||
"__inchart__": [],
|
||||
"__subplots__": [],
|
||||
}
|
||||
new_cls = super().__new__(mcs, name, bases, attrs, **kwargs)
|
||||
for base in reversed(new_cls.__mro__):
|
||||
for elem, value in base.__dict__.items():
|
||||
if elem in indicators:
|
||||
del indicators[elem]
|
||||
|
||||
is_static_method = isinstance(value, staticmethod)
|
||||
if is_static_method:
|
||||
value = value.__func__
|
||||
if isinstance(value, Indicator):
|
||||
if is_static_method:
|
||||
raise TypeError(
|
||||
f"Indicator {value.name} can't be a static method"
|
||||
)
|
||||
indicators[value.name] = value
|
||||
elif is_static_method and elem not in new_cls.__static_methods__:
|
||||
new_cls.__static_methods__.append(elem)
|
||||
|
||||
if elem in ["__ma_mode__", "__inchart__", "__subplots__"]:
|
||||
cls_attrs[elem].extend(value)
|
||||
|
||||
new_cls.__indicators__ = list(indicators.values())
|
||||
new_cls.__static_methods__ = list(set(new_cls.__static_methods__))
|
||||
new_cls.__ma_mode__ = list(set(cls_attrs["__ma_mode__"]))
|
||||
new_cls.__inchart__ = list(set(cls_attrs["__inchart__"]))
|
||||
new_cls.__subplots__ = list(set(cls_attrs["__subplots__"]))
|
||||
|
||||
return new_cls
|
||||
|
||||
def __iter__(cls: Type["PluginMeta"]) -> Iterator[Indicator]: # type: ignore
|
||||
return iter(cls.__indicators__)
|
||||
|
||||
# pylint: disable=unused-argument
|
||||
def __init__(cls, *args: Any, **kwargs: Any) -> None:
|
||||
super().__init__(*args, **kwargs)
|
||||
|
||||
|
||||
class PltTA(metaclass=PluginMeta):
|
||||
"""The base class that all Plotly plugins must inherit from."""
|
||||
|
||||
indicators: ChartIndicators
|
||||
intraday: bool = False
|
||||
df_stock: pd.DataFrame
|
||||
df_ta: pd.DataFrame
|
||||
df_fib: pd.DataFrame
|
||||
close_column: Optional[str] = "close"
|
||||
params: Dict[str, TAIndicator] = {}
|
||||
inchart_colors: List[str] = []
|
||||
show_volume: bool = True
|
||||
|
||||
__static_methods__: list = []
|
||||
__indicators__: List[Indicator] = []
|
||||
__ma_mode__: List[str] = []
|
||||
__inchart__: List[str] = []
|
||||
__subplots__: List[str] = []
|
||||
|
||||
# pylint: disable=unused-argument
|
||||
def __new__(cls, *args: Any, **kwargs: Any) -> "PltTA":
|
||||
if cls is PltTA:
|
||||
raise TypeError("Can't instantiate abstract class Plugin directly")
|
||||
self = super().__new__(cls)
|
||||
|
||||
static_methods = cls.__static_methods__
|
||||
indicators = cls.__indicators__
|
||||
|
||||
for item in indicators:
|
||||
# we make sure that the indicator is bound to the instance
|
||||
if not hasattr(self, item.name):
|
||||
setattr(self, item.name, item.func.__get__(self, cls))
|
||||
|
||||
for static_method in static_methods:
|
||||
if not hasattr(self, static_method):
|
||||
setattr(self, static_method, staticmethod(getattr(self, static_method)))
|
||||
|
||||
for attr, value in cls.__dict__.items():
|
||||
if attr in [
|
||||
"__ma_mode__",
|
||||
"__inchart__",
|
||||
"__subplots__",
|
||||
] and value not in getattr(self, attr):
|
||||
getattr(self, attr).extend(value)
|
||||
|
||||
return self
|
||||
|
||||
@property
|
||||
def ma_mode(self) -> List[str]:
|
||||
return list(set(self.__ma_mode__))
|
||||
|
||||
@ma_mode.setter
|
||||
def ma_mode(self, value: List[str]):
|
||||
self.__ma_mode__ = value
|
||||
|
||||
def add_plugins(self, plugins: List["PltTA"]) -> None:
|
||||
"""Add plugins to current instance"""
|
||||
for plugin in plugins:
|
||||
for item in plugin.__indicators__:
|
||||
# pylint: disable=unnecessary-dunder-call
|
||||
if not hasattr(self, item.name):
|
||||
setattr(self, item.name, item.func.__get__(self, type(self)))
|
||||
self.__indicators__.append(item)
|
||||
|
||||
for static_method in plugin.__static_methods__:
|
||||
if not hasattr(self, static_method):
|
||||
setattr(
|
||||
self, static_method, staticmethod(getattr(self, static_method))
|
||||
)
|
||||
for attr, value in plugin.__dict__.items():
|
||||
if attr in [
|
||||
"__ma_mode__",
|
||||
"__inchart__",
|
||||
"__subplots__",
|
||||
] and value not in getattr(self, attr):
|
||||
getattr(self, attr).extend(value)
|
||||
|
||||
def remove_plugins(self, plugins: List["PltTA"]) -> None:
|
||||
"""Remove plugins from current instance"""
|
||||
for plugin in plugins:
|
||||
for item in plugin.__indicators__:
|
||||
delattr(self, item.name)
|
||||
self.__indicators__.remove(item)
|
||||
|
||||
for static_method in plugin.__static_methods__:
|
||||
delattr(self, static_method)
|
||||
|
||||
def __iter__(self) -> Iterator[Indicator]:
|
||||
return iter(self.__indicators__)
|
||||
|
||||
def get_float_precision(self) -> str:
|
||||
"""Returns f-string precision format"""
|
||||
price = self.df_stock[self.close_column].tail(1).values[0]
|
||||
float_precision = (
|
||||
",.2f" if price > 1.10 else "" if len(str(price)) < 8 else ".6f"
|
||||
)
|
||||
return float_precision
|
||||
|
||||
|
||||
def indicator(
|
||||
name: str = "",
|
||||
**attrs: Any,
|
||||
) -> Callable:
|
||||
"""Decorator for adding indicators to a plugin class."""
|
||||
attrs["name"] = name
|
||||
|
||||
def decorator(func: Callable) -> Indicator:
|
||||
if not attrs.pop("name", ""):
|
||||
name = func.__name__
|
||||
|
||||
return Indicator(func, name, **attrs)
|
||||
|
||||
return decorator
|
||||
@@ -1,335 +0,0 @@
|
||||
# pylint: disable=C0302,R0915,R0914,R0913,R0903,R0904
|
||||
|
||||
import sys
|
||||
import warnings
|
||||
from dataclasses import dataclass
|
||||
from typing import Any, Dict, List, Optional, Union
|
||||
|
||||
import pandas as pd
|
||||
import pandas_ta as ta
|
||||
|
||||
from .ta_helpers import check_columns
|
||||
|
||||
# pylint: disable=E1123
|
||||
datacls_kwargs = {"slots": True} if sys.version_info >= (3, 10) else {}
|
||||
|
||||
|
||||
def columns_regex(df_ta: pd.DataFrame, name: str) -> List[str]:
|
||||
"""Return columns that match regex name"""
|
||||
column_name = df_ta.filter(regex=rf"{name}(?=[^\d]|$)").columns.tolist()
|
||||
|
||||
return column_name
|
||||
|
||||
|
||||
@dataclass(**datacls_kwargs)
|
||||
class Arguments:
|
||||
label: str
|
||||
values: Any
|
||||
|
||||
def __post_init__(self):
|
||||
if isinstance(self.values, list) and len(self.values) == 1:
|
||||
self.values = self.values[0]
|
||||
|
||||
|
||||
@dataclass(**datacls_kwargs)
|
||||
class TAIndicator:
|
||||
name: str
|
||||
args: List[Arguments]
|
||||
|
||||
def __post_init__(self):
|
||||
self.args = [Arguments(**arg) for arg in self.args]
|
||||
|
||||
def __iter__(self):
|
||||
"""Return iterator"""
|
||||
return iter(self.args)
|
||||
|
||||
def get_args(self, label: str) -> Union[Arguments, None]:
|
||||
"""Return arguments by label"""
|
||||
output = None
|
||||
for opt in self.args:
|
||||
if opt.label == label:
|
||||
output = opt
|
||||
return output
|
||||
|
||||
def get_argument_values(self, label: str) -> Union[List[Any], Any]:
|
||||
"""Returns arguments values by label"""
|
||||
output = []
|
||||
options = self.get_args(label)
|
||||
if options is not None:
|
||||
output = options.values
|
||||
return output
|
||||
|
||||
|
||||
@dataclass(**datacls_kwargs)
|
||||
class ChartIndicators:
|
||||
indicators: Optional[List[TAIndicator]] = None
|
||||
|
||||
def __post_init__(self):
|
||||
self.indicators = (
|
||||
[TAIndicator(**indicator) for indicator in self.indicators]
|
||||
if self.indicators
|
||||
else []
|
||||
)
|
||||
|
||||
def get_indicator(self, name: str) -> Union[TAIndicator, None]:
|
||||
"""Returns indicator with given name"""
|
||||
output = None
|
||||
for indicator in self.indicators: # type: ignore
|
||||
if indicator.name == name:
|
||||
output = indicator
|
||||
return output
|
||||
|
||||
def get_indicator_args(self, name: str, label: str) -> Union[Arguments, None]:
|
||||
"""Returns argument values for given indicator and label"""
|
||||
output = None
|
||||
indicator = self.get_indicator(name)
|
||||
if indicator is not None:
|
||||
output = indicator.get_args(label)
|
||||
if output is not None:
|
||||
output = output.values
|
||||
return output
|
||||
|
||||
def get_indicators(self) -> Optional[List[TAIndicator]]:
|
||||
"""Return active indicators and their arguments"""
|
||||
return self.indicators
|
||||
|
||||
def get_params(self) -> Dict[str, TAIndicator]:
|
||||
"""Return dictionary of active indicators and their arguments"""
|
||||
output = {}
|
||||
if self.indicators:
|
||||
output = {indicator.name: indicator for indicator in self.indicators}
|
||||
return output
|
||||
|
||||
def get_active_ids(self) -> List[str]:
|
||||
"""Returns list of names of active indicators"""
|
||||
active_ids = []
|
||||
if self.indicators:
|
||||
active_ids = [indicator.name for indicator in self.indicators]
|
||||
return active_ids
|
||||
|
||||
def get_arg_names(self, name: str) -> List[str]:
|
||||
"""Returns list of argument labels for given indicator"""
|
||||
output = []
|
||||
indicator = self.get_indicator(name)
|
||||
if indicator is not None:
|
||||
for opt in indicator.args:
|
||||
output.append(opt.label)
|
||||
return output
|
||||
|
||||
def get_options_dict(self, name: str) -> Dict[str, Optional[Arguments]]:
|
||||
"""Returns dictionary of argument labels and values for given indicator"""
|
||||
output = None
|
||||
options = self.get_arg_names(name)
|
||||
if options:
|
||||
output = {}
|
||||
for opt in options:
|
||||
output[opt] = self.get_indicator_args(name, opt)
|
||||
|
||||
return output
|
||||
|
||||
@classmethod
|
||||
def from_dict(cls, indicators: Dict[str, Dict[str, Any]]) -> "ChartIndicators":
|
||||
"""Return ChartIndicators from dictionary"""
|
||||
data = []
|
||||
for indicator in indicators:
|
||||
args = []
|
||||
for arg in indicators[indicator]:
|
||||
args.append({"label": arg, "values": indicators[indicator][arg]})
|
||||
data.append({"name": indicator, "args": args})
|
||||
|
||||
return cls(indicators=data) # type: ignore
|
||||
|
||||
def to_dataframe(
|
||||
self, df_ta: pd.DataFrame, ma_mode: Optional[List[str]] = None
|
||||
) -> pd.DataFrame:
|
||||
"""Calculate technical analysis indicators and return dataframe."""
|
||||
output = df_ta.copy()
|
||||
if not output.empty and self.indicators:
|
||||
try:
|
||||
output = TA_Data(output, self, ma_mode).to_dataframe()
|
||||
except Exception as err:
|
||||
warnings.warn(str(err))
|
||||
|
||||
return output
|
||||
|
||||
def get_indicator_data(self, df_ta: pd.DataFrame, indicator: TAIndicator, **kwargs):
|
||||
"""Return dataframe with technical analysis indicators."""
|
||||
output = None
|
||||
if self.indicators:
|
||||
try:
|
||||
output = TA_Data(df_ta, self).get_indicator_data(indicator, **kwargs)
|
||||
except Exception as err:
|
||||
warnings.warn(str(err))
|
||||
|
||||
return output
|
||||
|
||||
def remove_indicator(self, name: str) -> None:
|
||||
"""Remove indicator from active indicators"""
|
||||
if self.indicators:
|
||||
for indicator in self.indicators:
|
||||
if indicator.name == name:
|
||||
self.indicators.remove(indicator)
|
||||
|
||||
|
||||
class TA_DataException(Exception):
|
||||
pass
|
||||
|
||||
|
||||
class TA_Data:
|
||||
"""Process technical analysis data
|
||||
|
||||
|
||||
Parameters
|
||||
----------
|
||||
df_ta : pd.DataFrame
|
||||
Dataframe with OHLCV data
|
||||
indicators : Union[ChartIndicators, Dict[str, Dict[str, Any]]]
|
||||
ChartIndicators object or dictionary with indicators and arguments
|
||||
Example:
|
||||
dict(
|
||||
sma=dict(length=[20, 50, 100]),
|
||||
adx=dict(length=14),
|
||||
macd=dict(fast=12, slow=26, signal=9),
|
||||
rsi=dict(length=14),
|
||||
)
|
||||
|
||||
|
||||
Methods
|
||||
-------
|
||||
to_dataframe()
|
||||
Return dataframe with technical analysis indicators
|
||||
get_indicator_data(indicator: TAIndicator, **kwargs)
|
||||
Return dataframe given indicator and arguments
|
||||
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
df_ta: Union[pd.DataFrame, pd.Series],
|
||||
indicators: Union[ChartIndicators, Dict[str, Dict[str, Any]]],
|
||||
ma_mode: Optional[List[str]] = None,
|
||||
):
|
||||
if isinstance(df_ta, pd.Series):
|
||||
df_ta = df_ta.to_frame()
|
||||
|
||||
if not isinstance(indicators, ChartIndicators):
|
||||
indicators = ChartIndicators.from_dict(indicators)
|
||||
|
||||
self.df_ta: pd.DataFrame = df_ta
|
||||
self.indicators: ChartIndicators = indicators
|
||||
self.ma_mode: List[str] = ma_mode or ["sma", "ema", "wma", "hma", "zlma", "rma"]
|
||||
self.close_col = check_columns(df_ta)
|
||||
if self.close_col is None:
|
||||
raise ValueError("No close column found in dataframe")
|
||||
|
||||
self.columns: Dict[str, List[str]] = {
|
||||
"ad": ["high", "low", self.close_col, "volume"],
|
||||
"adosc": ["high", "low", self.close_col, "volume"],
|
||||
"adx": ["high", "low", self.close_col],
|
||||
"aroon": ["high", "low"],
|
||||
"atr": ["high", "low", self.close_col],
|
||||
"cci": ["high", "low", self.close_col],
|
||||
"donchian": ["high", "low"],
|
||||
"fisher": ["high", "low"],
|
||||
"kc": ["high", "low", self.close_col],
|
||||
"obv": [self.close_col, "volume"],
|
||||
"stoch": ["high", "low", self.close_col],
|
||||
"vwap": ["high", "low", self.close_col, "volume"],
|
||||
}
|
||||
|
||||
self.has_volume = "volume" in df_ta.columns and bool(df_ta["volume"].sum() > 0)
|
||||
|
||||
def get_indicator_data(self, indicator: TAIndicator, **args) -> pd.DataFrame:
|
||||
"""Returns dataframe with indicator data
|
||||
|
||||
Parameters
|
||||
----------
|
||||
indicator : TAIndicator
|
||||
TAIndicator object
|
||||
args : dict
|
||||
Arguments for given indicator
|
||||
|
||||
Returns
|
||||
-------
|
||||
pd.DataFrame
|
||||
Dataframe with indicator data
|
||||
"""
|
||||
output = None
|
||||
if indicator and indicator.name in self.ma_mode:
|
||||
if isinstance(indicator.get_argument_values("length"), list):
|
||||
df_ta = pd.DataFrame()
|
||||
|
||||
for length in indicator.get_argument_values("length"):
|
||||
df_ma = getattr(ta, indicator.name)(
|
||||
self.df_ta[self.close_col], length=length
|
||||
)
|
||||
df_ta.insert(0, f"{indicator.name.upper()}_{length}", df_ma)
|
||||
|
||||
output = df_ta
|
||||
|
||||
else:
|
||||
output = getattr(ta, indicator.name)(
|
||||
self.df_ta[self.close_col],
|
||||
length=indicator.get_argument_values("length"),
|
||||
)
|
||||
if indicator.name == "zlma" and output is not None:
|
||||
output.name = output.name.replace("ZL_EMA", "ZLMA")
|
||||
|
||||
elif indicator.name == "vwap":
|
||||
ta_columns = self.columns[indicator.name]
|
||||
ta_columns = [self.df_ta[col] for col in ta_columns] # type: ignore
|
||||
|
||||
output = getattr(ta, indicator.name)(
|
||||
*ta_columns,
|
||||
)
|
||||
elif indicator.name in self.columns:
|
||||
ta_columns = self.columns[indicator.name]
|
||||
ta_columns = [self.df_ta[col] for col in ta_columns] # type: ignore
|
||||
|
||||
if indicator.get_argument_values("use_open") is True:
|
||||
ta_columns.append(self.df_ta["open"])
|
||||
|
||||
output = getattr(ta, indicator.name)(*ta_columns, **args)
|
||||
else:
|
||||
output = getattr(ta, indicator.name)(self.df_ta[self.close_col], **args)
|
||||
|
||||
# Drop NaN values from output and return None if empty
|
||||
if output is not None:
|
||||
output.dropna(inplace=True)
|
||||
if output.empty:
|
||||
output = None
|
||||
|
||||
return output
|
||||
|
||||
def to_dataframe(self) -> pd.DataFrame:
|
||||
"""Returns dataframe with all indicators"""
|
||||
active_indicators = self.indicators.get_indicators()
|
||||
|
||||
if not active_indicators:
|
||||
return None
|
||||
|
||||
output = self.df_ta
|
||||
for indicator in active_indicators:
|
||||
if (
|
||||
indicator.name in self.columns
|
||||
and "volume" in self.columns[indicator.name]
|
||||
and not self.has_volume
|
||||
):
|
||||
continue
|
||||
if indicator.name in ["fib", "srlines", "clenow", "demark", "ichimoku"]:
|
||||
continue
|
||||
try:
|
||||
indicator_data = self.get_indicator_data(
|
||||
indicator,
|
||||
**self.indicators.get_options_dict(indicator.name) or {},
|
||||
)
|
||||
except Exception as e:
|
||||
indicator_data = None
|
||||
raise TA_DataException(
|
||||
f"Error processing indicator {indicator.name}: {e}"
|
||||
) from e
|
||||
|
||||
if indicator_data is not None:
|
||||
output = output.join(indicator_data).interpolate("linear")
|
||||
|
||||
return output
|
||||
@@ -1,211 +0,0 @@
|
||||
import warnings
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from openbb_charting.core.config.openbb_styles import PLT_FIB_COLORWAY
|
||||
from openbb_charting.core.openbb_figure import OpenBBFigure
|
||||
from openbb_charting.core.plotly_ta.base import PltTA, indicator
|
||||
|
||||
|
||||
class Custom(PltTA):
|
||||
"""Volatility technical indicators."""
|
||||
|
||||
@indicator()
|
||||
def plot_srlines(self, fig: OpenBBFigure, df_ta: pd.DataFrame):
|
||||
"""Add support and resistance lines to plotly figure."""
|
||||
window = self.params["srlines"].get_argument_values("window")
|
||||
window = window[0] if isinstance(window, list) and len(window) > 0 else 200
|
||||
|
||||
def is_far_from_level(value, levels, df_stock):
|
||||
ave = np.mean(df_stock["high"] - df_stock["low"])
|
||||
return np.sum([abs(value - level) < ave for _, level in levels]) == 0
|
||||
|
||||
def is_support(df, i):
|
||||
cond1 = df["low"][i] < df["low"][i - 1]
|
||||
cond2 = df["low"][i] < df["low"][i + 1]
|
||||
cond3 = df["low"][i + 1] < df["low"][i + 2]
|
||||
cond4 = df["low"][i - 1] < df["low"][i - 2]
|
||||
return cond1 and cond2 and cond3 and cond4
|
||||
|
||||
def is_resistance(df, i):
|
||||
cond1 = df["high"][i] > df["high"][i - 1]
|
||||
cond2 = df["high"][i] > df["high"][i + 1]
|
||||
cond3 = df["high"][i + 1] > df["high"][i + 2]
|
||||
cond4 = df["high"][i - 1] > df["high"][i - 2]
|
||||
return cond1 and cond2 and cond3 and cond4
|
||||
|
||||
df_ta2 = df_ta.copy()
|
||||
today = pd.to_datetime(datetime.now(), unit="ns")
|
||||
start_date = pd.to_datetime(datetime.now() - timedelta(days=window), unit="ns")
|
||||
|
||||
df_ta2 = df_ta2.loc[(df_ta2.index >= start_date) & (df_ta2.index < today)]
|
||||
|
||||
if df_ta2.index[-2].date() != df_ta2.index[-1].date():
|
||||
interval = 1440
|
||||
else:
|
||||
interval = (df_ta2.index[1] - df_ta2.index[0]).seconds / 60
|
||||
|
||||
if interval <= 15:
|
||||
cut_days = 1 if interval < 15 else 2
|
||||
dt_unique_days = df_ta2.index.normalize().unique()
|
||||
df_ta2 = df_ta2.loc[
|
||||
(df_ta2.index >= pd.to_datetime(dt_unique_days[-cut_days], unit="ns"))
|
||||
& (df_ta2.index < today)
|
||||
].copy()
|
||||
|
||||
levels: list = []
|
||||
x_range = df_ta2.index[-1].replace(hour=15, minute=59)
|
||||
if interval > 15:
|
||||
x_range = df_ta2.index[-1] + timedelta(days=15)
|
||||
if x_range.weekday() > 4:
|
||||
x_range = x_range + timedelta(days=7 - x_range.weekday())
|
||||
|
||||
elif df_ta2.index[-1] >= today.replace(hour=15, minute=0):
|
||||
x_range = (df_ta2.index[-1] + timedelta(days=1)).replace(hour=11, minute=0)
|
||||
if x_range.weekday() > 4:
|
||||
x_range = x_range + timedelta(days=7 - x_range.weekday())
|
||||
|
||||
for i in range(2, len(df_ta2) - 2):
|
||||
if is_support(df_ta2, i):
|
||||
lv = df_ta2["low"][i]
|
||||
if is_far_from_level(lv, levels, df_ta2):
|
||||
levels.append((i, lv))
|
||||
fig.add_scatter(
|
||||
x=[df_ta.index[0], x_range],
|
||||
y=[lv, lv],
|
||||
opacity=1,
|
||||
mode="lines+text",
|
||||
text=["", f"{lv:{self.get_float_precision()}}"],
|
||||
textposition="top center",
|
||||
textfont=dict(
|
||||
family="Arial Black", color="rgb(120, 70, 200)", size=10
|
||||
),
|
||||
line=dict(
|
||||
width=2, dash="dash", color="rgba(120, 70, 200, 0.70)"
|
||||
),
|
||||
connectgaps=True,
|
||||
showlegend=False,
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
elif is_resistance(df_ta2, i):
|
||||
lv = df_ta2["high"][i]
|
||||
if is_far_from_level(lv, levels, df_ta2):
|
||||
levels.append((i, lv))
|
||||
fig.add_scatter(
|
||||
x=[df_ta.index[0], x_range],
|
||||
y=[lv, lv],
|
||||
opacity=1,
|
||||
mode="lines+text",
|
||||
text=["", f"{lv:{self.get_float_precision()}}"],
|
||||
textposition="top center",
|
||||
textfont=dict(
|
||||
family="Arial Black", color="rgb(120, 70, 200)", size=10
|
||||
),
|
||||
line=dict(
|
||||
width=2, dash="dash", color="rgba(120, 70, 200, 0.70)"
|
||||
),
|
||||
connectgaps=True,
|
||||
showlegend=False,
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
return fig
|
||||
|
||||
@indicator()
|
||||
def plot_fib(self, fig: OpenBBFigure, df_ta: pd.DataFrame):
|
||||
"""Add fibonacci to plotly figure."""
|
||||
try:
|
||||
from openbb_ta.ta_helpers import calculate_fib_levels
|
||||
except ImportError:
|
||||
warnings.warn(
|
||||
"In order to use the Fibonacci indicator in your plot,"
|
||||
" you need to install the `openbb_ta` package."
|
||||
)
|
||||
return fig
|
||||
|
||||
limit = self.params["fib"].get_argument_values("limit") or 120
|
||||
start_date = self.params["fib"].get_argument_values("start_date") or None
|
||||
end_date = self.params["fib"].get_argument_values("end_date") or None
|
||||
close = self.params["fib"].get_argument_values("close") or "close"
|
||||
(
|
||||
df_fib,
|
||||
min_date,
|
||||
max_date,
|
||||
min_pr,
|
||||
max_pr,
|
||||
lvl_text,
|
||||
) = calculate_fib_levels(df_ta, close, limit, start_date, end_date)
|
||||
levels = df_fib.Price
|
||||
fibs = [
|
||||
"<b>0</b>",
|
||||
"<b>0.235</b>",
|
||||
"<b>0.382</b>",
|
||||
"<b>0.5</b>",
|
||||
"<b>0.618</b>",
|
||||
"<b>0.65</b>",
|
||||
"<b>1</b>",
|
||||
]
|
||||
min_date = pd.to_datetime(min_date).to_pydatetime()
|
||||
max_date = pd.to_datetime(max_date).to_pydatetime()
|
||||
self.df_fib = df_fib # pylint: disable=attribute-defined-outside-init
|
||||
|
||||
fig.add_scatter(
|
||||
x=[min_date, max_date],
|
||||
y=[min_pr, max_pr],
|
||||
opacity=0.85,
|
||||
mode="lines",
|
||||
connectgaps=True,
|
||||
line=PLT_FIB_COLORWAY[8],
|
||||
showlegend=False,
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
df_ta2 = df_ta.copy()
|
||||
interval = 1440
|
||||
if df_ta2.index[-2].date() == df_ta2.index[-1].date():
|
||||
interval = (df_ta2.index[1] - df_ta2.index[0]).seconds / 60
|
||||
dt_unique_days = df_ta2.index.normalize().unique()
|
||||
|
||||
if interval not in [15, 30, 60] and len(dt_unique_days) <= 3:
|
||||
df_ta2 = df_ta2.loc[
|
||||
(df_ta2.index >= dt_unique_days[-1])
|
||||
& (df_ta2.index < datetime.now())
|
||||
].copy()
|
||||
df_ta2 = df_ta2.between_time("09:30", "20:00").copy()
|
||||
|
||||
for i in range(7):
|
||||
idx_int = 4 if lvl_text == "left" else 5
|
||||
text_pos = f"bottom {lvl_text}" if i != idx_int else f"top {lvl_text}"
|
||||
|
||||
if fibs[i] == "<b>0</b>":
|
||||
text_pos = (
|
||||
f"top {lvl_text}" if lvl_text != "right" else f"bottom {lvl_text}"
|
||||
)
|
||||
text = ["", f"<b>{fibs[i]} ({levels[i]:{self.get_float_precision()}})</b>"]
|
||||
if lvl_text == "right":
|
||||
text = [text[1], text[0]]
|
||||
|
||||
fig.add_scatter(
|
||||
name=fibs[i],
|
||||
x=[min_date, df_ta2.index.max()],
|
||||
y=[levels[i], levels[i]],
|
||||
opacity=0.9,
|
||||
mode="lines+text",
|
||||
text=text,
|
||||
textposition=text_pos,
|
||||
textfont=dict(PLT_FIB_COLORWAY[7], color=PLT_FIB_COLORWAY[i]),
|
||||
line_color=PLT_FIB_COLORWAY[i],
|
||||
line_width=1.5,
|
||||
showlegend=False,
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
return fig
|
||||
@@ -1,624 +0,0 @@
|
||||
import warnings
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
import pandas_ta as ta
|
||||
from openbb_charting.core.openbb_figure import OpenBBFigure
|
||||
from openbb_charting.core.plotly_ta.base import (
|
||||
PltTA,
|
||||
indicator,
|
||||
)
|
||||
from openbb_charting.core.plotly_ta.data_classes import (
|
||||
columns_regex,
|
||||
)
|
||||
|
||||
|
||||
class Momentum(PltTA):
|
||||
"""Momentum technical indicators."""
|
||||
|
||||
__subplots__ = ["rsi", "macd", "stoch", "cci", "fisher", "cg"]
|
||||
__inchart__ = ["clenow", "demark", "ichimoku"]
|
||||
|
||||
@indicator()
|
||||
def plot_cci(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Add CCI to plotly figure."""
|
||||
cci_col = columns_regex(df_ta, "CCI")[0]
|
||||
dmax = df_ta[cci_col].max()
|
||||
dmin = df_ta[cci_col].min()
|
||||
fig.add_scatter(
|
||||
name="CCI",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="#e0b700"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[cci_col].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_hrect(
|
||||
y0=100,
|
||||
y1=dmax,
|
||||
fillcolor=fig.theme.down_color,
|
||||
opacity=0.2,
|
||||
layer="below",
|
||||
line_width=0,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_hrect(
|
||||
y0=-100,
|
||||
y1=dmin,
|
||||
fillcolor=fig.theme.up_color,
|
||||
opacity=0.2,
|
||||
layer="below",
|
||||
line_width=0,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_hline(
|
||||
y=100,
|
||||
opacity=1,
|
||||
layer="below",
|
||||
line=dict(width=2, color=fig.theme.down_color, dash="dash"),
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_hline(
|
||||
y=-100,
|
||||
opacity=1,
|
||||
layer="below",
|
||||
line=dict(width=2, color=fig.theme.up_color, dash="dash"),
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>CCI</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.97,
|
||||
font_size=14,
|
||||
font_color="#e0b700",
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row + 1}"].update(nticks=5, autorange=True)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
|
||||
@indicator()
|
||||
def plot_cg(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Add cg to plotly figure."""
|
||||
cg_col = columns_regex(df_ta, "CG")[0]
|
||||
fig.add_scatter(
|
||||
name="CG",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="#ffed00"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[cg_col].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name="Signal",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="#ef7d00"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[cg_col].shift(1),
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>CG</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-10,
|
||||
y=0.97,
|
||||
font_size=14,
|
||||
font_color="#ffed00",
|
||||
)
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="Signal",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.97,
|
||||
yshift=-20,
|
||||
font_size=14,
|
||||
font_color="#ef7d00",
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row + 1}"].update(nticks=5, autorange=True)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
|
||||
@indicator()
|
||||
def plot_clenow(self, fig: OpenBBFigure, df_ta: pd.DataFrame, inchart_index: int):
|
||||
"""Add current close price to plotly figure."""
|
||||
|
||||
try:
|
||||
from openbb_ta.ta_helpers import clenow_momentum
|
||||
except ImportError:
|
||||
warnings.warn(
|
||||
"In order to use the Clenow momentum indicator in your plot,"
|
||||
" you need to install the `openbb_ta` package."
|
||||
)
|
||||
return fig, inchart_index
|
||||
|
||||
window = self.params["clenow"].get_argument_values("window") or 90
|
||||
_, _, fit_data = clenow_momentum(df_ta[self.close_column], window=window)
|
||||
|
||||
fig.add_scatter(
|
||||
x=df_ta.index[-window:], # type: ignore
|
||||
y=pow(np.e, fit_data),
|
||||
name="CLenow",
|
||||
mode="lines",
|
||||
line=dict(color=self.inchart_colors[inchart_index], width=2),
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_annotation(
|
||||
xref="paper",
|
||||
yref="paper",
|
||||
text="<b>CLenow</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
yshift=-inchart_index * 18,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color=self.inchart_colors[inchart_index],
|
||||
opacity=1,
|
||||
)
|
||||
return fig, inchart_index + 1
|
||||
|
||||
@indicator()
|
||||
def plot_demark(self, fig: OpenBBFigure, df_ta: pd.DataFrame, inchart_index: int):
|
||||
"""Add demark to plotly figure."""
|
||||
min_val = self.params["demark"].get_argument_values("min_val") or 5
|
||||
|
||||
demark = ta.td_seq(df_ta[self.close_column], asint=True)
|
||||
demark = demark.set_index(df_ta.index)
|
||||
|
||||
# pylint: disable=unsupported-assignment-operation
|
||||
demark["up"] = demark.TD_SEQ_UPa.apply(
|
||||
lambda x: f"<b>{x}</b>" if x >= min_val else None
|
||||
)
|
||||
|
||||
# pylint: disable=unsupported-assignment-operation
|
||||
demark["down"] = demark.TD_SEQ_DNa.apply(
|
||||
lambda x: f"<b>{x}</b>" if x >= min_val else None
|
||||
)
|
||||
|
||||
# we only keep the values that are not None in up/down columns
|
||||
high = df_ta["high"][demark["up"].notnull()]
|
||||
low = df_ta["low"][demark["down"].notnull()]
|
||||
demark = demark[demark["up"].notnull() | demark["down"].notnull()]
|
||||
|
||||
fig.add_scatter(
|
||||
x=low.index,
|
||||
y=low,
|
||||
name="Demark Down",
|
||||
mode="text",
|
||||
text=demark["down"],
|
||||
textposition="bottom center",
|
||||
textfont=dict(color=fig.theme.down_color, size=14.5),
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
x=high.index,
|
||||
y=high,
|
||||
name="Demark Up",
|
||||
mode="text",
|
||||
text=demark["up"],
|
||||
textposition="top center",
|
||||
textfont=dict(color=fig.theme.up_color, size=14.5),
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref="paper",
|
||||
yref="paper",
|
||||
text="<b>Demark</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
yshift=-inchart_index * 18,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color=self.inchart_colors[inchart_index],
|
||||
opacity=1,
|
||||
)
|
||||
|
||||
return fig, inchart_index + 1
|
||||
|
||||
@indicator()
|
||||
def plot_fisher(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Add fisher to plotly figure."""
|
||||
fishert_col = columns_regex(df_ta, "FISHERT")[0]
|
||||
fishers_col = columns_regex(df_ta, "FISHERTs")[0]
|
||||
fig.add_scatter(
|
||||
name="Fisher",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="#e0b700"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[fishert_col].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name="Fisher Signal",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="#9467bd"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[fishers_col].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
dmax = df_ta[fishers_col].max()
|
||||
dmin = df_ta[fishers_col].min()
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>FISHER</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color="#e0b700",
|
||||
)
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>SIGNAL</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.01,
|
||||
font_size=13,
|
||||
font_color="#9467bd",
|
||||
)
|
||||
fig.add_hrect(
|
||||
y0=2,
|
||||
y1=(dmax + 4),
|
||||
fillcolor=fig.theme.down_color,
|
||||
opacity=0.2,
|
||||
layer="below",
|
||||
line_width=0,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_hrect(
|
||||
y0=-2,
|
||||
y1=(dmin - 4),
|
||||
fillcolor=fig.theme.up_color,
|
||||
opacity=0.2,
|
||||
layer="below",
|
||||
line_width=0,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_hline(
|
||||
y=2,
|
||||
fillcolor=fig.theme.down_color,
|
||||
opacity=1,
|
||||
layer="below",
|
||||
line=dict(width=2, color=fig.theme.down_color, dash="dash"),
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_hline(
|
||||
y=-2,
|
||||
fillcolor=fig.theme.up_color,
|
||||
opacity=1,
|
||||
layer="below",
|
||||
line=dict(width=2, color=fig.theme.up_color, dash="dash"),
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row + 1}"].update(nticks=5, autorange=True)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
|
||||
@indicator()
|
||||
def plot_macd(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Add macd to plotly figure."""
|
||||
|
||||
fig.add_bar(
|
||||
name="MACD Histogram",
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "MACDh")[0]].values,
|
||||
opacity=0.9,
|
||||
marker_color="#1a97ea",
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name="MACD",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="#9467bd"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "MACD")[0]].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name="MACD Signal",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="rgb(7, 166, 52)"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "MACDs")[0]].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>MACD</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color="#9467bd",
|
||||
)
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>SIGNAL</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
y=0.70,
|
||||
font_size=13,
|
||||
xshift=-3,
|
||||
font_color="rgb(7, 166, 52)",
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row + 1}"].update(autorange=True, nticks=5)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
|
||||
@indicator()
|
||||
def plot_rsi(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Add rsi to plotly figure."""
|
||||
rsi_col = columns_regex(df_ta, "RSI")[0]
|
||||
fig.add_scatter(
|
||||
name="RSI",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="rgb(0, 122, 204, 1)"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[rsi_col].values,
|
||||
opacity=1,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>RSI</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color="rgb(0, 122, 204, 1)",
|
||||
)
|
||||
fig.add_hrect(
|
||||
y0=70,
|
||||
y1=100,
|
||||
fillcolor=fig.theme.down_color,
|
||||
opacity=0.2,
|
||||
layer="below",
|
||||
line_width=0,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_hrect(
|
||||
y0=0,
|
||||
y1=30,
|
||||
fillcolor=fig.theme.up_color,
|
||||
opacity=0.2,
|
||||
layer="below",
|
||||
line_width=0,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_hline(
|
||||
y=70,
|
||||
fillcolor=fig.theme.down_color,
|
||||
opacity=1,
|
||||
layer="below",
|
||||
line=dict(width=2, color=fig.theme.down_color, dash="dash"),
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_hline(
|
||||
y=30,
|
||||
fillcolor=fig.theme.up_color,
|
||||
opacity=1,
|
||||
layer="below",
|
||||
line=dict(width=2, color=fig.theme.up_color, dash="dash"),
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row + 1}"].update(tickvals=[0, 30, 70, 100])
|
||||
|
||||
return fig, subplot_row + 1
|
||||
|
||||
@indicator()
|
||||
def plot_stoch(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Add stoch to plotly figure."""
|
||||
fig.add_scatter(
|
||||
name="STOCH %K",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="#e0b700"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "STOCHk")[0]].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name="STOCH %D",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="#9467bd", dash="dash"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "STOCHd")[0]].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>STOCH</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color="#e0b700",
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row + 1}"].update(nticks=5, autorange=True)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
|
||||
@indicator()
|
||||
def plot_ichimoku(self, fig: OpenBBFigure, df_ta: pd.DataFrame, inchart_index: int):
|
||||
# Calculate Ichimoku indicator
|
||||
conversion_period = (
|
||||
self.params["ichimoku"].get_argument_values("conversion_period") or 9
|
||||
)
|
||||
base_period = self.params["ichimoku"].get_argument_values("base_period") or 26
|
||||
lagging_line_period = (
|
||||
self.params["ichimoku"].get_argument_values("lagging_line_period") or 52
|
||||
)
|
||||
displacement = self.params["ichimoku"].get_argument_values("displacement") or 26
|
||||
|
||||
# Tenkan-sen (Conversion Line)
|
||||
conversion_line = (
|
||||
df_ta["high"].rolling(window=conversion_period).max()
|
||||
+ df_ta["low"].rolling(window=conversion_period).min()
|
||||
) / 2
|
||||
|
||||
# Kijun-sen (Base Line)
|
||||
base_line = (
|
||||
df_ta["high"].rolling(window=base_period).max()
|
||||
+ df_ta["low"].rolling(window=base_period).min()
|
||||
) / 2
|
||||
|
||||
# Senkou Span A (Leading Span A)
|
||||
leading_span_a = ((conversion_line + base_line) / 2).shift(displacement)
|
||||
|
||||
# Senkou Span B (Leading Span B)
|
||||
lagging_line = df_ta[self.close_column].shift(-lagging_line_period) # type: ignore
|
||||
leading_span_b = (
|
||||
(
|
||||
lagging_line.rolling(window=base_period).max()
|
||||
+ lagging_line.rolling(window=base_period).min()
|
||||
)
|
||||
/ 2
|
||||
).shift(displacement)
|
||||
|
||||
# Plot Tenkan-sen and Kijun-sen
|
||||
fig.add_scatter(
|
||||
x=df_ta.index,
|
||||
y=conversion_line,
|
||||
line=dict(color="orange", width=1),
|
||||
name="Tenkan-sen",
|
||||
secondary_y=False,
|
||||
showlegend=True,
|
||||
opacity=1,
|
||||
)
|
||||
fig.add_scatter(
|
||||
x=df_ta.index,
|
||||
y=base_line,
|
||||
line=dict(color="blue", width=1),
|
||||
name="Kijun-sen",
|
||||
secondary_y=False,
|
||||
showlegend=True,
|
||||
opacity=1,
|
||||
)
|
||||
|
||||
# Plot Senkou Span A and Senkou Span B as a filled area
|
||||
fig.add_scatter(
|
||||
x=df_ta.index,
|
||||
y=leading_span_a,
|
||||
line=dict(color="#009600", width=1),
|
||||
fill="tonexty",
|
||||
fillcolor="rgba(0, 150, 0, 0.1)",
|
||||
name="Senkou Span A",
|
||||
secondary_y=False,
|
||||
showlegend=False,
|
||||
opacity=0.2,
|
||||
)
|
||||
fig.add_scatter(
|
||||
x=df_ta.index,
|
||||
y=leading_span_b,
|
||||
line=dict(color="#c80000", width=1),
|
||||
fill="tonexty",
|
||||
fillcolor="rgba(200, 0, 0, 0.1)",
|
||||
name="Senkou Span B",
|
||||
showlegend=False,
|
||||
secondary_y=False,
|
||||
opacity=0.2,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref="paper",
|
||||
yref="paper",
|
||||
text="<b><span style='color:#009600'>Ichi</span>"
|
||||
"<span style='color:#c80000'>moku</span></b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
yshift=-inchart_index * 18,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
opacity=1,
|
||||
)
|
||||
|
||||
return fig, inchart_index + 1
|
||||
@@ -1,93 +0,0 @@
|
||||
import warnings
|
||||
|
||||
import pandas as pd
|
||||
from openbb_charting.core.openbb_figure import OpenBBFigure
|
||||
from openbb_charting.core.plotly_ta.base import (
|
||||
PltTA,
|
||||
indicator,
|
||||
)
|
||||
from openbb_charting.core.plotly_ta.data_classes import (
|
||||
columns_regex,
|
||||
)
|
||||
|
||||
|
||||
class Overlap(PltTA):
|
||||
"""Overlap technical indicators"""
|
||||
|
||||
__inchart__ = ["vwap"]
|
||||
__ma_mode__ = ["sma", "ema", "wma", "hma", "zlma", "rma"]
|
||||
|
||||
@indicator()
|
||||
def plot_ma(self, fig: OpenBBFigure, df_ta: pd.DataFrame, inchart_index: int):
|
||||
"""Adds moving average to plotly figure"""
|
||||
check_ma = [ma for ma in self.ma_mode if ma in self.indicators.get_active_ids()]
|
||||
if check_ma:
|
||||
for ma in check_ma:
|
||||
column_names = columns_regex(df_ta, ma.upper())
|
||||
try:
|
||||
for column in column_names:
|
||||
if df_ta[column].empty:
|
||||
continue
|
||||
|
||||
fig.add_scatter(
|
||||
name=column.replace("RMA", "MA"),
|
||||
mode="lines",
|
||||
line=dict(
|
||||
width=1.2, color=self.inchart_colors[inchart_index]
|
||||
),
|
||||
x=df_ta.index,
|
||||
y=df_ta[column].values,
|
||||
opacity=0.9,
|
||||
connectgaps=True,
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_annotation(
|
||||
xref="paper",
|
||||
yref="paper",
|
||||
text=f"<b>{column.replace('_', '').replace('RMA', 'MA')}</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
yshift=-inchart_index * 18,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color=self.inchart_colors[inchart_index],
|
||||
opacity=1,
|
||||
)
|
||||
inchart_index += 1
|
||||
|
||||
except Exception as e:
|
||||
warnings.warn(f"Error adding {ma.upper()} to plot - {e}")
|
||||
|
||||
return fig, inchart_index
|
||||
|
||||
@indicator()
|
||||
def plot_vwap(self, fig: OpenBBFigure, df_ta: pd.DataFrame, inchart_index: int):
|
||||
"""Adds vwap to plotly figure"""
|
||||
fig.add_scatter(
|
||||
name=columns_regex(df_ta, "VWAP_")[0],
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color=self.inchart_colors[inchart_index]),
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "VWAP_")[0]].values,
|
||||
opacity=0.8,
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_annotation(
|
||||
xref="paper",
|
||||
yref="paper",
|
||||
text="<b>VWAP</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
yshift=-inchart_index * 18,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color=self.inchart_colors[inchart_index],
|
||||
)
|
||||
|
||||
return fig, inchart_index + 1
|
||||
@@ -1,194 +0,0 @@
|
||||
import pandas as pd
|
||||
from openbb_charting.core.openbb_figure import OpenBBFigure
|
||||
from openbb_charting.core.plotly_ta.base import (
|
||||
PltTA,
|
||||
indicator,
|
||||
)
|
||||
from openbb_charting.core.plotly_ta.data_classes import (
|
||||
columns_regex,
|
||||
)
|
||||
|
||||
|
||||
class Trend(PltTA):
|
||||
"""Trend technical indicators."""
|
||||
|
||||
__subplots__ = ["adx", "aroon"]
|
||||
|
||||
@indicator()
|
||||
def plot_adx(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Add ADX to plotly figure."""
|
||||
fig.add_scatter(
|
||||
name="ADX",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="#e0b700"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "ADX")[0]].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name="+DI",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color=fig.theme.up_color),
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "DMP")[0]].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name="-DI",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color=fig.theme.down_color),
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "DMN")[0]].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>ADX</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.97,
|
||||
font_size=14,
|
||||
font_color="#e0b700",
|
||||
)
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text=(
|
||||
f"<span style='color: {fig.theme.up_color}'>D+</span><br>"
|
||||
f"<span style='color: {fig.theme.down_color}'>D-</span>"
|
||||
),
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-14,
|
||||
y=0.97,
|
||||
yshift=-20,
|
||||
font_size=14,
|
||||
font_color=fig.theme.up_color,
|
||||
)
|
||||
fig.add_hline(
|
||||
y=25,
|
||||
fillcolor="white",
|
||||
opacity=1,
|
||||
layer="below",
|
||||
line_width=1.5,
|
||||
line=dict(color="white", dash="dash"),
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row + 1}"].update(nticks=5, autorange=True)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
|
||||
@indicator()
|
||||
def plot_aroon(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Adds aroon to plotly figure"""
|
||||
aroon_up_col = columns_regex(df_ta, "AROONU")[0]
|
||||
aroon_down_col = columns_regex(df_ta, "AROOND")[0]
|
||||
aroon_osc_col = columns_regex(df_ta, "AROONOSC")[0]
|
||||
fig.add_scatter(
|
||||
name="Aroon Up",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color=fig.theme.up_color),
|
||||
x=df_ta.index,
|
||||
y=df_ta[aroon_up_col].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name="Aroon Down",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color=fig.theme.down_color),
|
||||
x=df_ta.index,
|
||||
y=df_ta[aroon_down_col].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>Aroon</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=1,
|
||||
font_size=14,
|
||||
font_color="#e0b700",
|
||||
)
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text=(
|
||||
f"<span style='color: {fig.theme.up_color}'>↑</span><br>"
|
||||
f"<span style='color: {fig.theme.down_color}'>↓</span>"
|
||||
),
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-14,
|
||||
y=0.75,
|
||||
font_size=14,
|
||||
font_color=fig.theme.down_color,
|
||||
)
|
||||
fig.add_hline(
|
||||
y=50,
|
||||
fillcolor="white",
|
||||
opacity=1,
|
||||
layer="below",
|
||||
line_width=1.5,
|
||||
line=dict(color="white", dash="dash"),
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
subplot_row += 1
|
||||
|
||||
fig.add_scatter(
|
||||
name="Aroon Oscillator",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color="#e0b700"),
|
||||
x=df_ta.index,
|
||||
y=df_ta[aroon_osc_col].values,
|
||||
connectgaps=True,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>Aroon<br>OSC</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color="#e0b700",
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row + 1}"].update(
|
||||
tickvals=[-100, 0, 100],
|
||||
ticktext=["-100", "0", "100"],
|
||||
nticks=5,
|
||||
autorange=True,
|
||||
)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
@@ -1,223 +0,0 @@
|
||||
import pandas as pd
|
||||
from openbb_charting.core.openbb_figure import OpenBBFigure
|
||||
from openbb_charting.core.plotly_ta.base import (
|
||||
PltTA,
|
||||
indicator,
|
||||
)
|
||||
from openbb_charting.core.plotly_ta.data_classes import (
|
||||
columns_regex,
|
||||
)
|
||||
|
||||
|
||||
class Volatility(PltTA):
|
||||
"""Volatility technical indicators"""
|
||||
|
||||
__inchart__ = ["bbands", "donchian", "kc"]
|
||||
__subplots__ = ["atr"]
|
||||
|
||||
@indicator()
|
||||
def plot_atr(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Adds average true range to plotly figure"""
|
||||
|
||||
fig.add_scatter(
|
||||
name=f"{columns_regex(df_ta, 'ATR')[0]}",
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "ATR")[0]].values,
|
||||
mode="lines",
|
||||
line=dict(width=1, color=fig.theme.get_colors()[1]),
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>ATR</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color=fig.theme.get_colors()[1],
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row}"].update(nticks=5, autorange=True)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
|
||||
@indicator()
|
||||
def plot_bbands(self, fig: OpenBBFigure, df_ta: pd.DataFrame, inchart_index: int):
|
||||
"""Adds bollinger bands to plotly figure"""
|
||||
|
||||
bbands_opacity = 0.8 if fig.theme.plt_style == "light" else 1
|
||||
|
||||
fig.add_scatter(
|
||||
name=f"{columns_regex(df_ta, 'BBU')[0]}",
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "BBU")[0]].values,
|
||||
opacity=bbands_opacity,
|
||||
mode="lines",
|
||||
line=dict(width=1, color=fig.theme.up_color),
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name=f"{columns_regex(df_ta, 'BBL')[0]}",
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "BBL")[0]].values,
|
||||
opacity=bbands_opacity,
|
||||
mode="lines",
|
||||
line=dict(width=1, color=fig.theme.down_color),
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name=f"{columns_regex(df_ta, 'BBM')[0]}",
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "BBM")[0]].values,
|
||||
opacity=1,
|
||||
mode="lines",
|
||||
line=dict(width=1, color=fig.theme.get_colors()[1], dash="dash"),
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
bbands_text = (
|
||||
columns_regex(df_ta, "BBL")[0].replace("BBL_", "BB").replace("_", ",")
|
||||
)
|
||||
if float(bbands_text.split(",")[1]) % 1 == 0:
|
||||
bbands_text = bbands_text.split(".")[0]
|
||||
fig.add_annotation(
|
||||
xref="paper",
|
||||
yref="paper",
|
||||
text=f"<b>{bbands_text}</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
yshift=-inchart_index * 18,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color=fig.theme.get_colors()[1],
|
||||
opacity=0.9,
|
||||
)
|
||||
|
||||
return fig, inchart_index + 1
|
||||
|
||||
@indicator()
|
||||
def plot_donchian(self, fig: OpenBBFigure, df_ta: pd.DataFrame, inchart_index: int):
|
||||
"""Adds donchian channels to plotly figure"""
|
||||
|
||||
if fig.theme.plt_style == "light":
|
||||
fillcolor = "rgba(239, 103, 137, 0.05)"
|
||||
donchian_opacity = 0.4
|
||||
else:
|
||||
fillcolor = "rgba(239, 103, 137, 0.05)"
|
||||
donchian_opacity = 0.4
|
||||
|
||||
fig.add_scatter(
|
||||
name=f"{columns_regex(df_ta, 'DCU')[0]}",
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "DCU")[0]].values,
|
||||
opacity=donchian_opacity,
|
||||
mode="lines",
|
||||
line=dict(width=0.3, color="#EF6689"),
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name=f"{columns_regex(df_ta, 'DCL')[0]}",
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "DCL")[0]].values,
|
||||
opacity=donchian_opacity,
|
||||
mode="lines",
|
||||
line=dict(width=0.3, color="#EF6689"),
|
||||
fill="tonexty",
|
||||
fillcolor=fillcolor,
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
donchian_text = (
|
||||
columns_regex(df_ta, "DCL")[0]
|
||||
.replace("DCL_", "DC")
|
||||
.replace("_", ",")
|
||||
.split(".")[0]
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref="paper",
|
||||
yref="paper",
|
||||
text=f"<b>{donchian_text}</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
yshift=-inchart_index * 18,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color="#B47DA0",
|
||||
opacity=0.9,
|
||||
)
|
||||
|
||||
return fig, inchart_index + 1
|
||||
|
||||
@indicator()
|
||||
def plot_kc(self, fig: OpenBBFigure, df_ta: pd.DataFrame, inchart_index: int):
|
||||
"""Adds Keltner channels to plotly figure"""
|
||||
mamode = (self.params["kc"].get_argument_values("mamode") or "ema").lower() # type: ignore
|
||||
|
||||
if fig.theme.plt_style == "light":
|
||||
fillcolor = "rgba(239, 103, 137, 0.05)"
|
||||
kc_opacity = 0.4
|
||||
else:
|
||||
fillcolor = "rgba(239, 103, 137, 0.05)"
|
||||
kc_opacity = 0.4
|
||||
|
||||
fig.add_scatter(
|
||||
name=f"{columns_regex(df_ta, 'KCU')[0]}",
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "KCU")[0]].values,
|
||||
opacity=kc_opacity,
|
||||
mode="lines",
|
||||
line=dict(width=0.3, color="#EF6689"),
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.add_scatter(
|
||||
name=f"{columns_regex(df_ta, 'KCL')[0]}",
|
||||
x=df_ta.index,
|
||||
y=df_ta[columns_regex(df_ta, "KCL")[0]].values,
|
||||
opacity=kc_opacity,
|
||||
mode="lines",
|
||||
line=dict(width=0.3, color="#EF6689"),
|
||||
fill="tonexty",
|
||||
fillcolor=fillcolor,
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
kctext = (
|
||||
columns_regex(df_ta, "KCL")[0]
|
||||
.replace(f"KCL{mamode[0]}_", "KC")
|
||||
.replace("_", ",")
|
||||
.split(".")[0]
|
||||
)
|
||||
fig.add_annotation(
|
||||
xref="paper",
|
||||
yref="paper",
|
||||
text=f"<b>{kctext}</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
yshift=-inchart_index * 18,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color="#B47DA0",
|
||||
opacity=0.9,
|
||||
)
|
||||
|
||||
return fig, inchart_index + 1
|
||||
@@ -1,122 +0,0 @@
|
||||
import pandas as pd
|
||||
from openbb_charting.core.openbb_figure import OpenBBFigure
|
||||
from openbb_charting.core.plotly_ta.base import (
|
||||
PltTA,
|
||||
indicator,
|
||||
)
|
||||
from openbb_charting.core.plotly_ta.data_classes import (
|
||||
columns_regex,
|
||||
)
|
||||
|
||||
|
||||
class Volume(PltTA):
|
||||
"""Volume technical indicators."""
|
||||
|
||||
__subplots__ = ["ad", "adosc", "obv"]
|
||||
|
||||
# Useless super delegation
|
||||
# def __init__(self, *args, **kwargs):
|
||||
# super().__init__(*args, **kwargs)
|
||||
|
||||
@indicator()
|
||||
def plot_ad(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Adds ad to plotly figure"""
|
||||
ad_col = columns_regex(df_ta, "AD")[0]
|
||||
fig.add_scatter(
|
||||
name="AD",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color=fig.theme.get_colors()[1]),
|
||||
x=df_ta.index,
|
||||
y=df_ta[ad_col].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_hline(
|
||||
y=0,
|
||||
fillcolor="white",
|
||||
opacity=1,
|
||||
layer="below",
|
||||
line=dict(color="white", dash="dash", width=2),
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>AD</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color=fig.theme.get_colors()[1],
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row + 1}"].update(nticks=3, autorange=True)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
|
||||
@indicator()
|
||||
def plot_adosc(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Adds adosc to plotly figure"""
|
||||
ad_col = columns_regex(df_ta, "ADOSC")[0]
|
||||
fig.add_scatter(
|
||||
name="ADOSC",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color=fig.theme.get_colors()[1]),
|
||||
x=df_ta.index,
|
||||
y=df_ta[ad_col].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>ADOSC</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color=fig.theme.get_colors()[1],
|
||||
)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
|
||||
@indicator()
|
||||
def plot_obv(self, fig: OpenBBFigure, df_ta: pd.DataFrame, subplot_row: int):
|
||||
"""Adds obv to plotly figure"""
|
||||
obv_col = columns_regex(df_ta, "OBV")[0]
|
||||
fig.add_scatter(
|
||||
name="OBV",
|
||||
mode="lines",
|
||||
line=dict(width=1.5, color=fig.theme.get_colors()[1]),
|
||||
x=df_ta.index,
|
||||
y=df_ta[obv_col].values,
|
||||
opacity=0.9,
|
||||
row=subplot_row,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
|
||||
fig.add_annotation(
|
||||
xref=f"x{subplot_row} domain",
|
||||
yref=f"y{subplot_row + 1} domain",
|
||||
text="<b>OBV</b>",
|
||||
x=0,
|
||||
xanchor="right",
|
||||
xshift=-6,
|
||||
y=0.98,
|
||||
font_size=14,
|
||||
font_color=fig.theme.get_colors()[1],
|
||||
)
|
||||
fig["layout"][f"yaxis{subplot_row + 1}"].update(nticks=5, autorange=True)
|
||||
|
||||
return fig, subplot_row + 1
|
||||
@@ -1,591 +0,0 @@
|
||||
# pylint: disable=R0902
|
||||
import importlib
|
||||
import inspect
|
||||
import sys
|
||||
import warnings
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, List, Optional, Type, Union
|
||||
|
||||
import pandas as pd
|
||||
from openbb_charting.core.chart_style import ChartStyle
|
||||
from openbb_charting.core.openbb_figure import OpenBBFigure
|
||||
from openbb_core.app.model.charts.charting_settings import ChartingSettings
|
||||
|
||||
from .base import PltTA
|
||||
from .data_classes import ChartIndicators
|
||||
from .ta_helpers import check_columns
|
||||
|
||||
OPENBB_CHARTING_EXTENSION_PATH = Path(__file__).parent.parent.parent
|
||||
CHARTING_INSTALL_PATH = OPENBB_CHARTING_EXTENSION_PATH.parent
|
||||
PLUGINS_PATH = Path(__file__).parent / "plugins"
|
||||
PLOTLY_TA: Optional["PlotlyTA"] = None
|
||||
|
||||
|
||||
class PlotlyTA(PltTA):
|
||||
"""Plotly Technical Analysis class
|
||||
|
||||
This class is a singleton. It is created and then reused, to assure
|
||||
the plugins are only loaded once. This is done by overriding the __new__
|
||||
method. The __init__ method is overridden to do nothing, except to clear
|
||||
the internal data structures.
|
||||
|
||||
Attributes
|
||||
----------
|
||||
inchart_colors (List[str]):
|
||||
List of colors for inchart indicators
|
||||
show_volume (bool):
|
||||
Whether to show the volume subplot
|
||||
ma_mode (List[str]):
|
||||
List of available moving average modes
|
||||
inchart (List[str]):
|
||||
List of available inchart indicators
|
||||
subplots (List[str]):
|
||||
List of available subplots
|
||||
|
||||
StaticMethods
|
||||
-------------
|
||||
plot(
|
||||
df: pd.DataFrame,
|
||||
indicators: ChartIndicators,
|
||||
fig: Optional[OpenBBFigure] = None,
|
||||
symbol: Optional[str] = "",
|
||||
candles: bool = True,
|
||||
volume: bool = True,
|
||||
) -> OpenBBFigure:
|
||||
Plots the chart with the given indicators
|
||||
|
||||
|
||||
Examples
|
||||
--------
|
||||
>>> from openbb_terminal.sdk import openbb
|
||||
>>> from openbb_terminal.core.plots.plotly_ta.ta_class import PlotlyTA
|
||||
|
||||
>>> df = openbb.stocks.load("SPY")
|
||||
>>> indicators = dict(
|
||||
>>> sma=dict(length=[20, 50, 100]),
|
||||
>>> adx=dict(length=14),
|
||||
>>> macd=dict(fast=12, slow=26, signal=9),
|
||||
>>> rsi=dict(length=14),
|
||||
>>> )
|
||||
>>> fig = PlotlyTA.plot(df, indicators=indicators)
|
||||
>>> fig.show()
|
||||
|
||||
If you want to plot the chart with the same indicators, you can
|
||||
reuse the same instance of the class as follows:
|
||||
|
||||
>>> ta = PlotlyTA()
|
||||
>>> fig = ta.plot(df, indicators=indicators)
|
||||
>>> df2 = openbb.stocks.load("AAPL")
|
||||
>>> fig2 = ta.plot(df2)
|
||||
>>> fig.show()
|
||||
>>> fig2.show()
|
||||
"""
|
||||
|
||||
inchart_colors: List[str] = []
|
||||
plugins: List[Type[PltTA]] = []
|
||||
df_ta: pd.DataFrame = None
|
||||
close_column: Optional[str] = "close"
|
||||
has_volume: bool = True
|
||||
show_volume: bool = True
|
||||
prepost: bool = False
|
||||
charting_settings: ChartingSettings = ChartingSettings()
|
||||
theme: Optional[ChartStyle] = None
|
||||
|
||||
def __new__(cls, *args, **kwargs):
|
||||
"""This method is overridden to create a singleton instance of the class."""
|
||||
cls.charting_settings = kwargs.pop("charting_settings", cls.charting_settings)
|
||||
cls.theme = cls.setup_theme(cls.charting_settings)
|
||||
cls.inchart_colors = cls.theme.get_colors()
|
||||
|
||||
global PLOTLY_TA # pylint: disable=global-statement # noqa
|
||||
if PLOTLY_TA is None:
|
||||
# Creates the instance of the class and loads the plugins
|
||||
# We set the global variable to the instance of the class so that
|
||||
# the plugins are only loaded once
|
||||
PLOTLY_TA = super().__new__(cls)
|
||||
PLOTLY_TA._locate_plugins(cls.charting_settings.debug_mode)
|
||||
PLOTLY_TA.add_plugins(PLOTLY_TA.plugins)
|
||||
|
||||
return PLOTLY_TA
|
||||
|
||||
def __init__(
|
||||
self, *args, charting_settings: Optional[ChartingSettings] = None, **kwargs
|
||||
): # pylint: disable=unused-argument
|
||||
"""This method is overridden to do nothing, except to clear the internal data structures."""
|
||||
if not args and not kwargs:
|
||||
self._clear_data()
|
||||
else:
|
||||
self.df_fib = None
|
||||
super().__init__(*args, **kwargs)
|
||||
|
||||
@staticmethod
|
||||
def setup_theme(charting_settings: ChartingSettings) -> ChartStyle:
|
||||
"""Setup theme for charting"""
|
||||
return ChartStyle(
|
||||
charting_settings.chart_style,
|
||||
charting_settings.user_styles_directory,
|
||||
)
|
||||
|
||||
@property
|
||||
def ma_mode(self) -> List[str]:
|
||||
return list(set(self.__ma_mode__))
|
||||
|
||||
@ma_mode.setter
|
||||
def ma_mode(self, value: List[str]):
|
||||
self.__ma_mode__ = value
|
||||
|
||||
@property
|
||||
def inchart(self) -> List[str]:
|
||||
return list(set(self.__inchart__))
|
||||
|
||||
@inchart.setter
|
||||
def inchart(self, value: List[str]):
|
||||
self.__inchart__ = value
|
||||
|
||||
@property
|
||||
def subplots(self) -> List[str]:
|
||||
return list(set(self.__subplots__))
|
||||
|
||||
@subplots.setter
|
||||
def subplots(self, value: List[str]):
|
||||
self.__subplots__ = value
|
||||
|
||||
# pylint: disable=R0913
|
||||
def __plot__(
|
||||
self,
|
||||
df_stock: Union[pd.DataFrame, pd.Series],
|
||||
indicators: Optional[Union[ChartIndicators, Dict[str, Dict[str, Any]]]] = None,
|
||||
symbol: str = "",
|
||||
candles: bool = True,
|
||||
volume: bool = True,
|
||||
prepost: bool = False,
|
||||
fig: Optional[OpenBBFigure] = None,
|
||||
volume_ticks_x: int = 7,
|
||||
) -> OpenBBFigure:
|
||||
"""This method should not be called directly. Use the PlotlyTA.plot() static method instead."""
|
||||
if isinstance(df_stock, pd.Series):
|
||||
df_stock = df_stock.to_frame()
|
||||
|
||||
if not isinstance(indicators, ChartIndicators):
|
||||
indicators = ChartIndicators.from_dict(indicators or dict(dict()))
|
||||
|
||||
self.indicators = indicators
|
||||
self.intraday = df_stock.index[-2].time() != df_stock.index[-1].time()
|
||||
self.df_stock = df_stock.sort_index(ascending=True)
|
||||
self.close_column = check_columns(self.df_stock)
|
||||
self.params = self.indicators.get_params()
|
||||
|
||||
self.has_volume = "volume" in self.df_stock.columns and bool(
|
||||
self.df_stock["volume"].sum() > 0
|
||||
)
|
||||
self.show_volume = volume and self.has_volume
|
||||
|
||||
self.prepost = prepost
|
||||
|
||||
return self.plot_fig(
|
||||
fig=fig, symbol=symbol, candles=candles, volume_ticks_x=volume_ticks_x
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def plot(
|
||||
df_stock: Union[pd.DataFrame, pd.Series],
|
||||
indicators: Optional[Union[ChartIndicators, Dict[str, Dict[str, Any]]]] = None,
|
||||
symbol: str = "",
|
||||
candles: bool = True,
|
||||
volume: bool = True,
|
||||
prepost: bool = False,
|
||||
fig: Optional[OpenBBFigure] = None,
|
||||
volume_ticks_x: int = 7,
|
||||
) -> OpenBBFigure:
|
||||
"""Plot a chart with the given indicators.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
df_stock : pd.DataFrame
|
||||
Dataframe with stock data
|
||||
indicators : Union[ChartIndicators, Dict[str, Dict[str, Any]]]
|
||||
ChartIndicators object or dictionary with indicators and parameters to plot
|
||||
Example:
|
||||
dict(
|
||||
sma=dict(length=[20, 50, 100]),
|
||||
adx=dict(length=14),
|
||||
macd=dict(fast=12, slow=26, signal=9),
|
||||
rsi=dict(length=14),
|
||||
)
|
||||
symbol : str, optional
|
||||
Symbol to plot, by default uses the dataframe.name attribute if available or ""
|
||||
candles : bool, optional
|
||||
Plot a candlestick chart, by default True (if False, plots a line chart)
|
||||
volume : bool, optional
|
||||
Plot volume, by default True
|
||||
prepost : bool, optional
|
||||
Plot pre and post market data, by default False
|
||||
fig : OpenBBFigure, optional
|
||||
Plotly figure to plot on, by default None
|
||||
volume_ticks_x : int, optional
|
||||
Number to multiply volume, by default 7
|
||||
"""
|
||||
if indicators is None and PLOTLY_TA is not None:
|
||||
indicators = PLOTLY_TA.indicators
|
||||
|
||||
return PlotlyTA().__plot__(
|
||||
df_stock, indicators, symbol, candles, volume, prepost, fig, volume_ticks_x
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _locate_plugins(debug: Optional[bool] = False) -> None:
|
||||
"""Locate all the plugins in the plugins folder"""
|
||||
path = (
|
||||
Path(sys.executable).parent
|
||||
if hasattr(sys, "frozen")
|
||||
else CHARTING_INSTALL_PATH
|
||||
)
|
||||
if debug:
|
||||
warnings.warn(f"[bold green]Loading plugins from {path}[/]")
|
||||
warnings.warn("[bold green]Plugins found:[/]")
|
||||
|
||||
for plugin in Path(__file__).parent.glob("plugins/*_plugin.py"):
|
||||
python_path = plugin.relative_to(path).with_suffix("")
|
||||
|
||||
if debug:
|
||||
warnings.warn(f" [bold red]{plugin.name}[/]")
|
||||
warnings.warn(f" [bold yellow]{python_path}[/]")
|
||||
warnings.warn(f" [bold bright_cyan]{__package__}[/]")
|
||||
warnings.warn(f" [bold magenta]{python_path.parts}[/]")
|
||||
warnings.warn(
|
||||
f" [bold bright_magenta]{'.'.join(python_path.parts)}[/]"
|
||||
)
|
||||
|
||||
module = importlib.import_module(
|
||||
".".join(python_path.parts), package=__package__
|
||||
)
|
||||
for _, obj in inspect.getmembers(module):
|
||||
if (
|
||||
inspect.isclass(obj)
|
||||
and issubclass(obj, (PltTA))
|
||||
and obj != PlotlyTA.__class__
|
||||
) and obj not in PlotlyTA.plugins:
|
||||
PlotlyTA.plugins.append(obj)
|
||||
|
||||
def _clear_data(self):
|
||||
"""Clear and reset all data to default values"""
|
||||
self.df_stock = None
|
||||
self.indicators = {}
|
||||
self.params = None
|
||||
self.intraday = False
|
||||
self.show_volume = True
|
||||
|
||||
def calculate_indicators(self):
|
||||
"""Return dataframe with all indicators"""
|
||||
return self.indicators.to_dataframe(self.df_stock.copy(), self.ma_mode)
|
||||
|
||||
def get_subplot(self, subplot: str) -> bool:
|
||||
"""Return True if subplots will be able to be plotted with current data"""
|
||||
if subplot == "volume":
|
||||
return self.show_volume
|
||||
|
||||
if subplot in ["ad", "adosc", "obv", "vwap"] and not self.has_volume:
|
||||
self.indicators.remove_indicator(subplot)
|
||||
warnings.warn(
|
||||
f"[bold red]Warning:[/] [yellow]{subplot.upper()}"
|
||||
" requires volume data to be plotted but no volume data was found."
|
||||
" Indicator will not be plotted.[/]"
|
||||
)
|
||||
return False
|
||||
|
||||
output = False
|
||||
|
||||
try:
|
||||
indicator = self.indicators.get_indicator(subplot)
|
||||
if indicator is None:
|
||||
return False
|
||||
|
||||
output = self.indicators.get_indicator_data(
|
||||
self.df_stock.copy(),
|
||||
indicator,
|
||||
**self.indicators.get_options_dict(indicator.name) or {},
|
||||
)
|
||||
if not isinstance(output, bool):
|
||||
output = output.dropna()
|
||||
|
||||
if output is None or output.empty:
|
||||
output = False
|
||||
|
||||
return True
|
||||
|
||||
except Exception:
|
||||
output = False
|
||||
|
||||
return output
|
||||
|
||||
def check_subplots(self, subplots: list) -> list:
|
||||
"""Return list of subplots that can be plotted with current data"""
|
||||
output = []
|
||||
for subplot in subplots:
|
||||
if self.get_subplot(subplot):
|
||||
output.append(subplot)
|
||||
|
||||
return output
|
||||
|
||||
def get_fig_settings_dict(self):
|
||||
"""Return dictionary with settings for plotly figure"""
|
||||
row_params = {
|
||||
"0": dict(rows=1, row_width=[1]),
|
||||
"1": dict(rows=2, row_width=[0.3, 0.7]),
|
||||
"2": dict(rows=3, row_width=[0.15, 0.15, 0.7]),
|
||||
"3": dict(rows=4, row_width=[0.2, 0.2, 0.2, 0.4]),
|
||||
"4": dict(rows=5, row_width=[0.15, 0.15, 0.15, 0.15, 0.4]),
|
||||
}
|
||||
|
||||
check_active = self.indicators.get_active_ids()
|
||||
subplots = [subplot for subplot in self.subplots if subplot in check_active]
|
||||
|
||||
check_rows = min(len(self.check_subplots(subplots)), 4)
|
||||
check_rows += 1 if "aroon" in subplots and (check_rows + 1) < 5 else 0
|
||||
|
||||
specs = [[{"secondary_y": True}]] + [[{"secondary_y": False}]] * check_rows
|
||||
|
||||
output = row_params.get(str(check_rows), dict(rows=1, row_width=[1]))
|
||||
output.update(dict(cols=1, vertical_spacing=0.04, specs=specs))
|
||||
|
||||
return output
|
||||
|
||||
def init_plot(self, symbol: str = "", candles: bool = True) -> OpenBBFigure:
|
||||
"""Create plotly figure with subplots
|
||||
|
||||
Parameters
|
||||
----------
|
||||
symbol : str, optional
|
||||
Symbol to plot, by default uses the dataframe.name attribute if available or ""
|
||||
candles : bool, optional
|
||||
Plot a candlestick chart, by default True (if False, plots a line chart)
|
||||
|
||||
Returns
|
||||
-------
|
||||
fig : OpenBBFigure
|
||||
Plotly figure with candlestick/line chart and volume bar chart (if enabled)
|
||||
"""
|
||||
fig = OpenBBFigure(charting_settings=self.charting_settings)
|
||||
fig = fig.create_subplots(
|
||||
1,
|
||||
1,
|
||||
shared_xaxes=True,
|
||||
vertical_spacing=0.06,
|
||||
horizontal_spacing=0.01,
|
||||
row_width=[1],
|
||||
specs=[[{"secondary_y": True}]],
|
||||
)
|
||||
cc_linewidth = (
|
||||
0.8 if len(self.df_stock.index) > 500 else 0.9 if self.intraday else 1.1
|
||||
)
|
||||
if candles:
|
||||
fig.add_candlestick(
|
||||
x=self.df_stock.index,
|
||||
open=self.df_stock.open,
|
||||
high=self.df_stock.high,
|
||||
low=self.df_stock.low,
|
||||
close=self.df_stock.close,
|
||||
decreasing=dict(line=dict(width=cc_linewidth)),
|
||||
increasing=dict(line=dict(width=cc_linewidth)),
|
||||
name=f"{symbol} OHLC",
|
||||
showlegend=False,
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
else:
|
||||
fig.add_scatter(
|
||||
x=self.df_stock.index,
|
||||
y=self.df_stock[self.close_column],
|
||||
name=f"{symbol} Close",
|
||||
connectgaps=True,
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
)
|
||||
fig.update_layout(yaxis=dict(nticks=15))
|
||||
if self.theme:
|
||||
self.inchart_colors = self.theme.get_colors()[1:]
|
||||
|
||||
fig.set_title(symbol, x=0.5, y=0.98, xanchor="center", yanchor="top")
|
||||
return fig
|
||||
|
||||
def plot_fig(
|
||||
self,
|
||||
fig: Optional[OpenBBFigure] = None,
|
||||
symbol: str = "",
|
||||
candles: bool = True,
|
||||
volume_ticks_x: int = 7,
|
||||
) -> OpenBBFigure:
|
||||
"""Plot indicators on plotly figure
|
||||
|
||||
Parameters
|
||||
----------
|
||||
fig : OpenBBFigure, optional
|
||||
Plotly figure to plot indicators on, by default None
|
||||
symbol : str, optional
|
||||
Symbol to plot, by default uses the dataframe.name attribute if available or ""
|
||||
candles : bool, optional
|
||||
Plot a candlestick chart, by default True (if False, plots a line chart)
|
||||
volume_ticks_x : int, optional
|
||||
Number to multiply volume, by default 7
|
||||
|
||||
Returns
|
||||
-------
|
||||
fig : OpenBBFigure
|
||||
Plotly figure with candlestick/line chart and volume bar chart (if enabled)
|
||||
"""
|
||||
self.df_ta = self.calculate_indicators()
|
||||
|
||||
symbol = (
|
||||
self.df_stock.name
|
||||
if hasattr(self.df_stock, "name") and not symbol
|
||||
else symbol
|
||||
)
|
||||
|
||||
figure = self.init_plot(symbol, candles) if fig is None else fig
|
||||
|
||||
subplot_row, fig_new = 2, {}
|
||||
inchart_index, ma_done = 0, False
|
||||
|
||||
figure = self.process_fig(figure, volume_ticks_x)
|
||||
|
||||
# Aroon indicator is always plotted first since it has 2 subplot rows
|
||||
plot_indicators = sorted(
|
||||
self.indicators.get_active_ids(),
|
||||
key=lambda x: 50 if x == "aroon" else 999 if x in self.subplots else 1,
|
||||
)
|
||||
|
||||
for indicator in plot_indicators:
|
||||
try:
|
||||
if indicator in self.subplots:
|
||||
figure, subplot_row = getattr(self, f"plot_{indicator}")(
|
||||
figure, self.df_ta, subplot_row
|
||||
)
|
||||
elif indicator in self.ma_mode or indicator in self.inchart:
|
||||
if indicator in self.ma_mode:
|
||||
if ma_done:
|
||||
continue
|
||||
indicator, ma_done = "ma", True # noqa
|
||||
|
||||
figure, inchart_index = getattr(self, f"plot_{indicator}")(
|
||||
figure, self.df_ta, inchart_index
|
||||
)
|
||||
elif indicator in ["fib", "srlines", "demark", "clenow", "ichimoku"]:
|
||||
figure = getattr(self, f"plot_{indicator}")(figure, self.df_ta)
|
||||
else:
|
||||
raise ValueError(f"Unknown indicator: {indicator}")
|
||||
|
||||
fig_new.update(figure.to_plotly_json())
|
||||
|
||||
remaining_subplots = (
|
||||
list(
|
||||
set(plot_indicators[plot_indicators.index(indicator) + 1 :])
|
||||
- set(self.inchart)
|
||||
)
|
||||
if indicator != "ma"
|
||||
else []
|
||||
)
|
||||
if subplot_row > 5 and remaining_subplots:
|
||||
warnings.warn(
|
||||
f"[bold red]Reached max number of subplots. "
|
||||
f"Skipping {', '.join(remaining_subplots)}[/]"
|
||||
)
|
||||
break
|
||||
except Exception as e:
|
||||
warnings.warn(f"[bold red]Error plotting {indicator}: {e}[/]")
|
||||
continue
|
||||
|
||||
figure.update(fig_new)
|
||||
figure.update_yaxes(
|
||||
row=1,
|
||||
col=1,
|
||||
secondary_y=False,
|
||||
nticks=15 if subplot_row < 3 else 10,
|
||||
tickfont=dict(size=16),
|
||||
)
|
||||
figure.update_traces(
|
||||
selector=dict(type="scatter", mode="lines"), connectgaps=True
|
||||
)
|
||||
figure.update_layout(showlegend=False)
|
||||
figure.hide_holidays(self.prepost)
|
||||
|
||||
if not self.show_volume:
|
||||
figure.update_layout(margin=dict(l=20))
|
||||
|
||||
# We remove xaxis labels from all but bottom subplot, and we make sure
|
||||
# they all match the bottom one
|
||||
xbottom = f"y{subplot_row+1}"
|
||||
xaxes = list(figure.select_xaxes())
|
||||
for xa in xaxes:
|
||||
if xa == xaxes[-1]:
|
||||
xa.showticklabels = True
|
||||
if not xa.showticklabels and xa.anchor != xbottom:
|
||||
xa.showticklabels = False
|
||||
if xa.anchor != xbottom:
|
||||
xa.matches = xbottom.replace("y", "x")
|
||||
|
||||
return figure
|
||||
|
||||
def process_fig(self, fig: OpenBBFigure, volume_ticks_x: int = 7) -> OpenBBFigure:
|
||||
"""Process plotly figure before plotting indicators
|
||||
|
||||
Parameters
|
||||
----------
|
||||
fig : OpenBBFigure
|
||||
Plotly figure to process
|
||||
volume_ticks_x : int, optional
|
||||
Number to multiply volume, by default 7
|
||||
|
||||
Returns
|
||||
-------
|
||||
fig : OpenBBFigure
|
||||
Processed plotly figure
|
||||
"""
|
||||
new_subplot = OpenBBFigure(charting_settings=self.charting_settings)
|
||||
new_subplot = fig.create_subplots(
|
||||
shared_xaxes=True, **self.get_fig_settings_dict()
|
||||
)
|
||||
|
||||
subplots: Dict[str, Dict[str, List[Any]]] = {}
|
||||
grid_ref = fig._validate_get_grid_ref() # pylint: disable=protected-access
|
||||
for r, plot_row in enumerate(grid_ref):
|
||||
for c, plot_refs in enumerate(plot_row):
|
||||
if not plot_refs:
|
||||
continue
|
||||
for subplot_ref in plot_refs:
|
||||
if subplot_ref.subplot_type == "xy":
|
||||
xaxis, yaxis = subplot_ref.layout_keys
|
||||
xref = xaxis.replace("axis", "")
|
||||
yref = yaxis.replace("axis", "")
|
||||
row = r + 1
|
||||
col = c + 1
|
||||
subplots.setdefault(xref, {}).setdefault(yref, []).append(
|
||||
(row, col)
|
||||
)
|
||||
|
||||
for trace in fig.select_traces():
|
||||
xref, yref = trace.xaxis, trace.yaxis
|
||||
row, col = subplots[xref][yref][0]
|
||||
new_subplot.add_trace(trace, row=row, col=col, secondary_y=False)
|
||||
|
||||
fig_json = fig.to_plotly_json()["layout"]
|
||||
for layout in fig_json:
|
||||
if (
|
||||
isinstance(fig_json[layout], dict)
|
||||
and "domain" in fig_json[layout]
|
||||
and any(x in layout for x in ["xaxis", "yaxis"])
|
||||
):
|
||||
fig_json[layout]["domain"] = new_subplot.to_plotly_json()["layout"][
|
||||
layout
|
||||
]["domain"]
|
||||
|
||||
fig.layout.update({layout: fig_json[layout]})
|
||||
new_subplot.layout.update({layout: fig.layout[layout]})
|
||||
|
||||
if self.show_volume:
|
||||
new_subplot.add_inchart_volume(
|
||||
self.df_stock, self.close_column, volume_ticks_x=volume_ticks_x
|
||||
)
|
||||
|
||||
return new_subplot
|
||||
@@ -1,43 +0,0 @@
|
||||
import re
|
||||
from typing import Optional
|
||||
|
||||
import pandas as pd
|
||||
|
||||
|
||||
def check_columns(
|
||||
data: pd.DataFrame, high: bool = True, low: bool = True, close: bool = True
|
||||
) -> Optional[str]:
|
||||
"""Returns the close columns, or None if the dataframe does not have required columns
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data: pd.DataFrame
|
||||
The dataframe to check
|
||||
high: bool
|
||||
Whether to check for high column
|
||||
low: bool
|
||||
Whether to check for low column
|
||||
close: bool
|
||||
Whether to check for close column
|
||||
|
||||
Returns
|
||||
-------
|
||||
Optional[str]
|
||||
The name of the close column, none if df is invalid
|
||||
|
||||
"""
|
||||
close_regex = r"(Adj\sClose|adj_close|Close)"
|
||||
# pylint: disable=too-many-boolean-expressions
|
||||
if (
|
||||
(re.findall(r"High", str(data.columns), re.IGNORECASE) is None and high)
|
||||
or (re.findall(r"Low", str(data.columns), re.IGNORECASE) is None and low)
|
||||
or (close_col := re.findall(close_regex, str(data.columns), re.IGNORECASE))
|
||||
is None
|
||||
and close
|
||||
):
|
||||
raise ValueError(
|
||||
" Please make sure that the columns 'High', 'Low', and 'Close'"
|
||||
" are in the dataframe."
|
||||
)
|
||||
|
||||
return [col for col in close_col if col in data.columns][-1]
|
||||
File diff suppressed because one or more lines are too long
@@ -1,63 +0,0 @@
|
||||
from typing import Any, Dict, Optional, Tuple, Union
|
||||
|
||||
import pandas as pd
|
||||
from openbb_charting.core.openbb_figure import OpenBBFigure
|
||||
from openbb_charting.core.plotly_ta.data_classes import ChartIndicators
|
||||
from openbb_charting.core.plotly_ta.ta_class import PlotlyTA
|
||||
from openbb_core.app.model.charts.charting_settings import ChartingSettings
|
||||
|
||||
|
||||
def to_chart(
|
||||
charting_settings: ChartingSettings,
|
||||
data: Union[pd.DataFrame, pd.Series],
|
||||
indicators: Optional[Union[ChartIndicators, Dict[str, Dict[str, Any]]]] = None,
|
||||
symbol: str = "",
|
||||
candles: bool = True,
|
||||
volume: bool = True,
|
||||
prepost: bool = False,
|
||||
volume_ticks_x: int = 7,
|
||||
) -> Tuple[OpenBBFigure, Dict[str, Any]]:
|
||||
"""
|
||||
Returns the plotly json representation of the chart.
|
||||
This function is used so it can be called at the module level and used out of the box,
|
||||
which allows some more flexibility, ease of use and doesn't require the user to know
|
||||
about the PlotlyTA class.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
charting_settings : ChartingSettings
|
||||
Charting settings.
|
||||
data : Union[pd.DataFrame, pd.Series]
|
||||
Data to be plotted.
|
||||
indicators : Optional[Union[ChartIndicators, Dict[str, Dict[str, Any]]]], optional
|
||||
Indicators to be plotted, by default None
|
||||
symbol : str, optional
|
||||
Symbol to be plotted, by default ""
|
||||
candles : bool, optional
|
||||
If True, candles will be plotted, by default True
|
||||
volume : bool, optional
|
||||
If True, volume will be plotted, by default True
|
||||
prepost : bool, optional
|
||||
If True, prepost will be plotted, by default False
|
||||
volume_ticks_x : int, optional
|
||||
Volume ticks, by default 7
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
Plotly json representation of the chart.
|
||||
"""
|
||||
|
||||
ta = PlotlyTA(charting_settings=charting_settings)
|
||||
fig = ta.plot(
|
||||
df_stock=data,
|
||||
indicators=indicators,
|
||||
symbol=symbol,
|
||||
candles=candles,
|
||||
volume=volume,
|
||||
prepost=prepost,
|
||||
volume_ticks_x=volume_ticks_x,
|
||||
)
|
||||
content = fig.show(external=True).to_plotly_json()
|
||||
|
||||
return fig, content
|
||||
@@ -1,132 +0,0 @@
|
||||
{
|
||||
"line": {
|
||||
"up_color": "#00ACFF",
|
||||
"down_color": "#e4003a",
|
||||
"color": "#ffed00",
|
||||
"width": 1.5
|
||||
},
|
||||
"data": {
|
||||
"candlestick": [
|
||||
{
|
||||
"decreasing": {
|
||||
"fillcolor": "#e4003a",
|
||||
"line": {
|
||||
"color": "#e4003a"
|
||||
}
|
||||
},
|
||||
"increasing": {
|
||||
"fillcolor": "#00ACFF",
|
||||
"line": {
|
||||
"color": "#00ACFF"
|
||||
}
|
||||
},
|
||||
"type": "candlestick"
|
||||
}
|
||||
]
|
||||
},
|
||||
"layout": {
|
||||
"annotationdefaults": {
|
||||
"showarrow": false
|
||||
},
|
||||
"autotypenumbers": "strict",
|
||||
"colorway": [
|
||||
"#ffed00",
|
||||
"#ef7d00",
|
||||
"#e4003a",
|
||||
"#c13246",
|
||||
"#822661",
|
||||
"#48277c",
|
||||
"#005ca9",
|
||||
"#00aaff",
|
||||
"#9b30d9",
|
||||
"#af005f",
|
||||
"#5f00af",
|
||||
"#af87ff"
|
||||
],
|
||||
"dragmode": "pan",
|
||||
"font": {
|
||||
"family": "Fira Code",
|
||||
"size": 18
|
||||
},
|
||||
"hoverlabel": {
|
||||
"align": "left"
|
||||
},
|
||||
"mapbox": {
|
||||
"style": "dark"
|
||||
},
|
||||
"hovermode": "x",
|
||||
"legend": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0.5)",
|
||||
"x": 0.01,
|
||||
"xanchor": "left",
|
||||
"y": 0.99,
|
||||
"yanchor": "top",
|
||||
"font": {
|
||||
"size": 15
|
||||
}
|
||||
},
|
||||
"legend2": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0.5)",
|
||||
"font": {
|
||||
"size": 15
|
||||
}
|
||||
},
|
||||
"legend3": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0.5)",
|
||||
"font": {
|
||||
"size": 15
|
||||
}
|
||||
},
|
||||
"legend4": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0.5)",
|
||||
"font": {
|
||||
"size": 15
|
||||
}
|
||||
},
|
||||
"legend5": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0.5)",
|
||||
"font": {
|
||||
"size": 15
|
||||
}
|
||||
},
|
||||
"paper_bgcolor": "#000000",
|
||||
"plot_bgcolor": "#000000",
|
||||
"xaxis": {
|
||||
"automargin": true,
|
||||
"autorange": true,
|
||||
"rangeslider": {
|
||||
"visible": false
|
||||
},
|
||||
"showgrid": true,
|
||||
"showline": true,
|
||||
"tickfont": {
|
||||
"size": 14
|
||||
},
|
||||
"zeroline": false,
|
||||
"tick0": 1,
|
||||
"title": {
|
||||
"standoff": 20
|
||||
},
|
||||
"linecolor": "#F5EFF3",
|
||||
"mirror": true,
|
||||
"ticks": "outside"
|
||||
},
|
||||
"yaxis": {
|
||||
"anchor": "x",
|
||||
"automargin": true,
|
||||
"fixedrange": false,
|
||||
"zeroline": false,
|
||||
"showgrid": true,
|
||||
"showline": true,
|
||||
"side": "right",
|
||||
"tick0": 0.5,
|
||||
"title": {
|
||||
"standoff": 20
|
||||
},
|
||||
"gridcolor": "#283442",
|
||||
"linecolor": "#F5EFF3",
|
||||
"mirror": true,
|
||||
"ticks": "outside"
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,871 +0,0 @@
|
||||
{
|
||||
"line": {
|
||||
"up_color": "#009600",
|
||||
"down_color": "#c80000",
|
||||
"color": "#0d0887",
|
||||
"width": 1.5,
|
||||
"down_color_transparent": "rgba(200, 0, 0, 0.4)",
|
||||
"up_color_transparent": "rgba(0, 150, 0, 0.4)"
|
||||
},
|
||||
"data": {
|
||||
"barpolar": [
|
||||
{
|
||||
"marker": {
|
||||
"line": {
|
||||
"color": "white",
|
||||
"width": 0.5
|
||||
},
|
||||
"pattern": {
|
||||
"fillmode": "overlay",
|
||||
"size": 10,
|
||||
"solidity": 0.2
|
||||
}
|
||||
},
|
||||
"type": "barpolar"
|
||||
}
|
||||
],
|
||||
"bar": [
|
||||
{
|
||||
"error_x": {
|
||||
"color": "#2a3f5f"
|
||||
},
|
||||
"error_y": {
|
||||
"color": "#2a3f5f"
|
||||
},
|
||||
"marker": {
|
||||
"line": {
|
||||
"color": "white",
|
||||
"width": 0.5
|
||||
},
|
||||
"pattern": {
|
||||
"fillmode": "overlay",
|
||||
"size": 10,
|
||||
"solidity": 0.2
|
||||
}
|
||||
},
|
||||
"type": "bar"
|
||||
}
|
||||
],
|
||||
"carpet": [
|
||||
{
|
||||
"aaxis": {
|
||||
"endlinecolor": "#2a3f5f",
|
||||
"gridcolor": "#C8D4E3",
|
||||
"linecolor": "#C8D4E3",
|
||||
"minorgridcolor": "#C8D4E3",
|
||||
"startlinecolor": "#2a3f5f"
|
||||
},
|
||||
"baxis": {
|
||||
"endlinecolor": "#2a3f5f",
|
||||
"gridcolor": "#C8D4E3",
|
||||
"linecolor": "#C8D4E3",
|
||||
"minorgridcolor": "#C8D4E3",
|
||||
"startlinecolor": "#2a3f5f"
|
||||
},
|
||||
"type": "carpet"
|
||||
}
|
||||
],
|
||||
"choropleth": [
|
||||
{
|
||||
"colorbar": {
|
||||
"outlinewidth": 0,
|
||||
"ticks": ""
|
||||
},
|
||||
"type": "choropleth"
|
||||
}
|
||||
],
|
||||
"contourcarpet": [
|
||||
{
|
||||
"colorbar": {
|
||||
"outlinewidth": 0,
|
||||
"ticks": ""
|
||||
},
|
||||
"type": "contourcarpet"
|
||||
}
|
||||
],
|
||||
"contour": [
|
||||
{
|
||||
"colorbar": {
|
||||
"outlinewidth": 0,
|
||||
"ticks": ""
|
||||
},
|
||||
"colorscale": [
|
||||
[
|
||||
0.0,
|
||||
"#0d0887"
|
||||
],
|
||||
[
|
||||
0.1111111111111111,
|
||||
"#46039f"
|
||||
],
|
||||
[
|
||||
0.2222222222222222,
|
||||
"#7201a8"
|
||||
],
|
||||
[
|
||||
0.3333333333333333,
|
||||
"#9c179e"
|
||||
],
|
||||
[
|
||||
0.4444444444444444,
|
||||
"#bd3786"
|
||||
],
|
||||
[
|
||||
0.5555555555555556,
|
||||
"#d8576b"
|
||||
],
|
||||
[
|
||||
0.6666666666666666,
|
||||
"#ed7953"
|
||||
],
|
||||
[
|
||||
0.7777777777777778,
|
||||
"#fb9f3a"
|
||||
],
|
||||
[
|
||||
0.8888888888888888,
|
||||
"#fdca26"
|
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"ticks": ""
|
||||
},
|
||||
"bgcolor": "white",
|
||||
"radialaxis": {
|
||||
"gridcolor": "#EBF0F8",
|
||||
"linecolor": "#EBF0F8",
|
||||
"ticks": ""
|
||||
}
|
||||
},
|
||||
"scene": {
|
||||
"xaxis": {
|
||||
"backgroundcolor": "white",
|
||||
"gridcolor": "#DFE8F3",
|
||||
"gridwidth": 2,
|
||||
"linecolor": "#EBF0F8",
|
||||
"showbackground": true,
|
||||
"ticks": "",
|
||||
"zerolinecolor": "#EBF0F8"
|
||||
},
|
||||
"yaxis": {
|
||||
"backgroundcolor": "white",
|
||||
"gridcolor": "#DFE8F3",
|
||||
"gridwidth": 2,
|
||||
"linecolor": "#EBF0F8",
|
||||
"showbackground": true,
|
||||
"ticks": "",
|
||||
"zerolinecolor": "#EBF0F8"
|
||||
},
|
||||
"zaxis": {
|
||||
"backgroundcolor": "white",
|
||||
"gridcolor": "#DFE8F3",
|
||||
"gridwidth": 2,
|
||||
"linecolor": "#EBF0F8",
|
||||
"showbackground": true,
|
||||
"ticks": "",
|
||||
"zerolinecolor": "#EBF0F8"
|
||||
}
|
||||
},
|
||||
"shapedefaults": {
|
||||
"line": {
|
||||
"color": "#2a3f5f"
|
||||
}
|
||||
},
|
||||
"ternary": {
|
||||
"aaxis": {
|
||||
"gridcolor": "#DFE8F3",
|
||||
"linecolor": "#A2B1C6",
|
||||
"ticks": ""
|
||||
},
|
||||
"baxis": {
|
||||
"gridcolor": "#DFE8F3",
|
||||
"linecolor": "#A2B1C6",
|
||||
"ticks": ""
|
||||
},
|
||||
"bgcolor": "white",
|
||||
"caxis": {
|
||||
"gridcolor": "#DFE8F3",
|
||||
"linecolor": "#A2B1C6",
|
||||
"ticks": ""
|
||||
}
|
||||
},
|
||||
"title": {
|
||||
"x": 0.05
|
||||
},
|
||||
"xaxis": {
|
||||
"automargin": true,
|
||||
"ticks": "",
|
||||
"zerolinewidth": 2,
|
||||
"rangeslider": {
|
||||
"visible": false
|
||||
},
|
||||
"showgrid": true,
|
||||
"showline": true,
|
||||
"tickfont": {
|
||||
"size": 15
|
||||
},
|
||||
"mirror": true,
|
||||
"zeroline": false
|
||||
},
|
||||
"yaxis": {
|
||||
"automargin": true,
|
||||
"ticks": "",
|
||||
"tickfont": {
|
||||
"size": 15
|
||||
},
|
||||
"zerolinewidth": 2,
|
||||
"fixedrange": false,
|
||||
"showgrid": true,
|
||||
"showline": true,
|
||||
"side": "right",
|
||||
"mirror": true,
|
||||
"zeroline": false
|
||||
},
|
||||
"dragmode": "pan",
|
||||
"legend": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0)",
|
||||
"x": 1.1,
|
||||
"xanchor": "left",
|
||||
"y": 0.99,
|
||||
"yanchor": "top"
|
||||
},
|
||||
"legend2": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0)"
|
||||
},
|
||||
"legend3": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0)"
|
||||
},
|
||||
"legend4": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0)"
|
||||
},
|
||||
"legend5": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0)"
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,102 +0,0 @@
|
||||
{
|
||||
"data": {
|
||||
"candlestick": [
|
||||
{
|
||||
"decreasing": {
|
||||
"fillcolor": "#e4003a",
|
||||
"line": {
|
||||
"color": "#e4003a"
|
||||
}
|
||||
},
|
||||
"increasing": {
|
||||
"fillcolor": "#00ACFF",
|
||||
"line": {
|
||||
"color": "#00ACFF"
|
||||
}
|
||||
},
|
||||
"type": "candlestick"
|
||||
}
|
||||
]
|
||||
},
|
||||
"layout": {
|
||||
"annotationdefaults": {
|
||||
"showarrow": false
|
||||
},
|
||||
"autotypenumbers": "strict",
|
||||
"colorway": [
|
||||
"#ffed00",
|
||||
"#ef7d00",
|
||||
"#e4003a",
|
||||
"#c13246",
|
||||
"#822661",
|
||||
"#48277c",
|
||||
"#005ca9",
|
||||
"#00aaff",
|
||||
"#9b30d9",
|
||||
"#af005f",
|
||||
"#5f00af",
|
||||
"#af87ff"
|
||||
],
|
||||
"dragmode": "pan",
|
||||
"font": {
|
||||
"family": "Fira Code",
|
||||
"size": 18
|
||||
},
|
||||
"hoverlabel": {
|
||||
"align": "left"
|
||||
},
|
||||
"mapbox": {
|
||||
"style": "light"
|
||||
},
|
||||
"hovermode": "x",
|
||||
"legend": {
|
||||
"bgcolor": "rgba(0, 0, 0, 0)",
|
||||
"x": 0.01,
|
||||
"xanchor": "left",
|
||||
"y": 0.99,
|
||||
"yanchor": "top",
|
||||
"font": {
|
||||
"size": 15
|
||||
}
|
||||
},
|
||||
"paper_bgcolor": "white",
|
||||
"plot_bgcolor": "white",
|
||||
"xaxis": {
|
||||
"automargin": true,
|
||||
"autorange": true,
|
||||
"rangeslider": {
|
||||
"visible": false
|
||||
},
|
||||
"showgrid": true,
|
||||
"showline": true,
|
||||
"tickfont": {
|
||||
"size": 14
|
||||
},
|
||||
"zeroline": false,
|
||||
"tick0": 1,
|
||||
"title": {
|
||||
"standoff": 20
|
||||
},
|
||||
"linecolor": "#F5EFF3",
|
||||
"mirror": true,
|
||||
"ticks": "outside"
|
||||
},
|
||||
"yaxis": {
|
||||
"anchor": "x",
|
||||
"automargin": true,
|
||||
"fixedrange": false,
|
||||
"zeroline": false,
|
||||
"showgrid": true,
|
||||
"showline": true,
|
||||
"side": "right",
|
||||
"tick0": 0.5,
|
||||
"title": {
|
||||
"standoff": 20
|
||||
},
|
||||
"gridcolor": "#283442",
|
||||
"linecolor": "#F5EFF3",
|
||||
"mirror": true,
|
||||
"ticks": "outside"
|
||||
}
|
||||
}
|
||||
}
|
||||
2132
openbb_sdk/extensions/charting/poetry.lock
generated
vendored
2132
openbb_sdk/extensions/charting/poetry.lock
generated
vendored
File diff suppressed because it is too large
Load Diff
28
openbb_sdk/extensions/charting/pyproject.toml
vendored
28
openbb_sdk/extensions/charting/pyproject.toml
vendored
@@ -1,28 +0,0 @@
|
||||
[tool.poetry]
|
||||
name = "openbb-charting"
|
||||
version = "0.1.0"
|
||||
description = "Charting extension for OpenBB SDK"
|
||||
authors = ["OpenBB Team <hello@openbb.co>"]
|
||||
readme = "README.md"
|
||||
packages = [{ include = "openbb_charting" }]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = ">=3.8,<3.12" # scipy forces python <4.0 explicitly
|
||||
openbb-core = { path = "../../sdk/core" }
|
||||
scipy = "^1.10.0"
|
||||
plotly = "^5.15.0"
|
||||
statsmodels = "^0.14.0"
|
||||
reportlab = "^4.0.4"
|
||||
pywry = "^0.5.13"
|
||||
svglib = "^1.5.1"
|
||||
aiohttp = "^3.8.4"
|
||||
nbformat = "^5.9.0"
|
||||
pandas = ">1.5.3"
|
||||
pandas-ta = "^0.3.14b0"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry.plugins."openbb_core_extension"]
|
||||
openbb_charting = "openbb_charting.charting_router:router"
|
||||
11
openbb_sdk/extensions/crypto/README.md
vendored
11
openbb_sdk/extensions/crypto/README.md
vendored
@@ -1,11 +0,0 @@
|
||||
# Crypto data extension for OpenBB SDK
|
||||
|
||||
This extension provides a set of commands for crypto data retrieval.
|
||||
|
||||
## Installation
|
||||
|
||||
To install the extension, run the following command in this folder:
|
||||
|
||||
```bash
|
||||
pip install .
|
||||
```
|
||||
@@ -1,24 +0,0 @@
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = Router(prefix="")
|
||||
|
||||
|
||||
# pylint: disable=unused-argument
|
||||
@router.command(model="CryptoEOD")
|
||||
def load(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Crypto EOD Price."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
927
openbb_sdk/extensions/crypto/poetry.lock
generated
vendored
927
openbb_sdk/extensions/crypto/poetry.lock
generated
vendored
@@ -1,927 +0,0 @@
|
||||
# This file is automatically @generated by Poetry 1.6.0 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "3.7.1"
|
||||
description = "High level compatibility layer for multiple asynchronous event loop implementations"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
|
||||
{file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
|
||||
idna = ">=2.8"
|
||||
sniffio = ">=1.1"
|
||||
|
||||
[package.extras]
|
||||
doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
|
||||
test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
|
||||
trio = ["trio (<0.22)"]
|
||||
|
||||
[[package]]
|
||||
name = "backoff"
|
||||
version = "2.2.1"
|
||||
description = "Function decoration for backoff and retry"
|
||||
optional = false
|
||||
python-versions = ">=3.7,<4.0"
|
||||
files = [
|
||||
{file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
|
||||
{file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "bcrypt"
|
||||
version = "4.0.1"
|
||||
description = "Modern password hashing for your software and your servers"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-macosx_10_10_universal2.whl", hash = "sha256:b1023030aec778185a6c16cf70f359cbb6e0c289fd564a7cfa29e727a1c38f8f"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:08d2947c490093a11416df18043c27abe3921558d2c03e2076ccb28a116cb6d0"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0eaa47d4661c326bfc9d08d16debbc4edf78778e6aaba29c1bc7ce67214d4410"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ae88eca3024bb34bb3430f964beab71226e761f51b912de5133470b649d82344"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_24_x86_64.whl", hash = "sha256:a522427293d77e1c29e303fc282e2d71864579527a04ddcfda6d4f8396c6c36a"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:fbdaec13c5105f0c4e5c52614d04f0bca5f5af007910daa8b6b12095edaa67b3"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:ca3204d00d3cb2dfed07f2d74a25f12fc12f73e606fcaa6975d1f7ae69cacbb2"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:089098effa1bc35dc055366740a067a2fc76987e8ec75349eb9484061c54f535"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:e9a51bbfe7e9802b5f3508687758b564069ba937748ad7b9e890086290d2f79e"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-win32.whl", hash = "sha256:2caffdae059e06ac23fce178d31b4a702f2a3264c20bfb5ff541b338194d8fab"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-win_amd64.whl", hash = "sha256:8a68f4341daf7522fe8d73874de8906f3a339048ba406be6ddc1b3ccb16fc0d9"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf4fa8b2ca74381bb5442c089350f09a3f17797829d958fad058d6e44d9eb83c"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:67a97e1c405b24f19d08890e7ae0c4f7ce1e56a712a016746c8b2d7732d65d4b"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b3b85202d95dd568efcb35b53936c5e3b3600c7cdcc6115ba461df3a8e89f38d"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cbb03eec97496166b704ed663a53680ab57c5084b2fc98ef23291987b525cb7d"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:5ad4d32a28b80c5fa6671ccfb43676e8c1cc232887759d1cd7b6f56ea4355215"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b57adba8a1444faf784394de3436233728a1ecaeb6e07e8c22c8848f179b893c"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:705b2cea8a9ed3d55b4491887ceadb0106acf7c6387699fca771af56b1cdeeda"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:2b3ac11cf45161628f1f3733263e63194f22664bf4d0c0f3ab34099c02134665"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:3100851841186c25f127731b9fa11909ab7b1df6fc4b9f8353f4f1fd952fbf71"},
|
||||
{file = "bcrypt-4.0.1.tar.gz", hash = "sha256:27d375903ac8261cfe4047f6709d16f7d18d39b1ec92aaf72af989552a650ebd"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
tests = ["pytest (>=3.2.1,!=3.3.0)"]
|
||||
typecheck = ["mypy"]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2023.7.22"
|
||||
description = "Python package for providing Mozilla's CA Bundle."
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
|
||||
{file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "charset-normalizer"
|
||||
version = "3.2.0"
|
||||
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
|
||||
optional = false
|
||||
python-versions = ">=3.7.0"
|
||||
files = [
|
||||
{file = "charset-normalizer-3.2.0.tar.gz", hash = "sha256:3bb3d25a8e6c0aedd251753a79ae98a093c7e7b471faa3aa9a93a81431987ace"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0b87549028f680ca955556e3bd57013ab47474c3124dc069faa0b6545b6c9710"},
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c57e4c1349fbe0e446c9fa7b19ed2f8a4417233b6984277cce392819123142d3"},
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||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b627c266f295de9dea86bd1112ed3d5fafb69a348af30a2422e16590a8ecba13"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:05a7233089f8bd355e8cbe127c2e8ca0b4ea55467861906b80d2ebc7db4d6b72"},
|
||||
{file = "websockets-10.4.tar.gz", hash = "sha256:eef610b23933c54d5d921c92578ae5f89813438fded840c2e9809d378dc765d3"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.16.2"
|
||||
description = "Backport of pathlib-compatible object wrapper for zip files"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"},
|
||||
{file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.8"
|
||||
content-hash = "ed5c1001c4f47bae1cfde8d8509294643e3b3ea101a8482c3f0248085360bb18"
|
||||
18
openbb_sdk/extensions/crypto/pyproject.toml
vendored
18
openbb_sdk/extensions/crypto/pyproject.toml
vendored
@@ -1,18 +0,0 @@
|
||||
[tool.poetry]
|
||||
name = "openbb-crypto"
|
||||
version = "0.1.1"
|
||||
description = ""
|
||||
authors = ["OpenBB Team <hello@openbb.co>"]
|
||||
readme = "README.md"
|
||||
packages = [{ include = "openbb_crypto" }]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.8"
|
||||
openbb-core = { path = "../../sdk/core" }
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry.plugins."openbb_core_extension"]
|
||||
crypto = "openbb_crypto.crypto_router:router"
|
||||
11
openbb_sdk/extensions/economy/README.md
vendored
11
openbb_sdk/extensions/economy/README.md
vendored
@@ -1,11 +0,0 @@
|
||||
# OpenBB Economy Extension
|
||||
|
||||
The Economy extension provides global macroeconomic data access for the OpenBB SDK.
|
||||
|
||||
## Installation
|
||||
|
||||
To install the extension, run the following command in this folder:
|
||||
|
||||
```bash
|
||||
pip install .
|
||||
```
|
||||
@@ -1,332 +0,0 @@
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = Router(prefix="")
|
||||
|
||||
|
||||
# Remove this once the placeholders are replaced with real commands.
|
||||
|
||||
# pylint: disable=unused-argument
|
||||
|
||||
|
||||
@router.command
|
||||
def corecpi(
|
||||
cc: CommandContext, provider_choices: ProviderChoices
|
||||
) -> OBBject[Empty]: # type: ignore
|
||||
"""CORECPI."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="MajorIndicesConstituents")
|
||||
def const(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Get the constituents of an index."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="CPI")
|
||||
def cpi(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""CPI."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def cpi_options(
|
||||
cc: CommandContext, provider_choices: ProviderChoices
|
||||
) -> OBBject[Empty]:
|
||||
"""Get the options for v3 cpi(options=True)"""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="MajorIndicesEOD")
|
||||
def index(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Get OHLCV data for an index."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="AvailableIndices")
|
||||
def available_indices(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""AVAILABLE_INDICES."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="RiskPremium")
|
||||
def risk(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Market Risk Premium."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def macro(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]: # type: ignore
|
||||
"""Query EconDB for macro data."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def macro_countries(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""MACRO_COUNTRIES."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def macro_parameters(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""MACRO_PARAMETERS."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def balance(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""BALANCE."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def bigmac(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""BIGMAC."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def country_codes(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""COUNTRY_CODES."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def currencies(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""CURRENCIES."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def debt(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""DEBT."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def events(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""EVENTS."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def fgdp(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""FGDP."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def fred(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""FRED."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def fred_search(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""FRED Search (was fred_notes)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def futures(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""FUTURES. 2 sources"""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def gdp(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""GDP."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def glbonds(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""GLBONDS."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def indices(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""INDICES."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def overview(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""OVERVIEW."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def perfmap(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""PERFMAP."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def performance(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""PERFORMANCE."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def revenue(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""REVENUE."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def rgdp(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""RGDP."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def rtps(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""RTPS."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def search_index(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""SEARCH_INDEX."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def spending(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""SPENDING."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def trust(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""TRUST."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def usbonds(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""USBONDS."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def valuation(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
) -> OBBject[Empty]:
|
||||
"""VALUATION."""
|
||||
return OBBject(results=Empty())
|
||||
927
openbb_sdk/extensions/economy/poetry.lock
generated
vendored
927
openbb_sdk/extensions/economy/poetry.lock
generated
vendored
@@ -1,927 +0,0 @@
|
||||
# This file is automatically @generated by Poetry 1.6.0 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "3.7.1"
|
||||
description = "High level compatibility layer for multiple asynchronous event loop implementations"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
|
||||
{file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
|
||||
idna = ">=2.8"
|
||||
sniffio = ">=1.1"
|
||||
|
||||
[package.extras]
|
||||
doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
|
||||
test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
|
||||
trio = ["trio (<0.22)"]
|
||||
|
||||
[[package]]
|
||||
name = "backoff"
|
||||
version = "2.2.1"
|
||||
description = "Function decoration for backoff and retry"
|
||||
optional = false
|
||||
python-versions = ">=3.7,<4.0"
|
||||
files = [
|
||||
{file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
|
||||
{file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "bcrypt"
|
||||
version = "4.0.1"
|
||||
description = "Modern password hashing for your software and your servers"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-macosx_10_10_universal2.whl", hash = "sha256:b1023030aec778185a6c16cf70f359cbb6e0c289fd564a7cfa29e727a1c38f8f"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:08d2947c490093a11416df18043c27abe3921558d2c03e2076ccb28a116cb6d0"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0eaa47d4661c326bfc9d08d16debbc4edf78778e6aaba29c1bc7ce67214d4410"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ae88eca3024bb34bb3430f964beab71226e761f51b912de5133470b649d82344"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_24_x86_64.whl", hash = "sha256:a522427293d77e1c29e303fc282e2d71864579527a04ddcfda6d4f8396c6c36a"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:fbdaec13c5105f0c4e5c52614d04f0bca5f5af007910daa8b6b12095edaa67b3"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:ca3204d00d3cb2dfed07f2d74a25f12fc12f73e606fcaa6975d1f7ae69cacbb2"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:089098effa1bc35dc055366740a067a2fc76987e8ec75349eb9484061c54f535"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:e9a51bbfe7e9802b5f3508687758b564069ba937748ad7b9e890086290d2f79e"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-win32.whl", hash = "sha256:2caffdae059e06ac23fce178d31b4a702f2a3264c20bfb5ff541b338194d8fab"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-win_amd64.whl", hash = "sha256:8a68f4341daf7522fe8d73874de8906f3a339048ba406be6ddc1b3ccb16fc0d9"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf4fa8b2ca74381bb5442c089350f09a3f17797829d958fad058d6e44d9eb83c"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:67a97e1c405b24f19d08890e7ae0c4f7ce1e56a712a016746c8b2d7732d65d4b"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b3b85202d95dd568efcb35b53936c5e3b3600c7cdcc6115ba461df3a8e89f38d"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cbb03eec97496166b704ed663a53680ab57c5084b2fc98ef23291987b525cb7d"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:5ad4d32a28b80c5fa6671ccfb43676e8c1cc232887759d1cd7b6f56ea4355215"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b57adba8a1444faf784394de3436233728a1ecaeb6e07e8c22c8848f179b893c"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:705b2cea8a9ed3d55b4491887ceadb0106acf7c6387699fca771af56b1cdeeda"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:2b3ac11cf45161628f1f3733263e63194f22664bf4d0c0f3ab34099c02134665"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:3100851841186c25f127731b9fa11909ab7b1df6fc4b9f8353f4f1fd952fbf71"},
|
||||
{file = "bcrypt-4.0.1.tar.gz", hash = "sha256:27d375903ac8261cfe4047f6709d16f7d18d39b1ec92aaf72af989552a650ebd"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
tests = ["pytest (>=3.2.1,!=3.3.0)"]
|
||||
typecheck = ["mypy"]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2023.7.22"
|
||||
description = "Python package for providing Mozilla's CA Bundle."
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
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||||
{file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "charset-normalizer"
|
||||
version = "3.2.0"
|
||||
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
|
||||
optional = false
|
||||
python-versions = ">=3.7.0"
|
||||
files = [
|
||||
{file = "charset-normalizer-3.2.0.tar.gz", hash = "sha256:3bb3d25a8e6c0aedd251753a79ae98a093c7e7b471faa3aa9a93a81431987ace"},
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||||
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||||
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|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a103b3a7069b62f5d4890ae1b8f0597618f628b286b03d4bc9195230b154bfa9"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94aea8eff76ee6d1cdacb07dd2123a68283cb5569e0250feab1240058f53b623"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:db901e2ac34c931d73054d9797383d0f8009991e723dab15109740a63e7f902a"},
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||||
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:193cbc708ea3aca45e7221ae58f0fd63f933753a9bfb498a3b474878f12caaad"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09393e1b2a9461950b1c9a45d5fd251dc7c6f228acab64da1c9c0165d9c7765c"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:baacc6aee0b2ef6f3d308e197b5d7a81c0e70b06beae1f1fcacffdbd124fe0e3"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:bf420121d4c8dce6b889f0e8e4ec0ca34b7f40186203f06a946fa0276ba54029"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:c04a46716adde8d927adb9457bbe39cf473e1e2c2f5d0a16ceb837e5d841ad4f"},
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||||
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||||
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-win32.whl", hash = "sha256:04e57ab9fbf9607b77f7d057974694b4f6b142da9ed4a199859d9d4d5c63fe96"},
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||||
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||||
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||||
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||||
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||||
{file = "charset_normalizer-3.2.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f25c229a6ba38a35ae6e25ca1264621cc25d4d38dca2942a7fce0b67a4efe918"},
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||||
{file = "charset_normalizer-3.2.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:2efb1bd13885392adfda4614c33d3b68dee4921fd0ac1d3988f8cbb7d589e72a"},
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{file = "websockets-10.4-cp38-cp38-win32.whl", hash = "sha256:db3c336f9eda2532ec0fd8ea49fef7a8df8f6c804cdf4f39e5c5c0d4a4ad9a7a"},
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{file = "websockets-10.4-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:40e826de3085721dabc7cf9bfd41682dadc02286d8cf149b3ad05bff89311e4f"},
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{file = "websockets-10.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:56029457f219ade1f2fc12a6504ea61e14ee227a815531f9738e41203a429112"},
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{file = "websockets-10.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f5fc088b7a32f244c519a048c170f14cf2251b849ef0e20cbbb0fdf0fdaf556f"},
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{file = "websockets-10.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2fc8709c00704194213d45e455adc106ff9e87658297f72d544220e32029cd3d"},
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{file = "websockets-10.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0154f7691e4fe6c2b2bc275b5701e8b158dae92a1ab229e2b940efe11905dff4"},
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{file = "websockets-10.4-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c6d2264f485f0b53adf22697ac11e261ce84805c232ed5dbe6b1bcb84b00ff0"},
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{file = "websockets-10.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:9bc42e8402dc5e9905fb8b9649f57efcb2056693b7e88faa8fb029256ba9c68c"},
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{file = "websockets-10.4-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:edc344de4dac1d89300a053ac973299e82d3db56330f3494905643bb68801269"},
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{file = "websockets-10.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:84bc2a7d075f32f6ed98652db3a680a17a4edb21ca7f80fe42e38753a58ee02b"},
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{file = "websockets-10.4-cp39-cp39-win32.whl", hash = "sha256:c94ae4faf2d09f7c81847c63843f84fe47bf6253c9d60b20f25edfd30fb12588"},
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{file = "websockets-10.4-cp39-cp39-win_amd64.whl", hash = "sha256:bbccd847aa0c3a69b5f691a84d2341a4f8a629c6922558f2a70611305f902d74"},
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{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d210abe51b5da0ffdbf7b43eed0cfdff8a55a1ab17abbec4301c9ff077dd0342"},
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||||
{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:942de28af58f352a6f588bc72490ae0f4ccd6dfc2bd3de5945b882a078e4e179"},
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||||
{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c9b27d6c1c6cd53dc93614967e9ce00ae7f864a2d9f99fe5ed86706e1ecbf485"},
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||||
{file = "websockets-10.4-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:3d3cac3e32b2c8414f4f87c1b2ab686fa6284a980ba283617404377cd448f631"},
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||||
{file = "websockets-10.4-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:da39dd03d130162deb63da51f6e66ed73032ae62e74aaccc4236e30edccddbb0"},
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||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:389f8dbb5c489e305fb113ca1b6bdcdaa130923f77485db5b189de343a179393"},
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||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09a1814bb15eff7069e51fed0826df0bc0702652b5cb8f87697d469d79c23576"},
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||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ff64a1d38d156d429404aaa84b27305e957fd10c30e5880d1765c9480bea490f"},
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||||
{file = "websockets-10.4-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:b343f521b047493dc4022dd338fc6db9d9282658862756b4f6fd0e996c1380e1"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:932af322458da7e4e35df32f050389e13d3d96b09d274b22a7aa1808f292fee4"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d6a4162139374a49eb18ef5b2f4da1dd95c994588f5033d64e0bbfda4b6b6fcf"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c57e4c1349fbe0e446c9fa7b19ed2f8a4417233b6984277cce392819123142d3"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b627c266f295de9dea86bd1112ed3d5fafb69a348af30a2422e16590a8ecba13"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:05a7233089f8bd355e8cbe127c2e8ca0b4ea55467861906b80d2ebc7db4d6b72"},
|
||||
{file = "websockets-10.4.tar.gz", hash = "sha256:eef610b23933c54d5d921c92578ae5f89813438fded840c2e9809d378dc765d3"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.16.2"
|
||||
description = "Backport of pathlib-compatible object wrapper for zip files"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"},
|
||||
{file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.8"
|
||||
content-hash = "ed5c1001c4f47bae1cfde8d8509294643e3b3ea101a8482c3f0248085360bb18"
|
||||
18
openbb_sdk/extensions/economy/pyproject.toml
vendored
18
openbb_sdk/extensions/economy/pyproject.toml
vendored
@@ -1,18 +0,0 @@
|
||||
[tool.poetry]
|
||||
name = "openbb-economy"
|
||||
version = "0.1.1"
|
||||
description = ""
|
||||
authors = ["OpenBB Team <hello@openbb.co>"]
|
||||
readme = "README.md"
|
||||
packages = [{ include = "openbb_economy" }]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.8"
|
||||
openbb-core = { path = "../../sdk/core" }
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry.plugins."openbb_core_extension"]
|
||||
economy = "openbb_economy.economy_router:router"
|
||||
13
openbb_sdk/extensions/fixedincome/README.md
vendored
13
openbb_sdk/extensions/fixedincome/README.md
vendored
@@ -1,13 +0,0 @@
|
||||
# OpenBB Fixed Income Extension
|
||||
|
||||
This extension provides fixed income data for the OpenBB SDK.
|
||||
|
||||
Features of the Fixed Income extension include information on government bonds and central bank rates.
|
||||
|
||||
## Installation
|
||||
|
||||
To install the extension, run the following command in this folder:
|
||||
|
||||
```bash
|
||||
pip install .
|
||||
```
|
||||
@@ -1,32 +0,0 @@
|
||||
# pylint: disable=W0613:unused-argument
|
||||
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = Router(prefix="")
|
||||
|
||||
|
||||
@router.command(model="TreasuryRates")
|
||||
def treasury(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Get treasury rates."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def ycrv() -> OBBject[Empty]: # type: ignore
|
||||
"""Yield curve."""
|
||||
return OBBject(results=Empty())
|
||||
927
openbb_sdk/extensions/fixedincome/poetry.lock
generated
vendored
927
openbb_sdk/extensions/fixedincome/poetry.lock
generated
vendored
@@ -1,927 +0,0 @@
|
||||
# This file is automatically @generated by Poetry 1.6.0 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "3.7.1"
|
||||
description = "High level compatibility layer for multiple asynchronous event loop implementations"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
|
||||
{file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
|
||||
idna = ">=2.8"
|
||||
sniffio = ">=1.1"
|
||||
|
||||
[package.extras]
|
||||
doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
|
||||
test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
|
||||
trio = ["trio (<0.22)"]
|
||||
|
||||
[[package]]
|
||||
name = "backoff"
|
||||
version = "2.2.1"
|
||||
description = "Function decoration for backoff and retry"
|
||||
optional = false
|
||||
python-versions = ">=3.7,<4.0"
|
||||
files = [
|
||||
{file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
|
||||
{file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "bcrypt"
|
||||
version = "4.0.1"
|
||||
description = "Modern password hashing for your software and your servers"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-macosx_10_10_universal2.whl", hash = "sha256:b1023030aec778185a6c16cf70f359cbb6e0c289fd564a7cfa29e727a1c38f8f"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:08d2947c490093a11416df18043c27abe3921558d2c03e2076ccb28a116cb6d0"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0eaa47d4661c326bfc9d08d16debbc4edf78778e6aaba29c1bc7ce67214d4410"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ae88eca3024bb34bb3430f964beab71226e761f51b912de5133470b649d82344"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_24_x86_64.whl", hash = "sha256:a522427293d77e1c29e303fc282e2d71864579527a04ddcfda6d4f8396c6c36a"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:fbdaec13c5105f0c4e5c52614d04f0bca5f5af007910daa8b6b12095edaa67b3"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:ca3204d00d3cb2dfed07f2d74a25f12fc12f73e606fcaa6975d1f7ae69cacbb2"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:089098effa1bc35dc055366740a067a2fc76987e8ec75349eb9484061c54f535"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:e9a51bbfe7e9802b5f3508687758b564069ba937748ad7b9e890086290d2f79e"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-win32.whl", hash = "sha256:2caffdae059e06ac23fce178d31b4a702f2a3264c20bfb5ff541b338194d8fab"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-win_amd64.whl", hash = "sha256:8a68f4341daf7522fe8d73874de8906f3a339048ba406be6ddc1b3ccb16fc0d9"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf4fa8b2ca74381bb5442c089350f09a3f17797829d958fad058d6e44d9eb83c"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:67a97e1c405b24f19d08890e7ae0c4f7ce1e56a712a016746c8b2d7732d65d4b"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b3b85202d95dd568efcb35b53936c5e3b3600c7cdcc6115ba461df3a8e89f38d"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cbb03eec97496166b704ed663a53680ab57c5084b2fc98ef23291987b525cb7d"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:5ad4d32a28b80c5fa6671ccfb43676e8c1cc232887759d1cd7b6f56ea4355215"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b57adba8a1444faf784394de3436233728a1ecaeb6e07e8c22c8848f179b893c"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:705b2cea8a9ed3d55b4491887ceadb0106acf7c6387699fca771af56b1cdeeda"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:2b3ac11cf45161628f1f3733263e63194f22664bf4d0c0f3ab34099c02134665"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:3100851841186c25f127731b9fa11909ab7b1df6fc4b9f8353f4f1fd952fbf71"},
|
||||
{file = "bcrypt-4.0.1.tar.gz", hash = "sha256:27d375903ac8261cfe4047f6709d16f7d18d39b1ec92aaf72af989552a650ebd"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
tests = ["pytest (>=3.2.1,!=3.3.0)"]
|
||||
typecheck = ["mypy"]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2023.7.22"
|
||||
description = "Python package for providing Mozilla's CA Bundle."
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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{file = "websockets-10.4-cp39-cp39-win32.whl", hash = "sha256:c94ae4faf2d09f7c81847c63843f84fe47bf6253c9d60b20f25edfd30fb12588"},
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||||
{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:942de28af58f352a6f588bc72490ae0f4ccd6dfc2bd3de5945b882a078e4e179"},
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||||
{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c9b27d6c1c6cd53dc93614967e9ce00ae7f864a2d9f99fe5ed86706e1ecbf485"},
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||||
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||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09a1814bb15eff7069e51fed0826df0bc0702652b5cb8f87697d469d79c23576"},
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||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ff64a1d38d156d429404aaa84b27305e957fd10c30e5880d1765c9480bea490f"},
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||||
{file = "websockets-10.4-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:b343f521b047493dc4022dd338fc6db9d9282658862756b4f6fd0e996c1380e1"},
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||||
{file = "websockets-10.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:932af322458da7e4e35df32f050389e13d3d96b09d274b22a7aa1808f292fee4"},
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||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d6a4162139374a49eb18ef5b2f4da1dd95c994588f5033d64e0bbfda4b6b6fcf"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c57e4c1349fbe0e446c9fa7b19ed2f8a4417233b6984277cce392819123142d3"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b627c266f295de9dea86bd1112ed3d5fafb69a348af30a2422e16590a8ecba13"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:05a7233089f8bd355e8cbe127c2e8ca0b4ea55467861906b80d2ebc7db4d6b72"},
|
||||
{file = "websockets-10.4.tar.gz", hash = "sha256:eef610b23933c54d5d921c92578ae5f89813438fded840c2e9809d378dc765d3"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.16.2"
|
||||
description = "Backport of pathlib-compatible object wrapper for zip files"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"},
|
||||
{file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.8"
|
||||
content-hash = "ed5c1001c4f47bae1cfde8d8509294643e3b3ea101a8482c3f0248085360bb18"
|
||||
18
openbb_sdk/extensions/fixedincome/pyproject.toml
vendored
18
openbb_sdk/extensions/fixedincome/pyproject.toml
vendored
@@ -1,18 +0,0 @@
|
||||
[tool.poetry]
|
||||
name = "openbb-fixedincome"
|
||||
version = "0.1.1"
|
||||
description = ""
|
||||
authors = ["OpenBB Team <hello@openbb.co>"]
|
||||
readme = "README.md"
|
||||
packages = [{ include = "openbb_fixedincome" }]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.8"
|
||||
openbb-core = { path = "../../sdk/core" }
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry.plugins."openbb_core_extension"]
|
||||
fixedincome = "openbb_fixedincome.fixedincome_router:router"
|
||||
11
openbb_sdk/extensions/forex/README.md
vendored
11
openbb_sdk/extensions/forex/README.md
vendored
@@ -1,11 +0,0 @@
|
||||
# OpenBB Forex Extension
|
||||
|
||||
This extension provides currency exchange related data for the OpenBB SDK.
|
||||
|
||||
## Installation
|
||||
|
||||
To install the extension, run the following command in this folder:
|
||||
|
||||
```bash
|
||||
pip install .
|
||||
```
|
||||
@@ -1,36 +0,0 @@
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = Router(prefix="")
|
||||
|
||||
|
||||
# pylint: disable=unused-argument
|
||||
@router.command(model="ForexPairs")
|
||||
def pairs(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Forex Available Pairs."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
# pylint: disable=unused-argument
|
||||
@router.command(model="ForexEOD")
|
||||
def load(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Forex Intraday Price."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
927
openbb_sdk/extensions/forex/poetry.lock
generated
vendored
927
openbb_sdk/extensions/forex/poetry.lock
generated
vendored
@@ -1,927 +0,0 @@
|
||||
# This file is automatically @generated by Poetry 1.6.0 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "3.7.1"
|
||||
description = "High level compatibility layer for multiple asynchronous event loop implementations"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
|
||||
{file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
|
||||
idna = ">=2.8"
|
||||
sniffio = ">=1.1"
|
||||
|
||||
[package.extras]
|
||||
doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
|
||||
test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
|
||||
trio = ["trio (<0.22)"]
|
||||
|
||||
[[package]]
|
||||
name = "backoff"
|
||||
version = "2.2.1"
|
||||
description = "Function decoration for backoff and retry"
|
||||
optional = false
|
||||
python-versions = ">=3.7,<4.0"
|
||||
files = [
|
||||
{file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
|
||||
{file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "bcrypt"
|
||||
version = "4.0.1"
|
||||
description = "Modern password hashing for your software and your servers"
|
||||
optional = false
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
|
||||
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|
||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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|
||||
18
openbb_sdk/extensions/forex/pyproject.toml
vendored
18
openbb_sdk/extensions/forex/pyproject.toml
vendored
@@ -1,18 +0,0 @@
|
||||
[tool.poetry]
|
||||
name = "openbb-forex"
|
||||
version = "0.1.1"
|
||||
description = ""
|
||||
authors = ["OpenBB Team <hello@openbb.co>"]
|
||||
readme = "README.md"
|
||||
packages = [{ include = "openbb_forex" }]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.8"
|
||||
openbb-core = { path = "../../sdk/core" }
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry.plugins."openbb_core_extension"]
|
||||
forex = "openbb_forex.forex_router:router"
|
||||
11
openbb_sdk/extensions/futures/README.md
vendored
11
openbb_sdk/extensions/futures/README.md
vendored
@@ -1,11 +0,0 @@
|
||||
# Futures data extension for OpenBB SDK
|
||||
|
||||
This extension provides a set of commands for futures data retrieval.
|
||||
|
||||
## Installation
|
||||
|
||||
To install the extension, run the following command in this folder:
|
||||
|
||||
```bash
|
||||
pip install .
|
||||
```
|
||||
@@ -1,35 +0,0 @@
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = Router(prefix="")
|
||||
|
||||
|
||||
# pylint: disable=unused-argument
|
||||
@router.command(model="FuturesEOD")
|
||||
def load(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Futures EOD Price."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="FuturesCurve")
|
||||
def curve(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Futures EOD Price."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
927
openbb_sdk/extensions/futures/poetry.lock
generated
vendored
927
openbb_sdk/extensions/futures/poetry.lock
generated
vendored
@@ -1,927 +0,0 @@
|
||||
# This file is automatically @generated by Poetry 1.6.0 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "3.7.1"
|
||||
description = "High level compatibility layer for multiple asynchronous event loop implementations"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
|
||||
{file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
|
||||
idna = ">=2.8"
|
||||
sniffio = ">=1.1"
|
||||
|
||||
[package.extras]
|
||||
doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
|
||||
test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
|
||||
trio = ["trio (<0.22)"]
|
||||
|
||||
[[package]]
|
||||
name = "backoff"
|
||||
version = "2.2.1"
|
||||
description = "Function decoration for backoff and retry"
|
||||
optional = false
|
||||
python-versions = ">=3.7,<4.0"
|
||||
files = [
|
||||
{file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
|
||||
{file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "bcrypt"
|
||||
version = "4.0.1"
|
||||
description = "Modern password hashing for your software and your servers"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-macosx_10_10_universal2.whl", hash = "sha256:b1023030aec778185a6c16cf70f359cbb6e0c289fd564a7cfa29e727a1c38f8f"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:08d2947c490093a11416df18043c27abe3921558d2c03e2076ccb28a116cb6d0"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0eaa47d4661c326bfc9d08d16debbc4edf78778e6aaba29c1bc7ce67214d4410"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ae88eca3024bb34bb3430f964beab71226e761f51b912de5133470b649d82344"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_24_x86_64.whl", hash = "sha256:a522427293d77e1c29e303fc282e2d71864579527a04ddcfda6d4f8396c6c36a"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:fbdaec13c5105f0c4e5c52614d04f0bca5f5af007910daa8b6b12095edaa67b3"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:ca3204d00d3cb2dfed07f2d74a25f12fc12f73e606fcaa6975d1f7ae69cacbb2"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:089098effa1bc35dc055366740a067a2fc76987e8ec75349eb9484061c54f535"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:e9a51bbfe7e9802b5f3508687758b564069ba937748ad7b9e890086290d2f79e"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-win32.whl", hash = "sha256:2caffdae059e06ac23fce178d31b4a702f2a3264c20bfb5ff541b338194d8fab"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-win_amd64.whl", hash = "sha256:8a68f4341daf7522fe8d73874de8906f3a339048ba406be6ddc1b3ccb16fc0d9"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf4fa8b2ca74381bb5442c089350f09a3f17797829d958fad058d6e44d9eb83c"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:67a97e1c405b24f19d08890e7ae0c4f7ce1e56a712a016746c8b2d7732d65d4b"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b3b85202d95dd568efcb35b53936c5e3b3600c7cdcc6115ba461df3a8e89f38d"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cbb03eec97496166b704ed663a53680ab57c5084b2fc98ef23291987b525cb7d"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:5ad4d32a28b80c5fa6671ccfb43676e8c1cc232887759d1cd7b6f56ea4355215"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b57adba8a1444faf784394de3436233728a1ecaeb6e07e8c22c8848f179b893c"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:705b2cea8a9ed3d55b4491887ceadb0106acf7c6387699fca771af56b1cdeeda"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:2b3ac11cf45161628f1f3733263e63194f22664bf4d0c0f3ab34099c02134665"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:3100851841186c25f127731b9fa11909ab7b1df6fc4b9f8353f4f1fd952fbf71"},
|
||||
{file = "bcrypt-4.0.1.tar.gz", hash = "sha256:27d375903ac8261cfe4047f6709d16f7d18d39b1ec92aaf72af989552a650ebd"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
tests = ["pytest (>=3.2.1,!=3.3.0)"]
|
||||
typecheck = ["mypy"]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2023.7.22"
|
||||
description = "Python package for providing Mozilla's CA Bundle."
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
|
||||
{file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "charset-normalizer"
|
||||
version = "3.2.0"
|
||||
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
|
||||
optional = false
|
||||
python-versions = ">=3.7.0"
|
||||
files = [
|
||||
{file = "charset-normalizer-3.2.0.tar.gz", hash = "sha256:3bb3d25a8e6c0aedd251753a79ae98a093c7e7b471faa3aa9a93a81431987ace"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0b87549028f680ca955556e3bd57013ab47474c3124dc069faa0b6545b6c9710"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7c70087bfee18a42b4040bb9ec1ca15a08242cf5867c58726530bdf3945672ed"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a103b3a7069b62f5d4890ae1b8f0597618f628b286b03d4bc9195230b154bfa9"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94aea8eff76ee6d1cdacb07dd2123a68283cb5569e0250feab1240058f53b623"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:db901e2ac34c931d73054d9797383d0f8009991e723dab15109740a63e7f902a"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b0dac0ff919ba34d4df1b6131f59ce95b08b9065233446be7e459f95554c0dc8"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:193cbc708ea3aca45e7221ae58f0fd63f933753a9bfb498a3b474878f12caaad"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09393e1b2a9461950b1c9a45d5fd251dc7c6f228acab64da1c9c0165d9c7765c"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:baacc6aee0b2ef6f3d308e197b5d7a81c0e70b06beae1f1fcacffdbd124fe0e3"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:bf420121d4c8dce6b889f0e8e4ec0ca34b7f40186203f06a946fa0276ba54029"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:c04a46716adde8d927adb9457bbe39cf473e1e2c2f5d0a16ceb837e5d841ad4f"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:aaf63899c94de41fe3cf934601b0f7ccb6b428c6e4eeb80da72c58eab077b19a"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:d62e51710986674142526ab9f78663ca2b0726066ae26b78b22e0f5e571238dd"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-win32.whl", hash = "sha256:04e57ab9fbf9607b77f7d057974694b4f6b142da9ed4a199859d9d4d5c63fe96"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-win_amd64.whl", hash = "sha256:48021783bdf96e3d6de03a6e39a1171ed5bd7e8bb93fc84cc649d11490f87cea"},
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||||
{file = "charset_normalizer-3.2.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:4957669ef390f0e6719db3613ab3a7631e68424604a7b448f079bee145da6e09"},
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||||
{file = "charset_normalizer-3.2.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:46fb8c61d794b78ec7134a715a3e564aafc8f6b5e338417cb19fe9f57a5a9bf2"},
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
{file = "charset_normalizer-3.2.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:41b25eaa7d15909cf3ac4c96088c1f266a9a93ec44f87f1d13d4a0e86c81b982"},
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||||
{file = "charset_normalizer-3.2.0-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f058f6963fd82eb143c692cecdc89e075fa0828db2e5b291070485390b2f1c9c"},
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||||
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||||
{file = "charset_normalizer-3.2.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eef9df1eefada2c09a5e7a40991b9fc6ac6ef20b1372abd48d2794a316dc0449"},
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{file = "websockets-10.4-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:82ff5e1cae4e855147fd57a2863376ed7454134c2bf49ec604dfe71e446e2193"},
|
||||
{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d210abe51b5da0ffdbf7b43eed0cfdff8a55a1ab17abbec4301c9ff077dd0342"},
|
||||
{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:942de28af58f352a6f588bc72490ae0f4ccd6dfc2bd3de5945b882a078e4e179"},
|
||||
{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c9b27d6c1c6cd53dc93614967e9ce00ae7f864a2d9f99fe5ed86706e1ecbf485"},
|
||||
{file = "websockets-10.4-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:3d3cac3e32b2c8414f4f87c1b2ab686fa6284a980ba283617404377cd448f631"},
|
||||
{file = "websockets-10.4-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:da39dd03d130162deb63da51f6e66ed73032ae62e74aaccc4236e30edccddbb0"},
|
||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:389f8dbb5c489e305fb113ca1b6bdcdaa130923f77485db5b189de343a179393"},
|
||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09a1814bb15eff7069e51fed0826df0bc0702652b5cb8f87697d469d79c23576"},
|
||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ff64a1d38d156d429404aaa84b27305e957fd10c30e5880d1765c9480bea490f"},
|
||||
{file = "websockets-10.4-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:b343f521b047493dc4022dd338fc6db9d9282658862756b4f6fd0e996c1380e1"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:932af322458da7e4e35df32f050389e13d3d96b09d274b22a7aa1808f292fee4"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d6a4162139374a49eb18ef5b2f4da1dd95c994588f5033d64e0bbfda4b6b6fcf"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c57e4c1349fbe0e446c9fa7b19ed2f8a4417233b6984277cce392819123142d3"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b627c266f295de9dea86bd1112ed3d5fafb69a348af30a2422e16590a8ecba13"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:05a7233089f8bd355e8cbe127c2e8ca0b4ea55467861906b80d2ebc7db4d6b72"},
|
||||
{file = "websockets-10.4.tar.gz", hash = "sha256:eef610b23933c54d5d921c92578ae5f89813438fded840c2e9809d378dc765d3"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.16.2"
|
||||
description = "Backport of pathlib-compatible object wrapper for zip files"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"},
|
||||
{file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.8"
|
||||
content-hash = "ed5c1001c4f47bae1cfde8d8509294643e3b3ea101a8482c3f0248085360bb18"
|
||||
18
openbb_sdk/extensions/futures/pyproject.toml
vendored
18
openbb_sdk/extensions/futures/pyproject.toml
vendored
@@ -1,18 +0,0 @@
|
||||
[tool.poetry]
|
||||
name = "openbb-futures"
|
||||
version = "0.1.1"
|
||||
description = ""
|
||||
authors = ["OpenBB Team <hello@openbb.co>"]
|
||||
readme = "README.md"
|
||||
packages = [{ include = "openbb_futures" }]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.8"
|
||||
openbb-core = { path = "../../sdk/core" }
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry.plugins."openbb_core_extension"]
|
||||
futures = "openbb_futures.futures_router:router"
|
||||
11
openbb_sdk/extensions/news/README.md
vendored
11
openbb_sdk/extensions/news/README.md
vendored
@@ -1,11 +0,0 @@
|
||||
# OpenBB News Extension
|
||||
|
||||
This extension provides news for the OpenBB SDK.
|
||||
|
||||
## Installation
|
||||
|
||||
To install the extension, run the following command in this folder:
|
||||
|
||||
```bash
|
||||
pip install .
|
||||
```
|
||||
@@ -1,33 +0,0 @@
|
||||
# pylint: disable=import-outside-toplevel, W0613:unused-argument
|
||||
"""News Router."""
|
||||
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = Router(prefix="")
|
||||
|
||||
|
||||
@router.command(model="GlobalNews")
|
||||
def globalnews(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Global News."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def sectornews() -> OBBject[Empty]: # type: ignore
|
||||
"""Sector news."""
|
||||
return OBBject(results=Empty())
|
||||
927
openbb_sdk/extensions/news/poetry.lock
generated
vendored
927
openbb_sdk/extensions/news/poetry.lock
generated
vendored
@@ -1,927 +0,0 @@
|
||||
# This file is automatically @generated by Poetry 1.6.0 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "3.7.1"
|
||||
description = "High level compatibility layer for multiple asynchronous event loop implementations"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
|
||||
{file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
|
||||
idna = ">=2.8"
|
||||
sniffio = ">=1.1"
|
||||
|
||||
[package.extras]
|
||||
doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
|
||||
test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
|
||||
trio = ["trio (<0.22)"]
|
||||
|
||||
[[package]]
|
||||
name = "backoff"
|
||||
version = "2.2.1"
|
||||
description = "Function decoration for backoff and retry"
|
||||
optional = false
|
||||
python-versions = ">=3.7,<4.0"
|
||||
files = [
|
||||
{file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
|
||||
{file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "bcrypt"
|
||||
version = "4.0.1"
|
||||
description = "Modern password hashing for your software and your servers"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-macosx_10_10_universal2.whl", hash = "sha256:b1023030aec778185a6c16cf70f359cbb6e0c289fd564a7cfa29e727a1c38f8f"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.manylinux_2_24_aarch64.whl", hash = "sha256:08d2947c490093a11416df18043c27abe3921558d2c03e2076ccb28a116cb6d0"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0eaa47d4661c326bfc9d08d16debbc4edf78778e6aaba29c1bc7ce67214d4410"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ae88eca3024bb34bb3430f964beab71226e761f51b912de5133470b649d82344"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_24_x86_64.whl", hash = "sha256:a522427293d77e1c29e303fc282e2d71864579527a04ddcfda6d4f8396c6c36a"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:fbdaec13c5105f0c4e5c52614d04f0bca5f5af007910daa8b6b12095edaa67b3"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:ca3204d00d3cb2dfed07f2d74a25f12fc12f73e606fcaa6975d1f7ae69cacbb2"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:089098effa1bc35dc055366740a067a2fc76987e8ec75349eb9484061c54f535"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:e9a51bbfe7e9802b5f3508687758b564069ba937748ad7b9e890086290d2f79e"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-win32.whl", hash = "sha256:2caffdae059e06ac23fce178d31b4a702f2a3264c20bfb5ff541b338194d8fab"},
|
||||
{file = "bcrypt-4.0.1-cp36-abi3-win_amd64.whl", hash = "sha256:8a68f4341daf7522fe8d73874de8906f3a339048ba406be6ddc1b3ccb16fc0d9"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bf4fa8b2ca74381bb5442c089350f09a3f17797829d958fad058d6e44d9eb83c"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:67a97e1c405b24f19d08890e7ae0c4f7ce1e56a712a016746c8b2d7732d65d4b"},
|
||||
{file = "bcrypt-4.0.1-pp37-pypy37_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b3b85202d95dd568efcb35b53936c5e3b3600c7cdcc6115ba461df3a8e89f38d"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cbb03eec97496166b704ed663a53680ab57c5084b2fc98ef23291987b525cb7d"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:5ad4d32a28b80c5fa6671ccfb43676e8c1cc232887759d1cd7b6f56ea4355215"},
|
||||
{file = "bcrypt-4.0.1-pp38-pypy38_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:b57adba8a1444faf784394de3436233728a1ecaeb6e07e8c22c8848f179b893c"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:705b2cea8a9ed3d55b4491887ceadb0106acf7c6387699fca771af56b1cdeeda"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_24_x86_64.whl", hash = "sha256:2b3ac11cf45161628f1f3733263e63194f22664bf4d0c0f3ab34099c02134665"},
|
||||
{file = "bcrypt-4.0.1-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:3100851841186c25f127731b9fa11909ab7b1df6fc4b9f8353f4f1fd952fbf71"},
|
||||
{file = "bcrypt-4.0.1.tar.gz", hash = "sha256:27d375903ac8261cfe4047f6709d16f7d18d39b1ec92aaf72af989552a650ebd"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
tests = ["pytest (>=3.2.1,!=3.3.0)"]
|
||||
typecheck = ["mypy"]
|
||||
|
||||
[[package]]
|
||||
name = "certifi"
|
||||
version = "2023.7.22"
|
||||
description = "Python package for providing Mozilla's CA Bundle."
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
|
||||
{file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "charset-normalizer"
|
||||
version = "3.2.0"
|
||||
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
|
||||
optional = false
|
||||
python-versions = ">=3.7.0"
|
||||
files = [
|
||||
{file = "charset-normalizer-3.2.0.tar.gz", hash = "sha256:3bb3d25a8e6c0aedd251753a79ae98a093c7e7b471faa3aa9a93a81431987ace"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0b87549028f680ca955556e3bd57013ab47474c3124dc069faa0b6545b6c9710"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7c70087bfee18a42b4040bb9ec1ca15a08242cf5867c58726530bdf3945672ed"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a103b3a7069b62f5d4890ae1b8f0597618f628b286b03d4bc9195230b154bfa9"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94aea8eff76ee6d1cdacb07dd2123a68283cb5569e0250feab1240058f53b623"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:db901e2ac34c931d73054d9797383d0f8009991e723dab15109740a63e7f902a"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b0dac0ff919ba34d4df1b6131f59ce95b08b9065233446be7e459f95554c0dc8"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:193cbc708ea3aca45e7221ae58f0fd63f933753a9bfb498a3b474878f12caaad"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09393e1b2a9461950b1c9a45d5fd251dc7c6f228acab64da1c9c0165d9c7765c"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:baacc6aee0b2ef6f3d308e197b5d7a81c0e70b06beae1f1fcacffdbd124fe0e3"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:bf420121d4c8dce6b889f0e8e4ec0ca34b7f40186203f06a946fa0276ba54029"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:c04a46716adde8d927adb9457bbe39cf473e1e2c2f5d0a16ceb837e5d841ad4f"},
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||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:aaf63899c94de41fe3cf934601b0f7ccb6b428c6e4eeb80da72c58eab077b19a"},
|
||||
{file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:d62e51710986674142526ab9f78663ca2b0726066ae26b78b22e0f5e571238dd"},
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|
||||
{file = "websockets-10.4-cp37-cp37m-win_amd64.whl", hash = "sha256:a9f9a735deaf9a0cadc2d8c50d1a5bcdbae8b6e539c6e08237bc4082d7c13f28"},
|
||||
{file = "websockets-10.4-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:5c1289596042fad2cdceb05e1ebf7aadf9995c928e0da2b7a4e99494953b1b94"},
|
||||
{file = "websockets-10.4-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:0cff816f51fb33c26d6e2b16b5c7d48eaa31dae5488ace6aae468b361f422b63"},
|
||||
{file = "websockets-10.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:dd9becd5fe29773d140d68d607d66a38f60e31b86df75332703757ee645b6faf"},
|
||||
{file = "websockets-10.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45ec8e75b7dbc9539cbfafa570742fe4f676eb8b0d3694b67dabe2f2ceed8aa6"},
|
||||
{file = "websockets-10.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4f72e5cd0f18f262f5da20efa9e241699e0cf3a766317a17392550c9ad7b37d8"},
|
||||
{file = "websockets-10.4-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:185929b4808b36a79c65b7865783b87b6841e852ef5407a2fb0c03381092fa3b"},
|
||||
{file = "websockets-10.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:7d27a7e34c313b3a7f91adcd05134315002aaf8540d7b4f90336beafaea6217c"},
|
||||
{file = "websockets-10.4-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:884be66c76a444c59f801ac13f40c76f176f1bfa815ef5b8ed44321e74f1600b"},
|
||||
{file = "websockets-10.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:931c039af54fc195fe6ad536fde4b0de04da9d5916e78e55405436348cfb0e56"},
|
||||
{file = "websockets-10.4-cp38-cp38-win32.whl", hash = "sha256:db3c336f9eda2532ec0fd8ea49fef7a8df8f6c804cdf4f39e5c5c0d4a4ad9a7a"},
|
||||
{file = "websockets-10.4-cp38-cp38-win_amd64.whl", hash = "sha256:48c08473563323f9c9debac781ecf66f94ad5a3680a38fe84dee5388cf5acaf6"},
|
||||
{file = "websockets-10.4-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:40e826de3085721dabc7cf9bfd41682dadc02286d8cf149b3ad05bff89311e4f"},
|
||||
{file = "websockets-10.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:56029457f219ade1f2fc12a6504ea61e14ee227a815531f9738e41203a429112"},
|
||||
{file = "websockets-10.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:f5fc088b7a32f244c519a048c170f14cf2251b849ef0e20cbbb0fdf0fdaf556f"},
|
||||
{file = "websockets-10.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2fc8709c00704194213d45e455adc106ff9e87658297f72d544220e32029cd3d"},
|
||||
{file = "websockets-10.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0154f7691e4fe6c2b2bc275b5701e8b158dae92a1ab229e2b940efe11905dff4"},
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||||
{file = "websockets-10.4-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4c6d2264f485f0b53adf22697ac11e261ce84805c232ed5dbe6b1bcb84b00ff0"},
|
||||
{file = "websockets-10.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:9bc42e8402dc5e9905fb8b9649f57efcb2056693b7e88faa8fb029256ba9c68c"},
|
||||
{file = "websockets-10.4-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:edc344de4dac1d89300a053ac973299e82d3db56330f3494905643bb68801269"},
|
||||
{file = "websockets-10.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:84bc2a7d075f32f6ed98652db3a680a17a4edb21ca7f80fe42e38753a58ee02b"},
|
||||
{file = "websockets-10.4-cp39-cp39-win32.whl", hash = "sha256:c94ae4faf2d09f7c81847c63843f84fe47bf6253c9d60b20f25edfd30fb12588"},
|
||||
{file = "websockets-10.4-cp39-cp39-win_amd64.whl", hash = "sha256:bbccd847aa0c3a69b5f691a84d2341a4f8a629c6922558f2a70611305f902d74"},
|
||||
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|
||||
{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d210abe51b5da0ffdbf7b43eed0cfdff8a55a1ab17abbec4301c9ff077dd0342"},
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||||
{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:942de28af58f352a6f588bc72490ae0f4ccd6dfc2bd3de5945b882a078e4e179"},
|
||||
{file = "websockets-10.4-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c9b27d6c1c6cd53dc93614967e9ce00ae7f864a2d9f99fe5ed86706e1ecbf485"},
|
||||
{file = "websockets-10.4-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:3d3cac3e32b2c8414f4f87c1b2ab686fa6284a980ba283617404377cd448f631"},
|
||||
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|
||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:389f8dbb5c489e305fb113ca1b6bdcdaa130923f77485db5b189de343a179393"},
|
||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09a1814bb15eff7069e51fed0826df0bc0702652b5cb8f87697d469d79c23576"},
|
||||
{file = "websockets-10.4-pp38-pypy38_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ff64a1d38d156d429404aaa84b27305e957fd10c30e5880d1765c9480bea490f"},
|
||||
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|
||||
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|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d6a4162139374a49eb18ef5b2f4da1dd95c994588f5033d64e0bbfda4b6b6fcf"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c57e4c1349fbe0e446c9fa7b19ed2f8a4417233b6984277cce392819123142d3"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b627c266f295de9dea86bd1112ed3d5fafb69a348af30a2422e16590a8ecba13"},
|
||||
{file = "websockets-10.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:05a7233089f8bd355e8cbe127c2e8ca0b4ea55467861906b80d2ebc7db4d6b72"},
|
||||
{file = "websockets-10.4.tar.gz", hash = "sha256:eef610b23933c54d5d921c92578ae5f89813438fded840c2e9809d378dc765d3"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "zipp"
|
||||
version = "3.16.2"
|
||||
description = "Backport of pathlib-compatible object wrapper for zip files"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"},
|
||||
{file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
|
||||
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.8"
|
||||
content-hash = "ed5c1001c4f47bae1cfde8d8509294643e3b3ea101a8482c3f0248085360bb18"
|
||||
18
openbb_sdk/extensions/news/pyproject.toml
vendored
18
openbb_sdk/extensions/news/pyproject.toml
vendored
@@ -1,18 +0,0 @@
|
||||
[tool.poetry]
|
||||
name = "openbb-news"
|
||||
version = "0.1.1"
|
||||
description = ""
|
||||
authors = ["OpenBB Team <hello@openbb.co>"]
|
||||
readme = "README.md"
|
||||
packages = [{ include = "openbb_news" }]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.8"
|
||||
openbb-core = { path = "../../sdk/core" }
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry.plugins."openbb_core_extension"]
|
||||
news = "openbb_news.news_router:router"
|
||||
15
openbb_sdk/extensions/qa/README.md
vendored
15
openbb_sdk/extensions/qa/README.md
vendored
@@ -1,15 +0,0 @@
|
||||
# OpenBB QA Extension
|
||||
|
||||
This extension provides Quantitative Analysis (QA) tools for the OpenBB SDK.
|
||||
|
||||
Features of the QA extension include various statistical tools and models.
|
||||
|
||||
This extension works nicely with a companion `openbb-charting` extension
|
||||
|
||||
## Installation
|
||||
|
||||
To install the extension, run the following command in this folder:
|
||||
|
||||
```bash
|
||||
pip install .
|
||||
```
|
||||
@@ -1,53 +0,0 @@
|
||||
"""Helper functions for QA"""
|
||||
|
||||
from io import BytesIO
|
||||
from urllib.request import urlopen
|
||||
from zipfile import ZipFile
|
||||
|
||||
import pandas as pd
|
||||
|
||||
|
||||
# ruff: ignore=S310
|
||||
def get_fama_raw(start_date: str, end_date: str) -> pd.DataFrame:
|
||||
"""Gets base Fama French data to calculate risk
|
||||
|
||||
Returns
|
||||
-------
|
||||
pd.DataFrame
|
||||
A data with fama french model information
|
||||
"""
|
||||
with urlopen( # nosec # noqa: S310
|
||||
"https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/F-F_Research_Data_Factors_CSV.zip"
|
||||
) as url:
|
||||
# Download Zipfile and create pandas DataFrame
|
||||
with ZipFile(BytesIO(url.read())) as zipfile:
|
||||
with zipfile.open("F-F_Research_Data_Factors.CSV") as zip_open:
|
||||
df = pd.read_csv(
|
||||
zip_open,
|
||||
header=0,
|
||||
names=["Date", "MKT-RF", "SMB", "HML", "RF"],
|
||||
skiprows=3,
|
||||
)
|
||||
|
||||
df = df[df["Date"].apply(lambda x: len(str(x).strip()) == 6)]
|
||||
df["Date"] = df["Date"].astype(str) + "01"
|
||||
df["Date"] = pd.to_datetime(df["Date"], format="%Y%m%d")
|
||||
df["MKT-RF"] = pd.to_numeric(df["MKT-RF"], downcast="float")
|
||||
df["SMB"] = pd.to_numeric(df["SMB"], downcast="float")
|
||||
df["HML"] = pd.to_numeric(df["HML"], downcast="float")
|
||||
df["RF"] = pd.to_numeric(df["RF"], downcast="float")
|
||||
df["MKT-RF"] = df["MKT-RF"] / 100
|
||||
df["SMB"] = df["SMB"] / 100
|
||||
df["HML"] = df["HML"] / 100
|
||||
df["RF"] = df["RF"] / 100
|
||||
df = df.set_index("Date")
|
||||
|
||||
dt_start_date = pd.to_datetime(start_date, format="%Y-%m-%d")
|
||||
if dt_start_date > df.index.max():
|
||||
raise ValueError(
|
||||
f"Start date '{dt_start_date}' is after the last date available for Fama-French '{df.index[-1]}'"
|
||||
)
|
||||
|
||||
df = df.loc[start_date:end_date] # type: ignore
|
||||
|
||||
return df
|
||||
@@ -1,52 +0,0 @@
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
class TestModel(BaseModel):
|
||||
statistic: float
|
||||
p_value: float
|
||||
|
||||
|
||||
class NormalityModel(BaseModel):
|
||||
kurtosis: TestModel
|
||||
skewness: TestModel
|
||||
jarque_bera: TestModel
|
||||
shapiro_wilk: TestModel
|
||||
kolmogorov_smirnov: TestModel
|
||||
|
||||
|
||||
class ADFTestModel(TestModel):
|
||||
nlags: int
|
||||
nobs: int
|
||||
icbest: float
|
||||
|
||||
|
||||
class KPSSTestModel(TestModel):
|
||||
nlags: int
|
||||
|
||||
|
||||
class UnitRootModel(BaseModel):
|
||||
adf: ADFTestModel
|
||||
kpss: KPSSTestModel
|
||||
|
||||
|
||||
class OmegaModel(BaseModel):
|
||||
threshold: float
|
||||
omega: float
|
||||
|
||||
|
||||
class SummaryModel(BaseModel):
|
||||
count: int
|
||||
mean: float
|
||||
std: float
|
||||
var: float
|
||||
min: float
|
||||
max: float
|
||||
p_25: float
|
||||
p_50: float
|
||||
p_75: float
|
||||
|
||||
|
||||
class CAPMModel(BaseModel):
|
||||
market_risk: float
|
||||
systematic_risk: float
|
||||
idiosyncratic_risk: float
|
||||
@@ -1,498 +0,0 @@
|
||||
from typing import List, Literal
|
||||
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.router import Router
|
||||
from openbb_core.app.utils import (
|
||||
basemodel_to_df,
|
||||
df_to_basemodel,
|
||||
get_target_column,
|
||||
get_target_columns,
|
||||
)
|
||||
from openbb_provider.abstract.data import Data
|
||||
from pydantic import NonNegativeFloat, PositiveInt
|
||||
|
||||
from openbb_qa.qa_helpers import get_fama_raw
|
||||
from openbb_qa.qa_models import (
|
||||
ADFTestModel,
|
||||
CAPMModel,
|
||||
KPSSTestModel,
|
||||
NormalityModel,
|
||||
OmegaModel,
|
||||
SummaryModel,
|
||||
TestModel,
|
||||
UnitRootModel,
|
||||
)
|
||||
|
||||
router = Router(prefix="")
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def normality(data: List[Data], target: str) -> OBBject[NormalityModel]:
|
||||
"""
|
||||
Normality Statistics.
|
||||
|
||||
- **Kurtosis**: whether the kurtosis of a sample differs from the normal distribution.
|
||||
- **Skewness**: whether the skewness of a sample differs from the normal distribution.
|
||||
- **Jarque-Bera**: whether the sample data has the skewness and kurtosis matching a normal distribution.
|
||||
- **Shapiro-Wilk**: whether a random sample comes from a normal distribution.
|
||||
- **Kolmogorov-Smirnov**: whether two underlying one-dimensional probability distributions differ.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : List[Data]
|
||||
Time series data.
|
||||
target : str
|
||||
Target column name.
|
||||
|
||||
Returns
|
||||
-------
|
||||
OBBject[NormalityModel]
|
||||
Normality tests summary. See qa_models.NormalityModel for details.
|
||||
"""
|
||||
|
||||
from scipy import stats
|
||||
|
||||
df = basemodel_to_df(data)
|
||||
series_target = get_target_column(df, target)
|
||||
|
||||
kt_statistic, kt_pvalue = stats.kurtosistest(series_target)
|
||||
sk_statistic, sk_pvalue = stats.skewtest(series_target)
|
||||
jb_statistic, jb_pvalue = stats.jarque_bera(series_target)
|
||||
sh_statistic, sh_pvalue = stats.shapiro(series_target)
|
||||
ks_statistic, ks_pvalue = stats.kstest(series_target, "norm")
|
||||
|
||||
norm_summary = NormalityModel(
|
||||
kurtosis=TestModel(statistic=kt_statistic, p_value=kt_pvalue),
|
||||
skewness=TestModel(statistic=sk_statistic, p_value=sk_pvalue),
|
||||
jarque_bera=TestModel(statistic=jb_statistic, p_value=jb_pvalue),
|
||||
shapiro_wilk=TestModel(statistic=sh_statistic, p_value=sh_pvalue),
|
||||
kolmogorov_smirnov=TestModel(statistic=ks_statistic, p_value=ks_pvalue),
|
||||
)
|
||||
|
||||
return OBBject(results=norm_summary)
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def capm(data: List[Data], target: str) -> OBBject[CAPMModel]:
|
||||
"""Capital Asset Pricing Model."""
|
||||
|
||||
import statsmodels.api as sm
|
||||
|
||||
df = basemodel_to_df(data)
|
||||
|
||||
df_target = get_target_columns(df, ["date", target])
|
||||
df_target = df_target.set_index("date")
|
||||
df_target.loc[:, "return"] = df_target.pct_change()
|
||||
df_target = df_target.dropna()
|
||||
start_date = df_target.index.min().strftime("%Y-%m-%d")
|
||||
end_date = df_target.index.max().strftime("%Y-%m-%d")
|
||||
df_fama = get_fama_raw(start_date, end_date)
|
||||
df_target = df_target.merge(df_fama, left_index=True, right_index=True)
|
||||
df_target["excess_return"] = df_target["return"] - df_target["RF"]
|
||||
df_target["excess_mkt"] = df_target["MKT-RF"] - df_target["RF"]
|
||||
df_target = df_target.dropna()
|
||||
|
||||
y = df_target[["excess_return"]]
|
||||
x = df_target["excess_mkt"]
|
||||
x = sm.add_constant(x)
|
||||
model = sm.OLS(y, x).fit()
|
||||
|
||||
results = CAPMModel(
|
||||
market_risk=model.params["excess_mkt"],
|
||||
systematic_risk=model.rsquared,
|
||||
idiosyncratic_risk=1 - model.rsquared,
|
||||
)
|
||||
|
||||
return OBBject(results=results)
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def qqplot() -> OBBject[Empty]:
|
||||
"""QQ Plot."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def om(
|
||||
data: List[Data],
|
||||
target: str,
|
||||
threshold_start: float = 0.0,
|
||||
threshold_end: float = 1.5,
|
||||
) -> OBBject[List[OmegaModel]]:
|
||||
"""Omega Ratio.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : List[Data]
|
||||
Time series data.
|
||||
target : str
|
||||
Target column name.
|
||||
threshold_start : float, optional
|
||||
Start threshold, by default 0.0
|
||||
threshold_end : float, optional
|
||||
End threshold, by default 1.5
|
||||
|
||||
Returns
|
||||
-------
|
||||
OBBject[List[OmegaModel]]
|
||||
Omega ratios.
|
||||
"""
|
||||
|
||||
df = basemodel_to_df(data)
|
||||
series_target = get_target_column(df, target)
|
||||
|
||||
def get_omega_ratio(df_target: pd.Series, threshold: float) -> float:
|
||||
"""Get omega ratio."""
|
||||
daily_threshold = (threshold + 1) ** np.sqrt(1 / 252) - 1
|
||||
excess = df_target - daily_threshold
|
||||
omega = excess[excess > 0].sum() / -excess[excess < 0].sum()
|
||||
return omega
|
||||
|
||||
threshold = np.linspace(threshold_start, threshold_end, 50)
|
||||
results = []
|
||||
for i in threshold:
|
||||
results.append(OmegaModel(threshold=i, omega=get_omega_ratio(series_target, i)))
|
||||
|
||||
return OBBject(results=results)
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def kurtosis(data: List[Data], target: str, window: PositiveInt) -> OBBject[List[Data]]:
|
||||
"""Kurtosis.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : List[Data]
|
||||
Time series data.
|
||||
target : str
|
||||
Target column name.
|
||||
window : PositiveInt
|
||||
Window size.
|
||||
|
||||
Returns
|
||||
-------
|
||||
OBBject[List[Data]]
|
||||
Kurtosis.
|
||||
"""
|
||||
|
||||
import pandas_ta as ta
|
||||
|
||||
df = basemodel_to_df(data)
|
||||
series_target = get_target_column(df, target)
|
||||
results = ta.kurtosis(close=series_target, length=window).dropna()
|
||||
results = df_to_basemodel(results)
|
||||
|
||||
return OBBject(results=results)
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def pick() -> OBBject[Empty]:
|
||||
"""Pick."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def spread() -> OBBject[Empty]:
|
||||
"""Spread."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def rolling() -> OBBject[Empty]:
|
||||
"""Rolling."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def var() -> OBBject[Empty]:
|
||||
"""Value at Risk."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def line() -> OBBject[Empty]:
|
||||
"""Line."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def hist() -> OBBject[Empty]:
|
||||
"""Histogram."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def unitroot(
|
||||
data: List[Data],
|
||||
target: str,
|
||||
fuller_reg: Literal["c", "ct", "ctt", "nc", "c"] = "c",
|
||||
kpss_reg: Literal["c", "ct"] = "c",
|
||||
) -> OBBject[UnitRootModel]:
|
||||
"""Unit Root Test.
|
||||
|
||||
Augmented Dickey-Fuller test for unit root.
|
||||
Kwiatkowski-Phillips-Schmidt-Shin test for unit root.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : List[Data]
|
||||
Time series data.
|
||||
target : str
|
||||
Target column name.
|
||||
fuller_reg : Literal["c", "ct", "ctt", "nc", "c"]
|
||||
Regression type for ADF test.
|
||||
kpss_reg : Literal["c", "ct"]
|
||||
Regression type for KPSS test.
|
||||
|
||||
Returns
|
||||
-------
|
||||
OBBject[UnitRootModel]
|
||||
Unit root tests summary.
|
||||
"""
|
||||
|
||||
from statsmodels.tsa import stattools
|
||||
|
||||
df = basemodel_to_df(data)
|
||||
series_target = get_target_column(df, target)
|
||||
|
||||
adf = stattools.adfuller(series_target, regression=fuller_reg)
|
||||
kpss = stattools.kpss(series_target, regression=kpss_reg, nlags="auto")
|
||||
|
||||
unitroot_summary = UnitRootModel(
|
||||
adf=ADFTestModel(
|
||||
statistic=adf[0],
|
||||
p_value=adf[1],
|
||||
nlags=adf[2] if isinstance(adf[2], int) else 0,
|
||||
nobs=adf[3] if isinstance(adf[3], int) else 0,
|
||||
icbest=adf[5] if isinstance(adf[5], float) else 0.0, # type: ignore
|
||||
),
|
||||
kpss=KPSSTestModel(
|
||||
statistic=kpss[0],
|
||||
p_value=kpss[1],
|
||||
nlags=kpss[2],
|
||||
),
|
||||
)
|
||||
return OBBject(results=unitroot_summary)
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def beta() -> OBBject[Empty]:
|
||||
"""Beta."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def sh(
|
||||
data: List[Data], target: str, rfr: float = 0.0, window: PositiveInt = 252
|
||||
) -> OBBject[List[Data]]:
|
||||
"""Sharpe Ratio.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : List[Data]
|
||||
Time series data.
|
||||
target : str
|
||||
Target column name.
|
||||
rfr : float, optional
|
||||
Risk-free rate, by default 0.0
|
||||
window : PositiveInt, optional
|
||||
Window size, by default 252
|
||||
|
||||
Returns
|
||||
-------
|
||||
OBBject[List[Data]]
|
||||
Sharpe ratio.
|
||||
"""
|
||||
|
||||
df = basemodel_to_df(data)
|
||||
series_target = get_target_column(df, target)
|
||||
|
||||
returns = series_target.pct_change().dropna().rolling(window).sum()
|
||||
std = series_target.rolling(window).std() / np.sqrt(window)
|
||||
results = ((returns - rfr) / std).dropna()
|
||||
|
||||
results = df_to_basemodel(results)
|
||||
|
||||
return OBBject(results=results)
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def so(
|
||||
data: List[Data],
|
||||
target: str,
|
||||
target_return: float = 0.0,
|
||||
window: PositiveInt = 252,
|
||||
adjusted: bool = False,
|
||||
) -> OBBject[List[Data]]:
|
||||
"""Sortino Ratio.
|
||||
|
||||
For method & terminology see: http://www.redrockcapital.com/Sortino__A__Sharper__Ratio_Red_Rock_Capital.pdf
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : List[Data]
|
||||
Time series data.
|
||||
target : str
|
||||
Target column name.
|
||||
target_return : float, optional
|
||||
Target return, by default 0.0
|
||||
window : PositiveInt, optional
|
||||
Window size, by default 252
|
||||
adjusted : bool, optional
|
||||
Adjust sortino ratio to compare it to sharpe ratio, by default False
|
||||
|
||||
Returns
|
||||
-------
|
||||
OBBject[List[Data]]
|
||||
Sortino ratio.
|
||||
"""
|
||||
|
||||
df = basemodel_to_df(data)
|
||||
series_target = get_target_column(df, target)
|
||||
|
||||
returns = series_target.pct_change().dropna().rolling(window).sum()
|
||||
downside_deviation = returns.rolling(window).apply(
|
||||
lambda x: (x.values[x.values < 0]).std() / np.sqrt(252) * 100
|
||||
)
|
||||
results = ((returns - target_return) / downside_deviation).dropna()
|
||||
|
||||
if adjusted:
|
||||
results = results / np.sqrt(2)
|
||||
|
||||
results = df_to_basemodel(results)
|
||||
|
||||
return OBBject(results=results)
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def cusum() -> OBBject[Empty]:
|
||||
"""Cumulative Sum."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def raw() -> OBBject[Empty]:
|
||||
"""Raw."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def cdf() -> OBBject[Empty]:
|
||||
"""Cumulative Distribution Function."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def decompose() -> OBBject[Empty]:
|
||||
"""Decompose."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def skew(data: List[Data], target: str, window: PositiveInt) -> OBBject[List[Data]]:
|
||||
"""Skewness.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : List[Data]
|
||||
Time series data.
|
||||
target : str
|
||||
Target column name.
|
||||
window : PositiveInt
|
||||
Window size.
|
||||
|
||||
Returns
|
||||
-------
|
||||
OBBject[List[Data]]
|
||||
Skewness.
|
||||
"""
|
||||
|
||||
import pandas_ta as ta
|
||||
|
||||
df = basemodel_to_df(data)
|
||||
series_target = get_target_column(df, target)
|
||||
results = ta.skew(close=series_target, length=window).dropna()
|
||||
results = df_to_basemodel(results)
|
||||
|
||||
return OBBject(results=results)
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def quantile(
|
||||
data: List[Data],
|
||||
target: str,
|
||||
window: PositiveInt,
|
||||
quantile_pct: NonNegativeFloat = 0.5,
|
||||
) -> OBBject[List[Data]]:
|
||||
"""Quantile."""
|
||||
|
||||
import pandas_ta as ta
|
||||
|
||||
df = basemodel_to_df(data)
|
||||
series_target = get_target_column(df, target)
|
||||
|
||||
df_median = ta.median(close=series_target, length=window).to_frame()
|
||||
df_quantile = ta.quantile(series_target, length=window, q=quantile_pct).to_frame()
|
||||
results = pd.concat([df_median, df_quantile], axis=1).dropna()
|
||||
|
||||
results = df_to_basemodel(results)
|
||||
|
||||
return OBBject(results=results)
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def bw() -> OBBject[Empty]:
|
||||
"""Bandwidth."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def es() -> OBBject[Empty]:
|
||||
"""Expected Shortfall."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def acf() -> OBBject[Empty]:
|
||||
"""Autocorrelation Function."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(methods=["POST"])
|
||||
def summary(data: List[Data], target: str) -> OBBject[SummaryModel]:
|
||||
"""Summary.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data : List[Data]
|
||||
Time series data.
|
||||
target : str
|
||||
Target column name.
|
||||
|
||||
Returns
|
||||
-------
|
||||
OBBject[SummaryModel]
|
||||
Summary table.
|
||||
"""
|
||||
|
||||
df = basemodel_to_df(data)
|
||||
series_target = get_target_column(df, target)
|
||||
|
||||
df_stats = series_target.describe(percentiles=[0.1, 0.25, 0.5, 0.75, 0.9])
|
||||
df_stats.loc["var"] = df_stats.loc["std"] ** 2
|
||||
results = SummaryModel(
|
||||
count=df_stats.loc["count"],
|
||||
mean=df_stats.loc["mean"],
|
||||
std=df_stats.loc["std"],
|
||||
var=df_stats.loc["var"],
|
||||
min=df_stats.loc["min"],
|
||||
p_25=df_stats.loc["25%"],
|
||||
p_50=df_stats.loc["50%"],
|
||||
p_75=df_stats.loc["75%"],
|
||||
max=df_stats.loc["max"],
|
||||
)
|
||||
|
||||
return OBBject(results=results)
|
||||
1056
openbb_sdk/extensions/qa/poetry.lock
generated
vendored
1056
openbb_sdk/extensions/qa/poetry.lock
generated
vendored
File diff suppressed because it is too large
Load Diff
21
openbb_sdk/extensions/qa/pyproject.toml
vendored
21
openbb_sdk/extensions/qa/pyproject.toml
vendored
@@ -1,21 +0,0 @@
|
||||
[tool.poetry]
|
||||
name = "openbb-qa"
|
||||
version = "0.1.0"
|
||||
description = "Quantitative Analysis for OpenBB"
|
||||
authors = ["OpenBB Team <hello@openbb.co>"]
|
||||
readme = "README.md"
|
||||
packages = [{ include = "openbb_qa" }]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = ">=3.8,<3.12" # scipy forces python <4.0 explicitly
|
||||
openbb-core = { path = "../../sdk/core" }
|
||||
scipy = "^1.10.1"
|
||||
statsmodels = "^0.14.0"
|
||||
pandas-ta = "^0.3.13"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry.plugins."openbb_core_extension"]
|
||||
qa = "openbb_qa.qa_router:router"
|
||||
0
openbb_sdk/extensions/qa/tests/.gitkeep
vendored
0
openbb_sdk/extensions/qa/tests/.gitkeep
vendored
24
openbb_sdk/extensions/stocks/README.md
vendored
24
openbb_sdk/extensions/stocks/README.md
vendored
@@ -1,24 +0,0 @@
|
||||
# OpenBB Stocks Extension
|
||||
|
||||
This extension provides stock market data tools for the OpenBB SDK.
|
||||
|
||||
Features of the Stocks extension include:
|
||||
|
||||
- Access to various stock market data sources
|
||||
- Sub-modules such as:
|
||||
- `ca` for fundamental analysis
|
||||
- `dd` for in-depth due diligence
|
||||
- `disc` for stock discovery
|
||||
- `dps` for Dark Pool Shorts data
|
||||
- `fa` for comparison analysis
|
||||
- `gov` for government contracts data
|
||||
- `ins` for insiders trading data
|
||||
- `options` for options
|
||||
|
||||
## Installation
|
||||
|
||||
To install the extension, run the following command in your OpenBB SDK environment:
|
||||
|
||||
```bash
|
||||
pip install .
|
||||
```
|
||||
@@ -1,87 +0,0 @@
|
||||
# pylint: disable=W0613:unused-argument
|
||||
"""Comparison Analysis Router."""
|
||||
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = Router(prefix="/ca")
|
||||
|
||||
|
||||
@router.command(model="StockPeers")
|
||||
def peers(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Company peers."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def balance() -> OBBject[Empty]: # type: ignore
|
||||
"""Company balance sheet."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def cashflow() -> OBBject[Empty]: # type: ignore
|
||||
"""Company cashflow."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def hcorr() -> OBBject[Empty]: # type: ignore
|
||||
"""Company historical correlation."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def hist() -> OBBject[Empty]: # type: ignore
|
||||
"""Company historical prices."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def income() -> OBBject[Empty]: # type: ignore
|
||||
"""Company income statement."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def scorr() -> OBBject[Empty]: # type: ignore
|
||||
"""Company sector correlation."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def screener() -> OBBject[Empty]: # type: ignore
|
||||
"""Company screener."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def sentiment() -> OBBject[Empty]: # type: ignore
|
||||
"""Company sentiment."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def similar() -> OBBject[Empty]: # type: ignore
|
||||
"""Company similar."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def volume() -> OBBject[Empty]: # type: ignore
|
||||
"""Company volume."""
|
||||
return OBBject(results=Empty())
|
||||
@@ -1,26 +0,0 @@
|
||||
# pylint: disable=W0613:unused-argument
|
||||
"""Due Diligence Router."""
|
||||
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = Router(prefix="/dd")
|
||||
|
||||
|
||||
@router.command(model="SECFilings")
|
||||
def sec(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""SEC Filings."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
@@ -1,111 +0,0 @@
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.router import Router
|
||||
|
||||
router = Router(prefix="/disc")
|
||||
|
||||
|
||||
@router.command
|
||||
def active() -> OBBject[Empty]: # type: ignore
|
||||
"""Most active stocks by intraday trade volumes."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def arkord() -> OBBject[Empty]: # type: ignore
|
||||
"""Order by ARK INvestment Management LLC."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def asc() -> OBBject[Empty]: # type: ignore
|
||||
"""Small cap stocks with revenue and earnings growth more than 25%."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def dividends() -> OBBject[Empty]: # type: ignore
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def filings() -> OBBject[Empty]: # type: ignore
|
||||
"""The most-recent form submissions to the SEC."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def fipo() -> OBBject[Empty]: # type: ignore
|
||||
"""Future IPOs dates."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def gainers() -> OBBject[Empty]: # type: ignore
|
||||
"""Show latest top gainers."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def gtech() -> OBBject[Empty]: # type: ignore
|
||||
"""Tech stocks with revenue and earnings growth more than 25%."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def hotpenny() -> OBBject[Empty]: # type: ignore
|
||||
"""Today's hot penny stocks."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def ipo() -> OBBject[Empty]: # type: ignore
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def losers() -> OBBject[Empty]: # type: ignore
|
||||
"""Show latest top losers."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def lowfloat() -> OBBject[Empty]: # type: ignore
|
||||
"""Low float stocks under 10M shares float."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def pipo() -> OBBject[Empty]: # type: ignore
|
||||
"""Past IPOs dates."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def rtat() -> OBBject[Empty]: # type: ignore
|
||||
"""Top 10 retail traded stocks per day."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def trending() -> OBBject[Empty]: # type: ignore
|
||||
"""Trending news."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def ugs() -> OBBject[Empty]: # type: ignore
|
||||
"""Undervalued stocks with revenue and earnings growth above 25%."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def ulc() -> OBBject[Empty]: # type: ignore
|
||||
"""Potentially undervalued large cap stocks."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def upcoming() -> OBBject[Empty]: # type: ignore
|
||||
"""Upcoming earnings release dates."""
|
||||
return OBBject(results=Empty())
|
||||
@@ -1,75 +0,0 @@
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.router import Router
|
||||
|
||||
router = Router(prefix="/dps")
|
||||
|
||||
|
||||
@router.command
|
||||
def psi() -> OBBject[Empty]: # type: ignore
|
||||
"""Price vs short interest volume"""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def ctb() -> OBBject[Empty]: # type: ignore
|
||||
"""Cost to borrow of stocks."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def dpotc() -> OBBject[Empty]: # type: ignore
|
||||
"""Dark pools (ATS) vs OTC data."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def ftd() -> OBBject[Empty]: # type: ignore
|
||||
"""Fails-to-deliver data."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def hsi() -> OBBject[Empty]: # type: ignore
|
||||
"""Show top high short interest stocks of over 20% ratio."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def pos() -> OBBject[Empty]: # type: ignore
|
||||
"""Dark pool short position."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def prom() -> OBBject[Empty]: # type: ignore
|
||||
"""Promising tickers based on dark pool shares regression."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def psi_q() -> OBBject[Empty]: # type: ignore
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def psi_sg() -> OBBject[Empty]: # type: ignore
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def shorted() -> OBBject[Empty]: # type: ignore
|
||||
"""Most shorted stocks."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def sidtc() -> OBBject[Empty]: # type: ignore
|
||||
"""Short interest and days to cover."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def spos() -> OBBject[Empty]: # type: ignore
|
||||
"""Net short vs position."""
|
||||
return OBBject(results=Empty())
|
||||
@@ -1,434 +0,0 @@
|
||||
# pylint: disable=W0613:unused-argument
|
||||
"""Fundamental Analysis Router."""
|
||||
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = Router(prefix="/fa")
|
||||
|
||||
|
||||
@router.command
|
||||
def analysis() -> OBBject[Empty]: # type: ignore
|
||||
"""Analyse SEC filings with the help of machine learning."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="BalanceSheet")
|
||||
def balance(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Balance Sheet."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="BalanceSheetGrowth")
|
||||
def balance_growth(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Balance Sheet Statement Growth."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="DividendCalendar")
|
||||
def cal(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Show Dividend Calendar for a given start and end dates."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="CashFlowStatement")
|
||||
def cash(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Cash Flow Statement."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="CashFlowStatementGrowth")
|
||||
def cash_growth(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Cash Flow Statement Growth."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="ExecutiveCompensation")
|
||||
def comp(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Executive Compensation."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="StockSplitCalendar")
|
||||
def comsplit(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Stock Split Calendar."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def customer() -> OBBject[Empty]: # type: ignore
|
||||
"""List of customers of the company."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def dcfc() -> OBBject[Empty]: # type: ignore
|
||||
"""Determine the (historical) discounted cash flow."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="HistoricalDividends")
|
||||
def divs(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Historical Dividends."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def dupont() -> OBBject[Empty]: # type: ignore
|
||||
"""Detailed breakdown for Return on Equity (RoE)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="EarningsCalendar")
|
||||
def earning(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Earnings Calendar."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="HistoricalEmployees")
|
||||
def emp(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Number of Employees."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def enterprise() -> OBBject[Empty]: # type: ignore
|
||||
"""Enterprise value."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def epsfc() -> OBBject[Empty]: # type: ignore
|
||||
"""Earnings Estimate by Analysts - EPS."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="AnalystEstimates")
|
||||
def est(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Analyst Estimates."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def fama_coe() -> OBBject[Empty]: # type: ignore
|
||||
"""Fama French 3 Factor Model - Coefficient of Earnings."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def fama_raw() -> OBBject[Empty]: # type: ignore
|
||||
"""Fama French 3 Factor Model - Raw Data."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def fraud() -> OBBject[Empty]: # type: ignore
|
||||
"""Key fraud ratios including M-score, Z-score and McKee."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def growth() -> OBBject[Empty]: # type: ignore
|
||||
"""Growth of financial statement items and ratios."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def historical_5() -> OBBject[Empty]: # type: ignore
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="IncomeStatement")
|
||||
def income(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Income Statement."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="IncomeStatementGrowth")
|
||||
def income_growth(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Income Statement Growth."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="StockInsiderTrading")
|
||||
def ins(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Stock Insider Trading."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="InstitutionalOwnership")
|
||||
def ins_own(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Institutional Ownership."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def key() -> OBBject[Empty]: # type: ignore
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="KeyMetrics")
|
||||
def metrics(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Key Metrics."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="KeyExecutives")
|
||||
def mgmt(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Key Executives."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def mktcap() -> OBBject[Empty]: # type: ignore
|
||||
"""Obtain the market capitalization or enterprise value."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command # CHECK IF NEWS IS NEEDED HERE
|
||||
def news() -> OBBject[Empty]: # type: ignore
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="CompanyOverview")
|
||||
def overview(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Company Overview."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="StockOwnership")
|
||||
def own(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Stock Ownership."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="PriceTargetConsensus")
|
||||
def pt(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Price Target Consensus."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="PriceTarget")
|
||||
def pta(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Price Target."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="FinancialRatios")
|
||||
def ratios(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Extensive set of ratios over time."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def rating() -> OBBject[Empty]: # type: ignore
|
||||
"""Analyst prices and ratings over time of the company."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def revfc() -> OBBject[Empty]: # type: ignore
|
||||
"""Earning Estimate by Analysts - Revenue."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="RevenueGeographic")
|
||||
def revgeo(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Revenue Geographic."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="RevenueBusinessLine")
|
||||
def revseg(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Revenue Business Line."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def rot() -> OBBject[Empty]: # type: ignore
|
||||
"""Number of analyst ratings over time on a monthly basis."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def score() -> OBBject[Empty]: # type: ignore
|
||||
"""Value investing scores for any time period."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def sec() -> OBBject[Empty]: # type: ignore
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def shares() -> OBBject[Empty]: # type: ignore
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="ShareStatistics")
|
||||
def shrs(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Share Statistics."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="HistoricalStockSplits")
|
||||
def split(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Historical Stock Splits."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def supplier() -> OBBject[Empty]: # type: ignore
|
||||
"""List of suppliers of the company."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="EarningsCallTranscript")
|
||||
def transcript(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Earnings Call Transcript."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
@@ -1,74 +0,0 @@
|
||||
"""Due Diligence Router."""
|
||||
|
||||
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.router import Router
|
||||
|
||||
router = Router(prefix="/gov")
|
||||
|
||||
|
||||
@router.command
|
||||
def contracts() -> OBBject[Empty]: # type: ignore
|
||||
"""Return government contracts."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def government_trading() -> OBBject[Empty]: # type: ignore
|
||||
"""Return government trading."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command # Isn't this one the same as the one above?
|
||||
def gtrades() -> OBBject[Empty]: # type: ignore
|
||||
"""Return government trades."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def histcont() -> OBBject[Empty]: # type: ignore
|
||||
"""Historical quarterly government contracts."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def lastcontracts() -> OBBject[Empty]: # type: ignore
|
||||
"""Return last government contracts given out."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def lasttrades() -> OBBject[Empty]: # type: ignore
|
||||
"""Last trades."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def lobbying() -> OBBject[Empty]: # type: ignore
|
||||
"""Corporate lobbying details."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def qtrcontracts() -> OBBject[Empty]: # type: ignore
|
||||
"""Quarterly government contracts analysis."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def topbuys() -> OBBject[Empty]: # type: ignore
|
||||
"""Show most purchased stocks."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def toplobbying() -> OBBject[Empty]: # type: ignore
|
||||
"""Top corporate lobbying tickers."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def topsells() -> OBBject[Empty]: # type: ignore
|
||||
"""Show most sold stocks."""
|
||||
return OBBject(results=Empty())
|
||||
@@ -1,104 +0,0 @@
|
||||
"""Due Diligence Router."""
|
||||
|
||||
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.router import Router
|
||||
|
||||
router = Router(prefix="/ins")
|
||||
|
||||
|
||||
@router.command
|
||||
def act() -> OBBject[Empty]: # type: ignore
|
||||
"""Insider activity over time."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def blcp() -> OBBject[Empty]: # type: ignore
|
||||
"""Big latest CEO/CFO purchaces ($25k+)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def blcs() -> OBBject[Empty]: # type: ignore
|
||||
"""Big latest CEO/CFO sales ($100k+)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def blip() -> OBBject[Empty]: # type: ignore
|
||||
"""Big latest insider purchaces ($25+)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def blis() -> OBBject[Empty]: # type: ignore
|
||||
"""Big latest insider sales ($100k+)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def blop() -> OBBject[Empty]: # type: ignore
|
||||
"""Big latest officer purchaces ($25k+)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def blos() -> OBBject[Empty]: # type: ignore
|
||||
"""Big latest officer sales ($100k+)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command # Can't use filter because it's a python keyword
|
||||
def filt() -> OBBject[Empty]: # type: ignore
|
||||
"""Filter insiders based on preset."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def lcb() -> OBBject[Empty]: # type: ignore
|
||||
"""Latest cluster buys."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def lins() -> OBBject[Empty]: # type: ignore
|
||||
"""Last insider trading of the company."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def lip() -> OBBject[Empty]: # type: ignore
|
||||
"""Latest insider purchaces."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def lis() -> OBBject[Empty]: # type: ignore
|
||||
"""Latest insider sales."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def lit() -> OBBject[Empty]: # type: ignore
|
||||
"""Latest insider trading (all filings)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def lpsb() -> OBBject[Empty]: # type: ignore
|
||||
"""Latest penny stock buys."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def print_insider_data() -> OBBject[Empty]: # type: ignore
|
||||
"""Print insider data."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def stats() -> OBBject[Empty]: # type: ignore
|
||||
"""Insider stats of the company."""
|
||||
return OBBject(results=Empty())
|
||||
@@ -1,56 +0,0 @@
|
||||
"""Options Router."""
|
||||
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
router = Router(prefix="/options")
|
||||
|
||||
|
||||
@router.command(model="OptionsChains")
|
||||
def chains(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Get the complete options chain for a ticker."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def eodchain() -> OBBject[Empty]: # type: ignore
|
||||
"""Gets option chain at a specific date."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def hist() -> OBBject[Empty]: # type: ignore
|
||||
"""Get historical data for a single option contract."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def info() -> OBBject[Empty]: # type: ignore
|
||||
"""Display option information (volatility, IV rank, etc.)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def pcr() -> OBBject[Empty]: # type: ignore
|
||||
"""Display historical rolling put/call ratio for ticker over a defined window."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command
|
||||
def unu() -> OBBject[Empty]: # type: ignore
|
||||
"""Show unusual options activity."""
|
||||
return OBBject(results=Empty())
|
||||
@@ -1,106 +0,0 @@
|
||||
# pylint: disable=import-outside-toplevel, W0613:unused-argument
|
||||
"""Stocks Router."""
|
||||
|
||||
|
||||
from openbb_core.app.model.command_context import CommandContext
|
||||
from openbb_core.app.model.obbject import OBBject
|
||||
from openbb_core.app.model.results.empty import Empty
|
||||
from openbb_core.app.provider_interface import (
|
||||
ExtraParams,
|
||||
ProviderChoices,
|
||||
StandardParams,
|
||||
)
|
||||
from openbb_core.app.query import Query
|
||||
from openbb_core.app.router import Router
|
||||
from pydantic import BaseModel
|
||||
|
||||
from openbb_stocks.ca.ca_router import router as ca_router
|
||||
from openbb_stocks.dd.dd_router import router as dd_router
|
||||
from openbb_stocks.disc.disc_router import router as disc_router
|
||||
from openbb_stocks.dps.dps_router import router as dps_router
|
||||
from openbb_stocks.fa.fa_router import router as fa_router
|
||||
from openbb_stocks.gov.gov_router import router as gov_router
|
||||
from openbb_stocks.ins.ins_router import router as ins_router
|
||||
from openbb_stocks.options.options_router import router as options_router
|
||||
|
||||
router = Router(prefix="")
|
||||
router.include_router(fa_router)
|
||||
router.include_router(ca_router)
|
||||
router.include_router(dd_router)
|
||||
router.include_router(dps_router)
|
||||
router.include_router(disc_router)
|
||||
router.include_router(gov_router)
|
||||
router.include_router(ins_router)
|
||||
router.include_router(options_router)
|
||||
|
||||
|
||||
@router.command(model="StockEOD")
|
||||
def load(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Load stock data for a specific ticker."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="StockNews")
|
||||
def news(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Get news for one or more stock tickers."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="StockMultiples")
|
||||
def multiples(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Get valuation multiples for a stock ticker."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command
|
||||
def tob() -> OBBject[Empty]:
|
||||
"""View top of book for loaded ticker (US exchanges only)."""
|
||||
return OBBject(results=Empty())
|
||||
|
||||
|
||||
@router.command(model="StockSearch")
|
||||
def search(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Search for a company or stock ticker."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="StockQuote")
|
||||
def quote(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Load stock data for a specific ticker."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
|
||||
|
||||
@router.command(model="StockInfo")
|
||||
def info(
|
||||
cc: CommandContext,
|
||||
provider_choices: ProviderChoices,
|
||||
standard_params: StandardParams,
|
||||
extra_params: ExtraParams,
|
||||
) -> OBBject[BaseModel]:
|
||||
"""Get general price and performance metrics of a stock."""
|
||||
return OBBject(results=Query(**locals()).execute())
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user