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[Docs] Charting Documentation (#6303)

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{
"label": "Charting",
"position": 3
}

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---
title: Examples
sidebar_position: 1
description: This page provides examples of creating charts with the `openbb-charting` extension.
keywords:
- tutorial
- OpenBB Platform
- Python client
- Fast API
- getting started
- extensions
- charting
- view
- Plotly
- toolkits
- how-to
- generic
- figure
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
<HeadTitle title="Examples - OpenBB Charting - Extensions | OpenBB Platform Docs" />
## Overview
This page will walk through creating different charts using the `openbb-charting` extension.
The perspective for this content is from the the Python Interface,
and the examples will assume that the OpenBB Platform is installed with all optional packages.
```python
from datetime import datetime, timedelta
from openbb import obb
```
## Cumulative Returns
The historical (equity) prices can be requested for multiple symbols.
The extension will attempt to handle variations accordingly.
By default, more than three symbols will draw the chart as cumulative returns from the beginning of the series.
### Default View
The tickers below are a collection of State Street Global Advisors SPDR funds, representing S&P 500 components.
The data is looking back five years.
```
SPDRS = [
"SPY",
"XLE",
"XLB",
"XLI",
"XHB",
"XLP",
"XLY",
"XRT",
"XLF",
"XLV",
"XLK",
"XLC",
"XLU",
"XLRE",
]
start_date = (datetime.now() - timedelta(weeks=52*5)).date()
spdrs = obb.equity.price.historical(SPDRS, start_date=start_date, provider="yfinance", chart=True)
spdrs.show()
```
![SPDRs Cumulative Returns - 5 years](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/8884f4ed-b09c-4161-9dc6-87ad66d9fc8b)
### Redraw as YTD
The `charting` attribute of the command output has methods for creating the chart again.
The `data` parameter allows modifications to the data before creating the figure.
In this example, the length of the data is trimmed to the beginning of the year.
```python
new_data = spdrs.to_df().loc[datetime(2023,12,29).date():]
spdrs.charting.to_chart(data=new_data, title="YTD")
```
:::note
This replaces the chart that was already created.
:::
![SPDRs Cumulative Returns - YTD](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/22ed2588-1098-4712-aec1-54dd22c324ef)
## Price Performance Bar Chart
The `obb.equity.price.performance` endpoint will create a bar chart over intervals.
```python
price_performance = obb.equity.price.performance(SPDRS, chart=True)
price_performance.show()
```
![Price Performance](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/0de3260d-7fce-490b-90e1-bdfa38d6ab23)
### Create Bar Chart
This example uses the `create_bar_chart()` method, which does not replace the existing chart, in `price_performance.chart`.
It isolates the one-month performance and orients the layout as horizontal.
```python
new_data = price_performance.to_df().set_index("symbol").multiply(100).reset_index()
price_performance.charting.create_bar_chart(
data=new_data,
x="symbol",
y="one_month",
orientation="h",
title="One Month Price Performance",
xtitle="Percent (%)"
)
```
![Horizonontal Price Performance](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/8da01f73-d7a8-4168-846a-9fa9ed6a0e39)
## Create Your Own
This example analyzes the share volume turnover of the S&P 500 Energy Sector constituents, year-to-date.
```python
symbols = [
'XOM',
'CVX',
'COP',
'EOG',
'MPC',
'SLB',
'PSX',
'PXD',
'VLO',
'WMB',
'OKE',
'OXY',
'HES',
'FANG',
'HAL',
'KMI',
'DVN',
'BKR',
'TRGP',
'CTRA',
'MRO',
'EQT',
'APA'
]
data = obb.equity.price.historical(symbols, start_date="2024-01-01", provider="yfinance")
create_bar_chart = data.charting.create_bar_chart
volume = data.to_df().groupby("symbol").sum()["volume"]
shares = obb.equity.profile(
symbols, provider="yfinance"
).to_df().set_index("symbol")["shares_float"]
df = volume.to_frame().join(shares)
df["Turnover"] = (df.shares_float/df.volume).round(4)
df = df.sort_values(by="Turnover", ascending=False).reset_index()
create_bar_chart(
data=df,
x="symbol",
y="Turnover",
title="S&P Energy Sector YTD Turnover Rate",
)
```
![S&P 500 Energy Sector Turnover Rate](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/4f59eb36-e637-4a54-87ab-e730e43baf8d)

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---
title: OpenBB Charting
sidebar_position: 1
description: This page introduces the optional openbb-charting extension.
keywords:
- explanation
- OpenBB Platform
- Python client
- Fast API
- getting started
- extensions
- charting
- view
- Plotly
- toolkits
- community
- Plotly
- OpenBBFigure
- PyWry
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
<HeadTitle title="OpenBB Charting - Extensions | OpenBB Platform Docs" />
## Overview
The `openbb-charting` extension provides elements for building and displaying interactive charts, tables, dashboards, and more, directly from the OpenBB Platform's Python Interface and FAST API.
It allows users to create a custom view, without any previous experience working with Plotly, from any response served by the OpenBB Platform.
The Python Interface includes a custom [PyWry](https://github.com/OpenBB-finance/pywry) backend for displaying any content, in a WebKit HTML window served over `localhost`. In an IDE setting, they will be rendered inline.
To install, follow the instructions [here](installation). The sections below provide a general explanation of the extension.
## How Does It Work?
It works by extending the `OBBject` class with a new attribute, `charting`. When it is installed, every response from the OpenBB Platform will be equipped with these tools.
For functions that have pre-defined views, it serves as an intermediary between the user request and the response, activated when `chart=True`. When a chart is created, it will populate the existing, `chart`, attribute of the `OBBject`. This is where it is served by the FAST API from the function request. In the Python Interface, charts can be generated post-request, regardless of `chart=True`.
The `chart` attribute in the OBBject contains three items, responses from the API have two:
- `fig`: The OpenBBFigure object - an extended Plotly GraphObjects class. Not included in the API response.
- `content`: The Plotly JSON representation of the chart - Returned to the API.
- `format`: The format of the chart - 'plotly' is currently the only charting library.
There is one OBBject class method, `show()`, which will display the contents of the `chart` attribute, if populated.
The new `charting` attribute that binds to the OBBject also has a `show()` method. This differs in that it overwrites the existing chart, effectively a 'reset' for the view.
The extension has a docstring, and it lists the class methods within `charting`.
```python
from openbb import obb
data = obb.equity.price.historical("AAPL")
data.charting?
```
```console
Charting extension.
Methods
-------
show
Display chart and save it to the OBBject.
to_chart
Redraw the chart and save it to the OBBject, with an optional entry point for Data.
functions
Return a list of Platform commands with charting functions.
get_params
Return the charting parameters for the function the OBBject was created from.
indicators
Return the list of the available technical indicators to use with the `to_chart` method and OHLC+V data.
table
Display an interactive table.
create_line_chart
Create a line chart from external data.
create_bar_chart
Create a bar chart, on a single x-axis with one or more values for the y-axis, from external data.
```
:::note
When creating a chart directly from the OpenBB Platform endpoint, chart parameters must be passed as a nested dictionary under the name, `chart_params`.
```python
chart_params = dict(
title="AAPL 50/200 Day EMA",
indicators=dict(
ema=dict(length=[50,200]),
),
)
params = dict(
symbol="AAPL",
start_date="2022-01-01",
provider="yfinance",
chart=True,
chart_params=chart_params,
)
data = obb.equity.price.historical(**params)
```
`chart_params` are sent in the body of the request when using the API.
:::
Passing only `chart=True` will return a default view which can be modified and drawn again post-request, via the `OBBject`.
```console
OBBject
id: 06614d74-7443-7201-8000-a65f358136a3
results: [{'date': datetime.date(2022, 1, 3), 'open': 177.8300018310547, 'high': 18...
provider: yfinance
warnings: None
chart: {'content': {'data': [{'close': [182.00999450683594, 179.6999969482422, 174....
extra: {'metadata': {'arguments': {'provider_choices': {'provider': 'yfinance'}, 's...
```
```python
data.show()
```
![candles with ema](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/b427d68b-777e-4230-852a-df749c5dbc46)
### No Render
The charts can be created without opening the PyWry window, and this is the default behaviour when `chart=True`.
With the `charting.show()` and `charting.to_chart()` methods, the default is `render=True`.
Setting as `False` will return the chart to itself, populating the `chart` attribute of OBBject.
## What Endpoints Have Charts?
The OpenBB Platform router, open_api.json, function signatures, and documentation are all generated based on your specific configuration. When the `openbb-charting` extension is installed, any function found in the "[charting_router](https://github.com/OpenBB-finance/OpenBBTerminal/blob/develop/openbb_platform/obbject_extensions/charting/openbb_charting/charting_router.py)" adds `chart: bool = False` to the command on build. For example, `obb.index.price.historical?`
```python
Signature:
obb.index.price.historical(
symbol: Annotated[Union[str, List[str]], OpenBBCustomParameter(description='Symbol to get data for. Multiple comma separated items allowed for provider(s): cboe, fmp, intrinio, polygon, yfinance.')],
...
chart: typing.Annotated[bool, OpenBBCustomParameter(description='Whether to create a chart or not, by default False.')] = False,
**kwargs,
) -> openbb_core.app.model.obbject.OBBject
```
### Charting Functions
The `charting` attribute of every command output has methods for identifying the charting functions and parameters.
While able to serve JSON-serializable charts, the `openbb-charting` extension is best-suited for use with the Python Interface. Much of the functionality is realized post-request.
Examine the extension by returning any command at all.
```python
from openbb import obb
data = obb.equity.price.historical("SPY,QQQ,XLK,BTC-USD", provider="yfinance")
data.charting.functions()
```
```console
['crypto_price_historical',
'currency_price_historical',
'economy_fred_series',
'equity_price_historical',
'equity_price_performance',
'etf_historical',
'etf_holdings',
'etf_price_performance',
'index_price_historical',
'technical_adx',
'technical_aroon',
'technical_cones',
'technical_ema',
'technical_hma',
'technical_macd',
'technical_rsi',
'technical_sma',
'technical_wma',
'technical_zlma']
```
:::tip
The list above should, as shown here, should not be considered as the source of truth. It's just a sample.
:::
If the `OBBject` in question has a dedicated charting function associated with it, parameters are detailed by the `get_params()` method.
```console
EquityPriceHistoricalChartQueryParams
Parameters
----------
data : Union[Data, list[Data], NoneType]
Filtered versions of the data contained in the original `self.results`.
Columns should be the same as the original data.
Example use is to reduce the number of columns, or the length of data, to plot.
title : Union[str, NoneType]
Title of the chart.
target : Union[str, NoneType]
The specific column to target.
If supplied, this will override the candles and volume parameters.
multi_symbol : bool
Flag to indicate whether the data contains multiple symbols.
This is mostly handled automatically, but if the chart fails to generate try setting this to True.
same_axis : bool
If True, forces all data to be plotted on the same axis.
normalize : bool
If True, the data will be normalized and placed on the same axis.
returns : bool
If True, the cumulative returns for the length of the time series will be calculated and plotted.
candles : bool
If True, and OHLC exists, and there is only one symbol in the data, candles will be plotted.
heikin_ashi : bool
If True, and `candles=True`, Heikin Ashi candles will be plotted.
volume : bool
If True, and volume exists, and `candles=True`, volume will be plotted.
indicators : Union[ChartIndicators, dict[str, dict[str, Any]], NoneType]
Indicators to be plotted, formatted as a dictionary.
Data containing multiple symbols will ignore indicators.
Example:
indicators = dict(
sma=dict(length=[20,30,50]),
adx=dict(length=14),
rsi=dict(length=14),
)
```
Not all commands will have the same `chart_params`, and some less than others, but it is always possible to redraw the chart with a different combination post-request. Here's what the default chart is from the output of the command above.
If `chart=True` was not specified, it will need to be created.
```python
data.charting.to_chart()
```
![obb.equity.price.historical()](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/9231c455-ee1b-47a8-a627-b0034ea52ecd)
The extension recognized that multiple symbols were within the object, and made a determination to display cumulative returns by default.
A candlestick chart will draw only when there is one symbol in the data.
```python
obb.equity.price.historical(
symbol="XLK",
start_date="2024-01-01",
provider="yfinance",
chart=True,
chart_params=dict(title="XLK YTD", heikin_ashi=True)
).show()
```
![obb.equity.price.historical()](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/13af30b3-7298-402d-ac32-1f7700cd08fd)
## Endpoints Without Charts
Most functions do not have dedicated charts. However, it's still possible to generate one automatically. Using the `data` above, we can try passing it through a quantitative analysis command.
```python
data = obb.equity.price.historical(
symbol="XLK",
start_date="2023-01-01",
provider="yfinance",
)
qa = obb.quantitative.rolling.stdev(data.results, target="close")
qa.charting.show(title="XLK Rolling 21 Day Standard Deviation")
```
![auto chart](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/f87a6648-7365-4529-a254-35897af448ca)
## Charts From Any Data
There are methods for creating a generic chart from any external data.
They will bypass any data contained in the parent object, unless specifically fed into itself.
- charting.create_bar_chart()
- charting.create_line_chart()
They can also be used as standalone components by initializing an empty instance of the OBBject class.
```python
from openbb import obb
from openbb_core.app.model.obbject import OBBject
create_bar_chart = OBBject(results=None).charting.create_bar_chart
create_bar_chart?
````
```console
Create a bar chart on a single x-axis with one or more values for the y-axis.
Parameters
----------
data : Union[list, dict, pd.DataFrame, List[pd.DataFrame], pd.Series, List[pd.Series], np.ndarray, Data]
Data to plot.
x : str
The x-axis column name.
y : Union[str, List[str]]
The y-axis column name(s).
barmode : Literal["group", "stack", "relative", "overlay"], optional
The bar mode, by default "group".
xtype : Literal["category", "multicategory", "date", "log", "linear"], optional
The x-axis type, by default "category".
title : Optional[str], optional
The title of the chart, by default None.
xtitle : Optional[str], optional
The x-axis title, by default None.
ytitle : Optional[str], optional
The y-axis title, by default None.
orientation : Literal["h", "v"], optional
The orientation of the chart, by default "v".
colors: Optional[List[str]], optional
Manually set the colors to cycle through for each column in 'y', by default None.
layout_kwargs : Optional[Dict[str, Any]], optional
Additional keyword arguments to apply with figure.update_layout(), by default None.
Returns
-------
OpenBBFigure
The OpenBBFigure object.
```
## Tables
The `openbb-charting` extension is equipped with interactive tables, utilizing the React framework. They are displayed by using the `table` method.
```python
data = obb.equity.price.quote("AAPL,MSFT,GOOGL,META,TSLA,AMZN", provider="yfinance")
data.charting.table()
```
![Interactive Tables](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/77f5f812-b933-4ced-929c-c1e39b2a3eed)
External data can also be supplied, providing an opportunity to filter or apply Pandas operations before display.
```
new_df = df.to_df().T
new_df.index.name="metric"
new_df.columns = new_df.loc["symbol"]
new_df.drop("symbol", inplace=True)
data.charting.table(data=new_df)
```
![Tables From External Data](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/d02f8c34-e1d1-4001-a73e-d3b948a4c5c1)
:::important
This does not alter the contents of the original object, the displayed data is a copy.
:::

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---
title: Indicators
sidebar_position: 2
description: A tutorial of the technical indicators included with the openbb-charting library, including how to get started using them.
keywords:
- tutorial
- OpenBB Platform
- getting started
- extensions
- charting
- view
- Plotly
- toolkits
- indicators
- Plotly
- OpenBBFigure
- PyWry
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
<HeadTitle title="Indicators - OpenBB Charting - Extensions | OpenBB Platform Docs" />
## Introduction
Select indicators (technical) can be added to a chart where the data is OHLC+V prices over time, and the data is for one symbol only.
They are meant as quick visualizations, and a way to build more complex charts.
As starting points, they can be refined to perfection by manipulating the figure object directly.
```python
from datetime import datetime, timedelta
from openbb import obb
data = obb.equity.price.historical(
"TSLA",
provider="yfinance",
interval="15m",
start_date=(datetime.now()-timedelta(days=21)).date(),
chart=True,
chart_params=dict(
heikin_ashi=True,
indicators=(dict(
ema=dict(length=[8,32]),
srlines={}, # For indicators, an empty dictionary implies the default state.
rsi=dict(length=32)
))
)
)
data.show()
```
![TSLA Intraday With Indicators](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/7d8d95d8-0383-4e9d-9477-7ad2424328df)
## Available Indicators
To get all the indicators, use the `charting.indicators()` method.
The object returned is a Pydantic model where each indicator is field.
If you don't catch it, it will print as a docstring to the console.
:::danger
Some indicators, like RSI and MACD, create subplots. Only 4 subplots (not including the main candles + volume) can be created within the same view.
:::
```python
data.charting.indicators()
```
```console
SMA:
Parameters
----------
length : Union[int, list[int]]
Window length for the moving average, by default is 50.
The number is relative to the interval of the time series data.
offset : int
Number of periods to offset for the moving average, by default is 0.
EMA:
Parameters
----------
length : Union[int, list[int]]
Window length for the moving average, by default is 50.
The number is relative to the interval of the time series data.
offset : int
Number of periods to offset for the moving average, by default is 0.
HMA:
Parameters
----------
length : Union[int, list[int]]
Window length for the moving average, by default is 50.
The number is relative to the interval of the time series data.
offset : int
Number of periods to offset for the moving average, by default is 0.
WMA:
Parameters
----------
length : Union[int, list[int]]
Window length for the moving average, by default is 50.
The number is relative to the interval of the time series data.
offset : int
Number of periods to offset for the moving average, by default is 0.
ZLMA:
Parameters
----------
length : Union[int, list[int]]
Window length for the moving average, by default is 50.
The number is relative to the interval of the time series data.
offset : int
Number of periods to offset for the moving average, by default is 0.
AD:
Parameters
----------
offset : int
Offset value for the AD, by default is 0.
AD Oscillator:
Parameters
----------
fast : int
Number of periods to use for the fast calculation, by default 3.
slow : int
Number of periods to use for the slow calculation, by default 10.
offset : int
Offset to be used for the calculation, by default is 0.
ADX:
Parameters
----------
length : int
Window length for the ADX, by default is 50.
scalar : float
Scalar to multiply the ADX by, default is 100.
drift : int
Drift value for the ADX, by default is 1.
Aroon:
Parameters
----------
length : int
Window length for the Aroon, by default is 50.
scalar : float
Scalar to multiply the Aroon by, default is 100.
ATR:
Parameters
----------
length : int
Window length for the ATR, by default is 14.
mamode : Literal[rma, ema, sma, wma]
The mode to use for the moving average calculation.
drift : int
The difference period.
offset : int
Number of periods to offset the result, by default is 0.
CCI:
Parameters
----------
length : int
Window length for the CCI, by default is 14.
scalar : float
Scalar to multiply the CCI by, default is 0.015.
Clenow:
Parameters
----------
period : int
The number of periods for the momentum, by default 90.
Demark:
Parameters
----------
show_all : bool
Show 1 - 13.
If set to False, show 6 - 9.
offset : int
Number of periods to offset the result, by default is 0.
Donchian:
Parameters
----------
lower : Union[int, NoneType]
Window length for the lower band, by default is 20.
upper : Union[int, NoneType]
Window length for the upper band, by default is 20.
offset : Union[int, NoneType]
Number of periods to offset the result, by default is 0.
Fib:
Parameters
----------
period : int
The period to calculate the Fibonacci Retracement, by default 120.
start_date : Union[str, NoneType]
The start date for the Fibonacci Retracement.
end_date : Union[str, NoneType]
The end date for the Fibonacci Retracement.
Fisher:
Parameters
----------
length : int
Window length for the Fisher Transform, by default is 14.
signal : int
Fisher Signal Period
Ichimoku:
Parameters
----------
conversion : int
The conversion line period, by default 9.
base : int
The base line period, by default 26.
lagging : int
The lagging line period, by default 52.
offset : int
The offset period, by default 26.
lookahead : bool
Drops the Chikou Span Column to prevent potential data leak
KC:
Parameters
----------
length : int
Window length for the Keltner Channel, by default is 20.
scalar : float
Scalar to multiply the ATR, by default is 2.
mamode : Literal[ema, sma, wma, hna, zlma, rma]
The mode to use for the moving average calculation, by default is ema.
offset : int
Number of periods to offset the result, by default is 0.
MACD:
Parameters
----------
fast : Union[int, NoneType]
Window length for the fast EMA, by default is 12.
slow : Union[int, NoneType]
Window length for the slow EMA, by default is 26.
signal : Union[int, NoneType]
Window length for the signal line, by default is 9.
scalar : Union[float, NoneType]
Scalar to multiply the MACD by, default is 100.
OBV:
Parameters
----------
offset : int
Number of periods to offset the result, by default is 0.
RSI:
Parameters
----------
length : int
Window length for the RSI, by default is 14.
scalar : float
Scalar to multiply the RSI by, default is 100.
drift : int
Drift value for the RSI, by default is 1.
SRLines:
Parameters
----------
show : bool
Show the support and resistance lines.
Stoch:
Parameters
----------
fast_k : int
The fast K period, by default 14.
slow_d : int
The slow D period, by default 3.
slow_k : int
The slow K period, by default 3.
```
The model can be converted to a dictionary and then passed through the `indicators` params.
The chart below is built from the same object as the one above.
```python
indicators = data.charting.indicators().dict()
macd=indicators.get("macd")
kc=indicators.get("kc")
chart_params=dict(
candles=False,
title="My New Chart",
indicators=(dict(
macd=macd,
kc=kc,
))
)
data.charting.to_chart(**chart_params)
```
![indicators2](https://github.com/OpenBB-finance/OpenBBTerminal/assets/85772166/76c06aff-a568-4b7f-80d4-c58a73c0f1d7)
:::tip
Data can be exported directly from the chart as a CSV. Use the button at the bottom-right of the mode bar.
:::

71
website/content/platform/extensions/charting/installation.md vendored Normal file
View File

@@ -0,0 +1,71 @@
---
title: Installation
sidebar_position: 1
description: This page outlines the installation of the openbb-charting extension.
keywords:
- tutorial
- OpenBB Platform
- Installation
- Python client
- Fast API
- getting started
- extensions
- charting
- view
- Plotly
- toolkit
- community
- Plotly
- OpenBBFigure
- PyWry
---
import HeadTitle from '@site/src/components/General/HeadTitle.tsx';
<HeadTitle title="Installation - Charting - Extensions | OpenBB Platform Docs" />
## PyPI
To install the extension, run the following command in this folder:
```bash
pip install openbb-charting
```
> Find the latest version on [PyPI](https://pypi.org/project/openbb-charting/).
## Editable Mode
To install from source in editable mode, navigate into the folder, `~/openbb_platform/extensions/charting`, and enter:
```console
pip install -e .
```
After installation, the Python interface will automatically rebuild on initialization. This process can also be triggered manually with:
```python
import openbb
openbb.build()
```
The Python interpreter may need to be restarted.
## PyWry Dependency In Linux
When using Linux distributions, the PyWry dependency requires certain dependencies to be installed first.
- Debian-based / Ubuntu / Mint:
`sudo apt install libwebkit2gtk-4.0-dev`
- Arch Linux / Manjaro:
`sudo pacman -S webkit2gtk`
- Fedora:
`sudo dnf install gtk3-devel webkit2gtk3-devel`
If Rust (Cargo) is required, install it:
```console
curl --proto '=https' --tlsv1.3 https://sh.rustup.rs -sSf | sh
```

50
website/content/platform/extensions/toolkit_extensions.md vendored
View File

@@ -40,14 +40,12 @@ The sections below outline any specific installation considerations for the exte
## Charting
The OpenBB Charting Extension supplies charting infrastructure and services to the OpenBB Platform. Figure objects are served via REST API or Python Client. It utilizes [PyWry](https://github.com/OpenBB-finance/pywry) for handling the display of interactive charts and tables in a separate window, with a Plotly library. The extension framework allows developers to easily insert other Python charting libraries into the router pipeline.
The OpenBB Charting Extension supplies charting infrastructure and services to the OpenBB Platform. Figure objects are served via REST API or Python Client. It utilizes [PyWry](https://github.com/OpenBB-finance/pywry) for handling the display of interactive charts and tables in a separate window, with a Plotly library.
Functions with charting enabled return figures to a field (`chart`) in the `OBBject` response object. They are displayed with the class method, `show()`.
> Additional Python libraries are installed with this extension: `aiohttp`, `nbformat`, `pandas-ta`, `plotly`, `pywry`, `reportlab`, `scipy`, `statsmodels`, and `svglib`.
Functions with dedicated views return figures to the `chart` attribute of the `OBBject` response object. They are displayed with the class method, `show()`.
:::tip
The `openbb-charting` is in fact an [`OBBject` extension](platform/development/how-to/add_obbject_extension.md) which means you'll have the functionality it exposes on every command result.
The `openbb-charting` is an [`OBBject` extension](platform/development/how-to/add_obbject_extension.md), which means the general functionality is exposed in every command result.
:::
The following packages are dependencies of the `openbb-charting` extension:
@@ -63,47 +61,7 @@ The following packages are dependencies of the `openbb-charting` extension:
### Installation
To install the extension, run the following command in this folder:
```bash
pip install openbb-charting
```
> Find the latest version on [PyPI](https://pypi.org/project/openbb-charting/).
To install from source in editable mode, navigate into the folder, `~/openbb_platform/extensions/charting`, and enter:
```console
pip install -e .
```
After installation, the Python interface will automatically rebuild on initialization. This process can also be triggered manually with:
```python
import openbb
openbb.build()
```
The Python interpreter may require a restart.
### PyWry dependency in Linux
When using Linux distributions, the PyWry dependency requires certain dependencies to be installed first.
- Debian-based / Ubuntu / Mint:
`sudo apt install libwebkit2gtk-4.0-dev`
- Arch Linux / Manjaro:
`sudo pacman -S webkit2gtk`
- Fedora:
`sudo dnf install gtk3-devel webkit2gtk3-devel`
If Rust (Cargo) is required, install it:
```console
curl --proto '=https' --tlsv1.3 https://sh.rustup.rs -sSf | sh
```
See the [charting](charting) section for more details and [installation](charting/installation) instructions.
## Devtools