mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-27 12:40:35 +00:00
Merge branch 'main' into add-unit-tests
This commit is contained in:
Artem Veremey
61
README.md
61
README.md
@@ -132,6 +132,21 @@ This is a library for package management, and ensures a smoother experience than
|
||||
python terminal.py
|
||||
```
|
||||
|
||||
### Advanced User Install - Python 3.8
|
||||
|
||||
*Note that the `conda deactivate` -> `conda activate` in the middle is on purpose, this is sometimes required to avoid issues with poetry*
|
||||
|
||||
```
|
||||
conda create -n gst python=3.8.8
|
||||
conda activate gst
|
||||
conda install poetry
|
||||
conda deactivate
|
||||
conda activate gst
|
||||
poetry install
|
||||
conda install -c conda-forge fbprophet numpy=1.19.5 hdf5=1.10.5
|
||||
poetry install -E prediction
|
||||
```
|
||||
|
||||
### Advanced User Install - Machine Learning
|
||||
|
||||
If you are an advanced user and use other Python distributions, we have several requirements.txt documents that you can pick from to download project dependencies.
|
||||
@@ -145,10 +160,17 @@ Note: The libraries specified in the [requirements.txt](/requirements.txt) file
|
||||
ENABLE_PREDICT = os.getenv("GTFF_ENABLE_PREDICT") or True
|
||||
```
|
||||
|
||||
* Install optional ML features dependencies collection with poetry:
|
||||
* Install optional ML features dependencies:
|
||||
```
|
||||
poetry install -E prediction
|
||||
```
|
||||
*If you run into issues installing or `Cannot convert a symbolic Tensor...` at runtime, try this:*
|
||||
|
||||
```
|
||||
conda install -c conda-forge fbprophet numpy=1.19.5 hdf5=1.10.5
|
||||
poetry install
|
||||
poetry install -E prediction
|
||||
```
|
||||
|
||||
*If you would like to set up a docker image:*
|
||||
|
||||
@@ -157,10 +179,40 @@ poetry install -E prediction
|
||||
|
||||
Note: The problem with docker is that it won't output matplotlib figures.
|
||||
|
||||
*Commands that may help you in case of an error:*
|
||||
* `conda install -c conda-forge fbprophet -y`
|
||||
*Commands that may help you in case of an error:
|
||||
|
||||
* `python -m pip install --upgrade pip`
|
||||
* `pip install pystan --upgrade`
|
||||
* `poetry update --lock`
|
||||
|
||||
### Other issues
|
||||
|
||||
If you run into trouble with poetry and the advice above did not help, your best bet is to try
|
||||
|
||||
1. `poetry update --lock`
|
||||
|
||||
2. `conda deactivate` -> `conda activate gst`, then try again
|
||||
|
||||
3. Delete the poetry cache, then try again
|
||||
|
||||
| Platform | Location |
|
||||
| -------- | ------------------------------- |
|
||||
| Linux | "~/.cache/pypoetry" |
|
||||
| Mac | "~/Library/Caches/pypoetry" |
|
||||
| Windows | "%localappdata%/pypoetry/cache" |
|
||||
|
||||
4. Track down the offensive package and purge it from your anaconda `<environment_name>` folder, then try again (removing through conda can sometimes leave locks behind)
|
||||
|
||||
| Platform | Location |
|
||||
| --------- | -------------------------------------------- |
|
||||
| Linux/Mac | "~/anaconda3/envs" or "~/opt/anaconda3/envs" |
|
||||
| Windows | "%userprofile%/anaconda3/envs" |
|
||||
|
||||
5. Completely nuke your conda environment folder and make a new environment from scratch
|
||||
|
||||
6. Reboot your computer and try again
|
||||
|
||||
7. Submit a ticket on github
|
||||
|
||||
### API Keys
|
||||
|
||||
@@ -173,10 +225,11 @@ These are the ones where a key is necessary:
|
||||
* Twitter: https://developer.twitter.com
|
||||
* Polygon: https://polygon.io
|
||||
* Financial Modeling Prep: https://financialmodelingprep.com/developer
|
||||
* FRED: https://fred.stlouisfed.org/docs/api/api_key.html
|
||||
|
||||
When these are obtained, don't forget to update [config_terminal.py](/gamestonk_terminal/config_terminal.py).
|
||||
|
||||
Alternatively, you can also set them to the following environment variables: GT_API_KEY_ALPHAVANTAGE, GT_API_KEY_FINANCIALMODELINGPREP, GT_API_KEY_QUANDL, GT_API_REDDIT_CLIENT_ID, GT_API_REDDIT_CLIENT_SECRET, GT_API_REDDIT_USERNAME, GT_API_REDDIT_USER_AGENT, GT_API_REDDIT_PASSWORD, GT_API_TWITTER_KEY, GT_API_TWITTER_SECRET_KEY, GT_API_TWITTER_BEARER_TOKEN, GT_API_POLYGON_KEY.
|
||||
Alternatively, you can also set them to the following environment variables: GT_API_KEY_ALPHAVANTAGE, GT_API_KEY_FINANCIALMODELINGPREP, GT_API_KEY_QUANDL, GT_API_REDDIT_CLIENT_ID, GT_API_REDDIT_CLIENT_SECRET, GT_API_REDDIT_USERNAME, GT_API_REDDIT_USER_AGENT, GT_API_REDDIT_PASSWORD, GT_API_TWITTER_KEY, GT_API_TWITTER_SECRET_KEY, GT_API_TWITTER_BEARER_TOKEN, GT_API_POLYGON_KEY, GT_FRED_API_KEY.
|
||||
|
||||
Example:
|
||||
```
|
||||
|
||||
59
ROADMAP.md
59
ROADMAP.md
@@ -1,6 +1,6 @@
|
||||
# Roadmap 📍
|
||||
|
||||
### Table of contents
|
||||
## Table of contents
|
||||
|
||||
* [Discovery](#Discovery)
|
||||
* [Behavioral Analysis](#Behavioral-Analysis)
|
||||
@@ -13,13 +13,17 @@
|
||||
* [Comparison Analysis](#Comparison-Analysis)
|
||||
* [Exploratory Data Analysis](#Exploratory-Data-Analysis)
|
||||
* [Portfolio Analysis](#Portfolio-Analysis)
|
||||
* [FRED](#FRED)
|
||||
* [Options](#Options)
|
||||
* [Credit Analysis](#Credit-Analysis)
|
||||
* [Cryptocurrencies](#Cryptocurrencies)
|
||||
|
||||
## Additional
|
||||
* [Backend](#Backend)
|
||||
* [Frontend](#Frontend)
|
||||
* [Developer Experience](#Developer-Experience)
|
||||
* [User Experience](#User-Experience)
|
||||
* [Options](#Options)
|
||||
|
||||
---
|
||||
|
||||
## Discovery
|
||||
@@ -40,6 +44,7 @@
|
||||
### Short term
|
||||
|
||||
- [ ] Implement a better Twitter client (@aia)
|
||||
- [x] Add FinBrain sentiment from news (@didier) - [PR #223](https://github.com/DidierRLopes/GamestonkTerminal/pull/223)
|
||||
|
||||
### Long term
|
||||
|
||||
@@ -89,10 +94,14 @@
|
||||
|
||||
### Short term
|
||||
|
||||
- [x] Add several exponential smoothing techniques [PR #132](https://github.com/DidierRLopes/GamestonkTerminal/pull/132)
|
||||
- [x] Add several exponential smoothing techniques (@didier) - [PR #132](https://github.com/DidierRLopes/GamestonkTerminal/pull/132)
|
||||
- [x] Allow backtesting (@didier) - [PR #169](https://github.com/DidierRLopes/GamestonkTerminal/pull/169)
|
||||
- [ ] Add averaging around multiple predictions - [IS #240](https://github.com/DidierRLopes/GamestonkTerminal/issues/240)
|
||||
|
||||
### Long term
|
||||
|
||||
- [ ] Combine Sentiment Analysis with Chart data - [IS #240](https://github.com/DidierRLopes/GamestonkTerminal/issues/240)
|
||||
|
||||
---
|
||||
|
||||
## Reports
|
||||
@@ -111,7 +120,7 @@
|
||||
### Short term
|
||||
|
||||
* [x] Add multi-ticker historical data comparison (@didier) - [PR #141](https://github.com/DidierRLopes/GamestonkTerminal/pull/141)
|
||||
* [ ] Add multi-ticker financials comparison (@didier)
|
||||
* [x] Add multi-ticker financials comparison (@didier) - [PR #237](https://github.com/DidierRLopes/GamestonkTerminal/pull/237)
|
||||
|
||||
### Long term
|
||||
|
||||
@@ -135,9 +144,37 @@
|
||||
* [ ] Merge data from different brokers
|
||||
* [ ] Refactor
|
||||
|
||||
- [x] Add robinhood (@jmaslek) - [PR #209](https://github.com/DidierRLopes/GamestonkTerminal/pull/209)
|
||||
- [ ] Add Brokers (td, alpaca, webull, etc) (@jmaslek)
|
||||
- [ ] Merge data from different brokers (@jmaslek)
|
||||
### Long term
|
||||
* [ ] Summaries / tear sheets
|
||||
* [ ] Portfolio Optimization
|
||||
|
||||
- [ ] Summaries / tear sheets (@jmaslek)
|
||||
- [ ] Portfolio Optimization (@jmaslek)
|
||||
|
||||
|
||||
---
|
||||
|
||||
## FRED
|
||||
|
||||
### Short term
|
||||
|
||||
- [x] Implement Economic data (gpd, unemployment rate, ...) (@jmaslek) - [PR #167](https://github.com/DidierRLopes/GamestonkTerminal/pull/167)
|
||||
### Long term
|
||||
|
||||
---
|
||||
|
||||
## Options
|
||||
|
||||
### Short term
|
||||
|
||||
- [x] Add Volume graph (@lolrenx) - [PR #209](https://github.com/DidierRLopes/GamestonkTerminal/pull/209)
|
||||
- [x] Add Open Interest graph (@lolrenx) - [PR #209](https://github.com/DidierRLopes/GamestonkTerminal/pull/209)
|
||||
|
||||
### Long term
|
||||
|
||||
- [ ] Add max pain graph (@lolrenx)
|
||||
|
||||
---
|
||||
|
||||
## Credit Analysis
|
||||
@@ -213,13 +250,3 @@
|
||||
|
||||
---
|
||||
|
||||
## Options
|
||||
|
||||
### Short term
|
||||
|
||||
- [ ] Add Volume graph (@lolrenx)
|
||||
- [ ] Add Open Interest graph (@lolrenx)
|
||||
|
||||
### Long term
|
||||
|
||||
- [ ] Add max pain graph
|
||||
|
||||
@@ -10,6 +10,12 @@ This menu aims to compare a pre-loaded stock with similar companies, and the usa
|
||||
* historical data comparison [Yahoo Finance]
|
||||
* [corr](#corr)
|
||||
* correlation between similar companies [Yahoo Finance]
|
||||
* [income](#income)
|
||||
* income financials comparison [Market Watch]
|
||||
* [balance](#balance)
|
||||
* balance financials comparison [Market Watch]
|
||||
* [cashflow](#cashflow)
|
||||
* cashflow financials comparison [Market Watch]
|
||||
|
||||
|
||||
## get <a name="get"></a>
|
||||
@@ -59,3 +65,53 @@ Historical price comparison between similar companies [Source: Yahoo Finance]
|
||||
* -t : type of candles: o-open, h-high, l-low, c-close, a-adjusted close. Default 'a'.
|
||||
|
||||
|
||||
|
||||
|
||||
## income <a name="income"></a>
|
||||
|
||||
```text
|
||||
usage: income [-s L_SIMILAR] [-a L_ALSO] [-t 31-Dec-2020/2017] [-q]
|
||||
```
|
||||
|
||||
Income financials comparison between similar companies [Source: Market Watch]
|
||||
|
||||
* -s : similar companies to compare with. Default pre-loaded ones.
|
||||
* -a : apart from loaded similar companies also compare with.
|
||||
* -t : timeframe of earnings. Default: Last.
|
||||
* -q : quarterly data instead of yearly. Default: False.
|
||||
|
||||
<img width="1007" alt="Captura de ecrã 2021-03-20, às 09 10 02" src="https://user-images.githubusercontent.com/25267873/111865162-4fe05d80-895d-11eb-8a0f-d7c2ba7700e2.png">
|
||||
|
||||
|
||||
## balance <a name="balance"></a>
|
||||
|
||||
```text
|
||||
usage: balance [-s L_SIMILAR] [-a L_ALSO] [-t 31-Dec-2020/2017] [-q]
|
||||
```
|
||||
|
||||
Balance financials comparison between similar companies [Source: Market Watch]
|
||||
|
||||
* -s : similar companies to compare with. Default pre-loaded ones.
|
||||
* -a : apart from loaded similar companies also compare with.
|
||||
* -t : timeframe of earnings. Default: Last.
|
||||
* -q : quarterly data instead of yearly. Default: False.
|
||||
|
||||
<img width="1014" alt="Captura de ecrã 2021-03-20, às 09 10 53" src="https://user-images.githubusercontent.com/25267873/111865168-5373e480-895d-11eb-960f-b919e338ab83.png">
|
||||
|
||||
## cashflow <a name="cashflow"></a>
|
||||
|
||||
```text
|
||||
usage: cashflow [-s L_SIMILAR] [-a L_ALSO] [-t 31-Dec-2020/2017] [-q]
|
||||
```
|
||||
|
||||
Cashflow financials comparison between similar companies [Source: Market Watch]
|
||||
|
||||
* -s : similar companies to compare with. Default pre-loaded ones.
|
||||
* -a : apart from loaded similar companies also compare with.
|
||||
* -t : timeframe of earnings. Default: Last.
|
||||
* -q : quarterly data instead of yearly. Default: False.
|
||||
|
||||
<img width="1010" alt="Captura de ecrã 2021-03-20, às 09 12 59" src="https://user-images.githubusercontent.com/25267873/111865169-54a51180-895d-11eb-8d31-b499ab74854e.png">
|
||||
|
||||
|
||||
|
||||
|
||||
252
gamestonk_terminal/comparison_analysis/ca_controller.py
Normal file
252
gamestonk_terminal/comparison_analysis/ca_controller.py
Normal file
@@ -0,0 +1,252 @@
|
||||
"""Comparison Analysis Controller Module"""
|
||||
__docformat__ = "numpy"
|
||||
|
||||
import argparse
|
||||
import requests
|
||||
from typing import List
|
||||
from datetime import datetime
|
||||
import pandas as pd
|
||||
|
||||
from gamestonk_terminal import feature_flags as gtff
|
||||
from gamestonk_terminal import config_terminal as cfg
|
||||
from gamestonk_terminal.helper_funcs import get_flair, parse_known_args_and_warn
|
||||
from gamestonk_terminal.comparison_analysis import yahoo_finance_api as yf_api
|
||||
from gamestonk_terminal.comparison_analysis import market_watch_api as mw_api
|
||||
from gamestonk_terminal.menu import session
|
||||
from prompt_toolkit.completion import NestedCompleter
|
||||
|
||||
|
||||
class ComparisonAnalysisController:
|
||||
"""Comparison Analysis Controller class"""
|
||||
|
||||
# Command choices
|
||||
CHOICES = [
|
||||
"help",
|
||||
"q",
|
||||
"quit",
|
||||
"get",
|
||||
"select",
|
||||
"historical",
|
||||
"corr",
|
||||
"income",
|
||||
"balance",
|
||||
"cashflow",
|
||||
]
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
stock: pd.DataFrame,
|
||||
ticker: str,
|
||||
start: datetime,
|
||||
interval: str,
|
||||
similar: List[str],
|
||||
user: bool,
|
||||
):
|
||||
"""Constructor"""
|
||||
self.similar = similar
|
||||
self.user = user
|
||||
self.stock = stock
|
||||
self.ticker = ticker
|
||||
self.start = start
|
||||
self.interval = interval
|
||||
self.ca_parser = argparse.ArgumentParser(add_help=False, prog="ca")
|
||||
self.ca_parser.add_argument(
|
||||
"cmd",
|
||||
choices=self.CHOICES,
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def print_help(self):
|
||||
"""Print help"""
|
||||
|
||||
s_intraday = (f"Intraday {self.interval}", "Daily")[self.interval == "1440min"]
|
||||
|
||||
if self.start:
|
||||
print(
|
||||
f"\n{s_intraday} Stock: {self.ticker} (from {self.start.strftime('%Y-%m-%d')})"
|
||||
)
|
||||
else:
|
||||
print(f"\n{s_intraday} Stock: {self.ticker}")
|
||||
|
||||
s_similar_source = ("Polygon API", "User")[self.user]
|
||||
|
||||
if self.similar:
|
||||
print(f"[{s_similar_source}] Similar Companies: {', '.join(self.similar)}")
|
||||
else:
|
||||
print(f"No similar companies [{s_similar_source}]")
|
||||
|
||||
print("\nComparison Analysis Mode:")
|
||||
print(" help show this comparison analysis menu again")
|
||||
print(" q quit this menu, and shows back to main menu")
|
||||
print(" quit quit to abandon program")
|
||||
print("")
|
||||
print(" get get similar companies [Polygon API]")
|
||||
print(" select select similar companies")
|
||||
print("")
|
||||
if self.similar:
|
||||
print(" historical historical data comparison")
|
||||
print(" corr correlation between similar companies")
|
||||
print("")
|
||||
print(" income income financials comparison")
|
||||
print(" balance balance financials comparison")
|
||||
print(" cashflow cashflow comparison")
|
||||
print("")
|
||||
return
|
||||
|
||||
@staticmethod
|
||||
def get_similar_companies(self, other_args: List[str]):
|
||||
""" Get similar companies. [Source: Polygon API] """
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
prog="get",
|
||||
description="""Get similar companies to compare with.""",
|
||||
)
|
||||
|
||||
try:
|
||||
ns_parser = parse_known_args_and_warn(parser, other_args)
|
||||
if not ns_parser:
|
||||
return
|
||||
|
||||
result = requests.get(
|
||||
f"https://api.polygon.io/v1/meta/symbols/{self.ticker.upper()}/company?&apiKey={cfg.API_POLYGON_KEY}"
|
||||
)
|
||||
|
||||
if result.status_code == 200:
|
||||
self.similar = result.json()["similar"]
|
||||
print(f"[Polygon API] Similar Companies: {', '.join(self.similar)}")
|
||||
self.user = False
|
||||
else:
|
||||
print(result.json()["error"])
|
||||
|
||||
except Exception as e:
|
||||
print(e)
|
||||
|
||||
print("")
|
||||
return
|
||||
|
||||
@staticmethod
|
||||
def select_similar_companies(self, other_args: List[str]):
|
||||
""" Select similar companies, e.g. NIO,XPEV,LI"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
prog="select",
|
||||
description="""Select similar companies to compare with.""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-s",
|
||||
"--similar",
|
||||
dest="l_similar",
|
||||
type=lambda s: [str(item).upper() for item in s.split(",")],
|
||||
default=[],
|
||||
help="similar companies to compare with.",
|
||||
)
|
||||
|
||||
try:
|
||||
# For the case where a user uses: 'select NIO,XPEV,LI'
|
||||
if other_args:
|
||||
if "-" not in other_args[0]:
|
||||
other_args.insert(0, "-s")
|
||||
|
||||
ns_parser = parse_known_args_and_warn(parser, other_args)
|
||||
if not ns_parser:
|
||||
return
|
||||
|
||||
self.similar = ns_parser.l_similar
|
||||
self.user = True
|
||||
|
||||
except Exception as e:
|
||||
print(e)
|
||||
|
||||
print("")
|
||||
|
||||
def switch(self, an_input: str):
|
||||
"""Process and dispatch input
|
||||
|
||||
Returns
|
||||
-------
|
||||
True, False or None
|
||||
False - quit the menu
|
||||
True - quit the program
|
||||
None - continue in the menu
|
||||
"""
|
||||
(known_args, other_args) = self.ca_parser.parse_known_args(an_input.split())
|
||||
|
||||
return getattr(
|
||||
self, "call_" + known_args.cmd, lambda: "Command not recognized!"
|
||||
)(other_args)
|
||||
|
||||
def call_help(self, _):
|
||||
"""Process Help command"""
|
||||
self.print_help(self)
|
||||
|
||||
def call_q(self, _):
|
||||
"""Process Q command - quit the menu"""
|
||||
return False
|
||||
|
||||
def call_quit(self, _):
|
||||
"""Process Quit command - quit the program"""
|
||||
return True
|
||||
|
||||
def call_get(self, other_args: List[str]):
|
||||
"""Process get command"""
|
||||
self.get_similar_companies(self, other_args)
|
||||
|
||||
def call_select(self, other_args: List[str]):
|
||||
"""Process select command"""
|
||||
self.select_similar_companies(self, other_args)
|
||||
|
||||
def call_historical(self, other_args: List[str]):
|
||||
"""Process historical command"""
|
||||
yf_api.historical(
|
||||
other_args, self.stock, self.ticker, self.start, self.interval, self.similar
|
||||
)
|
||||
|
||||
def call_corr(self, other_args: List[str]):
|
||||
"""Process correlation command"""
|
||||
yf_api.correlation(
|
||||
other_args, self.stock, self.ticker, self.start, self.interval, self.similar
|
||||
)
|
||||
|
||||
def call_income(self, other_args: List[str]):
|
||||
"""Process income command"""
|
||||
mw_api.compare_income(other_args, self.ticker, self.similar)
|
||||
|
||||
def call_balance(self, other_args: List[str]):
|
||||
"""Process balance command"""
|
||||
mw_api.compare_balance(other_args, self.ticker, self.similar)
|
||||
|
||||
def call_cashflow(self, other_args: List[str]):
|
||||
"""Process cashflow command"""
|
||||
mw_api.compare_cashflow(other_args, self.ticker, self.similar)
|
||||
|
||||
|
||||
def menu(stock: pd.DataFrame, ticker: str, start: datetime, interval: str):
|
||||
"""Comparison Analysis Menu"""
|
||||
|
||||
ca_controller = ComparisonAnalysisController(
|
||||
stock, ticker, start, interval, [], False
|
||||
)
|
||||
ca_controller.call_help(None)
|
||||
|
||||
while True:
|
||||
# Get input command from user
|
||||
if session and gtff.USE_PROMPT_TOOLKIT:
|
||||
completer = NestedCompleter.from_nested_dict(
|
||||
{c: None for c in ca_controller.CHOICES}
|
||||
)
|
||||
an_input = session.prompt(
|
||||
f"{get_flair()} (ca)> ",
|
||||
completer=completer,
|
||||
)
|
||||
else:
|
||||
an_input = input(f"{get_flair()} (ca)> ")
|
||||
|
||||
try:
|
||||
process_input = ca_controller.switch(an_input)
|
||||
|
||||
if process_input is not None:
|
||||
return process_input
|
||||
|
||||
except SystemExit:
|
||||
print("The command selected doesn't exist\n")
|
||||
continue
|
||||
@@ -1,168 +0,0 @@
|
||||
import argparse
|
||||
import requests
|
||||
|
||||
from gamestonk_terminal import config_terminal as cfg
|
||||
from gamestonk_terminal.helper_funcs import get_flair, parse_known_args_and_warn
|
||||
|
||||
from gamestonk_terminal.comparison_analysis import yahoo_finance_api as yf_api
|
||||
|
||||
|
||||
def get_similar_companies(l_args, s_ticker):
|
||||
""" Get similar companies. [Source: Polygon API] """
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
prog="get",
|
||||
description="""Get similar companies to compare with.""",
|
||||
)
|
||||
|
||||
l_similar = []
|
||||
try:
|
||||
ns_parser = parse_known_args_and_warn(parser, l_args)
|
||||
if not ns_parser:
|
||||
return
|
||||
|
||||
result = requests.get(
|
||||
f"https://api.polygon.io/v1/meta/symbols/{s_ticker}/company?&apiKey={cfg.API_POLYGON_KEY}"
|
||||
)
|
||||
|
||||
if result.status_code == 200:
|
||||
l_similar = result.json()["similar"]
|
||||
|
||||
except Exception as e:
|
||||
print(e)
|
||||
|
||||
print("")
|
||||
return l_similar
|
||||
|
||||
|
||||
def select_similar_companies(l_args):
|
||||
""" Select similar companies, e.g. NIO,XPEV,LI"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
prog="select",
|
||||
description="""Select similar companies to compare with.""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-s",
|
||||
"--similar",
|
||||
dest="l_similar",
|
||||
type=lambda s: [str(item) for item in s.split(",")],
|
||||
default=[],
|
||||
help="similar companies to compare with.",
|
||||
)
|
||||
|
||||
try:
|
||||
# For the case where a user uses: 'select NIO,XPEV,LI'
|
||||
if l_args:
|
||||
if "-" not in l_args[0]:
|
||||
l_args.insert(0, "-s")
|
||||
|
||||
ns_parser = parse_known_args_and_warn(parser, l_args)
|
||||
if not ns_parser:
|
||||
return
|
||||
|
||||
print("")
|
||||
return ns_parser.l_similar
|
||||
|
||||
except Exception as e:
|
||||
print(e)
|
||||
print("")
|
||||
return []
|
||||
|
||||
|
||||
def print_comparison_analysis(s_ticker, s_start, s_interval, l_similar, b_user):
|
||||
""" Print help """
|
||||
|
||||
s_intraday = (f"Intraday {s_interval}", "Daily")[s_interval == "1440min"]
|
||||
|
||||
if s_start:
|
||||
print(f"\n{s_intraday} Stock: {s_ticker} (from {s_start.strftime('%Y-%m-%d')})")
|
||||
else:
|
||||
print(f"\n{s_intraday} Stock: {s_ticker}")
|
||||
|
||||
s_similar_source = ("Polygon API", "User")[b_user]
|
||||
|
||||
if l_similar:
|
||||
print(f"[{s_similar_source}] Similar Companies: {', '.join(l_similar)}")
|
||||
else:
|
||||
print(f"No similar companies [{s_similar_source}]")
|
||||
|
||||
print("\nComparison Analysis Mode:")
|
||||
print(" help show this comparison analysis menu again")
|
||||
print(" q quit this menu, and shows back to main menu")
|
||||
print(" quit quit to abandon program")
|
||||
print("")
|
||||
print(" get get similar companies [Polygon API]")
|
||||
print(" select select similar companies")
|
||||
print("")
|
||||
print(" historical historical data comparison")
|
||||
print(" corr correlation between similar companies")
|
||||
print("")
|
||||
return
|
||||
|
||||
|
||||
def ca_menu(df_stock, s_ticker, s_start, s_interval):
|
||||
|
||||
# Add list of arguments that the comparison analysis parser accepts
|
||||
ca_parser = argparse.ArgumentParser(prog="ca", add_help=False)
|
||||
ca_parser.add_argument(
|
||||
"cmd",
|
||||
choices=[
|
||||
"help",
|
||||
"q",
|
||||
"quit",
|
||||
"get",
|
||||
"select",
|
||||
"historical",
|
||||
"corr",
|
||||
],
|
||||
)
|
||||
|
||||
b_user = False
|
||||
l_similar = get_similar_companies([], s_ticker)
|
||||
print_comparison_analysis(s_ticker, s_start, s_interval, l_similar, b_user)
|
||||
|
||||
# Loop forever and ever
|
||||
while True:
|
||||
# Get input command from user
|
||||
as_input = input(f"{get_flair()} (ca)> ")
|
||||
|
||||
# Parse fundamental analysis command of the list of possible commands
|
||||
try:
|
||||
(ns_known_args, l_args) = ca_parser.parse_known_args(as_input.split())
|
||||
|
||||
except SystemExit:
|
||||
print("The command selected doesn't exist\n")
|
||||
continue
|
||||
|
||||
if ns_known_args.cmd == "help":
|
||||
print_comparison_analysis(s_ticker, s_start, s_interval, l_similar, b_user)
|
||||
|
||||
elif ns_known_args.cmd == "q":
|
||||
# Just leave the CA menu
|
||||
return False
|
||||
|
||||
elif ns_known_args.cmd == "quit":
|
||||
# Abandon the program
|
||||
return True
|
||||
|
||||
elif ns_known_args.cmd == "get":
|
||||
l_similar = get_similar_companies(l_args, s_ticker)
|
||||
b_user = False
|
||||
|
||||
elif ns_known_args.cmd == "select":
|
||||
l_similar = select_similar_companies(l_args)
|
||||
b_user = True
|
||||
|
||||
elif ns_known_args.cmd == "historical":
|
||||
yf_api.historical(
|
||||
l_args, df_stock, s_ticker, s_start, s_interval, l_similar
|
||||
)
|
||||
|
||||
elif ns_known_args.cmd == "corr":
|
||||
yf_api.correlation(
|
||||
l_args, df_stock, s_ticker, s_start, s_interval, l_similar
|
||||
)
|
||||
|
||||
else:
|
||||
print("Command not recognized!")
|
||||
536
gamestonk_terminal/comparison_analysis/market_watch_api.py
Normal file
536
gamestonk_terminal/comparison_analysis/market_watch_api.py
Normal file
@@ -0,0 +1,536 @@
|
||||
""" Comparison Analysis Market Watch View """
|
||||
__docformat__ = "numpy"
|
||||
|
||||
import argparse
|
||||
from typing import List, Dict, Tuple
|
||||
import requests
|
||||
import pandas as pd
|
||||
from bs4 import BeautifulSoup
|
||||
from gamestonk_terminal.helper_funcs import (
|
||||
get_user_agent,
|
||||
parse_known_args_and_warn,
|
||||
patch_pandas_text_adjustment,
|
||||
financials_colored_values,
|
||||
)
|
||||
from gamestonk_terminal import feature_flags as gtff
|
||||
|
||||
|
||||
def compare_income(other_args: List[str], ticker: str, similar: List[str]):
|
||||
"""Compare income between companies
|
||||
|
||||
Parameters
|
||||
----------
|
||||
other_args : List[str]
|
||||
Command line arguments to be processed with argparse
|
||||
ticker : str
|
||||
Main ticker to compare income
|
||||
similar : List[str]
|
||||
Similar companies to compare income with
|
||||
"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
prog="income",
|
||||
description="""
|
||||
Prints either yearly or quarterly income statement the company, and compares
|
||||
it against similar companies. [Source: Market Watch]
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-s",
|
||||
"--similar",
|
||||
dest="l_similar",
|
||||
type=lambda s: [str(item).upper() for item in s.split(",")],
|
||||
default=similar,
|
||||
help="similar companies to compare with.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-a",
|
||||
"--also",
|
||||
dest="l_also",
|
||||
type=lambda s: [str(item).upper() for item in s.split(",")],
|
||||
default=[],
|
||||
help="apart from loaded similar companies also compare with.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-q",
|
||||
"--quarter",
|
||||
action="store_true",
|
||||
default=False,
|
||||
dest="b_quarter",
|
||||
help="Quarter financial data flag.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-t",
|
||||
"--timeframe",
|
||||
dest="s_timeframe",
|
||||
type=str,
|
||||
default=None,
|
||||
help="Specify yearly/quarterly timeframe. Default is last.",
|
||||
)
|
||||
|
||||
try:
|
||||
ns_parser = parse_known_args_and_warn(parser, other_args)
|
||||
if not ns_parser:
|
||||
return
|
||||
|
||||
l_similar = ns_parser.l_similar
|
||||
l_similar += ns_parser.l_also
|
||||
|
||||
# Add main ticker to similar list of companies
|
||||
l_similar.insert(0, ticker)
|
||||
|
||||
l_timeframes, ddf_financials = prepare_comparison_financials(
|
||||
l_similar, "income", ns_parser.b_quarter
|
||||
)
|
||||
|
||||
if ns_parser.s_timeframe:
|
||||
if ns_parser.s_timeframe not in l_timeframes:
|
||||
raise ValueError(
|
||||
f"Timeframe selected should be one of {', '.join(l_timeframes)}"
|
||||
)
|
||||
s_timeframe = ns_parser.s_timeframe
|
||||
else:
|
||||
s_timeframe = l_timeframes[-1]
|
||||
|
||||
print(
|
||||
f"Other available {('yearly', 'quarterly')[ns_parser.b_quarter]} timeframes are: {', '.join(l_timeframes)}\n"
|
||||
)
|
||||
|
||||
df_financials_compared = combine_similar_financials(
|
||||
ddf_financials, l_similar, s_timeframe, ns_parser.b_quarter
|
||||
)
|
||||
|
||||
if gtff.USE_COLOR:
|
||||
df_financials_compared = df_financials_compared.applymap(
|
||||
financials_colored_values
|
||||
)
|
||||
|
||||
patch_pandas_text_adjustment()
|
||||
pd.set_option("display.max_colwidth", None)
|
||||
pd.set_option("display.max_rows", None)
|
||||
|
||||
if not ns_parser.b_quarter:
|
||||
df_financials_compared.index.name = s_timeframe
|
||||
|
||||
print(df_financials_compared.to_string())
|
||||
print("")
|
||||
|
||||
except Exception as e:
|
||||
print(e, "\n")
|
||||
return
|
||||
|
||||
|
||||
def compare_balance(other_args: List[str], ticker: str, similar: List[str]):
|
||||
"""Compare balance between companies
|
||||
|
||||
Parameters
|
||||
----------
|
||||
other_args : List[str]
|
||||
Command line arguments to be processed with argparse
|
||||
ticker : str
|
||||
Main ticker to compare income
|
||||
similar : List[str]
|
||||
Similar companies to compare income with
|
||||
"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
prog="compare_balance",
|
||||
description="""
|
||||
Prints either yearly or quarterly balance statement the company, and compares
|
||||
it against similar companies. [Source: Market Watch]
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-s",
|
||||
"--similar",
|
||||
dest="l_similar",
|
||||
type=lambda s: [str(item).upper() for item in s.split(",")],
|
||||
default=similar,
|
||||
help="similar companies to compare with.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-a",
|
||||
"--also",
|
||||
dest="l_also",
|
||||
type=lambda s: [str(item).upper() for item in s.split(",")],
|
||||
default=[],
|
||||
help="apart from loaded similar companies also compare with.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-q",
|
||||
"--quarter",
|
||||
action="store_true",
|
||||
default=False,
|
||||
dest="b_quarter",
|
||||
help="Quarter financial data flag.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-t",
|
||||
"--timeframe",
|
||||
dest="s_timeframe",
|
||||
type=str,
|
||||
default=None,
|
||||
help="Specify yearly/quarterly timeframe. Default is last.",
|
||||
)
|
||||
|
||||
try:
|
||||
ns_parser = parse_known_args_and_warn(parser, other_args)
|
||||
if not ns_parser:
|
||||
return
|
||||
|
||||
l_similar = ns_parser.l_similar
|
||||
l_similar += ns_parser.l_also
|
||||
|
||||
# Add main ticker to similar list of companies
|
||||
l_similar.insert(0, ticker)
|
||||
|
||||
l_timeframes, ddf_financials = prepare_comparison_financials(
|
||||
l_similar, "balance", ns_parser.b_quarter
|
||||
)
|
||||
|
||||
if ns_parser.s_timeframe:
|
||||
if ns_parser.s_timeframe not in l_timeframes:
|
||||
raise ValueError(
|
||||
f"Timeframe selected should be one of {', '.join(l_timeframes)}"
|
||||
)
|
||||
s_timeframe = ns_parser.s_timeframe
|
||||
else:
|
||||
s_timeframe = l_timeframes[-1]
|
||||
|
||||
print(
|
||||
f"Other available {('yearly', 'quarterly')[ns_parser.b_quarter]} timeframes are: {', '.join(l_timeframes)}\n"
|
||||
)
|
||||
|
||||
df_financials_compared = combine_similar_financials(
|
||||
ddf_financials, l_similar, s_timeframe, ns_parser.b_quarter
|
||||
)
|
||||
|
||||
if gtff.USE_COLOR:
|
||||
df_financials_compared = df_financials_compared.applymap(
|
||||
financials_colored_values
|
||||
)
|
||||
|
||||
patch_pandas_text_adjustment()
|
||||
pd.set_option("display.max_colwidth", None)
|
||||
pd.set_option("display.max_rows", None)
|
||||
|
||||
if not ns_parser.b_quarter:
|
||||
df_financials_compared.index.name = s_timeframe
|
||||
|
||||
print(df_financials_compared.to_string())
|
||||
print("")
|
||||
|
||||
except Exception as e:
|
||||
print(e, "\n")
|
||||
return
|
||||
|
||||
|
||||
def compare_cashflow(other_args: List[str], ticker: str, similar: List[str]):
|
||||
"""Compare balance between companies
|
||||
|
||||
Parameters
|
||||
----------
|
||||
other_args : List[str]
|
||||
Command line arguments to be processed with argparse
|
||||
ticker : str
|
||||
Main ticker to compare income
|
||||
similar : List[str]
|
||||
Similar companies to compare income with
|
||||
"""
|
||||
parser = argparse.ArgumentParser(
|
||||
add_help=False,
|
||||
prog="compare_cashflow",
|
||||
description="""
|
||||
Prints either yearly or quarterly cash statement the company, and compares
|
||||
it against similar companies. [Source: Market Watch]
|
||||
""",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-s",
|
||||
"--similar",
|
||||
dest="l_similar",
|
||||
type=lambda s: [str(item).upper() for item in s.split(",")],
|
||||
default=similar,
|
||||
help="similar companies to compare with.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-a",
|
||||
"--also",
|
||||
dest="l_also",
|
||||
type=lambda s: [str(item).upper() for item in s.split(",")],
|
||||
default=[],
|
||||
help="apart from loaded similar companies also compare with.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-q",
|
||||
"--quarter",
|
||||
action="store_true",
|
||||
default=False,
|
||||
dest="b_quarter",
|
||||
help="Quarter financial data flag.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-t",
|
||||
"--timeframe",
|
||||
dest="s_timeframe",
|
||||
type=str,
|
||||
default=None,
|
||||
help="Specify yearly/quarterly timeframe. Default is last.",
|
||||
)
|
||||
|
||||
try:
|
||||
ns_parser = parse_known_args_and_warn(parser, other_args)
|
||||
if not ns_parser:
|
||||
return
|
||||
|
||||
l_similar = ns_parser.l_similar
|
||||
l_similar += ns_parser.l_also
|
||||
|
||||
# Add main ticker to similar list of companies
|
||||
l_similar.insert(0, ticker)
|
||||
|
||||
l_timeframes, ddf_financials = prepare_comparison_financials(
|
||||
l_similar, "cashflow", ns_parser.b_quarter
|
||||
)
|
||||
|
||||
if ns_parser.s_timeframe:
|
||||
if ns_parser.s_timeframe not in l_timeframes:
|
||||
raise ValueError(
|
||||
f"Timeframe selected should be one of {', '.join(l_timeframes)}"
|
||||
)
|
||||
s_timeframe = ns_parser.s_timeframe
|
||||
else:
|
||||
s_timeframe = l_timeframes[-1]
|
||||
|
||||
print(
|
||||
f"Other available {('yearly', 'quarterly')[ns_parser.b_quarter]} timeframes are: {', '.join(l_timeframes)}\n"
|
||||
)
|
||||
|
||||
df_financials_compared = combine_similar_financials(
|
||||
ddf_financials, l_similar, s_timeframe, ns_parser.b_quarter
|
||||
)
|
||||
|
||||
if gtff.USE_COLOR:
|
||||
df_financials_compared = df_financials_compared.applymap(
|
||||
financials_colored_values
|
||||
)
|
||||
|
||||
patch_pandas_text_adjustment()
|
||||
pd.set_option("display.max_colwidth", None)
|
||||
pd.set_option("display.max_rows", None)
|
||||
|
||||
if not ns_parser.b_quarter:
|
||||
df_financials_compared.index.name = s_timeframe
|
||||
|
||||
print(df_financials_compared.to_string())
|
||||
print("")
|
||||
|
||||
except Exception as e:
|
||||
print(e, "\n")
|
||||
return
|
||||
|
||||
|
||||
def prepare_df_financials(
|
||||
ticker: str, statement: str, quarter: bool = False
|
||||
) -> pd.DataFrame:
|
||||
"""Builds a DataFrame with financial statements for a given company
|
||||
|
||||
Parameters
|
||||
----------
|
||||
ticker : str
|
||||
Company's stock ticker
|
||||
statement : str
|
||||
Either income, balance or cashflow
|
||||
quarter : bool, optional
|
||||
Return quarterly financial statements instead of annual, by default False
|
||||
|
||||
Returns
|
||||
-------
|
||||
pd.DataFrame
|
||||
A DataFrame with financial info
|
||||
|
||||
Raises
|
||||
------
|
||||
ValueError
|
||||
If statement is not income, balance or cashflow
|
||||
"""
|
||||
financial_urls = {
|
||||
"income": {
|
||||
"quarter": "https://www.marketwatch.com/investing/stock/{}/financials/income/quarter",
|
||||
"annual": "https://www.marketwatch.com/investing/stock/{}/financials/income",
|
||||
},
|
||||
"balance": {
|
||||
"quarter": "https://www.marketwatch.com/investing/stock/{}/financials/balance-sheet/quarter",
|
||||
"annual": "https://www.marketwatch.com/investing/stock/{}/financials/balance-sheet",
|
||||
},
|
||||
"cashflow": {
|
||||
"quarter": "https://www.marketwatch.com/investing/stock/{}/financials/cash-flow/quarter",
|
||||
"annual": "https://www.marketwatch.com/investing/stock/{}/financials/cash-flow",
|
||||
},
|
||||
}
|
||||
|
||||
if statement not in financial_urls.keys():
|
||||
raise ValueError(f"type {statement} is not in {financial_urls.keys()}")
|
||||
|
||||
if quarter:
|
||||
period = "quarter"
|
||||
else:
|
||||
period = "annual"
|
||||
|
||||
text_soup_financials = BeautifulSoup(
|
||||
requests.get(
|
||||
financial_urls[statement][period].format(ticker),
|
||||
headers={"User-Agent": get_user_agent()},
|
||||
).text,
|
||||
"lxml",
|
||||
)
|
||||
|
||||
# Define financials columns
|
||||
a_financials_header = list()
|
||||
for financials_header in text_soup_financials.findAll(
|
||||
"th", {"class": "overflow__heading"}
|
||||
):
|
||||
a_financials_header.append(financials_header.text.strip("\n").split("\n")[0])
|
||||
|
||||
s_header_end_trend = ("5-year trend", "5- qtr trend")[quarter]
|
||||
df_financials = pd.DataFrame(
|
||||
columns=a_financials_header[0 : a_financials_header.index(s_header_end_trend)]
|
||||
)
|
||||
|
||||
find_table = text_soup_financials.findAll(
|
||||
"div", {"class": "element element--table table--fixed financials"}
|
||||
)
|
||||
|
||||
if not find_table:
|
||||
return df_financials
|
||||
|
||||
financials_rows = find_table[0].findAll(
|
||||
"tr", {"class": ["table__row is-highlighted", "table__row"]}
|
||||
)
|
||||
|
||||
for a_row in financials_rows:
|
||||
constructed_row = list()
|
||||
financial_columns = a_row.findAll(
|
||||
"td", {"class": ["overflow__cell", "overflow__cell fixed--column"]}
|
||||
)
|
||||
|
||||
if not financial_columns:
|
||||
continue
|
||||
|
||||
for a_column in financial_columns:
|
||||
column_to_text = a_column.text.strip()
|
||||
if "\n" in column_to_text:
|
||||
column_to_text = column_to_text.split("\n")[0]
|
||||
|
||||
if column_to_text == "":
|
||||
continue
|
||||
constructed_row.append(column_to_text)
|
||||
|
||||
df_financials.loc[len(df_financials)] = constructed_row
|
||||
|
||||
return df_financials
|
||||
|
||||
|
||||
def prepare_comparison_financials(
|
||||
similar: List[str], statement: str, quarter: bool
|
||||
) -> Tuple[List[str], Dict[str, pd.DataFrame]]:
|
||||
"""Builds a dictionary of DataFrame with financial statements for list of tickers
|
||||
|
||||
Parameters
|
||||
----------
|
||||
similar : List[str]
|
||||
List of similar stock tickers
|
||||
statement : str
|
||||
Either income, balance or cashflow
|
||||
quarter : bool
|
||||
Return quarterly financial statements instead of annual, by default False
|
||||
|
||||
Returns
|
||||
-------
|
||||
List[str]
|
||||
List of index headers
|
||||
Dict[str, pd.DataFrame]
|
||||
A dictionary of DataFrame with financial info from list of similar tickers
|
||||
"""
|
||||
|
||||
financials = {}
|
||||
# Get financial dataframe of each company
|
||||
for symbol in similar:
|
||||
financials[symbol] = prepare_df_financials(
|
||||
symbol, statement, quarter
|
||||
).set_index("Item")
|
||||
|
||||
if quarter:
|
||||
items = financials[similar[0]].columns
|
||||
|
||||
else:
|
||||
items = []
|
||||
# Get common headers between tickers
|
||||
for symbol in similar:
|
||||
if len(financials[symbol].columns) > len(items):
|
||||
items = financials[symbol].columns
|
||||
|
||||
# Add columns with N/A when data is not available, to have similar columns
|
||||
for symbol in similar:
|
||||
if len(financials[symbol].columns) < len(items):
|
||||
for item in items:
|
||||
if item not in financials[symbol].columns:
|
||||
financials[symbol][item] = "N/A"
|
||||
financials[symbol] = financials[symbol].reindex(sorted(items), axis=1)
|
||||
|
||||
return list(items), financials
|
||||
|
||||
|
||||
def combine_similar_financials(
|
||||
financials: Dict[str, pd.DataFrame],
|
||||
similar: List[str],
|
||||
timeframe: str,
|
||||
quarter: bool,
|
||||
) -> pd.DataFrame:
|
||||
"""Builds a DataFrame with financial statements from a certain timeframe of a list of tickers
|
||||
|
||||
Parameters
|
||||
----------
|
||||
financials : Dict[str, pd.DataFrame]
|
||||
A dictionary of DataFrame with financial info from list of similar tickers
|
||||
similar : List[str]
|
||||
List of similar stock tickers
|
||||
statement : str
|
||||
Either income, balance or cashflow
|
||||
quarter : bool
|
||||
False for yearly data, True for quarterly
|
||||
Returns
|
||||
-------
|
||||
pd.DataFrame
|
||||
A DataFrame with financial statements from a certain timeframe of a list of tickers
|
||||
"""
|
||||
|
||||
# Quarter data is a bit more confusing for comparison due to the fact that
|
||||
# the reports may occur at slight different moments. Hence we rely on the
|
||||
# order set by the Market Watch website
|
||||
|
||||
if quarter:
|
||||
compare_financials = financials[similar[0]][timeframe].to_frame()
|
||||
compare_financials.rename(columns={timeframe: similar[0]}, inplace=True)
|
||||
earnings_dates = [timeframe]
|
||||
idx = len(financials[similar[0]].columns) - list(
|
||||
financials[similar[0]].columns
|
||||
).index(timeframe)
|
||||
|
||||
for symbol in similar[1:]:
|
||||
report_quarter_date = list(financials[symbol].columns)[-idx]
|
||||
earnings_dates.append(report_quarter_date)
|
||||
compare_financials[symbol] = financials[symbol][report_quarter_date]
|
||||
|
||||
compare_financials.columns = pd.MultiIndex.from_tuples(
|
||||
zip(earnings_dates, compare_financials.columns),
|
||||
)
|
||||
|
||||
else:
|
||||
compare_financials = financials[similar[0]][timeframe].to_frame()
|
||||
compare_financials.rename(columns={timeframe: similar[0]}, inplace=True)
|
||||
|
||||
for symbol in similar[1:]:
|
||||
compare_financials[symbol] = financials[symbol][timeframe]
|
||||
|
||||
return compare_financials
|
||||
@@ -108,9 +108,10 @@ def historical(l_args, df_stock, s_ticker, s_start, s_interval, similar):
|
||||
plt.show()
|
||||
print("")
|
||||
|
||||
except SystemExit:
|
||||
print("Similar companies need to be provided", "\n")
|
||||
except Exception as e:
|
||||
print(e)
|
||||
print("")
|
||||
print(e, "\n")
|
||||
|
||||
|
||||
def correlation(l_args, df_stock, s_ticker, s_start, s_interval, similar):
|
||||
@@ -209,6 +210,7 @@ def correlation(l_args, df_stock, s_ticker, s_start, s_interval, similar):
|
||||
|
||||
print("")
|
||||
|
||||
except SystemExit:
|
||||
print("Similar companies need to be provided", "\n")
|
||||
except Exception as e:
|
||||
print(e)
|
||||
print("")
|
||||
print(e, "\n")
|
||||
|
||||
@@ -1,9 +1,16 @@
|
||||
from distutils.util import strtobool
|
||||
import os
|
||||
|
||||
# Use coloring features
|
||||
USE_COLOR = strtobool(os.getenv("GTFF_USE_COLOR", "True"))
|
||||
|
||||
# Select console flair (choose from config_terminal.py list)
|
||||
USE_FLAIR = os.getenv("GTFF_USE_FLAIR") or "stars"
|
||||
|
||||
# Enable interactive matplotlib mode
|
||||
USE_ION = strtobool(os.getenv("GTFF_USE_ION", "True"))
|
||||
|
||||
# Enable Prompt Toolkit
|
||||
USE_PROMPT_TOOLKIT = strtobool(os.getenv("GTFF_USE_PROMPT_TOOLKIT", "False"))
|
||||
|
||||
# Enable Prediction features
|
||||
@@ -11,3 +18,6 @@ ENABLE_PREDICT = strtobool(os.getenv("GTFF_ENABLE_PREDICT", "False"))
|
||||
|
||||
# Enable plot autoscaling
|
||||
USE_PLOT_AUTOSCALING = strtobool(os.getenv("GTFF_USE_PLOT_AUTOSCALING", "False"))
|
||||
|
||||
# Enable thoughts of the day
|
||||
ENABLE_THOUGHTS_DAY = strtobool(os.getenv("GTFF_ENABLE_THOUGHTS_DAY", "False"))
|
||||
|
||||
@@ -293,7 +293,9 @@ def parse_known_args_and_warn(parser, l_args):
|
||||
|
||||
|
||||
def financials_colored_values(val: str) -> str:
|
||||
if sum(c.isalpha() for c in val) < 2:
|
||||
if val == "N/A" or str(val) == "nan":
|
||||
val = f"{Fore.YELLOW}N/A{Style.RESET_ALL}"
|
||||
elif sum(c.isalpha() for c in val) < 2:
|
||||
if "%" in val:
|
||||
if "-" in val:
|
||||
val = f"{Fore.RED}{val}{Style.RESET_ALL}"
|
||||
@@ -301,6 +303,7 @@ def financials_colored_values(val: str) -> str:
|
||||
val = f"{Fore.GREEN}{val}{Style.RESET_ALL}"
|
||||
elif "(" in val:
|
||||
val = f"{Fore.RED}{val}{Style.RESET_ALL}"
|
||||
|
||||
return val
|
||||
|
||||
|
||||
|
||||
@@ -157,7 +157,7 @@ def load(l_args, s_ticker, s_start, s_interval, df_stock):
|
||||
return [s_ticker, s_start, s_interval, df_stock]
|
||||
|
||||
# Update values:
|
||||
s_ticker = ns_parser.s_ticker
|
||||
s_ticker = ns_parser.s_ticker.upper()
|
||||
s_start = ns_parser.s_start_date
|
||||
s_interval = str(ns_parser.n_interval) + "min"
|
||||
|
||||
@@ -278,6 +278,7 @@ def candle(s_ticker: str, s_start: str):
|
||||
candle_linewidth=1.0, candle_width=0.8, volume_linewidth=1.0
|
||||
),
|
||||
)
|
||||
print("")
|
||||
|
||||
|
||||
def view(l_args, s_ticker, s_start, s_interval, df_stock):
|
||||
|
||||
@@ -322,6 +322,42 @@
|
||||
"edh.draw_graph(\"XLF\", cache_dir, line_type=\"line\", draw_mas=(20,50,200), draw_volume=True, time_delta=360, low_trend=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "blistering-barnacles",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Materials - 2 year trend with 20, 50 and 200 day SMA"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "italian-portent",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"edh.draw_graph(\"XLB\", cache_dir, line_type=\"line\", draw_mas=(20,50,200), draw_volume=True, time_delta=720, low_trend=False)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "material-science",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Materials - 1 year trend with 20, 50 and 200 day SMA"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "bundle-enabler",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"edh.draw_graph(\"XLB\", cache_dir, line_type=\"line\", draw_mas=(20,50,200), draw_volume=True, time_delta=360, low_trend=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
|
||||
492
poetry.lock
generated
492
poetry.lock
generated
@@ -31,7 +31,7 @@ speedups = ["aiodns", "brotlipy", "cchardet"]
|
||||
|
||||
[[package]]
|
||||
name = "alpaca-trade-api"
|
||||
version = "1.0.1"
|
||||
version = "1.1.0"
|
||||
description = "Alpaca API python client"
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -102,6 +102,19 @@ dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest", "sphinx", "wheel", "p
|
||||
docs = ["sphinx"]
|
||||
tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"]
|
||||
|
||||
[[package]]
|
||||
name = "astroid"
|
||||
version = "2.5.1"
|
||||
description = "An abstract syntax tree for Python with inference support."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
lazy-object-proxy = ">=1.4.0"
|
||||
typed-ast = {version = ">=1.4.0,<1.5", markers = "implementation_name == \"cpython\" and python_version < \"3.8\""}
|
||||
wrapt = ">=1.11,<1.13"
|
||||
|
||||
[[package]]
|
||||
name = "astunparse"
|
||||
version = "1.6.3"
|
||||
@@ -313,14 +326,14 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||
|
||||
[[package]]
|
||||
name = "convertdate"
|
||||
version = "2.3.1"
|
||||
version = "2.3.2"
|
||||
description = "Converts between Gregorian dates and other calendar systems.Calendars included: Baha'i, French Republican, Hebrew, Indian Civil, Islamic, ISO, Julian, Mayan and Persian."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.5"
|
||||
|
||||
[package.dependencies]
|
||||
pymeeus = ">=0.3.6,<0.3.8 || >0.3.8,<=1"
|
||||
pymeeus = ">=0.3.13,<=1"
|
||||
pytz = ">=2014.10"
|
||||
|
||||
[package.extras]
|
||||
@@ -367,7 +380,7 @@ six = "*"
|
||||
|
||||
[[package]]
|
||||
name = "cython"
|
||||
version = "0.29.14"
|
||||
version = "0.29.17"
|
||||
description = "The Cython compiler for writing C extensions for the Python language."
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -399,7 +412,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||
|
||||
[[package]]
|
||||
name = "deprecated"
|
||||
version = "1.2.11"
|
||||
version = "1.2.12"
|
||||
description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
|
||||
category = "main"
|
||||
optional = true
|
||||
@@ -504,6 +517,20 @@ torch = ">=1.1.0"
|
||||
tqdm = ">=4.26.0"
|
||||
transformers = ">=3.5.0,<=3.5.1"
|
||||
|
||||
[[package]]
|
||||
name = "flake8"
|
||||
version = "3.9.0"
|
||||
description = "the modular source code checker: pep8 pyflakes and co"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
|
||||
|
||||
[package.dependencies]
|
||||
importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
|
||||
mccabe = ">=0.6.0,<0.7.0"
|
||||
pycodestyle = ">=2.7.0,<2.8.0"
|
||||
pyflakes = ">=2.3.0,<2.4.0"
|
||||
|
||||
[[package]]
|
||||
name = "flatbuffers"
|
||||
version = "1.12"
|
||||
@@ -574,28 +601,27 @@ tqdm = "*"
|
||||
|
||||
[[package]]
|
||||
name = "gensim"
|
||||
version = "3.8.3"
|
||||
version = "3.8.2"
|
||||
description = "Python framework for fast Vector Space Modelling"
|
||||
category = "main"
|
||||
optional = true
|
||||
python-versions = "*"
|
||||
|
||||
[package.dependencies]
|
||||
Cython = "0.29.14"
|
||||
numpy = ">=1.11.3"
|
||||
scipy = ">=0.18.1"
|
||||
scipy = ">=1.0.0"
|
||||
six = ">=1.5.0"
|
||||
smart-open = ">=1.8.1"
|
||||
|
||||
[package.extras]
|
||||
distributed = ["Pyro4 (>=4.27)"]
|
||||
docs = ["pytest", "pytest-rerunfailures", "mock", "cython", "nmslib", "pyemd", "testfixtures", "Morfessor (==2.0.2a4)", "python-Levenshtein (>=0.10.2)", "visdom (>0.1.8.7)", "scikit-learn", "Pyro4 (>=4.27)", "sphinx (<=2.4.4)", "sphinx-gallery", "sphinxcontrib.programoutput", "sphinxcontrib-napoleon", "matplotlib", "plotly", "memory-profiler", "annoy", "pyro4", "nltk", "statsmodels", "pandas"]
|
||||
test = ["pytest", "pytest-rerunfailures", "mock", "cython", "nmslib", "pyemd", "testfixtures", "Morfessor (==2.0.2a4)", "python-Levenshtein (>=0.10.2)", "visdom (>0.1.8.7)", "scikit-learn"]
|
||||
test-win = ["pytest", "pytest-rerunfailures", "mock", "cython", "nmslib", "pyemd", "testfixtures", "Morfessor (==2.0.2a4)", "python-Levenshtein (>=0.10.2)", "visdom (>0.1.8.7)", "scikit-learn"]
|
||||
docs = ["pytest", "pytest-rerunfailures", "mock", "cython", "testfixtures", "Morfessor (==2.0.2a4)", "python-Levenshtein (>=0.10.2)", "visdom (>0.1.8.7)", "scikit-learn", "Pyro4 (>=4.27)", "sphinx", "sphinxcontrib-napoleon", "plotly", "pattern (<=2.6)", "sphinxcontrib.programoutput"]
|
||||
test = ["pytest", "pytest-rerunfailures", "mock", "cython", "testfixtures", "Morfessor (==2.0.2a4)", "python-Levenshtein (>=0.10.2)", "visdom (>0.1.8.7)", "scikit-learn"]
|
||||
test-win = ["pytest", "pytest-rerunfailures", "mock", "cython", "testfixtures", "Morfessor (==2.0.2a4)", "python-Levenshtein (>=0.10.2)", "visdom (>0.1.8.7)", "scikit-learn"]
|
||||
|
||||
[[package]]
|
||||
name = "google-auth"
|
||||
version = "1.27.1"
|
||||
version = "1.28.0"
|
||||
description = "Google Authentication Library"
|
||||
category = "main"
|
||||
optional = true
|
||||
@@ -656,7 +682,7 @@ name = "h5py"
|
||||
version = "2.10.0"
|
||||
description = "Read and write HDF5 files from Python"
|
||||
category = "main"
|
||||
optional = true
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[package.dependencies]
|
||||
@@ -730,7 +756,7 @@ idna = ">=2.0"
|
||||
|
||||
[[package]]
|
||||
name = "importlib-metadata"
|
||||
version = "3.7.2"
|
||||
version = "3.7.3"
|
||||
description = "Read metadata from Python packages"
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -844,6 +870,19 @@ category = "main"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "isort"
|
||||
version = "5.7.0"
|
||||
description = "A Python utility / library to sort Python imports."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.6,<4.0"
|
||||
|
||||
[package.extras]
|
||||
pipfile_deprecated_finder = ["pipreqs", "requirementslib"]
|
||||
requirements_deprecated_finder = ["pipreqs", "pip-api"]
|
||||
colors = ["colorama (>=0.4.3,<0.5.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "janome"
|
||||
version = "0.4.1"
|
||||
@@ -925,7 +964,7 @@ qtconsole = "*"
|
||||
|
||||
[[package]]
|
||||
name = "jupyter-client"
|
||||
version = "6.1.11"
|
||||
version = "6.1.12"
|
||||
description = "Jupyter protocol implementation and client libraries"
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -940,11 +979,11 @@ traitlets = "*"
|
||||
|
||||
[package.extras]
|
||||
doc = ["sphinx (>=1.3.6)", "sphinx-rtd-theme", "sphinxcontrib-github-alt"]
|
||||
test = ["jedi (<=0.17.2)", "ipykernel", "ipython", "mock", "pytest", "pytest-asyncio", "async-generator", "pytest-timeout"]
|
||||
test = ["async-generator", "ipykernel", "ipython", "mock", "pytest-asyncio", "pytest-timeout", "pytest", "jedi (<0.18)"]
|
||||
|
||||
[[package]]
|
||||
name = "jupyter-console"
|
||||
version = "6.2.0"
|
||||
version = "6.3.0"
|
||||
description = "Jupyter terminal console"
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -1062,6 +1101,14 @@ python-versions = "*"
|
||||
[package.dependencies]
|
||||
six = "*"
|
||||
|
||||
[[package]]
|
||||
name = "lazy-object-proxy"
|
||||
version = "1.5.2"
|
||||
description = "A fast and thorough lazy object proxy."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
|
||||
|
||||
[[package]]
|
||||
name = "lunarcalendar"
|
||||
version = "0.0.9"
|
||||
@@ -1127,6 +1174,14 @@ pillow = ">=6.2.0"
|
||||
pyparsing = ">=2.0.3,<2.0.4 || >2.0.4,<2.1.2 || >2.1.2,<2.1.6 || >2.1.6"
|
||||
python-dateutil = ">=2.1"
|
||||
|
||||
[[package]]
|
||||
name = "mccabe"
|
||||
version = "0.6.1"
|
||||
description = "McCabe checker, plugin for flake8"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "mistune"
|
||||
version = "0.8.4"
|
||||
@@ -1153,7 +1208,7 @@ python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "mplfinance"
|
||||
version = "0.12.7a7"
|
||||
version = "0.12.7a10"
|
||||
description = "Utilities for the visualization, and visual analysis, of financial data"
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -1682,6 +1737,14 @@ python-versions = "*"
|
||||
[package.dependencies]
|
||||
pyasn1 = ">=0.4.6,<0.5.0"
|
||||
|
||||
[[package]]
|
||||
name = "pycodestyle"
|
||||
version = "2.7.0"
|
||||
description = "Python style guide checker"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
|
||||
|
||||
[[package]]
|
||||
name = "pycparser"
|
||||
version = "2.20"
|
||||
@@ -1690,6 +1753,14 @@ category = "main"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
|
||||
|
||||
[[package]]
|
||||
name = "pyflakes"
|
||||
version = "2.3.0"
|
||||
description = "passive checker of Python programs"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
|
||||
|
||||
[[package]]
|
||||
name = "pygments"
|
||||
version = "2.8.1"
|
||||
@@ -1698,9 +1769,27 @@ category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.5"
|
||||
|
||||
[[package]]
|
||||
name = "pylint"
|
||||
version = "2.7.2"
|
||||
description = "python code static checker"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = "~=3.6"
|
||||
|
||||
[package.dependencies]
|
||||
astroid = ">=2.5.1,<2.6"
|
||||
colorama = {version = "*", markers = "sys_platform == \"win32\""}
|
||||
isort = ">=4.2.5,<6"
|
||||
mccabe = ">=0.6,<0.7"
|
||||
toml = ">=0.7.1"
|
||||
|
||||
[package.extras]
|
||||
docs = ["sphinx (==3.5.1)", "python-docs-theme (==2020.12)"]
|
||||
|
||||
[[package]]
|
||||
name = "pymeeus"
|
||||
version = "0.5.9"
|
||||
version = "0.5.11"
|
||||
description = "Python implementation of Jean Meeus astronomical routines"
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -1743,11 +1832,14 @@ python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
|
||||
|
||||
[[package]]
|
||||
name = "pyrsistent"
|
||||
version = "0.17.3"
|
||||
version = "0.14.11"
|
||||
description = "Persistent/Functional/Immutable data structures"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=3.5"
|
||||
python-versions = "*"
|
||||
|
||||
[package.dependencies]
|
||||
six = "*"
|
||||
|
||||
[[package]]
|
||||
name = "pysocks"
|
||||
@@ -1872,7 +1964,7 @@ py = {version = "*", markers = "implementation_name == \"pypy\""}
|
||||
|
||||
[[package]]
|
||||
name = "qtconsole"
|
||||
version = "5.0.2"
|
||||
version = "5.0.3"
|
||||
description = "Jupyter Qt console"
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -1919,11 +2011,11 @@ six = "*"
|
||||
|
||||
[[package]]
|
||||
name = "rapidfuzz"
|
||||
version = "1.2.1"
|
||||
version = "1.3.0"
|
||||
description = "rapid fuzzy string matching"
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=2.7"
|
||||
python-versions = ">=3.5"
|
||||
|
||||
[[package]]
|
||||
name = "regex"
|
||||
@@ -2138,7 +2230,7 @@ webhdfs = ["requests"]
|
||||
|
||||
[[package]]
|
||||
name = "soupsieve"
|
||||
version = "2.2"
|
||||
version = "2.2.1"
|
||||
description = "A modern CSS selector implementation for Beautiful Soup."
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -2270,7 +2362,7 @@ python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
name = "terminado"
|
||||
version = "0.9.2"
|
||||
version = "0.9.3"
|
||||
description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
|
||||
category = "main"
|
||||
optional = false
|
||||
@@ -2468,16 +2560,16 @@ test = ["pytest (>=2.7.3)"]
|
||||
|
||||
[[package]]
|
||||
name = "urllib3"
|
||||
version = "1.26.3"
|
||||
version = "1.26.4"
|
||||
description = "HTTP library with thread-safe connection pooling, file post, and more."
|
||||
category = "main"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <4"
|
||||
|
||||
[package.extras]
|
||||
brotli = ["brotlipy (>=0.6.0)"]
|
||||
secure = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "certifi", "ipaddress"]
|
||||
socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
|
||||
brotli = ["brotlipy (>=0.6.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "user-agent"
|
||||
@@ -2553,7 +2645,7 @@ name = "wrapt"
|
||||
version = "1.12.1"
|
||||
description = "Module for decorators, wrappers and monkey patching."
|
||||
category = "main"
|
||||
optional = true
|
||||
optional = false
|
||||
python-versions = "*"
|
||||
|
||||
[[package]]
|
||||
@@ -2602,7 +2694,7 @@ prediction = ["fbprophet", "tensorflow", "pmdarima", "transformers", "flair", "t
|
||||
[metadata]
|
||||
lock-version = "1.1"
|
||||
python-versions = "^3.6.8"
|
||||
content-hash = "41505466aeea6223816cb2662cdc1db82d173bb049ef57894f0c4cdcab689519"
|
||||
content-hash = "6050ce94f3ec0988ef02b85642d7c33af3eb4622130bb303c3d44dbb471be5cb"
|
||||
|
||||
[metadata.files]
|
||||
absl-py = [
|
||||
@@ -2649,8 +2741,8 @@ aiohttp = [
|
||||
{file = "aiohttp-3.7.4.post0.tar.gz", hash = "sha256:493d3299ebe5f5a7c66b9819eacdcfbbaaf1a8e84911ddffcdc48888497afecf"},
|
||||
]
|
||||
alpaca-trade-api = [
|
||||
{file = "alpaca-trade-api-1.0.1.tar.gz", hash = "sha256:a2f321bda3db55f4cc1fece1075e642322de0220302b6a00a925a0bd08f250a0"},
|
||||
{file = "alpaca_trade_api-1.0.1-py3-none-any.whl", hash = "sha256:96938eee02fe620f2bb0d7a45df910174658953b456271e9ac835fd70d4997cc"},
|
||||
{file = "alpaca-trade-api-1.1.0.tar.gz", hash = "sha256:751e06db061cf69aeaf6e21e7cce1baee652cc222a4c00c9f3c2074f7711f757"},
|
||||
{file = "alpaca_trade_api-1.1.0-py3-none-any.whl", hash = "sha256:098cde3d3ce70a000c643131e6750f372184db79998e91bf9c5ed787a0da3b13"},
|
||||
]
|
||||
alpha-vantage = [
|
||||
{file = "alpha_vantage-2.3.1-py3-none-any.whl", hash = "sha256:5d05355febe6f0fafc4bd11dc6ce3504a02d9d3c105d60202539855c0f608661"},
|
||||
@@ -2688,6 +2780,10 @@ argon2-cffi = [
|
||||
{file = "argon2_cffi-20.1.0-cp39-cp39-win32.whl", hash = "sha256:e2db6e85c057c16d0bd3b4d2b04f270a7467c147381e8fd73cbbe5bc719832be"},
|
||||
{file = "argon2_cffi-20.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:8a84934bd818e14a17943de8099d41160da4a336bcc699bb4c394bbb9b94bd32"},
|
||||
]
|
||||
astroid = [
|
||||
{file = "astroid-2.5.1-py3-none-any.whl", hash = "sha256:21d735aab248253531bb0f1e1e6d068f0ee23533e18ae8a6171ff892b98297cf"},
|
||||
{file = "astroid-2.5.1.tar.gz", hash = "sha256:cfc35498ee64017be059ceffab0a25bedf7548ab76f2bea691c5565896e7128d"},
|
||||
]
|
||||
astunparse = [
|
||||
{file = "astunparse-1.6.3-py2.py3-none-any.whl", hash = "sha256:c2652417f2c8b5bb325c885ae329bdf3f86424075c4fd1a128674bc6fba4b8e8"},
|
||||
{file = "astunparse-1.6.3.tar.gz", hash = "sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872"},
|
||||
@@ -2799,8 +2895,8 @@ colorama = [
|
||||
{file = "colorama-0.4.4.tar.gz", hash = "sha256:5941b2b48a20143d2267e95b1c2a7603ce057ee39fd88e7329b0c292aa16869b"},
|
||||
]
|
||||
convertdate = [
|
||||
{file = "convertdate-2.3.1-py3-none-any.whl", hash = "sha256:ede4b0bfbef002de8e31b9d8c03dc619a210915ce453e7a4826ac8808110fcff"},
|
||||
{file = "convertdate-2.3.1.tar.gz", hash = "sha256:4eabe5cab9f7890c6bddab2133502de9d116ad81f2fcf16c4858fef2b737e328"},
|
||||
{file = "convertdate-2.3.2-py3-none-any.whl", hash = "sha256:8f5e9efc2b71410d33217012c0a215f83463f765c94d5883bf656ce7a962b888"},
|
||||
{file = "convertdate-2.3.2.tar.gz", hash = "sha256:57df962a6047534f1452c390ad48e3dc5c83052ad83ad6dd78d60ae22f99214c"},
|
||||
]
|
||||
cryptography = [
|
||||
{file = "cryptography-3.4.6-cp36-abi3-macosx_10_10_x86_64.whl", hash = "sha256:57ad77d32917bc55299b16d3b996ffa42a1c73c6cfa829b14043c561288d2799"},
|
||||
@@ -2825,38 +2921,39 @@ cycler = [
|
||||
{file = "cycler-0.10.0.tar.gz", hash = "sha256:cd7b2d1018258d7247a71425e9f26463dfb444d411c39569972f4ce586b0c9d8"},
|
||||
]
|
||||
cython = [
|
||||
{file = "Cython-0.29.14-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", hash = "sha256:47e5e1502d52ef03387cf9d3b3241007961a84a466e58a3b74028e1dd4957f8c"},
|
||||
{file = "Cython-0.29.14-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:1dcdaa319558eb924294a554dcf6c12383ec947acc7e779e8d3622409a7f7d28"},
|
||||
{file = "Cython-0.29.14-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:7bc18fc5a170f2c1cef5387a3d997c28942918bbee0f700e73fd2178ee8d474d"},
|
||||
{file = "Cython-0.29.14-cp27-cp27m-win32.whl", hash = "sha256:89458b49976b1dee5d89ab4ac943da3717b4292bf624367e862e4ee172fcce99"},
|
||||
{file = "Cython-0.29.14-cp27-cp27m-win_amd64.whl", hash = "sha256:c0b24bfe3431b3cb7ced323bca813dbd13aca973a1475b512d3331fd0de8ec60"},
|
||||
{file = "Cython-0.29.14-cp27-cp27mu-manylinux1_i686.whl", hash = "sha256:7f89eff20e4a7a64b55210dac17aea711ed8a3f2e78f2ff784c0e984302583dd"},
|
||||
{file = "Cython-0.29.14-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:6c53338c1811f8c6d7f8cb7abd874810b15045e719e8207f957035c9177b4213"},
|
||||
{file = "Cython-0.29.14-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", hash = "sha256:521340844cf388d109ceb61397f3fd5250ccb622a1a8e93559e8de76c80940a9"},
|
||||
{file = "Cython-0.29.14-cp34-cp34m-manylinux1_i686.whl", hash = "sha256:75c2dda47dcc3c77449712b1417bb6b89ec3b7b02e18c64262494dceffdf455e"},
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{file = "gensim-3.8.3-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:a8807ebf324dd11e1298a91a92d6e57c7bdabb91d0d5240bf1efa0c0eacd86f0"},
|
||||
{file = "gensim-3.8.3-cp38-cp38-win32.whl", hash = "sha256:90115d12ee545c21cc75521ef1bb3dd66aae8a378e9c2eb029c9f22df173c125"},
|
||||
{file = "gensim-3.8.3-cp38-cp38-win_amd64.whl", hash = "sha256:4e34cf2e50f3eab3e303da46089ea4972567bf216e28f7535ada155770784ac8"},
|
||||
{file = "gensim-3.8.3.tar.gz", hash = "sha256:786adb0571f75114e9c5f7a31dd2e6eb39a9791f22c8757621545e2ded3ea367"},
|
||||
{file = "gensim-3.8.2-cp35-cp35m-macosx_10_7_intel.whl", hash = "sha256:ae3b493154073d059242fd4929cec050db77995b34621d3c9c7a622689cae341"},
|
||||
{file = "gensim-3.8.2-cp35-cp35m-manylinux1_i686.whl", hash = "sha256:9d4407d0d866afa97c8a2c9d04ad0a6b996fe02f1f96144c0f929608bcdbff78"},
|
||||
{file = "gensim-3.8.2-cp35-cp35m-manylinux1_x86_64.whl", hash = "sha256:27806c022289a76dbce29cd0e00090abb4a0ae117ff714ca0b963bd13de52d5b"},
|
||||
{file = "gensim-3.8.2-cp35-cp35m-win32.whl", hash = "sha256:3d1c1a94688c4b6107a261b0af0f43f13edef7263716348ffff790d207f4a629"},
|
||||
{file = "gensim-3.8.2-cp35-cp35m-win_amd64.whl", hash = "sha256:446476a017105a549a0eafba6e8ebb50d973775f1cf7fc1d23ba04e2c5056be4"},
|
||||
{file = "gensim-3.8.2-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:1da1daed1d405c38541f4830981385fc4ae9ccb05cf01d4f49e184c4c0ccfe85"},
|
||||
{file = "gensim-3.8.2-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:806ea08d463931f4e44b2380bedf16325562bb047615de0e4bb95216074315d9"},
|
||||
{file = "gensim-3.8.2-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:c32506dd2d112ef33721e862009f0d7aa1d83a9d8f006faedc532a4fa4c201fa"},
|
||||
{file = "gensim-3.8.2-cp36-cp36m-win32.whl", hash = "sha256:5be9320d09babf386909be1c799ebcef5fc3b8d1ba595635768e83bd753cbb52"},
|
||||
{file = "gensim-3.8.2-cp36-cp36m-win_amd64.whl", hash = "sha256:0254577e162ae7fc99b7d47cdad121e2b120cb06fb4fdf88c2c7c67b0ac2af89"},
|
||||
{file = "gensim-3.8.2-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:b0d0c4750adeb169744e5e6b60eb3425bc47b2e19ca77ae2aeae26ca03d6c6c8"},
|
||||
{file = "gensim-3.8.2-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:77bfbc0a424611f50d87e38ee92c514870f4a9eb2eb92efd9478d66f14a3dacc"},
|
||||
{file = "gensim-3.8.2-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:7ddac73e8ad42f4522fb12a3b3c85192e28c67bb54dbc36ba7d53be8a7f8fed5"},
|
||||
{file = "gensim-3.8.2-cp37-cp37m-win32.whl", hash = "sha256:c8ae97aac860c57ffa444425a76566e1cf1d120daa2b3af6a748c2fe9edf48a5"},
|
||||
{file = "gensim-3.8.2-cp37-cp37m-win_amd64.whl", hash = "sha256:5a7227c03a9ab48d80e306104a295f518e4049f21e29a51f41702bda247d5478"},
|
||||
{file = "gensim-3.8.2.tar.gz", hash = "sha256:46e3065e82e11d2c50c682aa17729292734a8388cb7301f0e3204052d2df2ff5"},
|
||||
{file = "gensim-3.8.2.win-amd64-py3.5.exe", hash = "sha256:48c6653dcc1a168209108d7658cae3b9b8aa05b212252bb5a696d6ba9b1da09c"},
|
||||
{file = "gensim-3.8.2.win-amd64-py3.6.exe", hash = "sha256:db22e1f6bfd093dc8c143e75ce4eb21a5c96568822d2447d952ae65c5be8240b"},
|
||||
{file = "gensim-3.8.2.win-amd64-py3.7.exe", hash = "sha256:5a114d3c1339255496c0be7b20fa0b5740fb2ccde0b56f4631e48fefe4be7c06"},
|
||||
{file = "gensim-3.8.2.win32-py3.5.exe", hash = "sha256:8a96813bab1043544c8d20806663c649195dcf13270ed6f336748ceb4ab90bd6"},
|
||||
{file = "gensim-3.8.2.win32-py3.6.exe", hash = "sha256:a9f0a27126126e466db0faccfe506559d50d0346c12d4b4d8d796d60bb8776a8"},
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||||
{file = "gensim-3.8.2.win32-py3.7.exe", hash = "sha256:3234cbd52c0a4d548f385393040277fab03593358fee5673533e7ee6ed2f406c"},
|
||||
]
|
||||
google-auth = [
|
||||
{file = "google-auth-1.27.1.tar.gz", hash = "sha256:d8958af6968e4ecd599f82357ebcfeb126f826ed0656126ad68416f810f7531e"},
|
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{file = "google_auth-1.27.1-py2.py3-none-any.whl", hash = "sha256:63a5636d7eacfe6ef5b7e36e112b3149fa1c5b5ad77dd6df54910459bcd6b89f"},
|
||||
{file = "google-auth-1.28.0.tar.gz", hash = "sha256:9bd436d19ab047001a1340720d2b629eb96dd503258c524921ec2af3ee88a80e"},
|
||||
{file = "google_auth-1.28.0-py2.py3-none-any.whl", hash = "sha256:dcaba3aa9d4e0e96fd945bf25a86b6f878fcb05770b67adbeb50a63ca4d28a5e"},
|
||||
]
|
||||
google-auth-oauthlib = [
|
||||
{file = "google-auth-oauthlib-0.4.3.tar.gz", hash = "sha256:54431535309cfab50897d9c181e8c2226268825aa6e42e930b05b99c5041a18c"},
|
||||
@@ -3081,8 +3176,8 @@ idna-ssl = [
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||||
{file = "idna-ssl-1.1.0.tar.gz", hash = "sha256:a933e3bb13da54383f9e8f35dc4f9cb9eb9b3b78c6b36f311254d6d0d92c6c7c"},
|
||||
]
|
||||
importlib-metadata = [
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||||
{file = "importlib_metadata-3.7.2-py3-none-any.whl", hash = "sha256:407d13f55dc6f2a844e62325d18ad7019a436c4bfcaee34cda35f2be6e7c3e34"},
|
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{file = "importlib_metadata-3.7.2.tar.gz", hash = "sha256:18d5ff601069f98d5d605b6a4b50c18a34811d655c55548adc833e687289acde"},
|
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{file = "importlib_metadata-3.7.3-py3-none-any.whl", hash = "sha256:b74159469b464a99cb8cc3e21973e4d96e05d3024d337313fedb618a6e86e6f4"},
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{file = "importlib_metadata-3.7.3.tar.gz", hash = "sha256:742add720a20d0467df2f444ae41704000f50e1234f46174b51f9c6031a1bd71"},
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]
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inflection = [
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{file = "inflection-0.5.1-py2.py3-none-any.whl", hash = "sha256:f38b2b640938a4f35ade69ac3d053042959b62a0f1076a5bbaa1b9526605a8a2"},
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@@ -3112,6 +3207,10 @@ iso8601 = [
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{file = "iso8601-0.1.14-py2.py3-none-any.whl", hash = "sha256:e7e1122f064d626e17d47cd5106bed2c620cb38fe464999e0ddae2b6d2de6004"},
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{file = "iso8601-0.1.14.tar.gz", hash = "sha256:8aafd56fa0290496c5edbb13c311f78fa3a241f0853540da09d9363eae3ebd79"},
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||||
]
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isort = [
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{file = "isort-5.7.0-py3-none-any.whl", hash = "sha256:fff4f0c04e1825522ce6949973e83110a6e907750cd92d128b0d14aaaadbffdc"},
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{file = "isort-5.7.0.tar.gz", hash = "sha256:c729845434366216d320e936b8ad6f9d681aab72dc7cbc2d51bedc3582f3ad1e"},
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||||
]
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||||
janome = [
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{file = "Janome-0.4.1-py2.py3-none-any.whl", hash = "sha256:a650e2684e80af72f869eff17566f31dd4444f5443c4771dca1ada60cea5c251"},
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{file = "Janome-0.4.1.tar.gz", hash = "sha256:6c2c38d894014d57cb3151265c11146506ead3b3bc290898adc33711711612de"},
|
||||
@@ -3138,12 +3237,12 @@ jupyter = [
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||||
{file = "jupyter-1.0.0.zip", hash = "sha256:3e1f86076bbb7c8c207829390305a2b1fe836d471ed54be66a3b8c41e7f46cc7"},
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]
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jupyter-client = [
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||||
{file = "jupyter_client-6.1.11-py3-none-any.whl", hash = "sha256:5eaaa41df449167ebba5e1cf6ca9b31f7fd4f71625069836e2e4fee07fe3cb13"},
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{file = "jupyter_client-6.1.11.tar.gz", hash = "sha256:649ca3aca1e28f27d73ef15868a7c7f10d6e70f761514582accec3ca6bb13085"},
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{file = "jupyter_client-6.1.12-py3-none-any.whl", hash = "sha256:e053a2c44b6fa597feebe2b3ecb5eea3e03d1d91cc94351a52931ee1426aecfc"},
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{file = "jupyter_client-6.1.12.tar.gz", hash = "sha256:c4bca1d0846186ca8be97f4d2fa6d2bae889cce4892a167ffa1ba6bd1f73e782"},
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]
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||||
jupyter-console = [
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||||
{file = "jupyter_console-6.2.0-py3-none-any.whl", hash = "sha256:1d80c06b2d85bfb10bd5cc731b3db18e9023bc81ab00491d3ac31f206490aee3"},
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{file = "jupyter_console-6.2.0.tar.gz", hash = "sha256:7f6194f4f4692d292da3f501c7f343ccd5e36c6a1becf7b7515e23e66d6bf1e9"},
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{file = "jupyter_console-6.3.0-py3-none-any.whl", hash = "sha256:092283ba2c9b5ceb53f32d95891ecc59ed4bfeb69e36fe017db176213daa5b0e"},
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{file = "jupyter_console-6.3.0.tar.gz", hash = "sha256:947f66bbdeee2221b4fb3a6b78225d337b8f10832f14cecf7932183635abe1d9"},
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]
|
||||
jupyter-core = [
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||||
{file = "jupyter_core-4.7.1-py3-none-any.whl", hash = "sha256:8c6c0cac5c1b563622ad49321d5ec47017bd18b94facb381c6973a0486395f8e"},
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||||
@@ -3207,6 +3306,32 @@ langdetect = [
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||||
{file = "langdetect-1.0.8-py2-none-any.whl", hash = "sha256:f37495e63607865e47deed08d78f7f8e58172658216ff954b2f14671bcd87740"},
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{file = "langdetect-1.0.8.tar.gz", hash = "sha256:363795ea005f1243c958e953245dac5d814fabdc025c9afa91588c5fa6b2fa83"},
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||||
]
|
||||
lazy-object-proxy = [
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||||
{file = "lazy-object-proxy-1.5.2.tar.gz", hash = "sha256:5944a9b95e97de1980c65f03b79b356f30a43de48682b8bdd90aa5089f0ec1f4"},
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{file = "lazy_object_proxy-1.5.2-cp27-cp27m-macosx_10_14_x86_64.whl", hash = "sha256:e960e8be509e8d6d618300a6c189555c24efde63e85acaf0b14b2cd1ac743315"},
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{file = "lazy_object_proxy-1.5.2-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:522b7c94b524389f4a4094c4bf04c2b02228454ddd17c1a9b2801fac1d754871"},
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||||
{file = "lazy_object_proxy-1.5.2-cp35-cp35m-manylinux1_x86_64.whl", hash = "sha256:3782931963dc89e0e9a0ae4348b44762e868ea280e4f8c233b537852a8996ab9"},
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||||
{file = "lazy_object_proxy-1.5.2-cp35-cp35m-manylinux2014_aarch64.whl", hash = "sha256:429c4d1862f3fc37cd56304d880f2eae5bd0da83bdef889f3bd66458aac49128"},
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||||
{file = "lazy_object_proxy-1.5.2-cp35-cp35m-win32.whl", hash = "sha256:cd1bdace1a8762534e9a36c073cd54e97d517a17d69a17985961265be6d22847"},
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{file = "lazy_object_proxy-1.5.2-cp35-cp35m-win_amd64.whl", hash = "sha256:ddbdcd10eb999d7ab292677f588b658372aadb9a52790f82484a37127a390108"},
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||||
{file = "lazy_object_proxy-1.5.2-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:ecb5dd5990cec6e7f5c9c1124a37cb2c710c6d69b0c1a5c4aa4b35eba0ada068"},
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{file = "lazy_object_proxy-1.5.2-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:b6577f15d5516d7d209c1a8cde23062c0f10625f19e8dc9fb59268859778d7d7"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp36-cp36m-win32.whl", hash = "sha256:c8fe2d6ff0ff583784039d0255ea7da076efd08507f2be6f68583b0da32e3afb"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp36-cp36m-win_amd64.whl", hash = "sha256:fa5b2dee0e231fa4ad117be114251bdfe6afe39213bd629d43deb117b6a6c40a"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:1d33d6f789697f401b75ce08e73b1de567b947740f768376631079290118ad39"},
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||||
{file = "lazy_object_proxy-1.5.2-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:57fb5c5504ddd45ed420b5b6461a78f58cbb0c1b0cbd9cd5a43ad30a4a3ee4d0"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp37-cp37m-win32.whl", hash = "sha256:e7273c64bccfd9310e9601b8f4511d84730239516bada26a0c9846c9697617ef"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp37-cp37m-win_amd64.whl", hash = "sha256:6f4e5e68b7af950ed7fdb594b3f19a0014a3ace0fedb86acb896e140ffb24302"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:cadfa2c2cf54d35d13dc8d231253b7985b97d629ab9ca6e7d672c35539d38163"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:e7428977763150b4cf83255625a80a23dfdc94d43be7791ce90799d446b4e26f"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp38-cp38-win32.whl", hash = "sha256:2f2de8f8ac0be3e40d17730e0600619d35c78c13a099ea91ef7fb4ad944ce694"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp38-cp38-win_amd64.whl", hash = "sha256:38c3865bd220bd983fcaa9aa11462619e84a71233bafd9c880f7b1cb753ca7fa"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp39-cp39-macosx_10_14_x86_64.whl", hash = "sha256:8a44e9901c0555f95ac401377032f6e6af66d8fc1fbfad77a7a8b1a826e0b93c"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:fa7fb7973c622b9e725bee1db569d2c2ee64d2f9a089201c5e8185d482c7352d"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:71a1ef23f22fa8437974b2d60fedb947c99a957ad625f83f43fd3de70f77f458"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp39-cp39-win32.whl", hash = "sha256:ef3f5e288aa57b73b034ce9c1f1ac753d968f9069cd0742d1d69c698a0167166"},
|
||||
{file = "lazy_object_proxy-1.5.2-cp39-cp39-win_amd64.whl", hash = "sha256:37d9c34b96cca6787fe014aeb651217944a967a5b165e2cacb6b858d2997ab84"},
|
||||
]
|
||||
lunarcalendar = [
|
||||
{file = "LunarCalendar-0.0.9-py2.py3-none-any.whl", hash = "sha256:5ef25883d73898b37edb54da9e0f04215aaa68b897fd12e9d4b79756ff91c8cb"},
|
||||
{file = "LunarCalendar-0.0.9.tar.gz", hash = "sha256:681142f22fc353c3abca4b25699e3d1aa7083ad1c268dce36ba297eca04bed5a"},
|
||||
@@ -3335,6 +3460,10 @@ matplotlib = [
|
||||
{file = "matplotlib-3.3.4-pp37-pypy37_pp73-manylinux2010_x86_64.whl", hash = "sha256:cf3a7e54eff792f0815dbbe9b85df2f13d739289c93d346925554f71d484be78"},
|
||||
{file = "matplotlib-3.3.4.tar.gz", hash = "sha256:3e477db76c22929e4c6876c44f88d790aacdf3c3f8f3a90cb1975c0bf37825b0"},
|
||||
]
|
||||
mccabe = [
|
||||
{file = "mccabe-0.6.1-py2.py3-none-any.whl", hash = "sha256:ab8a6258860da4b6677da4bd2fe5dc2c659cff31b3ee4f7f5d64e79735b80d42"},
|
||||
{file = "mccabe-0.6.1.tar.gz", hash = "sha256:dd8d182285a0fe56bace7f45b5e7d1a6ebcbf524e8f3bd87eb0f125271b8831f"},
|
||||
]
|
||||
mistune = [
|
||||
{file = "mistune-0.8.4-py2.py3-none-any.whl", hash = "sha256:88a1051873018da288eee8538d476dffe1262495144b33ecb586c4ab266bb8d4"},
|
||||
{file = "mistune-0.8.4.tar.gz", hash = "sha256:59a3429db53c50b5c6bcc8a07f8848cb00d7dc8bdb431a4ab41920d201d4756e"},
|
||||
@@ -3347,8 +3476,8 @@ mpld3 = [
|
||||
{file = "mpld3-0.3.tar.gz", hash = "sha256:4d455884a211bf99b37ecc760759435c7bb6a5955de47d8daf4967e301878ab7"},
|
||||
]
|
||||
mplfinance = [
|
||||
{file = "mplfinance-0.12.7a7-py3-none-any.whl", hash = "sha256:08ac09b922c0e0482aadbb9a72f600415ad287db00f67227e042fd9a048e4d90"},
|
||||
{file = "mplfinance-0.12.7a7.tar.gz", hash = "sha256:a404e2a6b4c42edf06ac491e2a320b3dfa5d3435687b1e6df8c73ee8683b70f6"},
|
||||
{file = "mplfinance-0.12.7a10-py3-none-any.whl", hash = "sha256:aa4d9759a1befadfed190f9fc72ac8389d80fb61bc6f8ce6693d9c2627e88021"},
|
||||
{file = "mplfinance-0.12.7a10.tar.gz", hash = "sha256:f3745ad29ec834cd5505aa510f401f2c44b44328f92c781d093b3bb597641545"},
|
||||
]
|
||||
msgpack = [
|
||||
{file = "msgpack-1.0.2-cp35-cp35m-manylinux1_i686.whl", hash = "sha256:b6d9e2dae081aa35c44af9c4298de4ee72991305503442a5c74656d82b581fe9"},
|
||||
@@ -3698,16 +3827,28 @@ pyasn1-modules = [
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@@ -3734,7 +3875,7 @@ pyparsing = [
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@@ -3873,8 +4014,8 @@ pyzmq = [
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@@ -3885,64 +4026,67 @@ quandl = [
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|
||||
{file = "rapidfuzz-1.3.0-cp35-cp35m-win_amd64.whl", hash = "sha256:3d2d91358994e2b8379dc529399521c2a3ec727bfdcea7552b0877be1ec54117"},
|
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|
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|
||||
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|
||||
{file = "rapidfuzz-1.3.0-cp36-cp36m-manylinux2010_i686.whl", hash = "sha256:6f18c4d9fc65caf6068e306acc40192ade6d9af88939eeda3617864b4d2e8abf"},
|
||||
{file = "rapidfuzz-1.3.0-cp36-cp36m-manylinux2010_x86_64.whl", hash = "sha256:9aa106d30859a57a1447346cdeddeb7015748281f43f2054e3276551406c39c5"},
|
||||
{file = "rapidfuzz-1.3.0-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:3efb9f3c0d1ea0ec82d38075306f7e721dd88fb9ec0684dd350d73d83df6ba53"},
|
||||
{file = "rapidfuzz-1.3.0-cp36-cp36m-manylinux2014_ppc64le.whl", hash = "sha256:ed0387466970882468535a4a49bc14336783c55035a7e5d0edb36d05e253b8fe"},
|
||||
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|
||||
{file = "rapidfuzz-1.3.0-cp36-cp36m-win32.whl", hash = "sha256:1cb927ea0904caad8f2923dfdfa0975c93fdc8528b882feda78cbfc373ffa229"},
|
||||
{file = "rapidfuzz-1.3.0-cp36-cp36m-win_amd64.whl", hash = "sha256:2ba61d15d0ac83800f7a283b4c188ab54ac8595b1181714cc06b5f04ef33542a"},
|
||||
{file = "rapidfuzz-1.3.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:076943f5b318483c263584cec59763d1aac70ea0dab5f5653fde495cd1e6395f"},
|
||||
{file = "rapidfuzz-1.3.0-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:d25d6f7d94b17a962526c2261cc8fc2e292c5a071db810aeb9d48771ae9ec3e6"},
|
||||
{file = "rapidfuzz-1.3.0-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:d282448a4121a947daa540fdf0e9a8808adcf81168cfca0da9786768f6209fbb"},
|
||||
{file = "rapidfuzz-1.3.0-cp37-cp37m-manylinux2010_i686.whl", hash = "sha256:bdb9942565fb10bca30e707b8c96e6e5544bd4c604394fc92596355c34fef258"},
|
||||
{file = "rapidfuzz-1.3.0-cp37-cp37m-manylinux2010_x86_64.whl", hash = "sha256:324f6b13274abdbed51d709d6a930cf1408c26a8013e279283f0131b5fc29ac0"},
|
||||
{file = "rapidfuzz-1.3.0-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:aae04e463205b363f95ca6971d7f9e3ed39f65a5ef7fee35b01775bba1dde374"},
|
||||
{file = "rapidfuzz-1.3.0-cp37-cp37m-manylinux2014_ppc64le.whl", hash = "sha256:67a0af6e486bc706f9f64cbd024a0d8d8b63726df95bb7c7a155791391f19567"},
|
||||
{file = "rapidfuzz-1.3.0-cp37-cp37m-manylinux2014_s390x.whl", hash = "sha256:9931dad05f4d51cc4a610db3f33cc3631c4547412b4925380cca7f6f07041cb0"},
|
||||
{file = "rapidfuzz-1.3.0-cp37-cp37m-win32.whl", hash = "sha256:eeb6e1c0d63dc4909dfb7daa105c035ff6713189b5ea1c312f7e760f986296c0"},
|
||||
{file = "rapidfuzz-1.3.0-cp37-cp37m-win_amd64.whl", hash = "sha256:f22193795ef02f9a6bf90e3898a81b927dfdb80c62c6cd3e59d87330a6d4bcf1"},
|
||||
{file = "rapidfuzz-1.3.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:a73a69108cc96fad0f57f374315107eef9e80f997da7483799a262616cc0ef31"},
|
||||
{file = "rapidfuzz-1.3.0-cp38-cp38-manylinux1_i686.whl", hash = "sha256:9d97ae27902ffc2efa87b272a79a7376ddea1639b969bf995f2b521c88c2d99e"},
|
||||
{file = "rapidfuzz-1.3.0-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:a2122c78ffcae47f562450928be439a5b94ddb5b0e0d8e365ee1d08e8fe6874f"},
|
||||
{file = "rapidfuzz-1.3.0-cp38-cp38-manylinux2010_i686.whl", hash = "sha256:b4e16aacf5969f0a24dc530d0aa610df105d8fa7dd2aa282a7db98a8039c1719"},
|
||||
{file = "rapidfuzz-1.3.0-cp38-cp38-manylinux2010_x86_64.whl", hash = "sha256:1b52b7139b98d559bbd977bd28b7e68a8d75dc2345122ca8fcf938e7ff72b295"},
|
||||
{file = "rapidfuzz-1.3.0-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:25edcf5a805479dd434155ea88e9e76e9b3677b670800d5e95e04556e1a4a0e0"},
|
||||
{file = "rapidfuzz-1.3.0-cp38-cp38-manylinux2014_ppc64le.whl", hash = "sha256:92ee666f0cfa47e74e745e2bb794b43c6eeba2931c873a91b45b3439018cae77"},
|
||||
{file = "rapidfuzz-1.3.0-cp38-cp38-manylinux2014_s390x.whl", hash = "sha256:4ab4513fbe47618dab0ffbdea7beb73695d730a424b8df719aee80e48f8d00ff"},
|
||||
{file = "rapidfuzz-1.3.0-cp38-cp38-win32.whl", hash = "sha256:3db9d3ea27f0926a137f0e0169f5b29dd49b88fb0171ed7dfce224b890a86f11"},
|
||||
{file = "rapidfuzz-1.3.0-cp38-cp38-win_amd64.whl", hash = "sha256:41b28235f68475a865a94b4c0bee3259f525aac523d182432b68f5cafa35d9a1"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:7891ecf01052b69c0e0cc94695a506dd1374636292eca26e061a0c1dc3165f02"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:096b445dca7972161cdd1f856969414dde7cc9b09ff420005092d7b31139d41c"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:66c5579effe2a846117b4f499ab6910d164804c8fe31846a80981992d1b78e6e"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-manylinux1_i686.whl", hash = "sha256:2997f73a0cb5abc3a31e8c740a908be426d71db38827486881728470cc60b2c5"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:4fbbe7129df9ecd818f259136f598241206a6ac10b09763eafcf6fd1ca0fe83f"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-manylinux2010_i686.whl", hash = "sha256:24a8af40f7fc41795892be937cf3480d5cd8ae1f62ef6a845e7258d05c9ab35c"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-manylinux2010_x86_64.whl", hash = "sha256:f02b615ad69279e6ed61a7ba072494cd05cfddde210472956139d3361f8f20d1"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:45d20908601158d06c65d9ed4a54585dc32bd49cadefc385374f77b9a4696368"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-manylinux2014_ppc64le.whl", hash = "sha256:0e3570ea068e0704f7b43d5228e97c45954dec370114071139fdd9cf731a1750"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-manylinux2014_s390x.whl", hash = "sha256:f027a7df163f5f1d13d9ea60bf06d8bc0730194a2d584c3185c3a77c1a145916"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-win32.whl", hash = "sha256:460bacd89c129cf1aefc56ae465f642c712aa9b620e74305040a1cf6975cc510"},
|
||||
{file = "rapidfuzz-1.3.0-cp39-cp39-win_amd64.whl", hash = "sha256:5afa7539fb45b3c97fed67ca75a99ad7affce14561a3bd11e1c8d665b20ea8ab"},
|
||||
{file = "rapidfuzz-1.3.0-pp36-pypy36_pp73-macosx_10_9_x86_64.whl", hash = "sha256:5cadbd3f5df7e02dc11b819af860cb1a5365a49de515b76bf5dad62a3724ebaf"},
|
||||
{file = "rapidfuzz-1.3.0-pp36-pypy36_pp73-manylinux1_x86_64.whl", hash = "sha256:7e2196346ae5a1a2ac79c780d63983df93c1dbbea8aed910c43ad13c67bddc35"},
|
||||
{file = "rapidfuzz-1.3.0-pp36-pypy36_pp73-manylinux2010_x86_64.whl", hash = "sha256:ac3bc9341d8f265eb65a66ec88f351851e89a0f22be916ed4e74590e347f159e"},
|
||||
{file = "rapidfuzz-1.3.0-pp36-pypy36_pp73-win32.whl", hash = "sha256:3438c6db485dd5a3716a7f2e92a262b05db959f03712c4423b68a32453a5957d"},
|
||||
{file = "rapidfuzz-1.3.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:0ac6016f99dc36d490251c8b0910d7445921ca950ac204a4d299c0a298db8f0c"},
|
||||
{file = "rapidfuzz-1.3.0-pp37-pypy37_pp73-manylinux1_x86_64.whl", hash = "sha256:9573c989a78866269ced934a5a345ea44d05f4b69576d91c7e5b21771d19e030"},
|
||||
{file = "rapidfuzz-1.3.0-pp37-pypy37_pp73-manylinux2010_x86_64.whl", hash = "sha256:6f97fdca7a43ddb4258ddc2d6a8e960b0f5b369346d8bac02cc20b7b51721eb1"},
|
||||
{file = "rapidfuzz-1.3.0-pp37-pypy37_pp73-win32.whl", hash = "sha256:c92b7e3148a90ac9f8740e4235c64cf5a02d15a4cfbd3aa580e62327e22d4d6a"},
|
||||
{file = "rapidfuzz-1.3.0.tar.gz", hash = "sha256:f6a95ed17d7750ca75f11751ab46365c58f37a5d846e2b21d072d7a0e77ffa72"},
|
||||
]
|
||||
regex = [
|
||||
{file = "regex-2020.11.13-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:8b882a78c320478b12ff024e81dc7d43c1462aa4a3341c754ee65d857a521f85"},
|
||||
@@ -4119,8 +4263,8 @@ smart-open = [
|
||||
{file = "smart_open-4.2.0.tar.gz", hash = "sha256:d9f5a0f173ccb9bbae528db5a3804f57145815774f77ef755b9b0f3b4b2a9dcb"},
|
||||
]
|
||||
soupsieve = [
|
||||
{file = "soupsieve-2.2-py3-none-any.whl", hash = "sha256:d3a5ea5b350423f47d07639f74475afedad48cf41c0ad7a82ca13a3928af34f6"},
|
||||
{file = "soupsieve-2.2.tar.gz", hash = "sha256:407fa1e8eb3458d1b5614df51d9651a1180ea5fedf07feb46e45d7e25e6d6cdd"},
|
||||
{file = "soupsieve-2.2.1-py3-none-any.whl", hash = "sha256:c2c1c2d44f158cdbddab7824a9af8c4f83c76b1e23e049479aa432feb6c4c23b"},
|
||||
{file = "soupsieve-2.2.1.tar.gz", hash = "sha256:052774848f448cf19c7e959adf5566904d525f33a3f8b6ba6f6f8f26ec7de0cc"},
|
||||
]
|
||||
sqlitedict = [
|
||||
{file = "sqlitedict-1.7.0.tar.gz", hash = "sha256:2affcc301aacd4da7511692601ecbde392294205af418498f7d6d3ec0dbcad56"},
|
||||
@@ -4180,8 +4324,8 @@ termcolor = [
|
||||
{file = "termcolor-1.1.0.tar.gz", hash = "sha256:1d6d69ce66211143803fbc56652b41d73b4a400a2891d7bf7a1cdf4c02de613b"},
|
||||
]
|
||||
terminado = [
|
||||
{file = "terminado-0.9.2-py3-none-any.whl", hash = "sha256:23a053e06b22711269563c8bb96b36a036a86be8b5353e85e804f89b84aaa23f"},
|
||||
{file = "terminado-0.9.2.tar.gz", hash = "sha256:89e6d94b19e4bc9dce0ffd908dfaf55cc78a9bf735934e915a4a96f65ac9704c"},
|
||||
{file = "terminado-0.9.3-py3-none-any.whl", hash = "sha256:430e876ec9d4d93a4fd8a49e82dcfae0c25f846540d0c5ca774b397533e237e8"},
|
||||
{file = "terminado-0.9.3.tar.gz", hash = "sha256:261c0b7825fecf629666e1820b484a5380f7e54d6b8bd889fa482e99dcf9bde4"},
|
||||
]
|
||||
testpath = [
|
||||
{file = "testpath-0.4.4-py2.py3-none-any.whl", hash = "sha256:bfcf9411ef4bf3db7579063e0546938b1edda3d69f4e1fb8756991f5951f85d4"},
|
||||
@@ -4330,8 +4474,8 @@ update-checker = [
|
||||
{file = "update_checker-0.18.0.tar.gz", hash = "sha256:6a2d45bb4ac585884a6b03f9eade9161cedd9e8111545141e9aa9058932acb13"},
|
||||
]
|
||||
urllib3 = [
|
||||
{file = "urllib3-1.26.3-py2.py3-none-any.whl", hash = "sha256:1b465e494e3e0d8939b50680403e3aedaa2bc434b7d5af64dfd3c958d7f5ae80"},
|
||||
{file = "urllib3-1.26.3.tar.gz", hash = "sha256:de3eedaad74a2683334e282005cd8d7f22f4d55fa690a2a1020a416cb0a47e73"},
|
||||
{file = "urllib3-1.26.4-py2.py3-none-any.whl", hash = "sha256:2f4da4594db7e1e110a944bb1b551fdf4e6c136ad42e4234131391e21eb5b0df"},
|
||||
{file = "urllib3-1.26.4.tar.gz", hash = "sha256:e7b021f7241115872f92f43c6508082facffbd1c048e3c6e2bb9c2a157e28937"},
|
||||
]
|
||||
user-agent = [
|
||||
{file = "user_agent-0.1.9.tar.gz", hash = "sha256:8f1ad46cc4aef9f99515ea1c74bb8cacc43e23074c335b2ba2db7735ebe9c0d5"},
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
# https://python-poetry.org/docs/dependency-specification/
|
||||
[tool.poetry]
|
||||
name = "GamestonkTerminal"
|
||||
version = "0.1.0"
|
||||
@@ -6,7 +7,7 @@ authors = ["Didier Rodrigues Lopes"]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.6.8"
|
||||
pandas = "^1.1.5"
|
||||
pandas = "^1.1.5,<1.2"
|
||||
iso8601 = "^0.1.14"
|
||||
FundamentalAnalysis = "^0.2.6"
|
||||
requests = "^2.25.1"
|
||||
@@ -37,15 +38,22 @@ prompt-toolkit = "^3.0.16"
|
||||
jupyter = "^1.0.0"
|
||||
mplfinance = "^0.12.7-alpha.7"
|
||||
seaborn = "^0.11.0"
|
||||
scipy = "1.5.4"
|
||||
scipy = "~1.5.4"
|
||||
fredapi = "^0.4.3"
|
||||
screeninfo = "^0.6.7"
|
||||
numpy = "~1.19.5,<1.20"
|
||||
pyrsistent = "~0.14.11"
|
||||
regex = "~2020.11.13"
|
||||
h5py = "~2.10.0"
|
||||
robin-stocks = "^2.0.3"
|
||||
termcolor = "^1.1.0"
|
||||
alpaca-trade-api = "^1.0.1"
|
||||
|
||||
[tool.poetry.dev-dependencies]
|
||||
pytest = "^6.2.2"
|
||||
pylint = "^2.7.2"
|
||||
flake8 = "^3.9.0"
|
||||
black = "^20.8b1"
|
||||
|
||||
[tool.poetry.extras]
|
||||
prediction = ["fbprophet", "tensorflow", "pmdarima", "transformers", "flair", "torch"]
|
||||
@@ -53,3 +61,13 @@ prediction = ["fbprophet", "tensorflow", "pmdarima", "transformers", "flair", "t
|
||||
[build-system]
|
||||
requires = ["poetry-core>=1.0.0"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
# Notes for developers:
|
||||
# 1. numpy >= 1.20.0 sometimes has issues with tensorflow=2.4.1
|
||||
# 2. The following packages dropped support for python<3.7:
|
||||
# pandas >= 1.2.0
|
||||
# numpy >= 1.20.0
|
||||
# scipy >= 1.6.0
|
||||
# 3. The following often cause poetry to misbehave:
|
||||
# pyrsistent >= 0.17
|
||||
# regex >= 2021
|
||||
|
||||
@@ -38,6 +38,7 @@ filelock==3.0.12; python_full_version >= "3.6.0" and python_version >= "3.6"
|
||||
finviz==1.3.4
|
||||
flair==0.7; python_version >= "3.6"
|
||||
flatbuffers==1.12
|
||||
fredapi==0.4.3
|
||||
ftfy==5.9; python_version >= "3.6"
|
||||
fundamentalanalysis==0.2.6
|
||||
future==0.18.2; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.6"
|
||||
|
||||
@@ -28,6 +28,7 @@ filelock==3.0.12; python_full_version >= "3.6.0" and python_version >= "3.6"
|
||||
finviz==1.3.4
|
||||
flair==0.7; python_version >= "3.6"
|
||||
flatbuffers==1.12
|
||||
fredapi==0.4.3
|
||||
ftfy==5.9; python_version >= "3.6"
|
||||
fundamentalanalysis==0.2.6
|
||||
future==0.18.2; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.3.0" and python_version >= "3.6"
|
||||
|
||||
29
terminal.py
29
terminal.py
@@ -22,7 +22,7 @@ from gamestonk_terminal.menu import session
|
||||
from gamestonk_terminal.papermill import papermill_controller as mill
|
||||
from gamestonk_terminal.behavioural_analysis import ba_controller
|
||||
from gamestonk_terminal.technical_analysis import ta_menu as tam
|
||||
from gamestonk_terminal.comparison_analysis import ca_menu as cam
|
||||
from gamestonk_terminal.comparison_analysis import ca_controller
|
||||
from gamestonk_terminal.options import op_menu as opm
|
||||
from gamestonk_terminal.fred import fred_menu as fm
|
||||
from gamestonk_terminal.portfolio import port_menu
|
||||
@@ -85,13 +85,15 @@ def main():
|
||||
# Print first welcome message and help
|
||||
print("\nWelcome to Gamestonk Terminal 🚀\n")
|
||||
should_print_help = True
|
||||
parsed_stdin = False
|
||||
|
||||
print("-------------------")
|
||||
try:
|
||||
thought.get_thought_of_the_day()
|
||||
except Exception as e:
|
||||
print(e)
|
||||
print("")
|
||||
if gtff.ENABLE_THOUGHTS_DAY:
|
||||
print("-------------------")
|
||||
try:
|
||||
thought.get_thought_of_the_day()
|
||||
except Exception as e:
|
||||
print(e)
|
||||
print("")
|
||||
|
||||
# Loop forever and ever
|
||||
while True:
|
||||
@@ -100,8 +102,12 @@ def main():
|
||||
print_help(s_ticker, s_start, s_interval, b_is_stock_market_open())
|
||||
should_print_help = False
|
||||
|
||||
# Get input command from user
|
||||
if session and gtff.USE_PROMPT_TOOLKIT:
|
||||
# Get input command from stdin or user
|
||||
if not parsed_stdin and len(sys.argv) > 1:
|
||||
as_input = " ".join(sys.argv[1:])
|
||||
parsed_stdin = True
|
||||
print(f"{get_flair()}> {as_input}")
|
||||
elif session and gtff.USE_PROMPT_TOOLKIT:
|
||||
as_input = session.prompt(f"{get_flair()}> ", completer=completer)
|
||||
else:
|
||||
as_input = input(f"{get_flair()}> ")
|
||||
@@ -148,7 +154,8 @@ def main():
|
||||
|
||||
else:
|
||||
print(
|
||||
"No ticker selected. Use 'load ticker' to load the ticker you want to look at."
|
||||
"No ticker selected. Use 'load ticker' to load the ticker you want to look at.",
|
||||
"\n",
|
||||
)
|
||||
|
||||
main_cmd = True
|
||||
@@ -181,7 +188,7 @@ def main():
|
||||
b_quit = rm.res_menu(s_ticker, s_start, s_interval)
|
||||
|
||||
elif ns_known_args.opt == "ca":
|
||||
b_quit = cam.ca_menu(df_stock, s_ticker, s_start, s_interval)
|
||||
b_quit = ca_controller.menu(df_stock, s_ticker, s_start, s_interval)
|
||||
|
||||
elif ns_known_args.opt == "fa":
|
||||
b_quit = fam.fa_menu(s_ticker, s_start, s_interval)
|
||||
|
||||
Reference in New Issue
Block a user