Pstock
Disclaimer
You should refer to Yahoo!'s terms of use (here, here, and here) for details on your rights to use the actual data downloaded. Remember - the project is intended for personal use only.
Pstock is an open source tool/project that is not affiliated in any way to yahoo-finance. Nothing in this project should be considered investment advice.
Documentation: https://obendidi.github.io/pstock
Source Code: https://github.com/obendidi/pstock
Pstock is yet another python unoficial API for getting yahoo-finance data.
The key features are:
- Async first
- Data validation using pydantic
- Fully typed, with great editor support
- Easily extensible: Parse the yahoo-finance quote dict and extract any type of info you want.
- Follows the Sans-IO design pattern: Use your favourite http library (sync/async) and let
pstockparse your response to getAssetsorBars
Requirements
Python 3.8+ (support for 3.6/3.7 may be added later, contributions are welcome)
Pstock depends mainly on:
- pydantic: For data validation
- pandas: For structuring data in nice dataframes
- httpx: For the main async IO interface
Installation
Quickstart
- Download an asset:
import asyncio
from pstock import Asset
asset = asyncio.run(Asset.get("TSLA"))
print(asset)
# symbol='TSLA' name='Tesla, Inc.' asset_type='EQUITY' currency='USD' latest_price=920.0 sector='Consumer Cyclical' industry='Auto Manufacturers'
- Download a list of assets:
import asyncio
from pstock import Asset
assets = asyncio.run(Assets.get(["TSLA", "AAPL", "GME"]))
print(assets)
# __root__=[Asset(symbol='TSLA', name='Tesla, Inc.', asset_type='EQUITY', currency='USD', latest_price=918.97, sector='Consumer Cyclical', industry='Auto Manufacturers'), Asset(symbol='AAPL', name='Apple Inc.', asset_type='EQUITY', currency='USD', latest_price=172.345, sector='Technology', industry='Consumer Electronics'), Asset(symbol='GME', name='GameStop Corp.', asset_type='EQUITY', currency='USD', latest_price=125.0, sector='Consumer Cyclical', industry='Specialty Retail')]
print(assets[0])
# Asset(symbol='TSLA', name='Tesla, Inc.', asset_type='EQUITY', currency='USD', latest_price=918.97, sector='Consumer Cyclical', industry='Auto Manufacturers')
print(assets.df)
name asset_type currency ... earnings trends income_statement
symbol ...
AAPL Apple Inc. EQUITY USD ... [{'quarter': '1Q2021', 'estimate': 0.99, 'actu... [{'date': 2021-11-17, 'strong_buy': 13, 'buy':... [{'date': 2021-09-25, 'ebit': 108949000000.0, ...
GME GameStop Corp. EQUITY USD ... [{'quarter': '1Q2021', 'estimate': 1.35, 'actu... [{'date': 2021-11-17, 'strong_buy': 2, 'buy': ... [{'date': 2021-01-30, 'ebit': -249300000.0, 't...
TSLA Tesla, Inc. EQUITY USD ... [{'quarter': '1Q2021', 'estimate': 0.79, 'actu... [{'date': 2021-11-17, 'strong_buy': 4, 'buy': ... [{'date': 2021-12-31, 'ebit': 6523000000.0, 't...
- Download historical bars:
import asyncio
from pstock import Bars
bars = asyncio.run(Bars.get("TSLA"))
print(bars)
# __root__=[Bar(date=datetime.datetime(2010, 7, 1, 4, 0, tzinfo=datetime.timezone.utc), open=5.0, high=5.184000015258789, low=2.996000051498413, close=3.98799991607666, adj_close=3.98799991607666, volume=322879000.0, interval=Duration(months=1)), Bar(date=datetime.datetime(2010, 8, 1, 4, 0, tzinfo=datetime.timezone.utc), open=4.099999904632568, high=4.435999870300293, low=3.4779999256134033, close=3.8959999084472656, adj_close=3.8959999084472656, volume=75191000.0, interval=Duration(months=1)), Bar(date=datetime.datetime(2010, 9, 1, 4, 0, tzinfo=datetime.timezone.utc), open=3.9240000247955322, high=4.631999969482422, low=3.9000000953674316, close=4.081999778747559, adj_close=4.081999778747559, volume=90229500.0, interval=Duration(months=1)), Bar(date=datetime.datetime(2010, 10, 1, 4, 0, tzinfo=datetime.timezone.utc), open=4.138000011444092, high=4.374000072479248, low=4.0, close=4.368000030517578, adj_close=4.368000030517578, volume=32739000.0, interval=Duration(months=1)), ....]
print(bars.df)
open high low close adj_close volume interval
date
2010-07-01 5.000000 5.184000 2.996000 3.988000 3.988000 322879000.0 30 days
2010-08-01 4.100000 4.436000 3.478000 3.896000 3.896000 75191000.0 30 days
2010-09-01 3.924000 4.632000 3.900000 4.082000 4.082000 90229500.0 30 days
2010-10-01 4.138000 4.374000 4.000000 4.368000 4.368000 32739000.0 30 days
2010-11-01 4.388000 7.200000 4.210000 7.066000 7.066000 141575500.0 30 days
... ... ... ... ... ... ... ...
2021-11-01 1145.000000 1243.489990 978.599976 1144.760010 1144.760010 648671800.0 30 days
2021-12-01 1160.699951 1172.839966 886.119995 1056.780029 1056.780029 509945100.0 30 days
2022-01-01 1147.750000 1208.000000 792.010010 936.719971 936.719971 638471400.0 30 days
2022-02-01 935.210022 947.770020 850.700012 875.760010 875.760010 223112600.0 30 days
2022-02-15 900.000000 923.000000 893.377380 922.429993 922.429993 19085243.0 30 days
[141 rows x 7 columns]
- Download stock news:
import asyncio
from pstock import News
news = asyncio.run(News.get("TSLA"))
print(news.df)
title url summary
date
2022-02-15 12:11:46+00:00 Retail investor: 'I'm being careful just in ca... https://finance.yahoo.com/news/retail-investor... Some retail investors are being more cautious ...
2022-02-15 12:23:00+00:00 Tesla’s Elon Musk Gave Away $5.7 Billion. But ... https://finance.yahoo.com/m/d342cd56-d5bb-3957... Tesla CEO Elon Musk gave away more than 5 mill...
2022-02-15 13:07:02+00:00 Company News for Feb 15, 2022 https://finance.yahoo.com/news/company-news-fe... Companies In The News Are: IFS, OLK, THS, TSLA.
....
2022-02-15 19:23:43+00:00 Australia's Syrah Resources to expand Louisian... https://finance.yahoo.com/news/australias-syra... Australian industrial materials firm Syrah Res...
2022-02-15 20:31:30+00:00 Biggest Companies in the World by Market Cap https://finance.yahoo.com/m/8aead0a5-ef35-3d90... The world's biggest companies by market cap op...
Contributors
Feel free to contribute !