PyFyGentleScrap 0.4.11

Unofficial Yahoo finance scrapper

# PyFyGentleScrap: gently scrap financial data

## What is it?

PyFyGentleScrap is a python package that provide function to scrap financial data on websites, such as end of day tickers (EOD) list for a particular country or historical EOD values for a particular ticker.

Gentle scrapping means that all web requests are designed to avoid the remote servers to detect the requests as scraping.

All scrapped data are return as pandas.DataFrame to easily compute statistics, or storing data into a database.

NOTE: PyFyGentleScrap package is not affiliated to any website. Please use this package wisely to avoid to be block.

[](https://pypi.org/project/PyFyGentleScrap/) [](https://gitlab.com/OlivierLuG/pyfygentlescrap) [](https://github.com/psf/black) [](https://gitlab.com/OlivierLuG/pyfygentlescrap) [](https://gitlab.com/OlivierLuG/pyfygentlescrap) [](https://pyfygentlescrap.readthedocs.io/)

## Installing PyFyGentleScrap

PyFyGentleScrap is available on [PyPi](https://pypi.org/project/PyFyGentleScrap/): `sh pip install pyfygentlescrap `

## Main features

Example of equity download:

`python >>> import pyfygentlescrap as pfgs >>> df = pfgs.yahoo_ticker('AAPL') >>> print(df.columns) Index(['fullExchangeName', 'fiftyTwoWeekLowChangePercent', 'gmtOffSetMilliseconds', 'regularMarketOpen', 'language', 'regularMarketTime', 'regularMarketChangePercent', 'uuid', 'quoteType', 'regularMarketDayRange', 'fiftyTwoWeekLowChange', 'fiftyTwoWeekHighChangePercent', 'regularMarketDayHigh', 'tradeable', 'currency', 'sharesOutstanding', 'fiftyTwoWeekHigh', 'regularMarketPreviousClose', 'exchangeTimezoneName', 'marketCap', 'fiftyTwoWeekHighChange', 'fiftyTwoWeekRange', 'regularMarketChange', 'firstTradeDateMilliseconds', 'exchangeDataDelayedBy', 'exchangeTimezoneShortName', 'regularMarketPrice', 'fiftyTwoWeekLow', 'marketState', 'market', 'regularMarketVolume', 'quoteSourceName', 'messageBoardId', 'priceHint', 'exchange', 'sourceInterval', 'regularMarketDayLow', 'region', 'shortName', 'triggerable', 'longName'], dtype='object') >>> df[['regularMarketOpen', 'regularMarketVolume', 'marketState', 'shortName', 'marketCap']] regularMarketOpen regularMarketVolume marketState shortName marketCap symbol AAPL 122.43 81462378 CLOSED Apple Inc. 2081190313984 `

Example of region EOD download: `python >>> df = pfgs.yahoo_equity_screener(region='Belgium') >>> print(len(df.columns)) # 63 columns containing various data are scrapped 63 >>> print(df[['marketState', 'regularMarketOpen', 'regularMarketPrice']]) marketState regularMarketOpen regularMarketPrice symbol MSF.BR CLOSED 213.05 211.9 INCO.BR CLOSED 49.4 49.4 CIS.BR CLOSED 48.995 44.585 ... ... ... ... PAY.BR CLOSED 7.5 7.6 TEXF.BR CLOSED 36.6 36.4 WEB.BR CLOSED 43.4 40.5 [200 rows x 3 columns] `

Example of region historical EOD data download for one ticker:

`python >>> df = pfgs.yahoo_historical_data("AAPL", "2019-08-01", "2019-08-31") >>> print(df) . open high low close adjclose volume dividend split 2019-08-01 53.474998 54.507500 51.685001 52.107498 50.895054 216071600 0.0000 1.0 2019-08-02 51.382500 51.607498 50.407501 51.005001 49.818211 163448400 0.0000 1.0 2019-08-05 49.497501 49.662498 48.145000 48.334999 47.210331 209572000 0.0000 1.0 2019-08-06 49.077499 49.517502 48.509998 49.250000 48.104046 143299200 0.0000 1.0 2019-08-07 48.852501 49.889999 48.455002 49.759998 48.602177 133457600 0.0000 1.0 2019-08-08 50.049999 50.882500 49.847500 50.857498 49.674141 108038000 0.0000 1.0 2019-08-09 50.325001 50.689999 49.822498 50.247501 49.264809 98478800 0.1925 1.0 2019-08-12 49.904999 50.512501 49.787498 50.119999 49.139793 89927600 0.0000 1.0 2019-08-13 50.255001 53.035000 50.119999 52.242500 51.220791 188874000 0.0000 1.0 2019-08-14 50.790001 51.610001 50.647499 50.687500 49.696201 146189600 0.0000 1.0 2019-08-15 50.865002 51.285000 49.917500 50.435001 49.448643 108909600 0.0000 1.0 2019-08-16 51.070000 51.790001 50.959999 51.625000 50.615368 110481600 0.0000 1.0 2019-08-19 52.654999 53.182499 52.507500 52.587502 51.559048 97654400 0.0000 1.0 2019-08-20 52.720001 53.337502 52.580002 52.590000 51.561501 107537200 0.0000 1.0 2019-08-21 53.247501 53.412498 52.900002 53.160000 52.120346 86141600 0.0000 1.0 2019-08-22 53.297501 53.610001 52.687500 53.115002 52.076225 89014800 0.0000 1.0 2019-08-23 52.357498 53.012501 50.250000 50.660000 49.669239 187272000 0.0000 1.0 2019-08-26 51.465000 51.797501 51.264999 51.622501 50.612915 104174400 0.0000 1.0 2019-08-27 51.965000 52.137501 50.882500 51.040001 50.041805 103493200 0.0000 1.0 2019-08-28 51.025002 51.430000 50.830002 51.382500 50.377613 63755200 0.0000 1.0 2019-08-29 52.125000 52.330002 51.665001 52.252499 51.230591 83962000 0.0000 1.0 2019-08-30 52.540001 52.612499 51.799999 52.185001 51.164417 84573600 0.0000 1.0 `

## Documentation

See the full documentation at: https://pyfygentlescrap.readthedocs.io/en/latest/

## License [MIT License](https://gitlab.com/OlivierLuG/pyfygentlescrap/-/blob/master/LICENSE)