Metadata-Version: 2.1
Name: PyFyGentleScrap
Version: 0.2.21
Summary: Unofficial Yahoo finance scrapper
Home-page: https://gitlab.com/OlivierLuG/pyfygentlescrap
Author: OlivierLuG
Author-email: not_a_valid_email@gmail.com
License: UNKNOWN
Description: # PyFyGentleScrap: gently scrap financial data
        
        DISCLAIMER:
        When using **PyFyGentleScrap**, you implicitely accept cookies and third party policies
        of the scrapped websites.
        
        ## What is it?
        
        **PyFyGentleScrap** is a python module to scrap financial data. It's goal is to fetch
        financial data from websites and return them as *pandas* data.
        
        *Gentle* scrapping means that all web requests are designed to avoid the servers
        to detect the requests as scraping. This also means that cookies and licenses are
        accepted.
        
        ## Main features
        
        ### Yahoo scrapping (https://finance.yahoo.com)
        Two functions are available to scrap yahoo :
         - `yahoo_equity_screener(regions=['Belgium', 'United States'])`, which will 
        basically return EOD values (open/high/low/close/volume) + many additionnal
        informations.
         - ![not_developped](https://img.shields.io/badge/-not%20developped%20yet-critical) `yahoo_historical_data(equities=['AAPL'])`
        
        _ [https://finance.yahoo.com/screener/](https://finance.yahoo.com/screener/)
        
        
        
        ## Main dependencies
        
        - [Firefox](https://www.mozilla.org/fr/firefox/)
        - [Geckodriver](https://github.com/mozilla/geckodriver/releases)
        - [Selenium](https://pypi.org/project/selenium/)
        - [Requests](https://github.com/psf/requests)
        - [Pandas](https://github.com/pandas-dev/pandas)
        
        ## Guide to contribute to the code
        
        All contributions are welcome. If you think you've discovered an issue, please read
        [this stackoverflow article](https://stackoverflow.com/help/minimal-reproducible-example)
        for tips on writing a good bug report.
        
        1. Forking
        
        ```sh
        git clone https://gitlab.com/your-user-name/pyfygentlescrap.git
        cd pyfygentlescrap
        git remote add upstream https://gitlab.com/your-user-name/pyfygentlescrap
        ```
        
        2. Set a virtual environment
        3. Install main and development dependencies:
        
        ```sh
        pip3 install -r requirements.txt
        pip3 install -r requirements-dev.txt
        ```
        Note: Use the `--upgrade` option to update package to the last stable version.
        
        4. (optionnal) Run tests to check that everything is working fine:
        
        ```sh
        pytest
        ```
        
        5. Create a new branch, test it, check linting, pull it:
        
        ```sh
        git branch my_super_branch
        git checkout my_super_branch
        ```
        Code a super functionnality, then test it:
        ```sh
        # linting:
        black pyfygentlescrap
        flake8 pyfygentlescrap
        # building documention:
        cd docs && make html
        # testing, coverage:
        python3 -m pytest # or simply `pytest`
        python3 -m coverage run --source=. -m pytest && python3 -m coverage report -m
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
