Metadata-Version: 2.1
Name: nbapy
Version: 1.1.8
Summary: Python client for NBA statistics located at nba.com
Home-page: https://github.com/jtpavlock/nbapy
License: UNKNOWN
Description: <p align="center">
        <a href="https://github.com/jtpavlock/nbapy/actions"><img alt="Actions Status" src="https://github.com/jtpavlock/nbapy/workflows/CI/badge.svg"></a>
        <a href="https://pypi.org/project/nbapy/"><img alt="PyPI" src="https://img.shields.io/pypi/v/nbapy"></a>
        <a href="https://pepy.tech/project/nbapy"><img alt="Downloads" src="https://pepy.tech/badge/nbapy"></a>
        </p>
        
        # *nbapy - [stats.nba.com](https://stats.nba.com) API for python*
        
        ## Summary
        A python facing API for `stats.nba.com`
        
        ***Warning*** `stats.nba.com` is notorious for being extremely unreliable. Please report any issues you find.
        
        ## Usage
        
        All data is returned as a pandas dataframe (check out the [starter docs](https://pandas.pydata.org/pandas-docs/stable/getting_started/10min.html) if you're new to pandas). For example:
        
        ```python
        from nbapy import game
        import pandas as pd
        
        game_id = '0021900017'  # taken from 'https://stats.nba.com/game/0021900017/'
        stats = pd.DataFrame(game.BoxScore(game_id).players_stats())
        ```
        
        If you want to cache results so you don't have to reach the api every time, you can use [requests-cache](https://pypi.org/project/requests-cache/)
        ```python
        from nbapy import game
        import pandas as pd
        import requests_cache
        
        requests_cache.install_cache('nbapy_cache')
        
        game_id = '0021900017'
        stats = pd.DataFrame(game.BoxScore(game_id).players_stats())
        ```
        
        ## Documentation
        An ongoing process, but check out [the jupyter notebook docs](https://github.com/jtpavlock/nbapy/tree/master/docs), or feel free to poke around the codebase.
        
        
        ## Installation
        To install from pypi:
        
        ```bash
        $ python -m pip install nbapy
        ```
        
        Else:
        - Download from source (git clone, zipped package)
        - Run from the root directory:
        
        ```bash
        $ python -m pip install .
        ```
        
        ## Contributing
        #### 1. Fork the repository and create a feature/bug fix branch
        
        #### 2. Install development requirements
        ```bash
        $ python -m pip install -e . ".[dev]"
        ```
        
        #### 3. Hack away
        
        *Coding conventions*
        
        * [black](https://github.com/psf/black) for formatting
        * [google docstrings](https://google.github.io/styleguide/pyguide.html#38-comments-and-docstrings)
        * [flake8](https://flake8.pycqa.org/en/latest/index.html#quickstart) for linting
        * [mypy](http://mypy-lang.org/) for static typing analysis
        * [conventional commits](https://www.conventionalcommits.org/en/v1.0.0/) for commit style.
        
        *Optional (but recommended)*
        
        `nbapy` has a [pre-commit](https://pre-commit.com/) file that you can install to automatically enforce these conventions prior to committing via a git hook.
        
        To install: `$ pre-commit install`
        
        You can also use `$ pre-commit run -a` to run the checks manually.
        
        For commit messages, I recommend using [commtizen](https://github.com/commitizen-tools/commitizen). It is automatically installed in the dev dependencies, so to commit, you just run `cz c` and follow the prompts.
        
        #### 4. Create some tests
        
        #### 5. Make sure everything looks good
        `$ pytest --cov`* 
        
        `$ pre-commit run -a` (if you didn't install the pre-commit git hook)
        
        \* note the first time you run this, it may take a few minutes. However, the requests will cache, and subsequent runs should be much faster.
        
        #### 6. Submit a pull request
        
        Other ways to contribute involve submitting any issues or adding some documentation!
        
        ## To-Do
        - Finish Jupyter Notebook documentation
        
        ## Authors
        
        This is orginally based off of https://github.com/seemethere/nba_py so a lot of the work was done by those guys. My goal with this project is to clean up the code, add some proper documentation, and keep it up to date.
        
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: dev
