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basketballcrawler

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DEFUNCT - This is a python module to scrape basketball-reference.com and convert various stats into usable data structures for analysis

// repository documentation

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basketballcrawler
==================

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This is a python module to scrape [basketball-reference.com](http://www.basketball-reference.com/) and convert various
stats into usable data structures for analysis.

[Here](example_notebook.ipynb) is a link to a
sample IPython Notebook file demonstrating the library.

Requirements
------------

- [Beautiful Soup](http://www.crummy.com/software/BeautifulSoup/bs4/doc/#) >= 4.0
- [pandas](http://pandas.pydata.org/) >= 0.11
- [request](http://docs.python-requests.org/en/master/) >= 2.0

Usage
-----

Still developing the API.  Right now you can get a list of all player overview urls, generate a list of game log urls for
a given player, and convert that list into pandas dataframe.

Notes
-----

`players.json` was generated on 02/11/2016 by `buildPlayerDictionary()` and `savePlayerDictionary()`.
I'd recommend building your own, fresh copy. It takes about 10 minutes to scrape from the site.
To create the most recent `players.json`, you can use as follows.

```python
import basketballCrawler as bc
players = bc.buildPlayerDictionary()
bc.savePlayerDictionary(players, '/path/to/file')
```

You can also download generated `players.json`. However, note that it's a pretty large (13M) file.

```python
players = bc.loadPlayerDictionary('/path/to/players.json')
```

In order to search player name, use `searchForName` function, for example,

```python
searched_player = bc.searchForName(players, 'Murphey') # players is player dictionary
```

TODO
----
- Local Database construction.
- League-wide statistics.

basketballcrawler

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