Metadata-Version: 2.1
Name: steampi
Version: 0.5.2
Summary: Steam API on PyPI
Home-page: https://github.com/woctezuma/steampi
Author: Wok
Author-email: wok@tuta.io
License: UNKNOWN
Download-URL: https://github.com/woctezuma/steampi/archive/0.5.2.tar.gz
Description: # SteamPI: a simple API for Steam
        
        [![PyPI status][pypi-image]][pypi]
        [![Build status][build-image]][build]
        [![Updates][dependency-image]][pyup]
        [![Python 3][python3-image]][pyup]
        [![Code coverage][codecov-image]][codecov]
        [![Code Quality][codacy-image]][codacy]
        
        This repository contains Python code to download some data through Steam API.
        
        ## Installation
        
        The code is packaged for [PyPI](https://pypi.org/project/steampi/), so that the installation consists in running:
        
        ```bash
        pip install steampi
        ```
        
        ## Usage
        
        ### Download app details of a Steam game, given its appID
        
        ```python
        import steampi.api
        
        app_id = '440'
        (app_details, is_success, status_code) = steampi.api.load_app_details(app_id)
        ```
        
        ### Retrieve the release date of a Steam game, given its appID
        
        ```python
        import steampi.calendar
        
        app_id = '440'
        release_date = steampi.calendar.get_release_date_as_datetime(app_id)
        ```
        
        ### Retrieve the release year of a Steam game, given its appID
        
        ```python
        import steampi.calendar
        
        app_id = '440'
        release_year = steampi.calendar.get_release_year(app_id)
        ```
        
        ### Find the most similar game names to an input text
        
        #### Using the Levenshtein distance
        
        The Levenshtein distance is an edit distance, which is useful to fix typos for instance.
        
        ```python
        import steampi.text_distances
        import steamspypi
        
        steamspy_database = steamspypi.load()
        
        input_text = 'Crash Bandicoot'
        sorted_app_ids, text_distances = steampi.text_distances.find_most_similar_game_names(input_text,
                                                                                             steamspy_database)
        
        num_games_to_print = 5
        for i in range(num_games_to_print):
            similar_game_name = steamspy_database[sorted_app_ids[i]]
            print(similar_game_name)
        ```
        
        #### Using the longest contiguous matching subsequence
        
        The code snippet below makes use of the longest contiguous matching subsequence.
        This leads to different results compared to Levenshtein distance, which you might find more suitable for your needs.
        
        However:
        -   the code is slower than with Levenshtein distance: for instance, the run-time is 140% longer for the unit test,
        -   the text distances are bound to [0,1], so they do not have the same value range as for Levenshtein distance,
        -   the text distances do not have the same meaning as for Levenshtein distance, which was the minimal number of edits,
        -   the results do not contain all the text distances, but only these with less than 0.4 distance (i.e. 0.6 similarity).
        
        Junk characters can be specified with `junk_str`.
        
        ```python
        import steampi.text_distances
        import steamspypi
        
        steamspy_database = steamspypi.load()
        
        num_games_to_print = 5
        junk_str=''
        
        input_text = 'Crash Bandicoot'
        sorted_app_ids, text_distances = steampi.text_distances.find_most_similar_game_names(input_text,
                                                                                             steamspy_database,
                                                                                             use_levenshtein_distance=False,
                                                                                             n=num_games_to_print,
                                                                                             junk_str=junk_str,
                                                                                             )
        
        for i in range(len(sorted_app_ids)):
            similar_game_name = steamspy_database[sorted_app_ids[i]]
            print(similar_game_name)
        ```
        
        ## References
        
        -   [Levenshtein module](https://github.com/ztane/python-Levenshtein) for the Levenshtein distance,
        -   [Difflib module](https://docs.python.org/3/library/difflib.html) for the longest contiguous matching subsequence.
        
        <!-- Definitions for badges -->
        
        [pypi]: <https://pypi.python.org/pypi/steampi>
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        [codecov]: <https://codecov.io/gh/woctezuma/steampi>
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        [codacy]: <https://www.codacy.com/app/woctezuma/steampi>
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Keywords: steam,steamspy,api
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Games/Entertainment
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
