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A package to scrape game reviews from Steam.

Project description

Steam Review Scraper

Installation

The package can be installed by:

>>> pip install steam-review-scaper

Usage

search_game_id(search_term, all_results=False)

Return Dataframe of game ids of the search term from Steam’s search result page.

Args:

search_term (str): Game name to search. all_results (bool, optional): Whether to return all games results of the search term or the top one result. Defaults to False.

Returns:

Dataframe: Dataframe with two columns game and id.

Example:

>>> from steam_review_scraper import search_game_id
>>> search_game_id("Counter-Strike: Global Offensive")
                               game   id
0  Counter-Strike: Global Offensive  730

get_game_ids(n, filter='topsellers')

Return Dataframe of n games’ ids from Steam’s search result page.

Args:

n (int): number of games to collect. filter (str, optional): filter for search results. Defaults to ‘topsellers’.

Returns:

Dataframe: Dataframe with two columns game and id.

Example:

>>> from steam_review_scraper import get_game_ids
>>> get_game_ids(5)
                               game       id
0                         BIOMUTANT   597820
1    Mass Effect Legendary Edition  1328670
2                         Destiny 2  1085660
3  Counter-Strike: Global Offensive      730
4                     Apex Legends  1172470

get_review_count(id)

Return total number of reviews of default language.

Args:

id (int or str): Game id.

Returns:

int: Number of reviews.

Example:

>>> from steam_review_scraper import get_review_count
>>> get_review_count(730)
1646275

get_game_review(id, language='default')

Collect all review for a given game.

Args:

id (int or str): Game id language (str, optional): The language in which to get the reviews. Defaults to ‘default’, which is the default language of your Steam account.

Returns:

Dataframe: Dataframe for reviews with the following columns:

name description dtype
user user name of the review object
playtime total playtime (in hours) the user spent on this game float64
user_link user's profile page url object
post_date review's post date object
helpfulness number of people found this review helpful int64
review review content object
recommend whether the user recommend the game. object
early_access_review whether this is an early access review. object

Example:

English reviews for Counter-Strike: Global Offensive:

>>> from steam_review_scraper import get_game_review 
>>> reviews = get_game_review(730, language=english)

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