ResCSGO

An environment.yml and requirements.txt file are provided for you to install the necessary packages to run the code. Commands are:

conda env create -f environment.yml
pip install -r requirements.txt

Files

• scraper.py - The main file containing a generic scraper class which handles all things regarding selenium drivers.

• HLTVScraper.py - A scraper class that inherits from the generic scraper class. Contains methods for scraping HLTV data.

• OddsPortalScraper.py - A scraper class that inherits from the generic scraper class. Contains methods for scraping OddsPortal data.

• EGamersWorldScraper.py - A scraper class that inherits from the generic scraper class. Contains methods for scraping EGamersWorld data.

• RivalryScraper.py - A scraper class that inherits from the generic scraper class. Contains methods for scraping Rivalry data.(Not Implemented Yet)

• ./data/team_ratings.csv - A csv file containing all of the team names and their ratings, K/D, and KD Diff on HLTV.

• ./data/player_ids.csv - A csv file containing all of the player names and their ids on HLTV.

• ./data/oddsportal.csv - A csv file containing all of the odds from oddsportal.com.

• ./data/map_success.csv - A csv file containing all of the raw data scraped from the Historical Matches folder acquired from HLTV.

• ./data/learn_rating_tdiff.csv - A modified version of map_success.csv which selects for cases where winning teams have better ratings and vice versa.

• ./data/learn_map_success.csv - A modified version of map_success.csv which selects for cases where winning teams have better prob success on a given map than the opponent.

• ./data/learn_K-D_tdiff.csv - A modified version of map_success.csv which selects for cases where winning teams have better K/D Diff and vice versa.

• ./data/learn_all.csv - A modified version of map_success.csv which selects for cases where winning teams have all of the above and vice versa.

• ./data/egamersworld.csv - A csv file containing all of the odds from egamersworld.com.

• ./data/CSGO-odds.csv - A csv file containing all of the odds from oddsportal.com.

• ./pickles/set_names.pkl - A pickle file containing a set of all of the team names that have odds on oddsportal.com.

• ./pickles/team_ids.pkl - A pickle file containing a dictionary of all of the team names and their ids on HLTV.

• ./pickles/matched_names.pkl - A pickle file containing a dictionary of all of the team names and their ids on HLTV that have odds on oddsportal.com.

• ./pickles/player_ids.pkl - A pickle file containing a dictionary of all of the player names and their ids on HLTV.

• ./pickles/match_ids.pkl - A pickle file containing a dictionary of all of the match names and their ids on HLTV.

These scrapers have methods that can get specific things and store them in files for you(instead of doing redundant accesses). Feel free to use or modify any of the methods to help you for your task. I've tried to modularize the code around some uniform drivers which are instantiated at the beginning of each method. Ultimately the class definitions just serve as containers for unique methods.