GH Elephant

GH Elephant is a tool to download GitHub activity data from the GitHub Archive and store it in a PostgreSQL database for further analysis. For the full reference and a concrete use case of GH Elephant, see the Master's thesis for which GH Elephant was created.

Installation

• pip3 install -r requirements.txt
• complete variables.py with your database information and a path where to temporarily store the json and csv files.
• make sure you have psql running with an empty database as specified in variables.py

Usage

Creating a Database

• make sure you have about 100 GB of free storage for the temporary files; if that's out of reach, make the queues in manager.py smaller.
• run ./ghelephant.py with the required options -s and -e specifying start and end date for the downloads in the format "YYYY-MM-DD"
• run ./ghelephant.py with option -i to create indices for faster queries

Adding Additional Information

If you want to add additional information like user data or get commit details, you can use the GitHub API directly through GH Elephant to enrich your tables. To do so, you first need to export a table in csv format with header (e.g. copy (select actor_login, repo_name, sha, created_at from archive join commit on payload_id=push_id where type = 'PushEvent' limit 10) to '/my_path/table.csv' (format csv, header);).

Then, you can use the following two commands to extend your table with user data or commit information in JSON form. You should also use a Personal GitHub Access Token and provide it to GH Elephant with the -t flag.

• run ./ghelephant.py -u /my_path/table.csv to add user information into the csv (requires the presence of the actor_login column)
• run ./ghelephant.py -c /my_path/table.csv to add commit information into the csv (requires the presence of the repo_name and sha columns)
• run ./ghelephant.py -l /my_path/table.csv to convert the locations added with the -u option into uniform country codes

Cloning Repos

If you want to clone some repos you have in your database, export them to a csv file with header (see example above).

• run ./ghelephant.py -r /my_path/table.csv -o /path/to/folder (requires the presence of the repo_name column)