Github OrgStats

gh_orgstats is intended to provide some easy ways of getting stats for a GitHub org. gh_orgstats does this by wrapping some functions around PyGithub. This code is mainly intended to help generate reports as part of a GitHub actions pipeline to update stats for a funder. For an example of this being used for generating a weekly report see the Living with Machines Github stats report

To use PyGithub we need to authenticate with GitHub this is done via a token. This token is used to authenticate access and requires at least scope for public repos. See https://github.com/settings/tokens to register a token.

from dotenv import load_dotenv
import os

In this case we use dotenv to load the token from a .env files.

load_dotenv()
GH_TOKEN = os.getenv("GH_TOKEN")

Currently all functionality is contained within the stats module.

from gh_orgstats.stats import *

The OrgStats class is used to get stats for a GitHub organization. To create an instance of this class we need to pass a GitHub token to authenticate and the name of the Organization you want stats for.

test_org = OrgStats(GH_TOKEN, "ghorgstatstestorg")
test_org

OrgStats: ghorgstatstestorg

Organization repositories

As a start we can grab the repositories for an organization via the repos attribute of our OrgStats instance

test_org.repos

[Repository(full_name="ghorgstatstestorg/repo1"),
 Repository(full_name="ghorgstatstestorg/repo2"),
 Repository(full_name="ghorgstatstestorg/private_repo_1")]

We can also get a sense of what is in the repository by looking at the file extensions for each repository.

Repository file types

test_org.get_org_file_ext_frequency()

{'repo1': {'.md': 1},
 'repo2': {'.md': 1, '.py': 1},
 'private_repo_1': {'.md': 1}}

Filtering by publication status

We can also filter this by publication status

test_org.get_org_file_ext_frequency(pub_status='public')

{'repo1': {'.md': 1}, 'repo2': {'.md': 1, '.py': 1}}

Snapshot stats

Snapshot stats are captured based on the current view and aren't updated. These include forks and clones

test_org.snapshot_stats.to_dict()

{'stars': {'repo1': 1, 'repo2': 0}, 'forks': {'repo1': 0, 'repo2': 0}}

Traffic stats

We can also get a longer view by using traffic stats for views and clones

test_org.get_org_views_traffic(save_dir='readme_dir')

get_org_views_traffic will grab data via the GitHub api and update a CSV for each repository under the organization (by default only public) with views counts. This is largely intended to be used to semi-regularly update these stats by running this code as part of a GitHub Action or cron job.

If you want to load a DataFrame of traffic you can pass load=True

test_org.get_org_views_traffic(save_dir='readme_dir', load=True).to_dict()

{('repo1', 'total_views'): {Timestamp('2020-11-30 00:00:00'): 2,
  Timestamp('2020-12-01 00:00:00'): 1},
 ('repo1', 'unique_views'): {Timestamp('2020-11-30 00:00:00'): 1,
  Timestamp('2020-12-01 00:00:00'): 1},
 ('repo2', 'total_views'): {Timestamp('2020-11-30 00:00:00'): 8.0,
  Timestamp('2020-12-01 00:00:00'): nan},
 ('repo2', 'unique_views'): {Timestamp('2020-11-30 00:00:00'): 1.0,
  Timestamp('2020-12-01 00:00:00'): nan}}

Similarly the same can be done for clones