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https://github.com/borda/pyrepostats
Simple repository contribution statistics
https://github.com/borda/pyrepostats
contribution contributors issues prs repository statistics
Last synced: 20 days ago
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Simple repository contribution statistics
- Host: GitHub
- URL: https://github.com/borda/pyrepostats
- Owner: Borda
- License: mit
- Created: 2020-10-31T11:57:29.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2024-10-07T17:22:53.000Z (3 months ago)
- Last Synced: 2024-11-29T16:11:49.513Z (26 days ago)
- Topics: contribution, contributors, issues, prs, repository, statistics
- Language: Python
- Homepage: https://borda.github.io/pyRepoStats
- Size: 605 KB
- Stars: 12
- Watchers: 3
- Forks: 0
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# Repository Stats
[](https://github.com/Borda/pyRepoStats/actions/workflows/ci_testing.yml)
[](https://codecov.io/gh/Borda/pyRepoStats)
[](https://www.codefactor.io/repository/github/borda/pyrepostats)
[](https://results.pre-commit.ci/latest/github/Borda/pyRepoStats/main)
This simple tool aims on open-source projects providing simple repository stats which are a bit out of scope of base Git and need some more information about issues and PRs.
### Highlighted features
- cumulative **caching** (no need to full download, just incremental/needed update)
- collection of **overall user contributions** to issues/PRs
- visualization of **aggregated timeline** of past contributions
## Installation
Simple install with setuptools/pip as
```bash
pip install https://github.com/Borda/pyRepoStats/archive/main.zip
```
or after cloning the repository
```bash
python setup.py install
```
## Sample usage
Let's show how to pull data from Github repository, use of the following calls
- if you just clone this repo without installation, you need to install dependencies and call script
```bash
pip install -r requirements.txt
python src/repo_stats/__main__.py -gh PyTorchLightning/pytorch-lightning-bolts
```
- if you have already installed the package with `pip` or with `setup.py` you can call executable
```bash
repostat -gh PyTorchLightning/pytorch-lightning-bolts -t
```
or package with a pythonic way
```bash
python -m repo_stats -gh PyTorchLightning/pytorch-lightning-bolts
```
just note that with this way usage should also consider passing `-o` argument for output path, otherwise all caches and results will be saved in installation folder, most likely _site-packages_
To simplify the token passing in each call, you can export the token to environment variables `export GH_API_TOKEN=` for Github.
### Github use-case
For GitHub users we recommend using your personal GitHub token which significantly increases [request limit](https://developer.github.com/v3/#rate-limiting) per hour.
### Extra options
The calls above just pull the data, to get/show some results check available options `python -m repo_stats.cli --help`
- To see following summary table use `--users_summary "merged PRs" "commented PRs" "opened issues" "commented issues"` where the fist column is used for sorting rows with users:
| user | merged PRs | commented PRs | opened issues | commented issues |
| :------------------------------------------------ | ---------: | ------------: | ------------: | ---------------: |
| [williamFalcon](https://github.com/williamFalcon) | 74 | 21 | 14 | 8 |
| [Borda](https://github.com/Borda) | 42 | 35 | 4 | 18 |
| [akihironitta](https://github.com/akihironitta) | 17 | 1 | 5 | 5 |
| [ananyahjha93](https://github.com/ananyahjha93) | 14 | 2 | 6 | 21 |
| [annikabrundyn](https://github.com/annikabrundyn) | 12 | 0 | 0 | 2 |
| [djbyrne](https://github.com/djbyrne) | 11 | 2 | 4 | 4 |
| [nateraw](https://github.com/nateraw) | 9 | 1 | 6 | 8 |
| [teddykoker](https://github.com/teddykoker) | 3 | 2 | 0 | 0 |
- With `--min_contribution N` you can a simple filter what is the minimal number of contribution to show users in Table or Figures.
- You can also define a time frame with `--date_from` and `--date_to` for filtering events - created issues, merged PRs and comments/reviews.
- We also offer showing some contribution aggregation over time such as Day/Week/Month/Year, to do you use option `--user_comments W` which draw following double chart: (a) cumulative aggregation over all users and (b) heatmap like image with time in Y and user in X axis.
Moreover, you can also specify type such as issue or PR; so with `--user_comments W issue pr` you can simply get two figures - one with weekly aggregation for issue and another for PRs.
The very same way you can specify multiple time sampling `--user_comments W M` for weekly and monthly aggregations.
To deny showing figures set environment variable `export SHOW_FIGURES=0`.
## Contribution
Any help or suggestions are welcome, pls use Issues :\]