Tooling to track and visualize engagement with the mrpowers-io organization
ampere is available as a CLI tool and a self-hosted web application (dagster scheduled jobs, fastapi api, and plotly dash frontend)
- create a virtual env via
uv venv
- add the package to the virtual env via
uv add ampere-meter
- see available cli commands via
uv run ampere --help
orsource .venv/bin/activate && ampere --help
- run
pip install ampere-meter
- see available cli commands via
ampere --help
Warning
the package is not bottled so this will build from source (might take a few minutes)
- run
brew tap jeffbrennan/homebrew-ampere-meter && brew install ampere-meter
- see available cli commands via
ampere --help
Warning
this is a work in progress and init scripts are not yet available
- clone the repository
- configure required environment variables in
.env
- refer to.env.example
- run
uv sync --all-extras
to build the full .venv docker compose up --build
to start the api, backend, and frontend services
documentation available at https://api-ampere.jeffbrennan.dev/docs
currently supports three endpoints:
/repos
- list of current repos/feed
- recent github activity (stars, issues, prs, etc.)/downloads
- pypi download statistics (hourly, daily, weekly, monthly)
model definitions are available in the models directory
updated 4 times a day
- repos
- stars
- issues
- commits
- forks
- releases
- pull requests
updated daily
- python release downloads grouped by package version, python version, operating system, cloud platform
additionally gets download statistics for core project dependencies
- pyspark
- deltalake
Weekly github metrics
- stars
- issues
- commits
Weekly download statistics. Currently only includes python release downloads
- overall
- package version
- python version
- cloud platform
scrolling, color-coded table of recent organization activity
- stars
- issues
- commits
- forks
- pull requests
summary and details of current issues
- summary: open issues, median issue age, issues closed this month
- details: repo, author title, body, date, days old, comments
each star is a node, and people who have starred multiple repositories are connected to each other density of lines indicates common groups of stars edges of each cluster indicate users who have only starred one repository
each user is a node, internal (another organization user) followers and following are connected includes any user with a record in one of these tables:
- stg_stargazers
- stg_forks
- stg_commits
- stg_issues
- stg_pull_requests
blue edges are a mutual connection, grey edges are one-way color of node indicates number of followers
percentage of internal followers and following computed against user total followers and following
data quality page indicating the last time each data source was updated and the number of records in each table
repo summaries and links
This project is build with an open source (d)ata stack:
- Dagster: data orchestration
- Dash: visualization
- Delta: raw data storage
- dbt: data transformation
- Docker: containerization
- DuckDB: database
- dark mode
- page load speed
- mobile improvements
- create API
- create init scripts for first time setup
- add tests for API, CLI, and web application
- and github actions to run tests, linting checks
- publish to pypi
- add
ampere
tomrpowers-io
organization