https://github.com/dense-analysis/dense-python
A template for creating new Python projects
https://github.com/dense-analysis/dense-python
Last synced: 5 months ago
JSON representation
A template for creating new Python projects
- Host: GitHub
- URL: https://github.com/dense-analysis/dense-python
- Owner: dense-analysis
- License: mit
- Created: 2025-07-06T10:26:56.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-07-12T11:43:36.000Z (12 months ago)
- Last Synced: 2025-10-26T13:56:36.973Z (8 months ago)
- Language: Dockerfile
- Size: 16.6 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Example Project
This project serves as a template for creating Python projects in the Dense
Analysis preferred manner. See Development steps below for initial setup, and
after boostraping a new project edit project files as you see fit to start off
your Python project.
**NOTE:** This project template is released to the public domain free of charge,
and you may freely remove and replace the `LICENSE` file and copyright notice
when building your projects so you may use a license of our choice without
crediting Dense Analysis. We simply wish to help you get started with Python
projects quickly.
## Development
Set up virtualenv initially for local development like so:
```sh
pyenv install
python -m pip install uv
uv sync
```
If you are creating a new project, you can quickly set it up with the
convenience script, which will delete itself after it's run.
```sh
./bootstrap-project.sh new_project_name
```
You can check the project for errors like so:
```sh
# Run the linter and autofix warnings/errors.
uv run ruff check --fix
# Run the type checker to spot typing issues.
uv run pyright
# Run unit and integration tests.
uv run pytest
```
To add dependencies, use one of the following commands:
```sh
uv add some_package
uv add --dev some_package
```
You can run the project with `docker compose` like so:
```sh
docker compose up
```
You can test the docker image like so:
```sh
docker build --no-cache -t example_project:latest .
docker run -it --rm example_project:latest
```