onedev-python-project-boilerplate 0.1.2

A short description of your project

Python project boiler plate

This project aims to make the building, and deployment of python packages and docker containers using OneDev as simple as possible.

Features

• publish to DockerHub
• publish to pypi
• sync with GitHub

TODO

• add shields.io
• branch protection settings setup

How to Setup

• Make a new OneDev repository and copy the contents of this repository into it.
• Update the following values in setup.py:
  • name
    • note: this sets the name used on DockerHub, PyPI, and GitHub
  • version
  • description
  • author
  • license
  • classifiers
  • install requires
  • extras_require
• Update the docker file:
  • add your contact info to the MAINTAINER line
  • CMD to whatever command starts your app
• Create a Repository on GitHub with the same name as your OneDev project
• In OneDev:
  • Edit step templates in the .onedev-buildspec.yaml file::
    • Execute tests:Run Pytest:
      • add command to run test suite(s) if not pytest
    • Publish Docker Container to Dockerhub: publish to dockerhub:
      • update username to your dockerhub username
  • Under Settings > Build > Job Secrets add
    • your DockerHub password as dockerhub_password
    • your DockerHub password as dockerhub_user
    • your PyPI password as pypi_password
    • your PyPI user as pypi_user
    • your GitHub user as github_user
    • your GitHub token as github_token
  • If there isn't already, make a 'Server Docker Executor' called docker-executor under Administration > Job Executors
• fill in your README.md and remove this section

Contibuting

Contributions are welcome, this project is developed at dev.doze.dev where you can submit issues and open pull requests.

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My Project

Describe what your package is about

Package Distribution

Installation

pip install my-project

Use

python ./src/main.py

Docker Distibution

Installation

docker pull docker_user/project_name:latest

Use

docker run -p 5000:5000 project_name

or for detached mode:

docker run -d -p 5000:5000 project_name