np_data_validator_2
Very first steps
Initialize your code
- Initialize
git
inside your repo:
cd np_data_validator_2 && git init
- If you don't have
Poetry
installed run:
make poetry-download
- Initialize poetry and install
pre-commit
hooks:
make install
make pre-commit-install
- Run the codestyle:
make codestyle
- Upload initial code to GitHub:
git add .
git commit -m ":tada: Initial commit"
git branch -M main
git remote add origin https://github.com/np_data_validator_2/np_data_validator_2.git
git push -u origin main
Set up bots
- Set up Dependabot to ensure you have the latest dependencies.
- Set up Stale bot for automatic issue closing.
Poetry
Want to know more about Poetry? Check its documentation.
Details about Poetry
Poetry's commands are very intuitive and easy to learn, like:
poetry add numpy@latest
poetry run pytest
poetry publish --build
etc
Building and releasing your package
Building a new version of the application contains steps:
- Bump the version of your package
poetry version <version>
. You can pass the new version explicitly, or a rule such as major
, minor
, or patch
. For more details, refer to the Semantic Versions standard. - Make a commit to
GitHub
. - Create a
GitHub release
. - And... publish 🙂
poetry publish --build
🎯 What's next
Well, that's up to you 💪🏻. I can only recommend the packages and articles that helped me.
Typer
is great for creating CLI applications.Rich
makes it easy to add beautiful formatting in the terminal.Pydantic
– data validation and settings management using Python type hinting.Loguru
makes logging (stupidly) simple.tqdm
– fast, extensible progress bar for Python and CLI.IceCream
is a little library for sweet and creamy debugging.orjson
– ultra fast JSON parsing library.Returns
makes you function's output meaningful, typed, and safe!Hydra
is a framework for elegantly configuring complex applications.FastAPI
is a type-driven asynchronous web framework.
Articles:
🚀 Features
Development features
Deployment features
Installation
pip install -U np_data_validator_2
or install with Poetry
poetry add np_data_validator_2
Then you can run
np_data_validator_2 --help
or with Poetry
:
poetry run np_data_validator_2 --help
Makefile usage
Makefile
contains a lot of functions for faster development.
1. Download and remove Poetry
To download and install Poetry run:
make poetry-download
To uninstall
make poetry-remove
2. Install all dependencies and pre-commit hooks
Install requirements:
make install
Pre-commit hooks coulb be installed after git init
via
make pre-commit-install
3. Codestyle
Automatic formatting uses pyupgrade
, isort
and black
.
make codestyle
make formatting
Codestyle checks only, without rewriting files:
make check-codestyle
Note: check-codestyle
uses isort
, black
and darglint
library
Update all dev libraries to the latest version using one comand
make update-dev-deps
4. Code security
make check-safety
This command launches Poetry
integrity checks as well as identifies security issues with Safety
and Bandit
.
make check-safety
5. Type checks
Run mypy
static type checker
make mypy
6. Tests with coverage badges
Run pytest
make test
7. All linters
Of course there is a command to rule run all linters in one:
make lint
the same as:
make test && make check-codestyle && make mypy && make check-safety
8. Docker
make docker-build
which is equivalent to:
make docker-build VERSION=latest
Remove docker image with
make docker-remove
More information about docker.
9. Cleanup
Delete pycache files
make pycache-remove
Remove package build
make build-remove
Delete .DS_STORE files
make dsstore-remove
Remove .mypycache
make mypycache-remove
Or to remove all above run:
make cleanup
📈 Releases
You can see the list of available releases on the GitHub Releases page.
We follow Semantic Versions specification.
We use Release Drafter
. As pull requests are merged, a draft release is kept up-to-date listing the changes, ready to publish when you’re ready. With the categories option, you can categorize pull requests in release notes using labels.
List of labels and corresponding titles
Label | Title in Releases |
---|
enhancement , feature | 🚀 Features |
bug , refactoring , bugfix , fix | 🔧 Fixes & Refactoring |
build , ci , testing | 📦 Build System & CI/CD |
breaking | 💥 Breaking Changes |
documentation | 📝 Documentation |
dependencies | ⬆️ Dependencies updates |
You can update it in release-drafter.yml
.
GitHub creates the bug
, enhancement
, and documentation
labels for you. Dependabot creates the dependencies
label. Create the remaining labels on the Issues tab of your GitHub repository, when you need them.
🛡 License
![License](https://img.shields.io/github/license/np_data_validator_2/np_data_validator_2)
This project is licensed under the terms of the MIT
license. See LICENSE for more details.
📃 Citation
@misc{np_data_validator_2,
author = {np_data_validator_2},
title = {Awesome `np_data_validator_2` is a Python cli/package created with https://github.com/TezRomacH/python-package-template},
year = {2022},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/np_data_validator_2/np_data_validator_2}}
}
Credits ![🚀 Your next Python package needs a bleeding-edge project structure.](https://img.shields.io/badge/python--package--template-%F0%9F%9A%80-brightgreen)
This project was generated with python-package-template