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CONTRIBUTING.md

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Hi there, thank you for your interest in contributing! Please read the contribution guidelines below, before submitting your first pull request to the InvenTree codebase.

Quickstart

The following commands will get you quickly configure and run a development server, complete with a demo dataset to work with:

Bare Metal

git clone https://github.com/inventree/InvenTree.git && cd InvenTree
python3 -m venv env && source env/bin/activate
pip install invoke && invoke
pip install invoke && invoke setup-dev --tests

Docker

git clone https://github.com/inventree/InvenTree.git && cd InvenTree
docker compose run inventree-dev-server invoke install
docker compose run inventree-dev-server invoke setup-test --dev
docker compose up -d

Read the InvenTree setup documentation for a complete installation reference guide.

Setup Devtools

Run the following command to set up all toolsets for development.

invoke setup-dev

We recommend you run this command before starting to contribute. This will install and set up pre-commit to run some checks before each commit and help reduce errors.

Branches and Versioning

InvenTree roughly follow the GitLab flow branching style, to allow simple management of multiple tagged releases, short-lived branches, and development on the main branch.

Version Numbering

InvenTree version numbering follows the semantic versioning specification.

Master Branch

The HEAD of the "main" or "master" branch of InvenTree represents the current "latest" state of code development.

  • All feature branches are merged into master
  • All bug fixes are merged into master

No pushing to master: New features must be submitted as a pull request from a separate branch (one branch per feature).

Feature Branches

Feature branches should be branched from the master branch.

  • One major feature per branch / pull request
  • Feature pull requests are merged back into the master branch
  • Features may also be merged into a release candidate branch

Stable Branch

The HEAD of the "stable" branch represents the latest stable release code.

  • Versioned releases are merged into the "stable" branch
  • Bug fix branches are made from the "stable" branch

Release Candidate Branches

  • Release candidate branches are made from master, and merged into stable.
  • RC branches are targeted at a major/minor version e.g. "0.5"
  • When a release candidate branch is merged into stable, the release is tagged

Bugfix Branches

  • If a bug is discovered in a tagged release version of InvenTree, a "bugfix" or "hotfix" branch should be made from that tagged release
  • When approved, the branch is merged back into stable, with an incremented PATCH number (e.g. 0.4.1 -> 0.4.2)
  • The bugfix must also be cherry picked into the master branch.

Environment

Target version

We are currently targeting:

Name Minimum version
Python 3.9
Django 3.2

Auto creating updates

The following tools can be used to auto-upgrade syntax that was depreciated in new versions:

pip install pyupgrade
pip install django-upgrade

To update the codebase run the following script.

pyupgrade `find . -name "*.py"`
django-upgrade --target-version 3.2 `find . -name "*.py"`

Credits

If you add any new dependencies / libraries, they need to be added to the docs. Please try to do that as timely as possible.

Migration Files

Any required migration files must be included in the commit, or the pull-request will be rejected. If you change the underlying database schema, make sure you run invoke migrate and commit the migration files before submitting the PR.

Note: A github action checks for unstaged migration files and will reject the PR if it finds any!

Unit Testing

Any new code should be covered by unit tests - a submitted PR may not be accepted if the code coverage for any new features is insufficient, or the overall code coverage is decreased.

The InvenTree code base makes use of GitHub actions to run a suite of automated tests against the code base every time a new pull request is received. These actions include (but are not limited to):

  • Checking Python and Javascript code against standard style guides
  • Running unit test suite
  • Automated building and pushing of docker images
  • Generating translation files

The various github actions can be found in the ./github/workflows directory

Run tests locally

To run test locally, use:

invoke test

To run only partial tests, for example for a module use:

invoke test --runtest order

To see all the available options:

invoke test --help

Code Style

Code style is automatically checked as part of the project's CI pipeline on GitHub. This means that any pull requests which do not conform to the style guidelines will fail CI checks.

Backend Code

Backend code (Python) is checked against the PEP style guidelines. Please write docstrings for each function and class - we follow the google doc-style for python.

Frontend Code

Frontend code (Javascript) is checked using eslint. While docstrings are not enforced for front-end code, good code documentation is encouraged!

Running Checks Locally

If you have followed the setup devtools procedure, then code style checking is performend automatically whenever you commit changes to the code.

Django templates

Django are checked by djlint through pre-commit.

The following rules out of the default set are not applied:

D018: (Django) Internal links should use the { % url ... % } pattern
H006: Img tag should have height and width attributes
H008: Attributes should be double quoted
H021: Inline styles should be avoided
H023: Do not use entity references
H025: Tag seems to be an orphan
H030: Consider adding a meta description
H031: Consider adding meta keywords
T002: Double quotes should be used in tags

Documentation

New features or updates to existing features should be accompanied by user documentation.

Translations

Any user-facing strings must be passed through the translation engine.

  • InvenTree code is written in English
  • User translatable strings are provided in English as the primary language
  • Secondary language translations are provided via Crowdin

Note: Translation files are updated via GitHub actions - you do not need to compile translations files before submitting a pull request!

Python Code

For strings exposed via Python code, use the following format:

from django.utils.translation import gettext_lazy as _

user_facing_string = _('This string will be exposed to the translation engine!')

Templated Strings

HTML and javascript files are passed through the django templating engine. Translatable strings are implemented as follows:

{ % load i18n % }

<span>{ % trans "This string will be translated" % } - this string will not!</span>

Github use

Tags

The tags describe issues and PRs in multiple areas:

Area Name Description
Triage Labels
triage:not-checked Item was not checked by the core team
triage:not-approved Item is not green-light by maintainer
Type Labels
breaking Indicates a major update or change which breaks compatibility
bug Identifies a bug which needs to be addressed
dependency Relates to a project dependency
duplicate Duplicate of another issue or PR
enhancement This is an suggested enhancement, extending the functionality of an existing feature
experimental This is a new experimental feature which needs to be enabled manually
feature This is a new feature, introducing novel functionality
help wanted Assistance required
invalid This issue or PR is considered invalid
inactive Indicates lack of activity
migration Database migration, requires special attention
question This is a question
roadmap This is a roadmap feature with no immediate plans for implementation
security Relates to a security issue
starter Good issue for a developer new to the project
wontfix No work will be done against this issue or PR
Feature Labels
API Relates to the API
barcode Barcode scanning and integration
build Build orders
importer Data importing and processing
order Purchase order and sales orders
part Parts
plugin Plugin ecosystem
pricing Pricing functionality
report Report generation
stock Stock item management
user interface User interface
Ecosystem Labels
backport Tags that the issue will be backported to a stable branch as a bug-fix
demo Relates to the InvenTree demo server or dataset
docker Docker / docker-compose
CI CI / unit testing ecosystem
refactor Refactoring existing code
setup Relates to the InvenTree setup / installation process