Developing¶

If you already cloned the repository and you know that you need to deep dive in the code, here are some guidelines to set up your environment.

Commits¶

When making commits, use semantic commit messages system.

Format: <type>(<scope>): <subject>

Where <scope> is optional.

feat: add synchronous RabbitMQ wrapper
^--^  ^------------^
|     |
|     +-> Summary in present tense.
|
+-------> Type: chore, docs, feat, fix, refactor, style, or test.

More Examples:

feat: (New feature for the user, not a new feature for build script)
fix: (Bug fix for the user, not a fix to a build script)
docs: (Changes to the documentation)
style: (Formatting, linting)
refactor: (Refactoring code, eg. renaming a variable)
test: (Adding missing tests, refactoring tests)
chore: (Updating grunt tasks etc.)

References:

Virtual environment with `venv`¶

You can create a virtual environment in a directory using Python's venv module:

python -m venv venv

That will create a directory ./venv/ with the Python binaries and then you will be able to install packages for that isolated environment.

Activate the environment¶

Activate the new environment with:

source ./venv/bin/activate

Make sure you have the latest pip version on your virtual environment to

python -m pip install --upgrade pip

pip¶

After activating the environment as described above:

pip install -e ".[dev]"

It will install all the dependencies and your local Propan in your local environment.

Using your local Propan¶

If you create a Python file that imports and uses Propan, and run it with the Python from your local environment, it will use your local Propan source code.

And if you update that local Propan source code, as it is installed with -e, when you run that Python file again, it will use the fresh version of Propan you just edited.

That way, you don't have to "install" your local version to be able to test every change.

To use your local Propan CLI type:

python -m propan ...

Tests¶

Pytest¶

To run tests with your current Propan application and Python environment use:

pytest tests
# or
bash ./scripts/test.sh
# with coverage output
bash ./scripts/test-cov.sh

There are some pytest marks at project:

slow
rabbit
nats
sqs
kafka
redis
all

Default pytest calling runs "not slow" tests.

To run all tests use:

pytest -m 'all'

Also if you didn't up local rabbit or nats intance, run tests without that dependencies

pytest -m 'not rabbit and not nats'

To run all tests based on RabbitMQ, NATS or another dependencies you should run first following docker-compose.yml

version: "3"

services:
  rabbit:
    image: rabbitmq:3
    ports:
      - 5672:5672

  redis:
    image: redis:alpine3.18
    ports:
      - 6379:6379

  nats:
    image: nats
    command: -js
    ports:
      - 4222:4222
      - 8222:8222  # management

  kafka:
    image: bitnami/kafka:3.5.0
    ports:
      - 9092:9092
    environment:
      - KAFKA_ENABLE_KRAFT=yes
      - KAFKA_CFG_NODE_ID=1
      - KAFKA_CFG_PROCESS_ROLES=broker,controller
      - KAFKA_CFG_CONTROLLER_LISTENER_NAMES=CONTROLLER
      - KAFKA_CFG_LISTENERS=PLAINTEXT://:9092,CONTROLLER://:9093
      - KAFKA_CFG_LISTENER_SECURITY_PROTOCOL_MAP=CONTROLLER:PLAINTEXT,PLAINTEXT:PLAINTEXT
      - KAFKA_CFG_ADVERTISED_LISTENERS=PLAINTEXT://127.0.0.1:9092
      - KAFKA_BROKER_ID=1
      - KAFKA_CFG_CONTROLLER_QUORUM_VOTERS=1@kafka:9093
      - ALLOW_PLAINTEXT_LISTENER=yes

  sqs:
    image: softwaremill/elasticmq-native
    ports:
      - 9324:9324

docker compose up -d

Hatch¶

If you are using hatch use following environments to run tests:

TEST¶

Run tests at all python 3.7-3.11 versions.

All python versions should be avalilable at your system.

# Run fast smoketesting at all python 3.7-3.11 versions
hatch run test:run

# Run all tests at all python versions
hatch run test:run-all

TEST-LAST¶

Run tests at python 3.11 version.

# Run smoke tests at python 3.11
hatch run test-last:run

# Run all tests at python 3.11
hatch run test-last:run-all

# Run all tests at python 3.11 and show coverage
hatch run test-last:cov