Contributions

How to contribute to ANTA¶

Contribution model is based on a fork-model. Don’t push to arista-netdevops-community/anta directly. Always do a branch in your forked repository and create a PR.

To help development, open your PR as soon as possible even in draft mode. It helps other to know on what you are working on and avoid duplicate PRs.

Create a development environement¶

Run the following commands to create an ANTA development environement:

# Clone repository
$ git clone https://github.com/arista-netdevops-community/anta.git
$ cd anta

# Install ANTA in editable mode and its development tools
$ pip install -e .[dev]

# Verify installation
$ pip list -e
Package Version Editable project location
------- ------- -------------------------
anta    0.7.2   /mnt/lab/projects/anta

Then, tox is configued with few environments to run CI locally:

$ tox list -d
default environments:
clean  -> Erase previous coverage reports
lint   -> Check the code style
type   -> Check typing
py38   -> Run pytest with py38
py39   -> Run pytest with py39
py310  -> Run pytest with py310
py311  -> Run pytest with py311
report -> Generate coverage report

Code linting¶

tox -e lint
[...]
lint: commands[0]> black --check --diff --color .
All done! ✨ 🍰 ✨
104 files would be left unchanged.
lint: commands[1]> isort --check --diff --color .
Skipped 7 files
lint: commands[2]> flake8 --max-line-length=165 --config=/dev/null anta
lint: commands[3]> flake8 --max-line-length=165 --config=/dev/null tests
lint: commands[4]> pylint anta

--------------------------------------------------------------------
Your code has been rated at 10.00/10 (previous run: 10.00/10, +0.00)

.pkg: _exit> python /Users/guillaumemulocher/.pyenv/versions/3.8.13/envs/anta/lib/python3.8/site-packages/pyproject_api/_backend.py True setuptools.build_meta
  lint: OK (19.26=setup[5.83]+cmd[1.50,0.76,1.19,1.20,8.77] seconds)
  congratulations :) (19.56 seconds)

Code Typing¶

tox -e type

[...]
type: commands[0]> mypy --config-file=pyproject.toml anta
Success: no issues found in 52 source files
.pkg: _exit> python /Users/guillaumemulocher/.pyenv/versions/3.8.13/envs/anta/lib/python3.8/site-packages/pyproject_api/_backend.py True setuptools.build_meta
  type: OK (46.66=setup[24.20]+cmd[22.46] seconds)
  congratulations :) (47.01 seconds)

NOTE: Typing is configured quite strictly, do not hesitate to reach out if you have any questions, struggles, nightmares.

Unit tests¶

To keep high quality code, we require to provide a Pytest for every tests implemented in ANTA.

All submodule should have its own pytest section under tests/units/anta_tests/<submodule-name>. In this directory, you should have 3 files:

__init__.py: Just because it is used as a python module
data.py: Where all your parametrize go. So all your test information should be located here
test_exc.py: Pytest file with test definition.

A pytest definition should be similar to this template:

"""
Tests for anta.tests.hardware.py
"""
from __future__ import annotations

import asyncio
import logging
from typing import Any
from unittest.mock import MagicMock

import pytest

from anta.tests.hardware import VerifyAdverseDrops
from tests.lib.utils import generate_test_ids_list

from .data import INPUT_<TEST_NAME>

@pytest.mark.parametrize("test_data", INPUT_<TEST_NAME>, ids=generate_test_ids_list(INPUT_<TEST_NAME>))
def test_<TEST_CASE>(mocked_device: MagicMock, test_data: Any) -> None:
    """Check <TEST_CASE>."""

    test = <TEST_CASE>(mocked_device, eos_data=test_data["eos_data"])
    asyncio.run(test.test())

    logging.debug(f"test result is: {test.result}")

    assert str(test.result.name) == mocked_device.name
    assert test.result.result == test_data["expected_result"]

The mocked_device object is a fixture defined in Pytest to represent an InventoryDevice and the parametrize test_data is a list of dictionries with structure:

INPUT_RUNNING_CONFIG: List[Dict[str, Any]] = [
  # Test Case #1
    {
        "name": "failure",
        "eos_data": ["blah blah"],
        "side_effect": None,
        "expected_result": "failure",
        "expected_messages": ["blah blah"]
    },
    # Test Case #2
    {
      ...
    },
]

Where we have:

name: Name of the test displayed by Pytest
eos_data: a list of data coming from EOS.
side_effect: used to inject template and test parameters (look for some examples in the existing tests)
expected_result: Result we expect for this test
expected_messages: Optional messages we expect for the test.

Use Anta CLI to get test data

To complete this block, you can use anta debug commands to get AntaCommand output to use in your test.

Git Pre-commit hook¶

pip install pre-commit
pre-commit install

When running a commit or a pre-commit check:

❯ echo "import foobaz" > test.py && git add test.py
❯ pre-commit
pylint...................................................................Failed
- hook id: pylint
- exit code: 22

************* Module test
test.py:1:0: C0114: Missing module docstring (missing-module-docstring)
test.py:1:0: E0401: Unable to import 'foobaz' (import-error)
test.py:1:0: W0611: Unused import foobaz (unused-import)

NOTE: It could happen that pre-commit and tox disagree on something, in that case please open an issue on Github so we can take a look.. It is most probably wrong configuration on our side.

Configure MYPYPATH¶

In some cases, mypy can complain about not having MYPYPATH configured in your shell. It is especially the case when you update both an anta test and its unit test. So you can configure this environment variable with:

# Option 1: use local folder
export MYPYPATH=.

# Option 2: use absolute path
export MYPYPATH=/path/to/your/local/anta/repository

Documentation¶

mkdocs is used to generate the documentation. A PR should always update the documentation to avoid documentation debt.

Install documentation requirements¶

Run pip to install the documentation requirements from the root of the repo:

pip install -e .[doc]

Testing documentation¶

You can then check locally the documentation using the following command from the root of the repo:

mkdocs serve

By default, mkdocs listens to http://127.0.0.1:8000/, if you need to expose the documentation to another IP or port (for instance all IPs on port 8080), use the following command:

mkdocs serve --dev-addr=0.0.0.0:8080

Build class diagram¶

To build class diagram to use in API documentation, you can use pyreverse part of pylint with graphviz installed for jpeg generation.

pyreverse anta --colorized -a1 -s1 -o jpeg -m true -k --output-directory docs/imgs/uml/ -c <FQDN anta class>

Image will be generated under docs/imgs/uml/ and can be inserted in your documentation.

Checking links¶

Writing documentation is crucial but managing links can be cumbersome. To be sure there is no dead links, you can use muffet with the following command:

muffet -c 2 --color=always http://127.0.0.1:8000 -e fonts.gstatic.com

Continuous Integration¶

GitHub actions is used to test git pushes and pull requests. The workflows are defined in this directory. We can view the results here.

Last update: August 10, 2023