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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 environment

Run the following commands to create an ANTA development environment:

# Clone repository
$ git clone
$ 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    0.14.0   /mnt/lab/projects/anta

Then, tox is configured 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/ 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/ 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>.py.

How to write a unit test for an AntaTest subclass

The Python modules in the tests/units/anta_tests folder define test parameters for AntaTest subclasses unit tests. A generic test function is written for all unit tests in tests.lib.anta module. The pytest_generate_tests function definition in is called during test collection. The pytest_generate_tests function will parametrize the generic test function based on the DATA data structure defined in tests.units.anta_tests modules. See

The DATA structure is a list of dictionaries used to parametrize the test. The list elements have the following keys: - name (str): Test name as displayed by Pytest. - test (AntaTest): An AntaTest subclass imported in the test module - e.g. VerifyUptime. - eos_data (list[dict]): List of data mocking EOS returned data to be passed to the test. - inputs (dict): Dictionary to instantiate the test inputs as defined in the class from test. - expected (dict): Expected test result structure, a dictionary containing a key result containing one of the allowed status (Literal['success', 'failure', 'unset', 'skipped', 'error']) and optionally a key messages which is a list(str) and each message is expected to be a substring of one of the actual messages in the TestResult object.

In order for your unit tests to be correctly collected, you need to import the generic test function even if not used in the Python module.

Test example for anta.tests.system.VerifyUptime AntaTest.

# Import the generic test function
from tests.lib.anta import test  # noqa: F401

# Import your AntaTest
from anta.tests.system import VerifyUptime

# Define test parameters
DATA: list[dict[str, Any]] = [
        # Arbitrary test name
        "name": "success",
        # Must be an AntaTest definition
        "test": VerifyUptime,
        # Data returned by EOS on which the AntaTest is tested
        "eos_data": [{"upTime": 1186689.15, "loadAvg": [0.13, 0.12, 0.09], "users": 1, "currentTime": 1683186659.139859}],
        # Dictionary to instantiate VerifyUptime.Input
        "inputs": {"minimum": 666},
        # Expected test result
        "expected": {"result": "success"},
        "name": "failure",
        "test": VerifyUptime,
        "eos_data": [{"upTime": 665.15, "loadAvg": [0.13, 0.12, 0.09], "users": 1, "currentTime": 1683186659.139859}],
        "inputs": {"minimum": 666},
        # If the test returns messages, it needs to be expected otherwise test will fail.
        # NB: expected messages only needs to be included in messages returned by the test. Exact match is not required.
        "expected": {"result": "failure", "messages": ["Device uptime is 665.15 seconds"]},

Git Pre-commit hook

pip install pre-commit
pre-commit install

When running a commit or a pre-commit check:

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

************* Module test C0114: Missing module docstring (missing-module-docstring) E0401: Unable to import 'foobaz' (import-error) 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


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, 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=
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.

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 -e -b 8192

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.