---
anta_title: How to contribute to ANTA
---
<!--
  ~ Copyright (c) 2023-2025 Arista Networks, Inc.
  ~ Use of this source code is governed by the Apache License 2.0
  ~ that can be found in the LICENSE file.
  -->

Contribution model is based on a fork-model. Don't push to aristanetworks/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:

```bash
# Clone repository
$ git clone https://github.com/aristanetworks/anta.git
$ cd anta

# Install ANTA in editable mode and its development tools
$ pip install -e .[dev]
# To also install the CLI
$ pip install -e .[dev,cli]

# Verify installation
$ pip list -e
Package Version Editable project location
------- ------- -------------------------
anta    1.4.0   /mnt/lab/projects/anta
```

!!! info "Installation Note"
    1. If you are using a terminal such as zsh, ensure that commands involving shell expansions within editable installs (like specifying development dependencies) are enclosed in double quotes. For example: `pip install -e ."[dev]"`
    2. If you do not see any output when running the verification command (`pip list -e`), it is likely because the command needs to be executed from within the inner `anta` directory. Navigate to this directory and then verify the installation:

     ```
      $ cd anta/anta
      # Verify installation
      $ pip list -e
      Package Version Editable project location
      ------- ------- --------------------------
      anta    1.4.0   /mnt/lab/projects/anta
     ```

Then, [`tox`](https://tox.wiki/) is configured with few environments to run CI locally:

```bash
$ tox list -d
default environments:
clean  -> Erase previous coverage reports
lint   -> Check the code style
type   -> Check typing
py39   -> Run pytest with py39
py310  -> Run pytest with py310
py311  -> Run pytest with py311
py312  -> Run pytest with py312
report -> Generate coverage report
```

### Code linting

```bash
tox -e lint
[...]
lint: commands[0]> ruff check .
All checks passed!
lint: commands[1]> ruff format . --check
158 files already formatted
lint: commands[2]> pylint anta

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

lint: commands[3]> pylint tests

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

  lint: OK (22.69=setup[2.19]+cmd[0.02,0.02,9.71,10.75] seconds)
  congratulations :) (22.72 seconds)
```

### Code Typing

```bash
tox -e type

[...]
type: commands[0]> mypy --config-file=pyproject.toml anta
Success: no issues found in 68 source files
type: commands[1]> mypy --config-file=pyproject.toml tests
Success: no issues found in 82 source files
  type: OK (31.15=setup[14.62]+cmd[6.05,10.48] seconds)
  congratulations :) (31.18 seconds)
```

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

## Unit tests with Pytest

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.units.anta_tests` module.

The `pytest_generate_tests` function definition in `conftest.py` 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 https://docs.pytest.org/en/7.3.x/how-to/parametrize.html#basic-pytest-generate-tests-example

The `DATA` structure is a dictionary where:

- Each key is a tuple of size 2 containing:
  - An AntaTest subclass imported in the test module as first element - e.g. VerifyUptime.
  - A string used as name displayed by pytest as second element.
- Each value is an instance of AntaUnitTest, which is a Python TypedDict.

And AntaUnitTest have the following keys:

- `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[AntaTestStatus.SUCCESS, AntaTestStatus.FAILURE, AntaTestStatus.SKIPPED]`) 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.

``` python
# Import the generic test function
from tests.units.anta_tests import test

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

# Define test parameters
DATA: dict[tuple[type[AntaTest], str], AntaUnitTest] = {
  (VerifyUptime, "success"): {
    # 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": AntaTestStatus.SUCCESS},
  },
  (VerifyUptime, "failure"): {
    # Data returned by EOS on which the AntaTest is tested
    "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": AntaTestStatus.FAILURE, "messages": ["Device uptime is 665.15 seconds"]},
  }
}
```

## Git Pre-commit hook

```bash
pip install pre-commit
pre-commit install
```

When running a commit or a pre-commit check:

``` bash
❯ pre-commit
trim trailing whitespace.................................................Passed
fix end of files.........................................................Passed
check for added large files..............................................Passed
check for merge conflicts................................................Passed
Check and insert license on Python files.................................Passed
Check and insert license on Markdown files...............................Passed
Run Ruff linter..........................................................Passed
Run Ruff formatter.......................................................Passed
Check code style with pylint.............................................Passed
Checks for common misspellings in text files.............................Passed
Check typing with mypy...................................................Passed
Check Markdown files style...............................................Passed
```

## 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:

```bash
# Option 1: use local folder
export MYPYPATH=.

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

## Documentation

[`mkdocs`](https://www.mkdocs.org/) 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:

```bash
pip install -e .[doc]
```

### Testing documentation

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

```bash
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:

```bash
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`](https://graphviz.org/) installed for jpeg generation.

```bash
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`](https://github.com/raviqqe/muffet) with the following command:

```bash
muffet -c 2 --color=always http://127.0.0.1:8000 -e fonts.gstatic.com -b 8192
```

## Continuous Integration

GitHub actions is used to test git pushes and pull requests. The workflows are defined in this [directory](https://github.com/aristanetworks/anta/tree/main/.github/workflows). The results can be viewed [here](https://github.com/aristanetworks/anta/actions).
