Contribution guidelines#

These guidelines instruct how to submit issues and contribute code or documentation to the Robocop project. Another way to contribute includes participating in discussion and answering questions on our Slack channel #robocop-linter located in Robot Framework workspace. We have some dedicated channels for all different types of topics. One of the best ways to support is to help us grow so don’t hesitate and spread the word about Robocop!

These guidelines expect readers to have a basic knowledge about open source as well as why and how to contribute to open source projects. If you are totally new to these topics, it may be a good idea to look at the generic Open Source Guides first.

Submitting issues#

Bugs and enhancements are tracked in the issue tracker.

Before submitting a new issue, it is always a good idea to check if the same bug or enhancement is already reported. If it is, please add your comments to the existing issue instead of creating a new one.

Reporting bugs#

They'll fix you. They fix everything. - Robocop

The preferred way to report a bug is to create an issue using Bug report template and fill in the blanks:

  1. Explanation of a bug

  2. Steps to reproduce the problem

  3. Output with error message

  4. Expected behavior

  5. Version information (Robocop version, Python version, operating system etc.)

Notice that all information in the issue tracker is public. Do not include any confidential information there.

Enhancement requests#

To suggest an idea for the project please create an issue using Feature request template. Try to write clear and concise description of why this should be useful and what needs to be done to accomplish the goal.

Code contributions#

If you have fixed a bug or implemented an enhancement, you can contribute your changes via GitHub’s pull requests. This is not restricted to code, on the contrary, fixes and enhancements to documentation and tests alone are also very valuable.

Pull requests#

On GitHub pull requests are the main mechanism to contribute code. They are easy to use both for the contributor and for the person accepting the contribution, and with more complex contributions it is easy also for others to join the discussion. Preconditions for creating pull requests are having a GitHub account, installing Git and forking the Robocop project.

GitHub has good articles explaining how to set up Git, fork a repository and use pull requests and we do not go through them in more detail. We do, however, recommend to create dedicated topic branches for pull requests instead of creating them based on the master branch. This is especially important if you plan to work on multiple pull requests at the same time.

Coding conventions#

Stay out of trouble. - Robocop

General guidelines#

Robocop uses the general Python code conventions defined in PEP-8. An important guideline is that the code should be clear enough that comments are generally not needed.

All code, including test code, must be compatible with all supported Python interpreters and versions. Most importantly this means that the code must support Python 3.8+ and Robot Framework 3.2.2+.

To ensure high quality of the code we use pylama static code analysis tool to check against common errors and mistakes. The tool needs to be run with configuration file pylama.ini located in the root of the repository. Execute the command before creating a pull request (you must have pylama installed):

pylama -o pylama.ini

Docstrings#

Docstrings should be added to public APIs, but they are not generally needed in internal code. When docstrings are added, they should follow PEP-257.

Documentation#

With new features adequate documentation is as important as the actual functionality. Different documentation is needed depending on the issue but most of it is located inside docs directory. The files are usually written using reStructuredText format (.rst).

To generate our documentation use nox tool that will create environment with required dependencies and generate the documentation. Documentation will be available under docs/_build/index.html path:

nox -s docs

User manual#

Robocop’s main features are explained in the README. The whole documentation is available here.

Pre-commit checks#

Every change is required to pass pre-commit checks. To install pre-commit tool run:

pip install pre-commit

Then install the pre-commits for this repository run in the root:

pre-commit install

Now all commits will trigger pre-commit script that will scan & format your code.

Tests#

When submitting a pull request with a new feature or a fix, you should always include tests for your changes. These tests prove that your changes work, help prevent bugs in the future, and help document what your changes do. Depending on the change, you may need acceptance tests, unit tests or both.

Make sure to run all of the tests before submitting a pull request to be sure that your changes do not break anything. Pull requests are also automatically tested on continuous integration.

Most of our tests use pytest. To use it install Robocop with dev profile:

pip install robotframework-robocop[dev]

To run pytest tests navigate to directory with test files and run:

pytest .

Pytest will automatically discover all the tests, run them and display results.

You can test a specific rule by providing a path to the related test_rule.py file, e.g.:

pytest tests/atest/rules/spacing/empty_lines_between_sections/test_rule.py

Make sure that tests do not fail.

Nox#

Robocop contains nox file for running the tests on all supported major Robot Framework versions and generating the coverage or docs. The nox tool will create the virtual environment and install required dependencies for you.

Follow installation instruction from the nox documentation page. To execute Robocop tests run:

nox

Run the following command to see all possible sessions (acting as environments or targets):

nox --list

You can select only one session per run. For example, to only run tests for Python==3.10 and Robot Framework==3.*:

nox --session "unit-3.10(rf='3')"

Unit tests#

Unit tests are great for testing internal logic and should be added when appropriate. They are located in tests/utest directory.

Acceptance tests#

Acceptance tests check if Robocop rules report issues in test data files.

They are located in tests/atest/rules/{rules_category} directories. Each rule has its subdirectory with the name of the rule. Hyphens in the name are replaced by underscores. For example, rule-name from comments category rule should have tests/atest/rules/comments/rule_name directory. Inside each directory there should be an empty __init__.py file, test_rule.py file containing pytest tests, test data and expected data used by the tests.

Acceptance tests should use tests.atest.utils.RuleAcceptance class that contains helper methods and assertions for the tests purpose. Example of a simple test:

from tests.atest.utils import RuleAcceptance


class TestRuleAcceptance(RuleAcceptance):
    def test_rule(self):
        self.check_rule(src_files=["test.robot"], expected_file="expected_output.txt")

In this example we’re invoking Robocop on test.robot file inside the same directory and we’re comparing reported issues with the content of the expected_output.txt file.

Example of the expected file:

test.robot:8:1 [E] 0803 Multiple variables with name '${V AR}' in Variables section (first occurrence in line 6). Note that Robot Framework is case-insensitive

Issues are reported using following format: {source}:{line}:{col} [{severity}] {rule_id} {desc}. If your test data file is inside subdirectory, the path to file should use ${/} as path separator:

suite_dir{/}__init__.robot:4:1 [W] 0806 Duplicated metadata 'some text' (first occurrence in line 2)

If the rule behaves differently depending on the Robot Framework version, or it is enabled only for specific version, it is possible to set target version of the tests using version specifiers:

from tests.atest.utils import RuleAcceptance


class TestRule(RuleAcceptance):
    def test_rule(self):
        self.check_rule(expected_file="expected_output.txt", target_version=">=5.0")

    def test_rule_rf3(self):
        self.check_rule(expected_file="expected_output_rf4.txt", target_version="==4.1.3")

    def test_rule_rf4(self):
        self.check_rule(expected_file="expected_output_rf3.txt", target_version="==3.2.2")

You can provide custom configuration for the rule using config argument. It accepts either string or list:

from tests.atest.utils import RuleAcceptance


class TestRuleAcceptance(RuleAcceptance):
    def test_configure_pattern(self):
        self.check_rule(
            config="-c not-allowed-char-in-filename:pattern:\.(?!bar)",
            src_files=["allowed_suite_foo.bar.robot", "suite.withdot"],
            expected_file="expected_output_configured.txt",
        )

Set expected_file to None if you expect the rule to not raise any issues during run:

self.check_rule(src_files=["golden.robot"], expected_file=None)

E2E tests#

Simple E2E tests are also included in repository in tests/e2e directory. They are being run automatically along with unit tests when pytest is executed.

Coverage#

Tests coverage cannot drop under 90%. If your changes affect the coverage significantly, please write new tests to satisfy the expected threshold, otherwise continuous integration will not permit to merge the changes.

To calculate coverage locally run:

coverage run -m pytest

and then:

coverage html

You can also use nox tool:

nox -s coverage

HTML files will be generated - navigate to htmlcov directory and open index.html file.

Thank you for your cooperation. Good night. - Robocop