Code Quality Principles#
When writing a code snippet, remember the saying: “code is read more than written”. We want to maintain our code maintainable, readable and high quality.
Linting & Formatting#
To maintain code quality, we use Ruff as a linter and code formatter. A linter analyzes code to identify and flag potential errors, stylistic issues, and code that doesn’t adhere to defined standards (such as PEP8). A code formatter automatically restructures the code to ensure it is consistently styled and properly formatted, making it consistent across the code base.
Run ruff format to format all Python files:
poetry run ruff format .
Run ruff check to check for style and other issues. Many common warnings can be automatically fixed with the --fix flag:
poetry run ruff check tidy3d --fix
The configuration defining what ruff will correct lives in pyproject.toml under the [tool.ruff] section.
When submitting code, for tests to pass, ruff should give no warnings.
Documentation#
Document all code you write using NumPy-style docstrings.
Testing#
Here we will discuss how tests are defined and run in Tidy3d.
Unit Testing#
The tests live in tests/ directory.
We use pytest package for our testing.
To run all of the tests, call:
poetry run pytest -rA tests
This command will trigger pytest to go through each file in tests/ called test*.py and run each function in that file with a name starting with test.
If all of these functions run without any exceptions being raised, the tests pass!
The specific configuration we use for pytest lives in the [tool.pytest.ini_options] section of pyproject.toml.
These tests are automatically run when code is submitted using GitHub Actions, which tests on Python 3.9 through 3.12 running on Ubuntu, MacOS, and Windows operating systems, as well as Flexcompute’s servers.
Note: The -rA flag is optional but produces output that is easily readable.
Note: You may notice warnings and errors in the pytest output, this is because many of the tests intentionally trigger these warnings and errors to ensure they occur in certain situations. The important information about the success of the test is printed out at the bottom of the pytest output for each file.
To get a code coverage report:
pip install pytest-cov
if not already installed
To run coverage tests with results printed to STDOUT:
pytest tests --cov-report term-missing --cov=tidy3d
To run coverage tests and get output as .html (more intuitive):
pytest tests --cov-report=html --cov=tidy3d
open htmlcov/index.html
Automated Testing#
We use GitHub Actions to perform these tests automatically and across different operating systems.
On commits, each of the pytest tests are run using Python 3.9 - 3.12 installed on Ubuntu, MacOS, and Windows operating systems.
See the “actions” tab for details on previous tests and .github/workflows/run_tests.yml for the configuration and to see the specific tests run.
See this for more explanation.
Other Tests#
There are additional tests in both the documentation and our private backend code. The same practices outlined here apply to those tests.
More Resources on Testing#
A useful explanation for those curious to learn more about the reasoning behind these decisions:
https://www.youtube.com/watch?v=DhUpxWjOhME <https://www.youtube.com/watch?v=DhUpxWjOhME>