Coding conventions

Style

PEP 8 rules

We aspire to the Zen of Python

Enforced/auto-formatted via ruff ([tool.ruff] in pyproject.toml), line length 88.

docstrings

see detailed doc string conventions here

Package imports

At the top of each file we import packages in the following order

• Standard Python packages
• NumPy: import numpy as np
• SciPy: import script as sp
• Matplotlib
  • import matplotlib as mpl
  • import matplotlib.pyplot as ppt
  • import mpl_toolkits.mplot3d as mpl3d`
• Spatial Math Toolbox
  • import spatialmath as sm
  • from spatialmath import base
• Robotics Toolbox
  • for toolbox code, to avoid circular imports always just import the required class, eg. from roboticstoolbox.module import class
  • for application code, import roboticstoolbox as rtb
• all other imports

Unit testing

We use pytest

Code quality

We use codecov to analyse and display unit test coverage, we aim for over 90% coverage.

LGTM.com, previously used for static code-quality grading, shut down in December 2022 — RTB currently has no replacement quality-grade tool wired in (some sibling toolboxes use Codacy for this; it isn't set up on RTB).

Coding patterns

We strive to be Pythonic rather than MATLABish.

• we prefer for x in X rather than for i in range() and indexing. If X is a NumPy array then x iterates over matrix rows. If we do need an index as well as the object, then use enumerate().
• we test arguments for appropriateness and raise a ValueError or TypeError
• for argument checking we use spatialmath.base.argcheck
  • we test for a scalar argument using isscalar
  • we test for a vector argument using isvector which accepts a Python list, tuple or NumPy array