doc/devel/coding_guide.rst
.. _coding_guidelines:
Coding guidelines
We appreciate these guidelines being followed because it improves the readability, consistency, and maintainability of the code base.
.. admonition:: API guidelines :class: seealso
If adding new features, changing behavior or function signatures, or removing
public interfaces, please consult the :ref:`api_changes`.
.. _code-style:
Formatting should follow the recommendations of PEP8_, as enforced by flake8_. Matplotlib modifies PEP8 to extend the maximum line length to 88 characters. You can check flake8 compliance from the command line with ::
python -m pip install flake8
flake8 /path/to/module.py
or your editor may provide integration with it. Note that Matplotlib intentionally does not use the black_ auto-formatter (1__), in particular due to its inability to understand the semantics of mathematical expressions (2__, 3__).
.. _PEP8: https://www.python.org/dev/peps/pep-0008/ .. _flake8: https://flake8.pycqa.org/ .. _black: https://black.readthedocs.io/ .. __: https://github.com/matplotlib/matplotlib/issues/18796 .. __: https://github.com/psf/black/issues/148 .. __: https://github.com/psf/black/issues/1984
Import the following modules using the standard scipy conventions::
import numpy as np import numpy.ma as ma import matplotlib as mpl import matplotlib.pyplot as plt import matplotlib.cbook as cbook import matplotlib.patches as mpatches
In general, Matplotlib modules should not import .rcParams using from matplotlib import rcParams, but rather access it as mpl.rcParams. This
is because some modules are imported very early, before the .rcParams
singleton is constructed.
When feasible, please use our internal variable naming convention for objects of a given class and objects of any child class:
+------------------------------------+---------------+------------------------------------------+
| base class | variable | multiples |
+====================================+===============+==========================================+
| ~matplotlib.figure.FigureBase | fig | |
+------------------------------------+---------------+------------------------------------------+
| ~matplotlib.axes.Axes | ax | |
+------------------------------------+---------------+------------------------------------------+
| ~matplotlib.transforms.Transform | trans | trans_<source>_<target> |
+ + +
| | | trans_<source> when target is screen |
+------------------------------------+---------------+------------------------------------------+
Generally, denote more than one instance of the same class by adding suffixes to the variable names. If a format isn't specified in the table, use numbers or letters as appropriate.
.. _type-hints:
If you add new public API or change public API, update or add the
corresponding mypy <https://mypy.readthedocs.io/en/latest/>_ type hints.
We generally use stub files <https://typing.readthedocs.io/en/latest/source/stubs.html#type-stubs>_
(*.pyi) to store the type information; for example colors.pyi contains
the type information for colors.py. A notable exception is pyplot.py,
which is type hinted inline.
Type hints can be validated by the stubtest <https://mypy.readthedocs.io/en/stable/stubtest.html>_ tool, which can be run
locally using tox -e stubtest and is a part of the :ref:automated-tests
suite. Type hints for existing functions are also checked by the mypy
:ref:pre-commit hook <pre-commit-hooks>.
meson.build in the corresponding directories.Extensions may be written in C or C++.
Code style should conform to PEP7 (understanding that PEP7 doesn't address C++, but most of its admonitions still apply).
Python/C interface code should be kept separate from the core C/C++
code. The interface code should be named :file:FOO_wrap.cpp or
:file:FOO_wrapper.cpp.
Header file documentation (aka docstrings) should be in Numpydoc format. We don't plan on using automated tools for these docstrings, and the Numpydoc format is well understood in the scientific Python community.
C/C++ code in the :file:extern/ directory is vendored, and should be kept
close to upstream whenever possible. It can be modified to fix bugs or
implement new features only if the required changes cannot be made elsewhere
in the codebase. In particular, avoid making style fixes to it.
.. _keyword-argument-processing:
Matplotlib makes extensive use of **kwargs for pass-through customizations
from one function to another. A typical example is
~matplotlib.axes.Axes.text. The definition of matplotlib.pyplot.text is a
simple pass-through to matplotlib.axes.Axes.text::
def text(x, y, s, fontdict=None, **kwargs): return gca().text(x, y, s, fontdict=fontdict, **kwargs)
matplotlib.axes.Axes.text (simplified for illustration) just
passes all args and kwargs on to matplotlib.text.Text.__init__::
def text(self, x, y, s, fontdict=None, **kwargs): t = Text(x=x, y=y, text=s, **kwargs)
and matplotlib.text.Text.__init__ (again, simplified)
just passes them on to the matplotlib.artist.Artist.update method::
def init(self, x=0, y=0, text='', **kwargs): super().init() self.update(kwargs)
update does the work looking for methods named like
set_property if property is a keyword argument. i.e., no one
looks at the keywords, they just get passed through the API to the
artist constructor which looks for suitably named methods and calls
them with the value.
As a general rule, the use of **kwargs should be reserved for
pass-through keyword arguments, as in the example above. If all the
keyword args are to be used in the function, and not passed
on, use the key/value keyword args in the function definition rather
than the **kwargs idiom.
In some cases, you may want to consume some keys in the local
function, and let others pass through. Instead of popping arguments to
use off **kwargs, specify them as keyword-only arguments to the local
function. This makes it obvious at a glance which arguments will be
consumed in the function. For example, in
:meth:~matplotlib.axes.Axes.plot, scalex and scaley are
local arguments and the rest are passed on as
:meth:~matplotlib.lines.Line2D keyword arguments::
def plot(self, *args, scalex=True, scaley=True, **kwargs): lines = [] for line in self._get_lines(*args, **kwargs): self.add_line(line) lines.append(line)
.. _using_logging:
Matplotlib uses the standard Python logging library to write verbose
warnings, information, and debug messages. Please use it! In all those places
you write print calls to do your debugging, try using logging.debug
instead!
To include logging in your module, at the top of the module, you need to
import logging. Then calls in your code like::
_log = logging.getLogger(name) # right after the imports
_log.info('Here is some information') _log.debug('Here is some more detailed information')
will log to a logger named matplotlib.yourmodulename.
If an end-user of Matplotlib sets up logging to display at levels more
verbose than logging.WARNING in their code with the Matplotlib-provided
helper::
plt.set_loglevel("debug")
or manually with ::
import logging logging.basicConfig(level=logging.DEBUG) import matplotlib.pyplot as plt
Then they will receive messages like
.. code-block:: none
DEBUG:matplotlib.backends:backend MacOSX version unknown DEBUG:matplotlib.yourmodulename:Here is some information DEBUG:matplotlib.yourmodulename:Here is some more detailed information
Avoid using pre-computed strings (f-strings, str.format,etc.) for logging because
of security and performance issues, and because they interfere with style handlers. For
example, use _log.error('hello %s', 'world') rather than _log.error('hello {}'.format('world')) or _log.error(f'hello {s}').
There are five levels at which you can emit messages.
logging.critical and logging.error are really only there for errors that
will end the use of the library but not kill the interpreter.logging.warning and ._api.warn_external are used to warn the user,
see below.logging.info is for information that the user may want to know if the
program behaves oddly. They are not displayed by default. For instance, if
an object isn't drawn because its position is NaN, that can usually
be ignored, but a mystified user could call
logging.basicConfig(level=logging.INFO) and get an error message that
says why.logging.debug is the least likely to be displayed, and hence can be the
most verbose. "Expected" code paths (e.g., reporting normal intermediate
steps of layouting or rendering) should only log at this level.By default, logging displays all log messages at levels higher than
logging.WARNING to sys.stderr.
The logging tutorial_ suggests that the difference between logging.warning
and ._api.warn_external (which uses warnings.warn) is that
._api.warn_external should be used for things the user must change to stop
the warning (typically in the source), whereas logging.warning can be more
persistent. Moreover, note that ._api.warn_external will by default only
emit a given warning once for each line of user code, whereas
logging.warning will display the message every time it is called.
By default, warnings.warn displays the line of code that has the warn
call. This usually isn't more informative than the warning message itself.
Therefore, Matplotlib uses ._api.warn_external which uses warnings.warn,
but goes up the stack and displays the first line of code outside of
Matplotlib. For example, for the module::
# in my_matplotlib_module.py
import warnings
def set_range(bottom, top):
if bottom == top:
warnings.warn('Attempting to set identical bottom==top')
running the script::
from matplotlib import my_matplotlib_module
my_matplotlib_module.set_range(0, 0) # set range
will display
.. code-block:: none
UserWarning: Attempting to set identical bottom==top
warnings.warn('Attempting to set identical bottom==top')
Modifying the module to use ._api.warn_external::
from matplotlib import _api
def set_range(bottom, top):
if bottom == top:
_api.warn_external('Attempting to set identical bottom==top')
and running the same script will display
.. code-block:: none
UserWarning: Attempting to set identical bottom==top my_matplotlib_module.set_range(0, 0) # set range
.. _logging tutorial: https://docs.python.org/3/howto/logging.html#logging-basic-tutorial
.. _licence-coding-guide:
.. include:: license.rst :start-line: 2
.. toctree:: :hidden:
license.rst