.. todo:: - Testing Guidelines - Writing Command-Line Scripts - C or Cython Extensions
This section describes requirements and guidelines.
- All code must be compatible with Python 3.5 and later.
- The new Python 3 formatting style should be used (i.e.
"{0:s}".format("spam")
instead of"%s" % "spam"
).
- Docstrings must be present for all public classes/methods/functions, and must follow the form outlined by PEP8 Docstring Conventions.
- Unit tests should be provided for as many public methods and functions as possible, and should adhere to Pytest best practices.
- All persistent configuration should use python-dotenv.
Such configuration
.env
files should be placed at the top of theska_skeleton
module and provide a description that is sufficient for users to understand the settings changes.
The built-in print(...)
function should only be used for output that
is explicitly requested by the user, for example print_header(...)
or list_catalogs(...)
. Any other standard output, warnings, and
errors should follow these rules:
- For errors/exceptions, one should always use
raise
with one of the built-in exception classes, or a custom exception class. The nondescriptException
class should be avoided as much as possible, in favor of more specific exceptions (IOError, ValueError, etc.). - For warnings, one should always use
warnings.warn(message, warning_class)
. These get redirected tolog.warning()
by default. - For informational and debugging messages, one should always use
log.info(message)
andlog.debug(message)
.
The logging system should use the built-in Python logging module.
- The code will follow the standard PEP8 Style Guide for Python Code. In particular, this includes using only 4 spaces for indentation, and never tabs.
- The
import numpy as np
,import matplotlib as mpl
, andimport matplotlib.pyplot as plt
naming conventions should be used wherever relevant.from packagename import *
should never be used, except as a tool to flatten the namespace of a module. An example of the allowed usage is given in :ref:`import-star-example`. - Classes should either use direct variable access, or Python’s property
mechanism for setting object instance variables.
get_value
/set_value
style methods should be used only when getting and setting the values requires a computationally-expensive operation. :ref:`prop-get-set-example` below illustrates this guideline. - Classes should use the builtin :func:`super` function when making calls to methods in their super-class(es) unless there are specific reasons not to. :func:`super` should be used consistently in all subclasses since it does not work otherwise. :ref:`super-vs-direct-example` illustrates why this is important.
- Multiple inheritance should be avoided in general without good reason.
__init__.py
files for modules should not contain any significant implementation code.__init__.py
can contain docstrings and code for organizing the module layout, however (e.g.from submodule import *
in accord with the guideline above). If a module is small enough that it fits in one file, it should simply be a single file, rather than a directory with an__init__.py
file.
For maximum compatibility, we need to assume that writing non-ASCII characters to the console or to files will not work.
- When C extensions are used, the Python interface for those extensions must meet the aforementioned Python interface guidelines.
- The use of Cython is strongly recommended for C extensions. Cython extensions
should store
.pyx
files in the source code repository, but they should be compiled to.c
files that are updated in the repository when important changes are made to the.pyx
file. - In cases where C extensions are needed but Cython cannot be used, the PEP 7 Style Guide for C Code is recommended.
This section shows examples in order to illustrate points from the guidelines.
This example shows a sample class illustrating the guideline regarding the use of properties as opposed to getter/setter methods.
Let's assuming you've defined a ':class:`Star`'
class and create an instance
like this:
>>> s = Star(B=5.48, V=4.83)
You should always use attribute syntax like this:
>>> s.color = 0.4 >>> print(s.color) 0.4
Using Python properties, attribute syntax can still do anything possible with a get/set method. For lengthy or complex calculations, however, use a method:
>>> print(s.compute_color(5800, age=5e9)) 0.4
By calling :func:`super` the entire method resolution order for
D
is precomputed, enabling each superclass to cooperatively determine which
class should be handed control in the next :func:`super` call:
# This is safe class A(object): def method(self): print('Doing A') class B(A): def method(self): print('Doing B') super().method() class C(A): def method(self): print('Doing C') super().method() class D(C, B): def method(self): print('Doing D') super().method()
>>> d = D() >>> d.method() Doing D Doing C Doing B Doing A
As you can see, each superclass's method is entered only once. For this to
work it is very important that each method in a class that calls its
superclass's version of that method use :func:`super` instead of calling the
method directly. In the most common case of single-inheritance, using
super()
is functionally equivalent to calling the superclass's method
directly. But as soon as a class is used in a multiple-inheritance
hierarchy it must use super()
in order to cooperate with other classes in
the hierarchy.
Note
For more information on the the benefits of :func:`super`, see https://rhettinger.wordpress.com/2011/05/26/super-considered-super/
from module import *
is discouraged in a module that contains
implementation code, as it impedes clarity and often imports unused variables.
It can, however, be used for a package that is laid out in the following
manner:
packagename packagename/__init__.py packagename/submodule1.py packagename/submodule2.py
In this case, packagename/__init__.py
may be:
""" A docstring describing the package goes here """ from submodule1 import * from submodule2 import *
This allows functions or classes in the submodules to be used directly as
packagename.foo
rather than packagename.submodule1.foo
. If this is
used, it is strongly recommended that the submodules make use of the __all__
variable to specify which modules should be imported. Thus, submodule2.py
might read:
from numpy import array, linspace __all__ = ['foo', 'AClass'] def foo(bar): # the function would be defined here pass class AClass(object): # the class is defined here pass
This ensures that from submodule import *
only imports ':func:`foo'
and ':class:`AClass'
, but not ':class:`numpy.array'
or
':func:`numpy.linspace'
.
The present document's coding guidelines are derived from project Astropy's codding guidelines.