sphinx_typesafe
is a decorator which enables dynamic type checking on Python
method and function calls. It works in conjunction with Sphinx-style docstrings,
which makes it particularly convenient for keeping the documentation synchronized
with the code actually being executed.
Features is a Nutshell
- The decorator can be attached to any function or method.
- Raises
TypeError
if types of arguments do not match the specification. - Raises
TypeError
if type of return value does not match the specification. - Performs dynamic type checking.
Python2
Since function annotations are not available in Python2 the way type checking for Python2 is a documentation convention for parameters based on the info field lists of sphinx. So even when you don't use type checking you can use it to generate documentation.
Syntax for Python2 using sphinx style docstrings
This is the preferred way since you will be also documenting your code.
from sphinx_typesafe.typesafe import typesafe @typesafe def foo(param_a, param_b, param_c): """ :type param_a: types.StringType :type param_b: types.IntType :type param_c: types.NotImplementedType :rtype: types.BooleanType """ # Do Something return True
Note
Observe the usage of rtype
to specify the type returned by the function.
When rtype
is not specified, it is assumed to be types.NoneType
.
Note
When a parameter specifies types.NotImplementedType
, the type checking logic simply
ignores that parameter, which means that you can pass any type you wish.
Syntax for Python2 using decorator arguments
This is an alternative approach, useful in circunstances where Sphinx-style documentation is not allowed or desired, for whatever reason.
from sphinx_typesafe.typesafe import typesafe @typesafe( { 'param_a' : 'str', 'param_b' : 'types.IntType', 'param_c' : 'own_module.OwnType', 'return' : 'bool' } ) def foo(param_a, param_b, param_c): """ Some Docstring Info """ # Do Something return True
Note
Observe the usage of return
to specify the type returned by the function.
You can use any Python type
So if you have defined a Point
class in module mod1
like below:
# File: mod1.py class Point(object): def __init__(self, x = None, y = None): """ Initialize the Point. Can be used to give x,y directly.""" self.x = x self.y = y
then you can employ this type in your code like this:
from mod1 import Point from sphinx_typesafe.typesafe import typesafe @typesafe def foo(afunc): """ :type afunc: mod1.Point :rtype: types.BooleanType """ return True
Python3
Warning
This is a tentative implementation which is not finished at the moment!!
The base technique is the Function Annotations proposed in PEP-3107 which is documented in Python3 What's New (see section New Syntax).
Syntax for Python3
from sphinx_typesafe.typesafe import typesafe @typesafe def foo(param_a: str, param_b: int) -> bool: # Do Something return True
- The @typesafe decorator will then check all arguments dynamically whenever the foo is called for valid types.
- As a quoting remark from the PEP 3107: "All annotated parameter types can be any python expression.", but for typechecking only types make sense, though.
The idea and parts of the implementation were inspired by the book: Pro Python (Expert's Voice in Open Source)
Building from source
Start from a clean and minimalist virtual environment, for example:
$ pip list pip (1.4) setuptools (2.1) wsgiref (0.1.2)
Download sources and run test cases
$ git clone https://github.com/frgomes/sphinx_typesafe $ cd sphinx_typesafe $ python setup.py devtest && py.test
FAQ
Why it was called IcanHasTypeCheck ?
IcanHasTypeCheck (ICHTC), refers to the famous lolcats.
Why is now called sphinx_typesafe ?
Because typesafe tells immediatelly what it is about. Unfortunately, typesafe was already taken on PyPI, so sphinx_typesafe seemed to be a good alternative name which also relates to the documentation standard adopted.
Support
Please find links on the top of this page.