Experimental Python tools.
Python doesn't do type hints natively. You can add docstrings to document the expected types and add asserts to add checks at run-time. However, it's impossible to inspect those. Matchbox's type hints are really simple but still only provide run-time safety. The advantage of these type hints is that they can be used for more advanced stuff, like inspection.
>>> from matchbox import hint
>>> @hint(int)
... def add_one(n):
... return n + 1
>>> add_one(3.5)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "matchbox/__init__.py", line 21, in newf
raise TypeError('Argument %s should be %s (got %s)' % (index + 1, arg[1], arg[0]))
TypeError: Argument 1 should be <type 'int'> (got <type 'float'>)Rather than importing your dependencies locally, you are probably better off injecting dependencies into your objects. Doing this manually is a real hassle, so let the DI container do the heavy lifting for you!
>>> from matchbox import hint
>>> from matchbox.container import Container
>>>
>>> class Database(object):
... pass
...
>>> class UserController(object):
...
... def __init__(self, database):
... self.database = database
...
>>> app = Container()
>>> app.map(UserController, [Database])
>>> users = app.resolve(UserController)
>>> type(users.database)
<class '__main__.Database'>- Leverage type hints in DI so you're not required to add an explicit mapping (other than the type hint).
- Create some sort of interface binding.
Some of this stuff was inspired by the awesome work of the Laravel community.
MIT