I am using a decorator:
class Memoized(object):
__cache = {}
def __init__(self, func):
self.func = func
key = (func.__module__, func.__name__)
# print key
if key not in self.__cache:
self.__cache[key] = {}
self.mycache = self.__cache[key]
def __call__(self, *args):
try:
return self.mycache[args]
except KeyError:
value = self.func(*args)
self.mycache[args] = value
return value
except TypeError:
return self.func(*args)
def __get__(self, obj, objtype):
return functools.partial(self.__call__, obj)
def reset(self):
for v in self.__cache.itervalues():
v.clear()
and a function:
@Memoized
def is_tile_inside_border(x, y, z, border):
'''Checks if a tile is inside border or not
>>> is_tile_inside_border(85,53,7,'iran')
3
>>> is_tile_inside_border(85,15,7,'iran')
0
'''
binary_data = get_border_binary(border, z)
return isInside((x, y), binary_data)
But when using doctest module (python mycode.py -v):
if __name__ == '__main__':
import doctest
doctest.testmod()
Python can't find the test in doc-string. I know that is a problem with decorator. But how can I fix it?
PS: functools.update_wrapper(self, func)
is not working!
A decorator in Python is a function that takes another function as its argument, and returns yet another function . Decorators can be extremely useful as they allow the extension of an existing function, without any modification to the original function source code.
When the tests include values that are likely to change in unpredictable ways, and where the actual value is not important to the test results, you can use the ELLIPSIS option to tell doctest to ignore portions of the verification value.
doctest is a module included in the Python programming language's standard library that allows the easy generation of tests based on output from the standard Python interpreter shell, cut and pasted into docstrings.
How about we side-step the problem by using a memo
decorator which returns a function instead of a class instance:
import functools
def decorator(d):
"""Make function d a decorator: d wraps a function fn.
Authors: Peter Norvig and Darius Bacon"""
def _d(fn):
return functools.update_wrapper(d(fn), fn)
functools.update_wrapper(_d, d)
return _d
@decorator
def memo(f):
# by Peter Norvig
"""Decorator that caches the return value for each call to f(args).
Then when called again with same args, we can just look it up."""
cache = {}
def _f(*args):
try:
return cache[args]
except KeyError:
cache[args] = result = f(*args)
return result
except TypeError:
# some element of args can't be a dict key
return f(*args)
_f.cache = cache
return _f
@memo
def is_tile_inside_border(x, y, z, border):
'''Checks if a tile is inside border or not
>>> is_tile_inside_border(85,53,7,'iran')
3
>>> is_tile_inside_border(85,15,7,'iran')
0
'''
# binary_data = get_border_binary(border, z)
# return isInside((x, y), binary_data)
return True
class Foo(object):
@memo
def bar(self, x):
"""
>>> Foo().bar(1)
2
"""
return x
if __name__ == '__main__':
import doctest
doctest.testmod()
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