Undocumented
| Class | |
Rate-limit a function (or other callable) |
| Function | apply |
Decorate a function with a transform function that is invoked on results returned from the decorated function. |
| Function | assign |
Assign parameters from namespace where func solicits. |
| Function | call |
Call a function for its side effect after initialization. |
| Function | compose |
Compose any number of unary functions into a single unary function. |
| Function | except_ |
Replace the indicated exceptions, if raised, with the indicated literal replacement or evaluated expression (if present). |
| Function | first |
Return a function that when invoked will invoke func1 without any parameters (for its side-effect) and then invoke func2 with whatever parameters were passed, returning its result. |
| Function | method |
Wrap lru_cache to support storing the cache data in the object instances. |
| Function | method |
Return a function that will call a named method on the target object with optional positional and keyword arguments. |
| Function | once |
Decorate func so it's only ever called the first time. |
| Function | pass |
Wrap func so it's not called if its first param is None |
| Function | print |
Convert a generator into a function that prints all yielded elements |
| Function | result |
Decorate a function with an action function that is invoked on the results returned from the decorated function (for its side-effect), then return the original result. |
| Function | retry |
Decorator wrapper for retry_call. Accepts arguments to retry_call except func and then returns a decorator for the decorated function. |
| Function | retry |
Given a callable func, trap the indicated exceptions for up to 'retries' times, invoking cleanup on the exception. On the final attempt, allow any exceptions to propagate. |
| Function | save |
Wrap a method such that when it is called, the args and kwargs are saved on the method. |
| Type Variable | |
Undocumented |
| Function | _special |
Because Python treats special methods differently, it's not possible to use instance attributes to implement the cached methods. |
Decorate a function with a transform function that is invoked on results returned from the decorated function. >>> @apply(reversed) ... def get_numbers(start): ... "doc for get_numbers" ... return range(start, start+3) >>> list(get_numbers(4)) [6, 5, 4] >>> get_numbers.__doc__ 'doc for get_numbers'
Assign parameters from namespace where func solicits. >>> def func(x, y=3): ... print(x, y) >>> assigned = assign_params(func, dict(x=2, z=4)) >>> assigned() 2 3 The usual errors are raised if a function doesn't receive its required parameters: >>> assigned = assign_params(func, dict(y=3, z=4)) >>> assigned() Traceback (most recent call last): TypeError: func() ...argument... It even works on methods: >>> class Handler: ... def meth(self, arg): ... print(arg) >>> assign_params(Handler().meth, dict(arg='crystal', foo='clear'))() crystal
Call a function for its side effect after initialization. >>> @call_aside ... def func(): print("called") called >>> func() called Use functools.partial to pass parameters to the initial call >>> @functools.partial(call_aside, name='bingo') ... def func(name): print("called with", name) called with bingo
Compose any number of unary functions into a single unary function. >>> import textwrap >>> expected = str.strip(textwrap.dedent(compose.__doc__)) >>> strip_and_dedent = compose(str.strip, textwrap.dedent) >>> strip_and_dedent(compose.__doc__) == expected True Compose also allows the innermost function to take arbitrary arguments. >>> round_three = lambda x: round(x, ndigits=3) >>> f = compose(round_three, int.__truediv__) >>> [f(3*x, x+1) for x in range(1,10)] [1.5, 2.0, 2.25, 2.4, 2.5, 2.571, 2.625, 2.667, 2.7]
Replace the indicated exceptions, if raised, with the indicated literal replacement or evaluated expression (if present). >>> safe_int = except_(ValueError)(int) >>> safe_int('five') >>> safe_int('5') 5 Specify a literal replacement with ``replace``. >>> safe_int_r = except_(ValueError, replace=0)(int) >>> safe_int_r('five') 0 Provide an expression to ``use`` to pass through particular parameters. >>> safe_int_pt = except_(ValueError, use='args[0]')(int) >>> safe_int_pt('five') 'five'
Return a function that when invoked will invoke func1 without any parameters (for its side-effect) and then invoke func2 with whatever parameters were passed, returning its result.
CallableT, cache_wrapper: Callable[ = functools.lru_cache()) -> CallableT:
(source)
¶
Wrap lru_cache to support storing the cache data in the object instances. Abstracts the common paradigm where the method explicitly saves an underscore-prefixed protected property on first call and returns that subsequently. >>> class MyClass: ... calls = 0 ... ... @method_cache ... def method(self, value): ... self.calls += 1 ... return value >>> a = MyClass() >>> a.method(3) 3 >>> for x in range(75): ... res = a.method(x) >>> a.calls 75 Note that the apparent behavior will be exactly like that of lru_cache except that the cache is stored on each instance, so values in one instance will not flush values from another, and when an instance is deleted, so are the cached values for that instance. >>> b = MyClass() >>> for x in range(35): ... res = b.method(x) >>> b.calls 35 >>> a.method(0) 0 >>> a.calls 75 Note that if method had been decorated with ``functools.lru_cache()``, a.calls would have been 76 (due to the cached value of 0 having been flushed by the 'b' instance). Clear the cache with ``.cache_clear()`` >>> a.method.cache_clear() Same for a method that hasn't yet been called. >>> c = MyClass() >>> c.method.cache_clear() Another cache wrapper may be supplied: >>> cache = functools.lru_cache(maxsize=2) >>> MyClass.method2 = method_cache(lambda self: 3, cache_wrapper=cache) >>> a = MyClass() >>> a.method2() 3 Caution - do not subsequently wrap the method with another decorator, such as ``@property``, which changes the semantics of the function. See also http://code.activestate.com/recipes/577452-a-memoize-decorator-for-instance-methods/ for another implementation and additional justification.
Return a function that will call a named method on the target object with optional positional and keyword arguments. >>> lower = method_caller('lower') >>> lower('MyString') 'mystring'
Decorate func so it's only ever called the first time. This decorator can ensure that an expensive or non-idempotent function will not be expensive on subsequent calls and is idempotent. >>> add_three = once(lambda a: a+3) >>> add_three(3) 6 >>> add_three(9) 6 >>> add_three('12') 6 To reset the stored value, simply clear the property ``saved_result``. >>> del add_three.saved_result >>> add_three(9) 12 >>> add_three(8) 12 Or invoke 'reset()' on it. >>> add_three.reset() >>> add_three(-3) 0 >>> add_three(0) 0
Wrap func so it's not called if its first param is None >>> print_text = pass_none(print) >>> print_text('text') text >>> print_text(None)
Convert a generator into a function that prints all yielded elements >>> @print_yielded ... def x(): ... yield 3; yield None >>> x() 3 None
Decorate a function with an action function that is invoked on the results returned from the decorated function (for its side-effect), then return the original result. >>> @result_invoke(print) ... def add_two(a, b): ... return a + b >>> x = add_two(2, 3) 5 >>> x 5
Decorator wrapper for retry_call. Accepts arguments to retry_call except func and then returns a decorator for the decorated function. Ex: >>> @retry(retries=3) ... def my_func(a, b): ... "this is my funk" ... print(a, b) >>> my_func.__doc__ 'this is my funk'
Given a callable func, trap the indicated exceptions for up to 'retries' times, invoking cleanup on the exception. On the final attempt, allow any exceptions to propagate.
Wrap a method such that when it is called, the args and kwargs are saved on the method. >>> class MyClass: ... @save_method_args ... def method(self, a, b): ... print(a, b) >>> my_ob = MyClass() >>> my_ob.method(1, 2) 1 2 >>> my_ob._saved_method.args (1, 2) >>> my_ob._saved_method.kwargs {} >>> my_ob.method(a=3, b='foo') 3 foo >>> my_ob._saved_method.args () >>> my_ob._saved_method.kwargs == dict(a=3, b='foo') True The arguments are stored on the instance, allowing for different instance to save different args. >>> your_ob = MyClass() >>> your_ob.method({str('x'): 3}, b=[4]) {'x': 3} [4] >>> your_ob._saved_method.args ({'x': 3},) >>> my_ob._saved_method.args ()