lucasvl.nl/lib/python3.11/site-packages/setuptools/_vendor/jaraco/functools.py
2024-03-04 21:31:20 -06:00

526 lines
13 KiB
Python

import functools
import time
import inspect
import collections
import types
import itertools
import setuptools.extern.more_itertools
from typing import Callable, TypeVar
CallableT = TypeVar("CallableT", bound=Callable[..., object])
def compose(*funcs):
"""
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]
"""
def compose_two(f1, f2):
return lambda *args, **kwargs: f1(f2(*args, **kwargs))
return functools.reduce(compose_two, funcs)
def method_caller(method_name, *args, **kwargs):
"""
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'
"""
def call_method(target):
func = getattr(target, method_name)
return func(*args, **kwargs)
return call_method
def once(func):
"""
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
"""
@functools.wraps(func)
def wrapper(*args, **kwargs):
if not hasattr(wrapper, 'saved_result'):
wrapper.saved_result = func(*args, **kwargs)
return wrapper.saved_result
wrapper.reset = lambda: vars(wrapper).__delitem__('saved_result')
return wrapper
def method_cache(
method: CallableT,
cache_wrapper: Callable[
[CallableT], CallableT
] = functools.lru_cache(), # type: ignore[assignment]
) -> CallableT:
"""
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.
"""
def wrapper(self: object, *args: object, **kwargs: object) -> object:
# it's the first call, replace the method with a cached, bound method
bound_method: CallableT = types.MethodType( # type: ignore[assignment]
method, self
)
cached_method = cache_wrapper(bound_method)
setattr(self, method.__name__, cached_method)
return cached_method(*args, **kwargs)
# Support cache clear even before cache has been created.
wrapper.cache_clear = lambda: None # type: ignore[attr-defined]
return ( # type: ignore[return-value]
_special_method_cache(method, cache_wrapper) or wrapper
)
def _special_method_cache(method, cache_wrapper):
"""
Because Python treats special methods differently, it's not
possible to use instance attributes to implement the cached
methods.
Instead, install the wrapper method under a different name
and return a simple proxy to that wrapper.
https://github.com/jaraco/jaraco.functools/issues/5
"""
name = method.__name__
special_names = '__getattr__', '__getitem__'
if name not in special_names:
return
wrapper_name = '__cached' + name
def proxy(self, *args, **kwargs):
if wrapper_name not in vars(self):
bound = types.MethodType(method, self)
cache = cache_wrapper(bound)
setattr(self, wrapper_name, cache)
else:
cache = getattr(self, wrapper_name)
return cache(*args, **kwargs)
return proxy
def apply(transform):
"""
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'
"""
def wrap(func):
return functools.wraps(func)(compose(transform, func))
return wrap
def result_invoke(action):
r"""
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
"""
def wrap(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
result = func(*args, **kwargs)
action(result)
return result
return wrapper
return wrap
def call_aside(f, *args, **kwargs):
"""
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
"""
f(*args, **kwargs)
return f
class Throttler:
"""
Rate-limit a function (or other callable)
"""
def __init__(self, func, max_rate=float('Inf')):
if isinstance(func, Throttler):
func = func.func
self.func = func
self.max_rate = max_rate
self.reset()
def reset(self):
self.last_called = 0
def __call__(self, *args, **kwargs):
self._wait()
return self.func(*args, **kwargs)
def _wait(self):
"ensure at least 1/max_rate seconds from last call"
elapsed = time.time() - self.last_called
must_wait = 1 / self.max_rate - elapsed
time.sleep(max(0, must_wait))
self.last_called = time.time()
def __get__(self, obj, type=None):
return first_invoke(self._wait, functools.partial(self.func, obj))
def first_invoke(func1, func2):
"""
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.
"""
def wrapper(*args, **kwargs):
func1()
return func2(*args, **kwargs)
return wrapper
def retry_call(func, cleanup=lambda: None, retries=0, trap=()):
"""
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.
"""
attempts = itertools.count() if retries == float('inf') else range(retries)
for attempt in attempts:
try:
return func()
except trap:
cleanup()
return func()
def retry(*r_args, **r_kwargs):
"""
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'
"""
def decorate(func):
@functools.wraps(func)
def wrapper(*f_args, **f_kwargs):
bound = functools.partial(func, *f_args, **f_kwargs)
return retry_call(bound, *r_args, **r_kwargs)
return wrapper
return decorate
def print_yielded(func):
"""
Convert a generator into a function that prints all yielded elements
>>> @print_yielded
... def x():
... yield 3; yield None
>>> x()
3
None
"""
print_all = functools.partial(map, print)
print_results = compose(more_itertools.consume, print_all, func)
return functools.wraps(func)(print_results)
def pass_none(func):
"""
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)
"""
@functools.wraps(func)
def wrapper(param, *args, **kwargs):
if param is not None:
return func(param, *args, **kwargs)
return wrapper
def assign_params(func, namespace):
"""
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
"""
sig = inspect.signature(func)
params = sig.parameters.keys()
call_ns = {k: namespace[k] for k in params if k in namespace}
return functools.partial(func, **call_ns)
def save_method_args(method):
"""
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
()
"""
args_and_kwargs = collections.namedtuple('args_and_kwargs', 'args kwargs')
@functools.wraps(method)
def wrapper(self, *args, **kwargs):
attr_name = '_saved_' + method.__name__
attr = args_and_kwargs(args, kwargs)
setattr(self, attr_name, attr)
return method(self, *args, **kwargs)
return wrapper
def except_(*exceptions, replace=None, use=None):
"""
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'
"""
def decorate(func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
try:
return func(*args, **kwargs)
except exceptions:
try:
return eval(use)
except TypeError:
return replace
return wrapper
return decorate