functools
关于functools标准库：
>>> help(functools)
Help on module functools:
NAME
functools - functools.py - Tools for working with functions and callable objects
CLASSES
builtins.object
partial
partialmethod
class partial(builtins.object)
| partial(func, *args, **keywords) - new function with partial application
| of the given arguments and keywords.
|
| Methods defined here:
|
| call(self, /, *args, **kwargs)
| Call self as a function.
|
| delattr(self, name, /)
| Implement delattr(self, name).
|
| getattribute(self, name, /)
| Return getattr(self, name).
|
| reduce(...)
| Helper for pickle.
|
| repr(self, /)
| Return repr(self).
|
| setattr(self, name, value, /)
| Implement setattr(self, name, value).
|
| setstate(...)
|
| ----------------------------------------------------------------------
| Static methods defined here:
|
| new(*args, **kwargs) from builtins.type
| Create and return a new object. See help(type) for accurate signature.
|
| ----------------------------------------------------------------------
| Data descriptors defined here:
|
| dict
|
| args
| tuple of arguments to future partial calls
|
| func
| function object to use in future partial calls
|
| keywords
| dictionary of keyword arguments to future partial calls
class partialmethod(builtins.object)
| partialmethod(func, *args, **keywords)
|
| Method descriptor with partial application of the given arguments
| and keywords.
|
| Supports wrapping existing descriptors and handles non-descriptor
| callables as instance methods.
|
| Methods defined here:
|
| get(self, obj, cls)
|
| init(self, func, *args, **keywords)
| Initialize self. See help(type(self)) for accurate signature.
|
| repr(self)
| Return repr(self).
|
| ----------------------------------------------------------------------
| Data descriptors defined here:
|
| dict
| dictionary for instance variables (if defined)
|
| isabstractmethod
|
| weakref
| list of weak references to the object (if defined)
FUNCTIONS
cmp_to_key(...)
Convert a cmp= function into a key= function.
lru_cache(maxsize=128, typed=False)
Least-recently-used cache decorator.
If maxsize is set to None, the LRU features are disabled and the cache
can grow without bound.
If typed is True, arguments of different types will be cached separately.
For example, f(3.0) and f(3) will be treated as distinct calls with
distinct results.
Arguments to the cached function must be hashable.
View the cache statistics named tuple (hits, misses, maxsize, currsize)
with f.cache_info(). Clear the cache and statistics with f.cache_clear().
Access the underlying function with f.wrapped.
See: http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used
reduce(...)
reduce(function, sequence[, initial]) -> value
Apply a function of two arguments cumulatively to the items of a sequence,
from left to right, so as to reduce the sequence to a single value.
For example, reduce(lambda x, y: x+y, [1, 2, 3, 4, 5]) calculates
((((1+2)+3)+4)+5). If initial is present, it is placed before the items
of the sequence in the calculation, and serves as a default when the
sequence is empty.
singledispatch(func)
Single-dispatch generic function decorator.
Transforms a function into a generic function, which can have different
behaviours depending upon the type of its first argument. The decorated
function acts as the default implementation, and additional
implementations can be registered using the register() attribute of the
generic function.
total_ordering(cls)
Class decorator that fills in missing ordering methods
update_wrapper(wrapper, wrapped, assigned=('module', 'name', 'qualname', 'doc', 'annotations'), updated=('dict',))
Update a wrapper function to look like the wrapped function
wrapper is the function to be updated
wrapped is the original function
assigned is a tuple naming the attributes assigned directly
from the wrapped function to the wrapper function (defaults to
functools.WRAPPER_ASSIGNMENTS)
updated is a tuple naming the attributes of the wrapper that
are updated with the corresponding attribute from the wrapped
function (defaults to functools.WRAPPER_UPDATES)
wraps(wrapped, assigned=('module', 'name', 'qualname', 'doc', 'annotations'), updated=('dict',))
Decorator factory to apply update_wrapper() to a wrapper function
Returns a decorator that invokes update_wrapper() with the decorated
function as the wrapper argument and the arguments to wraps() as the
remaining arguments. Default arguments are as for update_wrapper().
This is a convenience function to simplify applying partial() to
update_wrapper().
DATA
WRAPPER_ASSIGNMENTS = ('module', 'name', 'qualname', '__do...
WRAPPER_UPDATES = ('dict',)
all = ['update_wrapper', 'wraps', 'WRAPPER_ASSIGNMENTS', 'WRAPPER_...
FILE
d:\programdata\anaconda3\lib\functools.py
装饰器functools.total_ordering可以简化实现让类支持比较的操作，见“类”页面笔记。
任何时候你定义装饰器的时候，都应该使用functools库中的 @wraps 装饰器来注解底层包装函数。见“元编程”页面笔记。
functools.partial()函数就是帮助我们创建一个偏函数的，见“函数”页面笔记。