gc.garbage A list of objects which the collector found to be unreachable but could not be freed (uncollectable objects). Starting with Python 3.4, this list should be empty most of the time, except when using instances of C extension types with a non-NULL tp_del slot. If DEBUG_SAVEALL is set, then all unreachable objects will be added to this list rather than freed. Changed in version 3.2: If this list is non-empty at interpreter shutdown, a ResourceWarning is emitted, which is silent by de

class functools.partialmethod(func, *args, **keywords) Return a new partialmethod descriptor which behaves like partial except that it is designed to be used as a method definition rather than being directly callable. func must be a descriptor or a callable (objects which are both, like normal functions, are handled as descriptors). When func is a descriptor (such as a normal Python function, classmethod(), staticmethod(), abstractmethod() or another instance of partialmethod), calls to __ge

@functools.wraps(wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES) This is a convenience function for invoking update_wrapper() as a function decorator when defining a wrapper function. It is equivalent to partial(update_wrapper, wrapped=wrapped, assigned=assigned, updated=updated). For example: >>> from functools import wraps >>> def my_decorator(f): ... @wraps(f) ... def wrapper(*args, **kwds): ... print('Calling decorated function') ...

functools.update_wrapper(wrapper, wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES) Update a wrapper function to look like the wrapped function. The optional arguments are tuples to specify which attributes of the original function are assigned directly to the matching attributes on the wrapper function and which attributes of the wrapper function are updated with the corresponding attributes from the original function. The default values for these arguments are the module leve

@functools.total_ordering Given a class defining one or more rich comparison ordering methods, this class decorator supplies the rest. This simplifies the effort involved in specifying all of the possible rich comparison operations: The class must define one of __lt__(), __le__(), __gt__(), or __ge__(). In addition, the class should supply an __eq__() method. For example: @total_ordering class Student: def _is_valid_operand(self, other): return (hasattr(other, "lastname") and

@functools.singledispatch(default) Transforms a function into a single-dispatch generic function. To define a generic function, decorate it with the @singledispatch decorator. Note that the dispatch happens on the type of the first argument, create your function accordingly: >>> from functools import singledispatch >>> @singledispatch ... def fun(arg, verbose=False): ... if verbose: ... print("Let me just say,", end=" ") ... print(arg) To add overloaded imp

exception FutureWarning Base class for warnings about constructs that will change semantically in the future.

functools.reduce(function, iterable[, initializer]) Apply function of two arguments cumulatively to the items of 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). The left argument, x, is the accumulated value and the right argument, y, is the update value from the sequence. If the optional initializer is present, it is placed before the items of the sequence in the calculation, a

functools.partial(func, *args, **keywords) Return a new partial object which when called will behave like func called with the positional arguments args and keyword arguments keywords. If more arguments are supplied to the call, they are appended to args. If additional keyword arguments are supplied, they extend and override keywords. Roughly equivalent to: def partial(func, *args, **keywords): def newfunc(*fargs, **fkeywords): newkeywords = keywords.copy() newkeywords.up

partial.keywords The keyword arguments that will be supplied when the partial object is called.