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>>> import __future__ >>> __future__.division _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)
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The process of freeing memory when it is not used anymore. Python performs garbage collection via reference counting and a cyclic garbage collector that is able to detect and break reference cycles.
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A function which returns an iterator. It looks like a normal function except that values are returned to the caller using a :keyword:`yield` statement instead of a :keyword:`return` statement. Generator functions often contain one or more :keyword:`for` or :keyword:`while` loops which :keyword:`yield` elements back to the caller. The function execution is stopped at the :keyword:`yield` keyword (returning the result) and is resumed there when the next element is requested by calling the :meth:`__next__` method of the returned iterator.
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An expression that returns an iterator. It looks like a normal expression followed by a :keyword:`for` expression defining a loop variable, range, and an optional :keyword:`if` expression. The combined expression generates values for an enclosing function::
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>>> sum(i*i for i in range(10)) # sum of squares 0, 1, 4, ... 81 285
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The lock used by Python threads to assure that only one thread executes in the :term:`CPython` :term:`virtual machine` at a time. This simplifies the CPython implementation by assuring that no two processes can access the same memory at the same time. Locking the entire interpreter makes it easier for the interpreter to be multi-threaded, at the expense of much of the parallelism afforded by multi-processor machines. Efforts have been made in the past to create a "free-threaded" interpreter (one which locks shared data at a much finer granularity), but so far none have been successful because performance suffered in the common single-processor case.
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An object is *hashable* if it has a hash value which never changes during its lifetime (it needs a :meth:`__hash__` method), and can be compared to other objects (it needs an :meth:`__eq__` method). Hashable objects which compare equal must have the same hash value.
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Hashability makes an object usable as a dictionary key and a set member, because these data structures use the hash value internally.
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All of Python's immutable built-in objects are hashable, while no mutable containers (such as lists or dictionaries) are. Objects which are instances of user-defined classes are hashable by default; they all compare unequal, and their hash value is their :func:`id`.
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