Python2 生成器 简介

1.

A generator: provide a kind of function that can return an intermediate result ("the next value") to its caller, but maintaining the function's local state so that the function can be resumed again right where it left off.

A very simple example:

def fib():
    a, b = 0, 1
    while 1:
       yield b
       a, b = b, a+b

When fib() is first invoked, it sets a to 0 and b to 1, then yields b back to its caller. The caller sees 1. When fib is resumed, from its point of view the yield statement is really the same as, say, a print statement: fib continues after the yield with all local state intact. a and b then become 1 and 1, and fib loops back to the yield, yielding 1 to its invoker. And so on. From fib's point of view it's just delivering a sequence of results. But from its caller's point of view, the fib invocation is an iterable object that can be resumed at will.

The yield statement may only be used inside functions. A function that contains a yield statement is called a generator function.

When a generator function is called, the actual arguments are bound to function-local formal argument names in the usual way, but no code in the body of the function is executed. Instead a generator-iterator object is returned; this conforms to the iterator protocol, so in particular can be used in for-loops in a natural way.

Each time the .next() method of a generator-iterator is invoked, the code in the body of the generator-function is executed until a yield or return statement (see below) is encountered, or until the end of the body is reached.

If a yield statement is encountered, the state of the function is frozen, and the value of expression_list is returned to .next()'s caller. By "frozen" we mean that all local state is retained, including the current bindings of local variables, the instruction pointer, and the internal evaluation stack: enough information is saved so that the next time .next() is invoked, the function can proceed exactly as if the yield statement were just another external call.

Note that an expression_list is not allowed on return statements in the body of a generator.

When a return statement is encountered, control proceeds as in any function return, executing the appropriate finally clauses (if any exist). Then a StopIteration exception is raised, signalling that the iterator is exhausted. A StopIteration exception is also raised if control flows off the end of the generator without an explicit return.

2: send

A new method for generator-iterators is proposed, called send(). It takes exactly one argument, which is the value that should be sent in to the generator. Calling send(None) is exactly equivalent to calling a generator's next() method. Calling send() with any other value is the same, except that the value produced by the generator's current yield expression will be different.

Because generator-iterators begin execution at the top of the generator's function body, there is no yield expression to receive a value when the generator has just been created. Therefore, calling send() with a non-None argument is prohibited when the generator iterator has just started, and a TypeError is raised if this occurs (presumably due to a logic error of some kind). Thus, before you can communicate with a coroutine you must first call next() or send(None) to advance its execution to the first yield expression.

The yield-statement will be allowed to be used on the right-hand side of an assignment; in that case it is referred to as yield-expression. The value of this yield-expression is None unless send() was called with a non-None argument; see below.

Note that a yield-statement or yield-expression without an expression is now legal. This makes sense: when the information flow in the next() call is reversed, it should be possible to yield without passing an explicit value (yield is of course equivalent to yield None).

When send(value) is called, the yield-expression that it resumes will return the passed-in value. When next() is called, the resumed yield-expression will return None. If the yield-expression is a yield-statement, this returned value is ignored, similar to ignoring the value returned by a function call used as a statement.

3: Exceptions and Cleanup

throw(type, value=None, traceback=None)

g.throw(type, value, traceback) causes the specified exception to be thrown at the point where the generator g is currently suspended (i.e. at a yield-statement, or at the start of its function body if next() has not been called yet). If the generator catches the exception and yields another value, that is the return value of g.throw(). If it doesn't catch the exception, the throw() appears to raise the same exception passed it (it falls through). If the generator raises another exception (this includes the StopIteration produced when it returns) that exception is raised by the throw() call. In summary, throw() behaves like next() or send(), except it raises an exception at the suspension point. If the generator is already in the closed state, throw() just raises the exception it was passed without executing any of the generator's code.

The effect of raising the exception is exactly as if the statement:  raise type, value, traceback

was executed at the suspension point. The type argument must not be None, and the type and value must be compatible.

g.close() is defined by the following pseudo-code:

def close(self):
    try:
        self.throw(GeneratorExit)
    except (GeneratorExit, StopIteration):
        pass
    else:
        raise RuntimeError("generator ignored GeneratorExit")
    # Other exceptions are not caught

https://www.python.org/dev/peps/pep-0342/

https://www.python.org/dev/peps/pep-0255/