generator

Properties

>>> def gen():
...     yield 1
...     yield 2
>>> g = gen()
>>> [name for name in dir(g) if not name.startswith("__")]
['close', 'gi_code', 'gi_frame', 'gi_running', 'gi_yieldfrom', 'send', 'throw']

Definition

A generator is an iterator created by a function that uses the yield keyword. Each yield pauses execution and produces a value; execution resumes from that point on the next iteration. Generators are single-use and lazy: values are produced on demand.

def count_up_to(n):
    i = 1
    while i <= n:
        yield i
        i += 1

for num in count_up_to(3):
    print(num)   # 1 2 3

Creating generators

• Generator function: any function containing yield.
• Generator expression: (expr for item in iterable if condition).

# generator expression
>>> squares = (x*x for x in range(3))
>>> list(squares)
[0, 1, 4]

Using generators

Generators implement the iterator protocol and can be consumed with for, next, list(), or any function that takes an iterable.

g = count_up_to(2)
next(g)  # 1
next(g)  # 2
next(g)  # StopIteration

Sending values in

send can inject a value into the generator, resuming it at the next yield expression.

def echo():
    received = yield "ready"
    yield received

g = echo()
next(g)         # 'ready'
g.send("hi")    # 'hi'

Throwing and closing

• throw raises an exception inside the generator.
• close raises GeneratorExit to stop the generator.

g = count_up_to(10)
next(g)      # 1
g.close()    # stops the generator

Dunder methods

Dunder Method	Operation	Example (normal syntax)	Example (dunder call)
__next__	Get next value	next(gen)	gen.__next__()
__iter__	Iterator protocol	for x in gen	gen.__iter__()
__send__	Send a value in	gen.send(10)	gen.__send__(10)
__throw__	Raise in generator	gen.throw(Exception)	gen.__throw__(Exception)
__close__	Stop generator	gen.close()	gen.__close__()