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python what does yield do


To understand what yield does, you must understand what generators are. And before you can understand generators, you must understand iterables.
Iterables

When you create a list, you can read its items one by one. Reading its items one by one is called iteration:

>>> mylist = [1, 2, 3]
>>> for i in mylist:
...    print(i)
1
2
3

mylist is an iterable. When you use a list comprehension, you create a list, and so an iterable:

>>> mylist = [x*x for x in range(3)]
>>> for i in mylist:
...    print(i)
0
1
4

Everything you can use "for... in..." on is an iterable; lists, strings, files...

These iterables are handy because you can read them as much as you wish, but you store all the values in memory and this is not always what you want when you have a lot of values.
Generators

Generators are iterators, a kind of iterable you can only iterate over once. Generators do not store all the values in memory, they generate the values on the fly:

>>> mygenerator = (x*x for x in range(3))
>>> for i in mygenerator:
...    print(i)
0
1
4

It is just the same except you used () instead of []. BUT, you cannot perform for i in mygenerator a second time since generators can only be used once: they calculate 0, then forget about it and calculate 1, and end calculating 4, one by one.
Yield

yield is a keyword that is used like return, except the function will return a generator.

>>> def createGenerator():
...    mylist = range(3)
...    for i in mylist:
...        yield i*i
...
>>> mygenerator = createGenerator() # create a generator
>>> print(mygenerator) # mygenerator is an object!
<generator object createGenerator at 0xb7555c34>
>>> for i in mygenerator:
...     print(i)
0
1
4

Here it's a useless example, but it's handy when you know your function will return a huge set of values that you will only need to read once.

To master yield, you must understand that when you call the function, the code you have written in the function body does not run. The function only returns the generator object, this is a bit tricky :-)

Then, your code will continue from where it left off each time for uses the generator.

Now the hard part:

The first time the for calls the generator object created from your function, it will run the code in your function from the beginning until it hits yield, then it'll return the first value of the loop. Then, each subsequent call will run another iteration of the loop you have written in the function and return the next value. This will continue until the generator is considered empty, which happens when the function runs without hitting yield. That can be because the loop has come to an end, or because you no longer satisfy an "if/else".
Comment

yield python

#"yield" returns a value continues the execution of the function
#"return" returns a value and terminates the execution of the function
Comment

python yield from

# In python construction 'yield from something' is just 
# the abbreviation of 'for i in something: yield i'
# So, we can change this:
def yieldOnly():
    yield "A"
    yield "B"
    yield "C"

def yieldFrom():
    for _ in [1, 2, 3]:
        yield from yieldOnly()

test = yieldFrom()
for i in test:
    print(i)
    
# to this:

def yieldOnly():
    yield "A"
    yield "B"
    yield "C"

def yieldFrom():
    for _ in [1, 2, 3]:
        for i in yieldOnly():
            yield i

test = yieldFrom()
for i in test:
    print(i)
Comment

Yield Expressions in python

yield_atom       ::=  "(" yield_expression ")"
yield_expression ::=  "yield" [expression_list | "from" expression]


#Using the yield operation in functions
def gen():  # defines a generator function
    yield 123

async def agen(): # defines an asynchronous generator function
    yield 123
Comment

python yield from

def iter_wrapper(iterator):
    for i in iterator:
    	yield i

def iter_wrapper(iterator):
    yield from iterator
Comment

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