PYTHON

python generator

# A generator-function is defined like a normal function, 
# but whenever it needs to generate a value, 
# it does so with the yield keyword rather than return. 
# If the body of a def contains yield, 
# the function automatically becomes a generator function.
# Python 3 example
def grepper_gen():
  yield "add"
  yield "grepper"
  yield "answer"
grepper = grepper_gen()
next(grepper)
> add
next(grepper)
> grepper
next(grepper)
> answer

python generator example

def my_generator():
	for i in range(10):
		yield i

for i in my_generator():
    print(i)

python generator

def count_to_ten_generator():
  for number in range(10):
    yield number
my_generator = count_to_ten_generator()
first_number = next(my_generator)
list_or_the_rest = list(my_generator)

python generator function

def gen_func():
	for i in range(10):
    	yield i

Python generator function

def gen_nums():
    n = 0
    while n < 4:
        yield n
        n += 1

python generator

# A recursive generator that generates Tree leaves in in-order.
def inorder(t):
    if t:
        for x in inorder(t.left):
            yield x

        yield t.label

        for x in inorder(t.right):
            yield x

python generators

# Size of generators is a huge advantage compared to list
import sys

n= 80000

# List
a=[n**2 for n in range(n)]

# Generator
# Be aware of the syntax to create generators, lika a list comprehension but with round brakets
b=(n**2 for n in range(n))

print(f"List: {sys.getsizeof(a)} bits
Generator: {sys.getsizeof(b)} bits")

python generators

def generador():
    n = 1
    yield n

    n += 1
    yield n

    n += 1
    yield n

python generators with for

for i in generador():
    print(i)
# Salida: 1, 2, 3

Python Generator

var code = Blockly.Python.workspaceToCode(workspace);

python generator

# A generator-function is defined like a normal function, 
# but whenever it needs to generate a value, 
# it does so with the yield keyword rather than return. 
# If the body of a def contains yield, 
# the function automatically becomes a generator function.
# Python 3 example
def grepper_gen():
  yield "add"
  yield "grepper"
  yield "answer"
grepper = grepper_gen()
next(grepper)
> add
next(grepper)
> grepper
next(grepper)
> answer

python generator example

def my_generator():
	for i in range(10):
		yield i

for i in my_generator():
    print(i)

python generator

def count_to_ten_generator():
  for number in range(10):
    yield number
my_generator = count_to_ten_generator()
first_number = next(my_generator)
list_or_the_rest = list(my_generator)

python generator function

def gen_func():
	for i in range(10):
    	yield i

Python generator function

def gen_nums():
    n = 0
    while n < 4:
        yield n
        n += 1

python generator

# A recursive generator that generates Tree leaves in in-order.
def inorder(t):
    if t:
        for x in inorder(t.left):
            yield x

        yield t.label

        for x in inorder(t.right):
            yield x

python generators

# Size of generators is a huge advantage compared to list
import sys

n= 80000

# List
a=[n**2 for n in range(n)]

# Generator
# Be aware of the syntax to create generators, lika a list comprehension but with round brakets
b=(n**2 for n in range(n))

print(f"List: {sys.getsizeof(a)} bits
Generator: {sys.getsizeof(b)} bits")

python generators

def generador():
    n = 1
    yield n

    n += 1
    yield n

    n += 1
    yield n

python generators with for

for i in generador():
    print(i)
# Salida: 1, 2, 3

Python Generator

var code = Blockly.Python.workspaceToCode(workspace);