12.2. Generator Expression

  • Comprehensions executes instantly

  • Comprehensions are stored in the memory until end of a program

  • Comprehensions should be used when accessing values more than one

  • Generator Expressions are lazy evaluated

  • Generator Expressions are cleared once they are executed

  • Generator Expressions should be used when accessing value once (for example in the loop)

12.2.1. List Comprehension

  • Comprehensions executes instantly

  • Comprehensions will be in the memory until end of a program

  • Comprehensions - Using values more than one

>>> data = [x for x in range(0,5)]
>>>
>>> print(data)
[0, 1, 2, 3, 4]
>>> list(data)
[0, 1, 2, 3, 4]

12.2.2. Generator Expression

  • Generators are lazy evaluated

  • Creates generator object and assign reference

  • Code is not executed instantly

  • Sometimes code is not executed at all!

  • Are cleared once they are executed

  • Generator will calculate next number for every loop iteration

  • Generator forgets previous number

  • Generator doesn't know the next number

  • It is used for one-time access to values (for example in the loop iterator)

>>> data = (x for x in range(0,5))
>>>
>>> print(data)  
<generator object <genexpr> at 0x...>
>>> list(data)
[0, 1, 2, 3, 4]

12.2.3. Example

>>> data = [x for x in range(0,5)]          # list comprehension
>>> data = (x for x in range(0,5))          # generator expression
>>> data = {x for x in range(0,5)}          # set comprehension
>>> data = {x:x for x in range(0,5)}        # dict comprehension
>>> data = list(x for x in range(0,5))      # list comprehension
>>> data = tuple(x for x in range(0,5))     # tuple comprehension
>>> data = set(x for x in range(0,5))       # set comprehension
>>> data = dict((x,x) for x in range(0,5))  # dict comprehension
>>> data = all(x for x in range(0,5))
>>> data = any(x for x in range(0,5))
>>> data = bool(x for x in range(0,5))
>>> data = sum(x for x in range(0,5))
>>> data = min(x for x in range(0,5))
>>> data = max(x for x in range(0,5))
>>> data = hash(x for x in range(0,5))
>>> data = callable(x for x in range(0,5))
>>> data = len(x for x in range(0,5))
Traceback (most recent call last):
TypeError: object of type 'generator' has no len()

12.2.4. Comprehensions or Generator Expression

  • If you need values evaluated instantly, there is no point in using generators

Comprehensions vs Generator Expression:

>>> data = [x for x in range(0,10)]
>>> print(data)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> data = (x for x in range(0,10))
>>> print(data)  
<generator object <genexpr> at 0x...>

Comprehension:

>>> data = [x for x in range(0,10)]
>>>
>>> for x in data:  
...     print(x, end=' ')
...     if x == 3:
...         break
0 1 2 3
>>>
>>> for x in data:  
...     print(x, end=' ')
...     if x == 6:
...         break
0 1 2 3 4 5 6
>>>
>>> print(list(data))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>>
>>> print(list(data))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

Generator Expressions:

>>> data = (x for x in range(0,10))
>>>
>>> for x in data:  
...     print(x, end=' ')
...     if x == 3:
...         break
0 1 2 3
>>>
>>> for x in data:  
...     print(x, end=' ')
...     if x == 6:
...         break
4 5 6
>>>
>>> print(list(data))
[7, 8, 9]
>>>
>>> print(list(data))
[]

12.2.5. Why Round Brackets?

  • Round brackets does not produce tuples (commas does)

  • Round brackets bounds context

>>> data = [x for x in range(0,5)]  # list comprehension
>>> data = (x for x in range(0,5))  # generator expression
>>> data = [1, 2, 3]
>>> type(data)
<class 'list'>
>>>
>>> data = (1, 2, 3)
>>> type(data)
<class 'tuple'>
>>>
>>> data = 1, 2, 3
>>> type(data)
<class 'tuple'>
>>> data = 1 + 2
>>> type(data)
<class 'int'>
>>>
>>> data = (1 + 2)
>>> type(data)
<class 'int'>
>>> data = (1, 2, 3)
>>> type(data)
<class 'tuple'>
>>>
>>> data = (1, 2)
>>> type(data)
<class 'tuple'>
>>>
>>> data = (1,)
>>> type(data)
<class 'tuple'>
>>>
>>> data = (1)
>>> type(data)
<class 'int'>
>>> data = 1, 2, 3
>>> type(data)
<class 'tuple'>
>>>
>>> data = 1, 2
>>> type(data)
<class 'tuple'>
>>>
>>> data = 1,
>>> type(data)
<class 'tuple'>
>>>
>>> data = 1
>>> type(data)
<class 'int'>