Have you ever thought on initializing a list with its values with a one liner expression? That's totally possible in Python using list comprehensions. But sometimes you wont use the list stored value for a while and you just wanted to initialize the values for a future use... That's a simple use case of or Generator Expressions.
PS: If you have read Fluent Python from @ramalhoorg , there is nothing new right here, but you can share this text to a friend, so she will be able to learn more about Python.
PS 2: Thanks @ramalhoorg for the examples on the book, they were very useful and some of them are used right here!
What are List Comprehensions?
List comprehensions are a list expression that creates a list with values already inside it, take a look at the example below:
>>> my_incredible_list = [x for x in range(5)]
>>> my_incredible_list
[0, 1, 2, 3, 4]
This list comprehension is the same as if you were doing a for loop appending values to a list.
>>> my_incredible_list = []
>>> for x in range(5):
>>> my_incredible_list.append(x)
>>> my_incredible_list
[0, 1, 2, 3, 4]
With list comprehensions, you are able to generate lists with tuples inside iterating two other lists.
>>> foods = "apple banana sausages".split() # We declare a list here with foods
>>> beverages = "coca-cola pepsi guarana".split() # We declare a list of beverages
>>> [(food, beverage) for food in foods for beverage in beverages]
[('apple', 'coca-cola'), ('apple', 'pepsi'), ('apple', 'guarana'), ('banana', 'coca-cola'), ('banana', 'pepsi'), ('banana', 'guarana'), ('sausages', 'coca-cola'), ('sausages', 'pepsi'), ('sausages', 'guarana')]
What are Generator Expressions?
So generator expressions are just like a list comprehension, but it doesn't store it's values on the memory, it only generate the value you are iterating on when the generator is called. Take a look at the example below:
>>> my_incredible_list = (x for x in range(5))
>>> my_incredible_list
<generator object <genexpr> at 0x7f14149a3db0>
To check for a value on a generator you can either iterate over the generator using a for loop or you can check the values using the next() operator.
>>> # Using the next operator
>>> next(my_incredible_list)
0
>>> next(my_incredible_list)
1
>>> next(my_incredible_list)
2
>>> next(my_incredible_list)
3
>>> next(my_incredible_list)
4
>>> next(my_incredible_list)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
StopIteration
>>>
>>> # Using a for loop
>>> for item in my_incredible_list:
... print(item)
...
0
1
2
3
4
Checking out the Assembly of both of them to see the differences
Assembly instructions from Python disassambler
>>> import dis
>>> my_incredible_list = [x for x in range(5)]
>>> dis.dis(my_incredible_list)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/lib/python3.6/dis.py", line 67, in dis
type(x).__name__)
TypeError: don't know how to disassemble list objects
>>> my_incredible_list = (x for x in range(5))
>>> dis.dis(my_incredible_list)
1 0 LOAD_FAST 0 (.0)
>> 2 FOR_ITER 10 (to 14)
4 STORE_FAST 1 (x)
6 LOAD_FAST 1 (x)
8 YIELD_VALUE
10 POP_TOP
12 JUMP_ABSOLUTE 2
>> 14 LOAD_CONST 0 (None)
16 RETURN_VALUE
>>>
So as we see right here, the disassemble of the list comprehension is not possible, because we cannot disassemble a data structure, but we can still disassemble the generator expression.
When we run dis.dis(<genexpr> right here) we are able to see that the expression is treated like a queue, we yield the value and then we pop it, so it's not called anymore.
If we call the dis.dis(<listcomp> here) we are able to see the running procedure to create a list using the listcomp expression:
>>> dis.dis("[x for x in range(5)]")
1 0 LOAD_CONST 0 (<code object <listcomp> at 0x7f14149c84b0, file "<dis>", line 1>)
2 LOAD_CONST 1 ('<listcomp>')
4 MAKE_FUNCTION 0
6 LOAD_NAME 0 (range)
8 LOAD_CONST 2 (5)
10 CALL_FUNCTION 1
12 GET_ITER
14 CALL_FUNCTION 1
16 RETURN_VALUE
So as we see, the MAKE_FUNCTION piece is run generating the values for the list, we instantiate the function range, load a value to it (5), we call it and them we save it to the list instead of just yielding the value every time the generator is called.
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