List Comprehension vs Generator Expressions in Python
A Generator Expression is doing basically the same thing as a List Comprehension does, but the GE does it lazily. The difference is quite similar to the difference between range and xrange.
A List Comprehension, just like the plain range function, executes immediately and returns a list.
A Generator Expression, just like xrange returns and object that can be iterated over.
The comparision is not perfect though, because in an object returned by the generator expression, we cannot access an element by index.
The difference between the two kinds of expressions is that the List comprehension is enclosed in square brackets  while the Generator expression is enclosed in plain parentheses ().
l = [n*2 for n in range(1000)] # List comprehension g = (n*2 for n in range(1000)) # Generator expression
The type of resulting values are list and generator respectively:
print(type(l)) # 'list' print(type(g)) # 'generator'
Size in memory
The size of the objects is 9032 bytes (the list), and 80 bytes (the generator):
print(sys.getsizeof(l)) # 9032 print(sys.getsizeof(g)) # 80
Access by Index
list, but if we try to access the elements of the generator we get a TypeError:
print(l) # 8 print(g) # TypeError: 'generator' object has no attribute '__getitem__'
Finally, but most importantly, we can iterate over either of them:
for v in l: pass for v in g: pass
The full example
#!/usr/bin/env python from __future__ import print_function import sys l = [n*2 for n in range(1000)] # List comprehension g = (n*2 for n in range(1000)) # Generator expression print(type(l)) # <type 'list'> print(type(g)) # <type 'generator'> print(sys.getsizeof(l)) # 9032 print(sys.getsizeof(g)) # 80 print(l) # 8 #print(g) # TypeError: 'generator' object has no attribute '__getitem__' for v in l: pass for v in g: pass