Python 3: Map with Side Effect Doesn't Work If Result is Not Used

By Xah Lee. Date: . Last updated: .

in Python 3, map with side effect doesn't work if you don't use the result.

# python 3

# in python 3, map returns a “iterator”. If you use map with side effects, it doesn't work if you don't use the result

a = 0

def ff(n):
    global a
    a = a+n
    return n+1

map(ff, [1,1,1])
print(a)   # 0

b = map(ff, [1,1,1])
print(a)   # 0

list(map(ff, [1,1,1]))
print(a)   # 3

Here's Python 2:

# -*- coding: utf-8 -*-
# python 2

a = 0

def ff(n):
    global a
    a = a+n
    return n+1

map(ff, [1,1,1])
print a # 3

Why is the Python 3 Iterator Way Bad?

The interesting point here is that, Python 3 introduced complexity.

in lisp, perl, Mathematica, you can map a function to a list.

; emacs lisp
(mapcar 'f mylist)」

[see Elisp: Map / Loop Thru List / Vector]

# perl
map {f $_} @mylist

[see Perl: Map Function to List]

(* Mathematica  *)
Map[f, mylist]

their semantics is simple. Apply f to each element of list, return the new list. The language doesn't care if your f has side effects. If it does, you wrote it that way, you have control of what you want. The semantics remains systematic and simple.

But in python 3, this is not so, due to its introduction of compiler engineering by-product concept of “iterator” and “generator”. For example, in python, when you do:

for x in myhash.keys():
    if x == 10: break

and suppose myhash is 10 billion elements. It's not efficient, because python creates a huge list first. Python solves this by introducing “iterator”, as in

for x in myhash.iterkeys():
    if x == 10: break

the issue here, is, for x in myhash.keys() should do the right thing without introducing a concept of iterator. The “iterator” is a by-product of computer engineering of object oriented programing. A extra layer of concept between the programer who needs to specify algorithms, and the compiler/machine that do the computation. It is created to solve compiler problem (speed, memory footprint), by shoving the problem to human.

thanks to • Fabrice Popineau, Yuri Khan

Python Semantic Bad

  1. Why List Comprehension is Bad
  2. Python 3: Map with Side Effect Doesn't Work If Result is Not Used
  3. The Idiocy of Python's Function Parameter Specification
  4. Python Scope Complexity, Shallow Copy, Deep Copy, Circular List, and the Garbage Underneath Computer Languages
  5. Python: dict={} vs dict.clear()
  6. Python: Get Number of Arguments of Function
  7. Python: Copy Nested List, Shallow/Deep Copy
  8. Python: Keyword Argument Default Value Unstable
  9. Python: Append String in Loop
  10. FCK Python: String Methods, Functions, Slashes and Backslashes
  11. Python Bitwise Invert Oddity
  12. From Why Not Ruby to FCK Python, Hello Ruby
  13. Why Learn Lisp When There Are Perl and Python

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