Is there a way to circumvent Python list.append() becoming progressively slower in a loop as the list grows?

by

The poor performance you observe is caused by a bug in the Python garbage collector in the version you are using. Upgrade to Python 2.7, or 3.1 or above to regain the amoritized 0(1) behavior expected of list appending in Python.

If you cannot upgrade, disable garbage collection as you build the list and turn it on after you finish.

(You can also tweak the garbage collector’s triggers or selectively call collect as you progress, but I do not explore these options in this answer because they are more complex and I suspect your use case is amenable to the above solution.)

Background:

See: https://bugs.python.org/issue4074 and also https://docs.python.org/release/2.5.2/lib/module-gc.html

The reporter observes that appending complex objects (objects that aren’t numbers or strings) to a list slows linearly as the list grows in length.

The reason for this behavior is that the garbage collector is checking and rechecking every object in the list to see if they are eligible for garbage collection. This behavior causes the linear increase in time to add objects to a list. A fix is expected to land in py3k, so it should not apply to the interpreter you are using.

Test:

I ran a test to demonstrate this. For 1k iterations I append 10k objects to a list, and record the runtime for each iteration. The overall runtime difference is immediately obvious. With garbage collection disabled during the inner loop of the test, runtime on my system is 18.6s. With garbage collection enabled for the entire test, runtime is 899.4s.

This is the test:

import time
import gc

class A:
    def __init__(self):
        self.x = 1
        self.y = 2
        self.why = 'no reason'

def time_to_append(size, append_list, item_gen):
    t0 = time.time()
    for i in xrange(0, size):
        append_list.append(item_gen())
    return time.time() - t0

def test():
    x = []
    count = 10000
    for i in xrange(0,1000):
        print len(x), time_to_append(count, x, lambda: A())

def test_nogc():
    x = []
    count = 10000
    for i in xrange(0,1000):
        gc.disable()
        print len(x), time_to_append(count, x, lambda: A())
        gc.enable()

Full source: https://hypervolu.me/~erik/programming/python_lists/listtest.py.txt

Graphical result: Red is with gc on, blue is with gc off. y-axis is seconds scaled logarithmically.


(source: hypervolu.me)

As the two plots differ by several orders of magnitude in the y component, here they are independently with the y-axis scaled linearly.


(source: hypervolu.me)


(source: hypervolu.me)

Interestingly, with garbage collection off, we see only small spikes in runtime per 10k appends, which suggests that Python’s list reallocation costs are relatively low. In any case, they are many orders of magnitude lower than the garbage collection costs.

The density of the above plots make it difficult to see that with the garbage collector on, most intervals actually have good performance; it’s only when the garbage collector cycles that we encounter the pathological behavior. You can observe this in this histogram of 10k append time. Most of the datapoints fall around 0.02s per 10k appends.


(source: hypervolu.me)

The raw data used to produce these plots can be found at http://hypervolu.me/~erik/programming/python_lists/

More Related Contents:

  1. What is the difference between Python’s list methods append and extend?
  2. Why does append() always return None in Python? [duplicate]
  3. Fastest way to check if a value exists in a list
  4. Get difference between two lists
  5. Python Sets vs Lists
  6. Python append() vs. + operator on lists, why do these give different results?
  7. Why does foo.append(bar) affect all elements in a list of lists?
  8. Are tuples more efficient than lists in Python?
  9. Why is [] faster than list()?
  10. What is the syntax to insert one list into another list in python?
  11. Appending item to lists within a list comprehension
  12. [] and {} vs list() and dict(), which is better?
  13. Appending a dictionary to a list in a loop
  14. Why is tuple faster than list in Python?
  15. Complexity of list.index(x) in Python
  16. How can I find same values in a list and group together a new list?
  17. Most efficient way for a lookup/search in a huge list (python)
  18. Create random list of integers in Python
  19. How to allow list append() method to return the new list
  20. Get difference between two lists with Unique Entries
  21. List as a member of a python class, why is its contents being shared across all instances of the class?
  22. What’s the difference between plus and append in python for list manipulation? [duplicate]
  23. sum each value in a list of tuples
  24. Python List Indexing Efficiency
  25. Python: iterating over list vs over dict items efficiency
  26. First items in inner list efficiently as possible [duplicate]
  27. Python The appended element in the list changes as its original variable changes
  28. Which is the most efficient way to iterate through a list in python?
  29. Length of longest word in a list
  30. deque.popleft() and list.pop(0). Is there performance difference?

Leave a Comment