Python: Append String in Loop

By Xah Lee. Date: . Last updated: .

Avoid using the + and += operators to accumulate a string within a loop. Since strings are immutable, this creates unnecessary temporary objects and results in quadratic rather than linear running time. Instead, add each substring to a list and ''.join the list after the loop terminates (or, write each substring to a cStringIO.StringIO buffer).

[from Google's python style guide. ]

They gave 2 examples, one using string append and the other using list append. Here's their examples, slightly modified to be runnable code:

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

# append string in a loop

employee_list = [["Mary", "Jane"], ["Jenny", "Doe"], ["Alice", "Johnson"]]

employee_table = '<table>'

for last_name, first_name in employee_list:
    employee_table += '<tr><td>%s, %s</td></tr>' % (last_name, first_name)

employee_table += '</table>'

print employee_table
# <table><tr><td>Mary, Jane</td></tr><tr><td>Jenny, Doe</td></tr><tr><td>Alice, Johnson</td></tr></table>

here's a version using array:

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

# append string in a loop, but using list instead

employee_list = [["Mary", "Jane"], ["Jenny", "Doe"], ["Alice", "Johnson"]]

items = ['<table>']

for last_name, first_name in employee_list:
    items.append('<tr><td>%s, %s</td></tr>' % (last_name, first_name))


employee_table = ''.join(items)

print employee_table
# <table><tr><td>Mary, Jane</td></tr><tr><td>Jenny, Doe</td></tr><tr><td>Alice, Johnson</td></tr></table>

This is interesting in 2 aspects:

  1. It is a nice Python trick to know. It makes your code a order of magnitude faster. (when your list has large number of items)
  2. It shows that the Python language and compiler combination is not smart enough. Clearly, using list to append string as a intermediate step to increase speed, is a hack. The direct string append is clear and is what programer want.

For a speed test, see: [Python Strings Accumulation Techniques By Magnun. At , accessed on 2018-07-09 ]

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

If you have a question, put $5 at patreon and message me.


  1. Python 3 Basics
  2. Python 2 Basics
  3. Python 2 and 3 Difference
  4. Print Version
  5. Builtin Help
  6. Quote String
  7. String Methods
  8. Format String
  9. Operators
  10. Complex Numbers
  11. True, False
  12. if then else
  13. Loop
  14. List Basics
  15. Loop Thru List
  16. Map f to List
  17. Copy Nested List
  18. List Comprehension
  19. List Methods
  20. Sort
  21. Dictionary
  22. Loop Thru Dict
  23. Dict Methods
  24. Tuple
  25. Sets
  26. Function
  27. Closure
  28. 2 Closure
  29. Decorator
  30. Class
  31. Object, ID, Type
  32. List Modules
  33. Write a Module
  34. Unicode 🐍


  1. Regex Basics
  2. Regex Reference

Text Processing

  1. Read/Write File
  2. Traverse Directory
  3. File Path
  4. Process Unicode
  5. Convert File Encoding
  6. Find Replace in dir
  7. Find Replace by Regex
  8. Count Word Frequency


  1. Send Email
  2. GET Web Page
  3. Web Crawler


  1. JSON
  2. Find Script Path
  3. Get Env Var
  4. System Call
  5. Decompress Gzip
  6. Append String in Loop
  7. Timing f timeit
  8. Keyword Arg Default Value Unstable
  9. Check Page Load Size
  10. Thumbnail Generation