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Python Tips

@python_tips

Programming tips, tricks, and news for the Python programming language.

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cPickle is a faster, C written module for pickle.


When applicable, place import statements inside functions to restrict their visibility and/or reduce initial startup time.


Python 3.2 alpha 2 released: http://www.python.org/download/releases/3.2/


Avoid using the addition "+" operator for string concatenation, as it is very expensive. Use str.join() instead.


Sorry that there haven't been any updates for awhile. My computer fried, but I just got a new one! Updates will now resume.


When possible, replace 'if/else' statements with 'try/except'. This will significantly increase performance.


Python 2.6.6 has been released: http://www.python.org/download/releases/2.6.6/


With regard to programming style, Python code should favor readability over conciseness.


Regular expressions are powerful, yet very expensive. Try using starswith, endswith, isdigit, etc. before using regular expressions.


Python 2.6.6 release candidate 2 (maintenance release) now available: http://www.python.org/download/releases/2.6.6/


Use list comprehensions instead of map or filter wherever possible. List comprehensions are easier to work with and much easier to read.


Python 2.6.6 Release Candidate 1 available for download now: http://www.python.org/download/releases/2.6.6/


List comprehension are faster than regular for-loops; therefore, use them for small, compact loops.


When possible, replace 'if/else' statements with 'try/except'. This will significantly increase performance.


Never use a constructor that takes optional arguments. This is an easy mistake to make, yet it can cause debugging nightmares.


While optimization is important, accuracy is paramount. First make it right, then make it fast.


Avoid dots and use local variables; store object methods in local variables and call the local ones.


import statements can be used almost anywhere; therefore, you may place them inside functions to reduce initial startup time.


Using 'from __future__ import division' will allow Python to always return a float as the result of integer division.


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