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

Joined January 2010
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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.
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Python 3.2 alpha 2 released: http://www.python.org/download/releases/3.2/
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Avoid using the addition " " operator for string concatenation, as it is very expensive. Use str.join() instead.
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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.
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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.
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Regular expressions are powerful, yet very expensive. Try using starswith, endswith, isdigit, etc. before using regular expressions.
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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.
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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.
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When possible, replace 'if/else' statements with 'try/except'. This will significantly increase performance.
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Never use a constructor that takes optional arguments. This is an easy mistake to make, yet it can cause debugging nightmares.
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While optimization is important, accuracy is paramount. First make it right, then make it fast.
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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.
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Using 'from __future__ import division' will allow Python to always return a float as the result of integer division.
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