Performance optimization

Remarks

When attempting to improve the performance of a Python script, first and foremost you should be able to find the bottleneck of your script and note that no optimization can compensate for a poor choice in data structures or a flaw in your algorithm design. Identifying performance bottlenecks can be done by profiling your script. Secondly do not try to optimize too early in your coding process at the expense of readability/design/quality.

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Performance optimization:

*Performance optimization

*Code profiling

Table Of Contents

0Getting Started

1List comprehension

10Importing modules

11Sorting Minimum and Maximium

12Operator module

13Variable Scope and Binding

14Basic Input and Output

15Files, Folders, I/O

17String Methods

19Indexing and Slicing

21Simple Mathematical Operators

24Exponentation

29Manipulating XML

30Date and Time

32Collections module

33Parallel computation

34Multithreading

35Writing C extensions

37Regular Expressions

38Bitwise Operators

39Incompatibilities moving from Python 2 to Python 3

40Virtual environments

43Context Managers with Statement

44Hidden Features

46String Formatting

49Unicode and bytes

50The __name__ special variable

51Check if path exists

53Asyncio Module

54Print Function

55os.path module

56Creating Python packages

57Parsing Command Line Arguments

59Subprocess Library

63Itertools Module

65Boolean Operators

68pip PyPI Package Manager

69locale module

73Distributing self-contained applications

74Property Objects

77Reading and Writing CSV

78Dynamic code execution with exec and eval

79PyInstaller - Distributing Python Code

80Iterables and Iterators

81Data Visualization

82The interpreter command line console

83args and kwargs

84functools module

85Garbage Collection

87Security and Cryptograhy

88Pickle data serialization

91Python and Excel

93Method Overriding

94Difference between a module and a package

95Data Serialization

96Python Concurrency

97RabbitMQ using AMQPStorm

100Common Pitfalls

101Multiprocessing

102Creating temporary files with tempfile

103Working with ZIP files

106User-Defined Methods

107Working around Global Interpreter Lock

108Deployment using conda

110Processes and Threads

112Comments and documentation

113Database Access

114Python HTTP Server

115Alternatives to switch statement from other languages

116List destructuring

117Accessing Python source code and bytecode

119Attribute Access

121Python Anti-Patterns

122Plugin and Extension Classes

124Immutable data types

125String representations of class

127Operator Precedence

128Polymorphism

129Alternative Python implementations

130List Comprehensions

131Web Server Gateway Intrerface WSGI

133Abstract Syntax Tree

134Abstract Base Classes

136ssh in Python

137Serial Communication with pyserial

139Performance optimization

142pass statement

143Testing with py.test

144Date Formatting

147CLI subcommands

148Defining functions with list arguments

149SQLite3 module

150Persistence with pickle

151Connecting to SQL Server

152Design Patterns

153Multidimensional arrays

156queue module

158webbrowser module

159base64 module

162Sockets and Message Encryption / Decryption

164Input Subset and Output External Data Files using Pandas

168Creating a Windows Service

169Mutable vs. Immutable

170configparser

171Common Exceptions

172Optical Character Recognition OCR

173Python Data Types

174Partial functions

175Generating graphs

176Unzipping Files

177Functional Programming

178Python Virtual Environment - virtualenv

180virtual environment with virtualenvwrapper

181virtualenvwrapper on Windows

182Python Requests Post

183Plotting with Matplotlib

184Python Lex-Yacc

187pip and PyPI Package Manager

188Writing to CSV from String or List

189Raise Custom Errors Exceptions

190Using loops within functions

191Contributors