Optimization of Python codes deals with selecting the best option among a number of possible options that are feasible to use for developers. Python is the most popular, dynamic, versatile, and one of the most sought after languages for mobile application development. Right from the programming projects like machine learning and data mining, Python is still the best and most relevant language for application developers.
Code Optimization Tips for Python Developers
In this post, I will discuss some of the optimization procedures and patterns in Python coding in an effort to improve the overall coding knowledge.
Optimizing Slow Code First
When you run your Python program, the source code .py is compiled using CPython into bytecode (.pyc file) saved in a folder (_pycache_) and at the end interpreted by Python virtual M2M code (machine to machine). Since Python uses an interpreter to execute the bytecode at runtime which makes the process a bit slower.
To make your execution faster on CPython, get PyPy v7.1 that include two different interpreters and the feature of its predecessor PyPy3.6-beta and Python 2.7. Compared to CPython it is 7.6X faster which is critical for coding. Programs in CPython takes a lot of space, but PyPy takes up less space in programs.
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