5 Easy Ways To Speed Up Python

5 Easy Ways To Speed Up Python

Python has quickly found itself to be one of the most popular programming languages in the world, bouncing between position one and two on the TIOBE Index. In this tutorial, we'll learn 5 Easy Ways To Speed Up Python. Very simple, in just a few steps.

Speed up your python using these 5 different techniques!

Introduction

Python has quickly found itself to be one of the most popular programming languages in the world, bouncing between position one and two on the TIOBE Index. Across the globe, Python is used for Data Science and machine learning, scripting, software engineering, and even web development. There are many reasons that this has become the case. First and foremost, Python is a very high-level scripting language. This makes Python incredibly easy to learn.

Another thing that should certainly be mentioned is Python’s fantastic ecosystem. Whereas most other package ecosystems in similar languages usually have less than fifty-thousand packages registered, Python has around two-hundred thousand. These packages also span a variety of different disciplines. This means that Python is most likely one of the most versatile languages used today. However, despite how great of an ecosystem Python has and how great of a language it is to use, no language without its problems.

Given Python’s high-level syntax and declarative programming nature, it can be assumed that Python is likely a scripting language. This means that instead of being compiled, it is instead actively read by a compiled programming language, which in this example is the C programming language. Luckily, C is the standard when it comes to lower-level, iterative programming. This means that Python generally gets along with a lot of other language that work with C as well as C itself. In fact, you can write Python from C.

However, with any interpreted programming language, there is always a concern of speed, and with Python there is no exception. Although Python is a pretty fast language when compared with other similar languages, it still does not match the speed of some compiled lower-level solutions like C or C++. Speed tends to be Python’s Achilles’ heel. Although the language has many strengths, the speed of the interpretation is generally regarded as its biggest weakness. However, there are some simple techniques available that can be used to speed Python up very effectively.

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