Python belongs to the most appreciated, adored and wanted languages that software developers use, and modules in Python are something that Python lovers simply cannot go without.
In the latest 2020 Developer Survey held by Stack Overflow, Python was dubbed the third most loved language or technology (as much as 66,7% of software developers who use Python, want to continue to develop with it), and the most wanted one (30% of those who don’t use it yet, want to start developing with it). What’s more, Python has taken the top spot on the latter list for four years running.
This growing popularity of Python may come as a surprise to many, considering that this programming language is more than 30 years old. But its users are well aware of why they like it so much. It’s highly productive (compared to languages such as Java, or C++), powerful, easy-to-learn, and cost-effective with a short development process, and very simple, well-structured code.
Additionally, Python offers vast support of a diverse and international community of programmers as well as access to a large standard library that encompasses internet protocols, program frameworks, generic operating system services, file formats, numeric and mathematical modules, built-in functions and types, and many useful Python modules. The latter are used, first and foremost, to logically and practically organize the Python code in the form of smaller files that larger programs are broken down into.
Let's get to know the modules in Python a little better.
Table of contents:
Python built in modules in a nutshell
Built-in modules in Python are simply files with Python code that come in packages. Those separate files or code groupings contain Python definitions and statements, pre-defined functions, as well as definitions and implementation of classes and are a part of Python libraries that encompas the source code for generic purposes.
There are dozens of available Python built-in modules to choose from, and they may be accessed by using the
>>> help('modules') command in the Python console. To import a module to a particular program, one needs to use the
What distinguishes Python built-in modules is that they:
- are written in C,
- are small batches of code that may later be reused and rerun easily,
- are simple and help develop programs that are easy-to-read, use, and follow,
- organize the Python code in a logical, well-structured way.
These are only some of the features that make modules in Python easy for use, and the development process – faster. Built-in modules in Python are versatile, and proper for many use cases, including web development, building concurrently running applications as well as being a base for third-party modules for Python which, on the other hand, are used for data science, game development, image, sound, and video manipulation and accessing data stored in databases.
But which of the frequently-used or popular Python modules are especially worth noting?
10 built-in modules in Python you should know
Creating the list of the most worth-knowing modules in Python is not an easy task as there are dozens of useful, popular, versatile, and extensible or simply cool ones to choose from. However, the term "Python common module" may be attributed to modules in Python such as:
Offers additional functionality and usability to built-in collections of basic contained types such as
This built-in module in Python is used for handling CSV (standing for comma-separated values) files and data interchange, i.e. downloading and uploading data from spreadsheets.
With this module, work with both date and time is possible, thanks to relevant classes for manipulating them, such as datetime Class, date Class, time Class, and timedelta Class.
Trigonometric, logarithmic, representation as well as angle conversion mathematical functions are all available upon importing the math module but not for use with complex numbers.
As one of Python’s standard utility modules, it provides functions and variables needed to manipulate various parts of the Python runtime environment.
Standing for regular expressions that help the computer to handle the incoming strings from other applications; one of the use cases is Markdown.
Used for generating data randomly, provides a great random number source for math simulations.
A very versatile, feature-rich, and extensible built-in module that may suit many applications, needs, and projects. Worth going the extra mile despite being quite complicated.
Perfect for performing speedy and efficient iterations, it makes many demanding tasks very easy.
Make sure to use these Python built-in modules in your own projects!
What makes coding in Python easy and pleasant are, among others, English-like commands, and simple programming syntax. And Python modules, like multiprocessing, collections, datetime, math, sys, os, re, random, or logging are similarly user-friendly and useful.
However, among important Python built-in modules that software developers appreciate and like using, we may find many others. The list is very long and embraces such modules as time, stat, argparse, configparser, urllib, json, subprocess, shutil, tempfile, threading, string, html, webbrowser, unittest, functools, codecs, to name but a few. Of course, the set of most commonly used built-in modules in Python differ per project type, or even the developer’s seniority.
Save the day with built-in modules in Python
Some of the most worth-noting and using built-in modules in Python include files such as collections, itertools, json, math, time, datetime, sys, os, re, random, and logging. All Python modules, however, may come in handy from time to time.
It’s also worth mentioning that there is a huge number of eagerly-used third-party modules for Python, that may save the day when "regular" Python built-in modules turn out to be insufficient. But very often the latter are perfect enough for various tasks and cases, and they serve as Python developers’ everyday companions. They enhance projects they are used in greatly by improving, smoothening, and speeding up the workflow. And because they stand the test of time, they are definitely worth learning or deepening.
And which built-in modules do you find the most useful when coding in Python? Which are the most versatile or flexible ones? Mastering which ones novice programmers should start with?