9 Best Python Libraries | List for Beginners and Advanced Programmers

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Here are the best and helpful Python Libraries for beginners and advanced programmers 2021:

1. Requests

   
   
   The requests library is considered as one in the list best Python library for machine learning and making HTTP requests in Python. It summarizes the complexities behind a beautiful, quick API to make requests so that you can concentrate on communicating with resources in your application and consuming data.
   
   In addition to sending HTTP requests to a server using the Requests library, it also allows you to add form data, content, headers, multi-part files, etc. with them. With the library, developers do not need to manually add a query to the URL or form-encode POST info.
   
   In a simple API, the Requests library abstracts the many complexities of creating HTTP requests so that developers can concentrate more on communicating with services. For Python 2.7, 3.4 and above, the library provides official support and works well on PyPy, too.
   
   Python Library for Machine Learning Supported Features:
   • Content auto-decoding and auto decompression
   • SSL verification
   • Customizable and optimum requirements
   • Connection Pooling and keep-alive
   • Supports multipart file uploads and streaming downloads
   • Supports international domains and URLs
   • Making HTTP requests simpler

2. Pillow

   
   A free Python library that adds an image processing capability to the Python interpreter is the Python Imaging Library or PIL. In simple terms, PIL allows various image file formats in Python to be manipulated, opened, and saved. Pillow, created by Alex Clark and Contributors, is a fork in the PIL library.
   
   We simply import the image module from the pillow to load the image and call the image. open(), passing the filename of the image. We will call the PIL module instead of calling the Pillow module to render it backward compatible with an older module called the Python Imaging Library (PIL).
   
   In addition to having strong image processing capabilities, this belonged to the list of python libraries provides efficient internal representation and detailed support for the file format. The core library of Python is designed for easy access to data stored in a few simple pixel formats.
   
   Python Library Supported Features:
   • Effective debugging support using the show() method
   • Ideal for batch processing applications
   • Identifies and reads a vast range of image file formats
   • Image manipulation
   • Offers BitmapImage, PhotoImage, and Window DIB interfaces
   • Supports arbitrary affine transforms, color space conversions, filtering with a set of built-in convolution kernels, image resizing and rotation, and point operations
   • The histogram method allows pulling some statistics out of an image, can be used for automatic contrast enhancement and global statistical analysis.

3. Asyncio

   
   Another one in the list of python libraries for beginners, Asyncio is a library using the async/await syntax to write concurrent code. Asyncio is used as a basis for various asynchronous Python frameworks that include high-performance networks and web servers, libraries of database links, distributed task queues, etc.
   
   This Python library for machine learning has been used to construct various asynchronous Python frameworks that include libraries for database connections, distributed task queues, high-performance network and web servers, and much more. A variety of high-level and low-level APIs come with the library.
   
   Python Library for Machine Learning Supported Features:
   • Allows controlling subprocesses, distribute tasks via queues, perform network IO and IPC, and synchronize concurrent code
   •Bridge callback-based libraries and code with async/await syntax using low-level APIs
   • Comes with a set of high-level APIs for concurrently running Python coroutines and having full control over their execution
   • Eases working with asynchronous code
   • Supports the creation and management of event loops, implementing effective protocols using transports
   • Working with the asynchronous code

4. Tkinter

   
   The basic GUI library for Python is Tkinter. Python offers a quick and simple way to build GUI applications when coupled with Tkinter. Tkinter provides the Tk GUI toolkit with a strong object-orientated interface. Import a module from this Python library.
   
   It’s really quick to build a GUI framework using Tkinter. All you need to do to use this one in the list of libraries is import Tkinter, create the main window for the GUI application under development and then add one or more Tkinter Widgets. Finally, enter the main event loop for taking action for each user-triggered event.
   
   Over 15 types of widgets, including buttons, labels, and text boxes, are supported by Tkinter. Each of them has access to certain particular methods of geometry management that serve the purpose of organizing widgets across the parent widget field.
   
   Python Library for Machine Learning Supported Features:
   • GUI development
   • Comes with a range of widgets that support geometry management methods
   • Eases developing GUI applications
   • Supports an effective object-oriented interface

5. Six

   
   Six is a powerful Python library that, though simplistic, is meant to smooth out the differences between different versions of Python 2 and Python 3. Six is intended to support codebases that can run without modifications on both Python 2 and Python 3.
   
   Thanks to being offered as a single Python file, the Six library is super-easy to use. Hence, copying the library into a Python project is ridiculously easy. (Python) 2 x (Python) 3 reflects the name Six.
   
   Python Library Supported Features:
   • Compatibility library (wrapping over differences between Python 2 and Python 3)
   • Simple utility functions for making Python code compatible with Python 2 and Python 3
   • Supports every version since Python 2.6
   • Too simple to use as contained in a single Python file

6. aiohttp

   
   Aiohttp is another basic but widely used Python library. Basically, it is intended to be a Python asynchronous HTTP client or server. There is nothing more to this Python library beyond this and offering out-of-the-box support for Client WebSockets and Server WebSockets.
   
   Python 3.5 has added some new syntax that makes it easier for developers to create asynchronous apps and packages. Aiohttp, which is an Asyncio HTTP client/server, is one such package. Basically, it enables asynchronous clients and servers to be published.
   
   Python Library Supported Features:
   • Offers a web server that has middlewares, pluggable routing, and signals
   • Provides out-of-the-box support for both Client WebSockets and Server WebSockets
   • Supports both Client and HTTP Server

7. Pygame

   
   Pygame is one in the list of best Python libraries for beginners that is free and open source python programming language library built on top of the excellent SDL library for creating multimedia applications such as games.
   
   For rapid prototyping of games, Python is an excellent alternative. But it does have performance limitations. You should therefore consider the industry standard, which is C # with Unity or C ++ with Unreal, for more resource-intensive games. Some popular games have been developed using Python, such as EVE Online and Pirates of the Caribbean.
   
   Under that same hood, the SDL (Simple DirectMedia Layer) library is used by Pygame. The Pygame library is extremely portable, like the SDL library, and thus offers support for a broad range of platforms and operating systems.
   
   On Android-powered devices such as smartphones and tablets, it is possible to port applications built using Pygame. Pgs4a (Pygame subset for Android) needs to be used for this very reason.
   
   Pygame is a free and open source Python library intended for the creation of multimedia applications in Python, especially two-dimensional gaming projects. Therefore, both casual and serious Python game developers use it extensively.
   
   Python Library Supported Features:
   • Doesn’t demand OpenGL
   • Makes easy for using multi-core CPUs
   • No GUI required for using all available functions
   • Provides support for a wide range of platforms and operating systems
   • Simple and easy to use
   • Uses Assembly code and optimized C code for implementing core functions

8. Kivy

   
   Kivy is a multi-platform, open source Python GUI development library that can run on iOS, Android, Windows, OS X, and GNU/Linux.
   
   Python developers rely on the Kivy library for constructing mobile applications and multi-touch application software with a NUI (Natural User Interface). Distributed under the MIT license, the free and open-source Python library runs on Android, iOS, Linux, macOS, and Windows.
   
   Kivy is, in fact, the evolution of the PyMT project. It includes all the elements required to create an intuitive multi-touch application, such as a graphics library, a wide range of multi-touch widgets, an intermediate language (Kv) and comprehensive input support.
   
   Python Library Supported Features:
   • Ability to natively use most devices, inputs, and protocols
   • Cross-platform
   • Offers over 20 highly-extensible widgets
   • Support graphics engine built over the OpenGL ES 2
   • Application development (with innovative user interfaces)

9. Bokeh

   
   Another presented python library for beginners, Bokeh is an interactive visualization Python library that targets Web browsers for representation. These bindings create a JSON file that acts as a BokehJS (Javascript library) input, which in turn presents information to modern web browsers. Bokeh, like D3, can create elegant and immersive visualizations.
   
   For modern web browsers, Bokeh is an immersive visualization library. It provides elegant, succinct building of versatile graphics and provides large or streaming datasets with high-performance interactivity.
   
   This Python library is authorized by BSD and is accessible on GitHub.
   
   Python Library Supported Features:
   • Allows building complex statistical plots with simple commands
   • Bokeh visualizations can be easily embedded into two of the most popular Python frameworks, Django and Flask
   • Capable of producing elegant and interactive data visualizations
   • Developing visualization-based applications
   • Multiple language bindings (Julia, Lua, Python, and R)
   • Various output formats