Python is one of the most loved programming languages which has its involvement in various domains of work. The demand for the language also calls for the libraries in it.
Python packages and libraries are a collection of essential modules to decrease our work by deduction of code. There exist over 1,37,000 python libraries and 198,826 python packages to ease developers’ part work.
Python libraries are a set of reusable and pre-written programs of the necessary functions that knock out the need of working on a code from scratch.
It just needs to get imported to start the usage. Now let’s discuss how to install and set up the libraries, then we will discuss some of the top Python libraries.
How to Install any library?
To install any library on your system, the basic syntax is almost the same for all.
- First, install the Python software on your device.
- Then type “pip install name_of_library” command in the command line prompt.
- Then type “import name_of_library” in your IDE (ex.- Anaconda) to use.
NumPy
NumPy (Numerical Python), an extension of Numeric and Numarray, is an open-source numerical Python library for scientific computing that can perform numerous mathematical operations on arrays like algebraic, trigonometric, routines, and statistical.
It is one of the most used libraries for tasks involving data science, machine learning, and modern scientific computations. It holds matric data structures and multi-dimensional arrays for showing sound waves, images, and many other raw binary streams.
It also has additional random number generating capabilities, Fourier transform, and linear algebra. It has great usage in data science. It also plays well with many other visualization libraries, such as Plotly, Seaborn, and Matplotlib.
Pandas
Pandas (Python Data Analysis Library) is an open-source library that is used for quicker data analysis and pre-processing, most demanded in the machine learning and data science sector.
It provides flexible, expressive, fast, easy to use, high-performance data analysis tools and data structures by allowing data importing from different file formats like SQL, MS Excel, JSON, etc. which can be “labeled” or “relational”.
It provides various operations for reshaping, merging, data cleaning, selecting, pivoting, data wrangling, and many more features of data manipulation. Pandas is best suitable and highly recommended for data analysis and manipulation tool.
wxPython
wxPython is an open-source, cross-platform highly functional GUI(Graphical User Interface) toolkit for python, which is used to easily create programs with a highly functional graphical user, which means developing applications.
The implementation is done by wrapping GUI components of the wxWidgets (written in C++) library, which are compiled as a set of Python extension modules. A similar program can run on multiple platforms without any modification.
To import it use the following syntax: import wx
Top Python Libraries for Data Modelling
Tensorflow
Tensorflow is an end-to-end open-source and free library for deep learning neural networks and machine learning.
It is a math library released by Google, allowing differentiable programming and dataflow through graphs or node series. It can train neural networks for image recognition, natural language processing, word embeddings, recurrent neural networks, and handwritten digit classification.
The biggest advantage of Tensorflow is an abstraction that lets developers focus on the min logic of the code of the application rather than small silly mistakes.
Keras
Keras, an open-source neural network library is a minimal structure API wrapper of high level which runs libraries like TensorFlow and Theano.
Its discrete deep learning components make it an optimal choice for this application. Options like the availability of convolutional and recurrent neural networks make experimentation and development easy and flexible, increasing computation scalability.
Models like pooling and embedding add up to make more complex models by different fusion. It can be tested on both CPU and GPU with easy to understand language.
Top Python Libraries for Data Deployment
Scrapy
“Scrapy” is an open-source python deployment library designed to provide a framework for rendering or spidering efficiently through various websites without official API and digging out the required information that is analyzed, processed, and structured in the desired format for final usage.
The Item Pipelines provided by it lets us mention the functions in our spider that can process on criteria like automated testing, validating data, deleting unnecessary data, and saving it to a database.
BeautifulSoup
“BeautifulSoup” is a python library that is helpful in displaying the extracted data from XML, HTML, and another markup language by parsing in the documents.
Many times, we suffer problems in downloading content directly, in such cases BeautifulSoup helps to pull out the required data and save data without HTML markup.
It navigates, searches, and modifies a parse tree and hence makes scraping easy. It also converts incoming document codes to Unicode and outgoing document codes to UTF-8.
Type these commands in in terminal to install beautifulsoup:
- pip install beautifulsoup4 OR sudo pip install beautifulsoup4
- pip install lxml OR sudo pip install lxml
- pip install future OR sudo pip install future
Requests
“Requests library” is one of the most popular libraries of python which aims at sending HTTP requests at ease.
It helps in adding headers, sending SSL verification, working on received responses, and forming data. Requests multipart files without any need for manual entrance of string queries for URL and lets the user freely interact with data and services and prevents application backing.
The data harvesting process is simplified as there is an introduction of API’s involvement which makes API’s working symbolize that of a browser.
Top Python Library for GUI Content
Tkinter
Tkinter, a cross-platform and standard GUI (Graphical User Interface) library for python which provides an easy path to create GUI desktop applications with a powerful object-oriented interface linked with the Tk GUI toolkit.
The interface is available on most Unix platforms and Windows Systems. Tkinter is used to build data fields, menus, create buttons, etc. which can be featured with functionalities.
Top Python Library for Game Development
Pygame
“Pygame” is an open-source cross-platform for game development. The computer sound and graphics libraries add up with the python programming language mainly used to develop client-side applications, wrapped to be standalone executable.
These include multimedia applications such as video games. In fact, it uses the SDL library which defeats the need for GUI for programming and acts as a better option by providing the feature of adding multimedia and developing fully- featured games.
Top Python Library for Data Visualization
Matplotlib
“Matplotlib” is the most common library for interactive, animated, and static data visualization and exploration for two-dimensional plots of arrays.
It is called as founder of all other libraries. It sets numerous features to our data like colors, palettes, fonts, themes, and all those of such sort which is customized into charts and graph plot such as line, histogram, scatter, bar. It can work on a huge amount of data from multi-platforms easily.
For installation, type this code in command line prompt:
python -mpip install -U matplotlib
For using, import it by the code:
from matplotlib import pyplot as plt OR import matplotlib.pyplot as plt
Top Python Library for Image and Video Manipulation
Pillow
“Pillow” is a fork of Python Imaging Library (PIL) which provides powerful image processing functionalities to the python library.
Apart from basic options of opening, editing, and saving the images, features like color space conversion, filtering pictures using convolution kernel which is built-in, applying point operations on images have also been added applicable on a variety of formats such as ”tiff”, “png”, “jpeg”, “ppm”, “gif”, “bmp”, “eps”, “im” , “pcx”, “tiff”, “WebP”, “ico”, “psd”, “pdf”, etc.
So, this library can be used to design attractive thumbnails, changing formats, and print images.
For installation, type this code in command line prompt:
python -m pip install pip
python -m pip install pillow
For using, import it by the code:
from PIL import Image
LightGBM
LightGBM library provides a highly optimized, scalable, and quick implementing framework for game boosting.
Its design provides better accuracy, lower memory usage, faster speed of drive along better efficiency. It’s also capable of handling a high capacity of data and is supported with distributed, parallel, scattered yet distributed, GPU learning.
It uses the expanded and detailed histogram-based algorithms on tree boosting. Some applications of LightGBM are it’s used in regression, LambdaRank, binary & multiple classifications, cross-entropy, and many more.
Conclusion
Python being an easy-to-understand language, is in high demand which calls for the need for libraries.
As almost all of the libraries are free, open-source, it eases and simplifies the developers’ tasks to a great extent.
The designing of the libraries is never-ending and goes with the flow of demand to avoid wastage of time in common codes and their errors, letting the user focus on the main designing of the application or program and putting out the innovation and creativity with ease.
Find details about Python Libraries here – https://docs.python.org/3/library/
So, I hope you get some idea about different libraries of python and their specialization in different fields.
