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Top 10 Python Tools

Top 10 Python Tools

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Python has undoubtedly become one of the most popular programming languages, among both freshers as well as experienced developers. This is mainly because of the easy syntax this language provides, and also the multiple libraries it hosts, thus making life of a programmer easier. Due to its enormous popularity, Python is now finding applications in fields like Data Science, DevOps, Machine Learning, etc.

Along with its libraries, Python is also popular for the multiple tools it hosts and how these help coders to develop softwares and programmes in an easier manner. Students who enroll in an online Python Certification course get deep knowledge about these tools. In this article, we will be discussing some of the top Python tools, their specific purpose, and why they are preferred. So let’s begin.

Before we start listing the tools, it is to be noted that Python tools can be categorized into major functions they are meant for. It will be on the lines of this, that our classification below will be done.

Python Tools for Automation Testing

Testing forms an integral part of any software development cycle and ensures the final product is bug free. Listed below are some top Python tools that make life easier for automation testers.

  • Selenium

Selenium is an open source platform that allows you to perform web based automation testing. With Selenium, you do not need to learn any additional script language. This tool helps you to write scripts in various other languages also like Java, C#, PHP, Perl, .NET, etc.

Selenium is supported on all major operating systems like Windows, Linux, macOS, and also allows you to function through various browsers like Chrome, Mozilla, Safari, Opera, etc. Selenium can also be used to automate tasks like opening a browser, dragging and dropping files.

  • Robot Framework

While Selenium relies on support of automation testers to execute any task, the Robot Framework makes use of test libraries. Also an open source tool, it is majorly used for Acceptance Test-Driven Development (ATTD).

The libraries of Robot framework can be integrated with other libraries of Java and Python, and it also allows testing on web, android as well as iOS.

  • TestComplete

TestComplete is another popular Python tool for automation testing, however, it is not open source but a commercial product. This means that you need to obtain a commercial license to be able to use this tool. With TestComplete, you do not need to maintain test scripts as the GUI recognition here can detect as well as update the UI objects.

Python Tools for Web Scraping

Web scraping is the practice of running scripts on different websites to extract data from them. Though it is a popular technique and is also used by search engines in some cases, web scraping is not permitted in every case, therefore, proper cautions need to be taken. Listed below are the best Python tools for web scraping.

  • Scrapy

Scrapy is a free, open-source web crawling framework that can also be used to extract data using APIs. Scrapy is also popular for other functions like Data Mining, Automation Testing, etc. Scrapy uses very easy and quick methods to extract information using HTML tags and CSS classes.

An important feature of Scrapy is that this tool can be extended to add new functions whenever required.

  • Beautiful Soup

Beautiful Soup is a python tool which is made specifically for crawling HTML and XML documents. It can be used for making parse trees, whether you want to navigate, search or modify it. An attractive feature of Beautiful Soup is its inherent ability to convert incoming documents to Unicode and outgoing documents to UTF-8. This tool can not only extract data from the HTML web pages but can also modify that.

  • LXML

Rich in various features, LXML is one of the easiest python tools which is used for scraping XML and HTML files. A mixture of speed and simplicity, this tool is designed majorly for C libraries but also extends support to XML Schema, XPath, XSLT, C14N, and others.

Python Tools for Image Processing

While most people rely on high end GUI softwares like Adobe Photoshop, Python also has a lot to offer when it comes to image processing.

  • Pillow

Pillow is an open source and free Python library that allows users to perform image processing and various other related functions in a very easy manner, and at a very fast speed. Utilizing the super easy syntax of python language, Pillow allows you to perform functions like blurring an image, manipulating pixels, enhancing image, adjusting brightness, adding text, contouring image, etc.

Pillow is an extension of the discontinued Python Image Library (PIL) project. It supports various file formats like JPEG, PNG, GIF, PPM, TIFF, and BMP.

Python Tools for Data Science

The most rapidly advancing IT sector is Data Science, including new age concepts like Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), etc. Python tools have been busy creating their presence in this realm also.

  • Keras

Keras is an open source python framework that provides interfaces for artificial neural networks (ANNs). Best python tool presently for ML and AI, Keras is user friendly and integrates the features of extensibility and modularity. Keras has an added advantage that it can operate with other neural network frameworks like TensorFlow, CNTK, Theano, etc.

  • Theano

A more to-the-ground tool, Theano is the python framework that works mainly with mathematical expressions and multi dimensional arrays. Theano computations can run efficiently on both CPU and GPU architectures, and this tool is capable of working on Windows, Linux and macOS. Theano is popular for extensively working, that too at a great speed, and it also allows you to optimize code.

  • Scikit-Learn

Scikit-Learn is another free and open source python framework, which is openly used by developers for functionalities like Data Mining and Machine Learning. The major features which make this tool popular are Regression, Clustering, Classification, and Preprocessing. This tool makes use of algorithms like Random Forest, Gradient Boosting, k-Means, etc.

In addition to these 10 tools mentioned above, Python has a huge list of frameworks suitable for other purposes like Generating Fake Data, Data Analytics, APIs, etc. The scope of this article is limited to identifying the top 10 trending python tools, but you can always explore more and find out which one best suits your needs.

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