

It also helps in web scraping, which has become quite essential these days for businesses. It has plenty of related libraries and frameworks such as PyBrain, Bottle, Flask, web3py, etc., useful in data science to visualize and analyze large volumes of data and other purposes. Data Science: Python is used extensively in Data Science.Python’s exclusive libraries, such as SciPy, Seaborn, TensorFlow, NumPy, Pandas, etc., serve these purposes. Machine learning and artificial intelligence: From search engines and social media to chatbots and virtual assistants, algorithms are everywhere and powered by machine learning and artificial intelligence.
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A few biggies who use it for software development include Dropbox, P圜hess, BitTorrent, Gramps, etc. You can also develop complex apps with scientific and numeric computing. Many Python packages, such as NumPy, Tkinter, SciPy, etc., simplify the software development procedures.

Python is a versatile programming language.
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So, you can use the same code across different platforms like Windows, macOS, Unix, or Linux.ĭid you know that Python is the second most popular programming language (right behind JavaScript)? 🤓 All the more reason to add it to your programming toolkit 🛠 Click to Tweet Where Is Python Used? As a result, it makes programming simpler and reduces many lines of code. Dynamically-typed: Specifying a variable type such as char, int, double, etc., is not needed in Python as it’s decided during code run time rather than at the start.This way, there’s no need for compilation, and debugging becomes easy. Interpreted and easy to debug: Python executes code linearly, like Java, C, and C++.Object-oriented: Python uses object-oriented programming concepts, such as objects, classes, inheritance, data encapsulation, and more.For example, you can add a programmable interface to an existing application. Extensible: Python is highly extensible with different modules to extend the core functionality.Examples include Django, Flask, NumPy, and SciPy. You can find reusable code for processes like image manipulation, unit testing, CGI, and more.

Extensive libraries: Python’s standard library is extensive with rich modules and functions that help you complete your projects faster instead of writing code from scratch.Hence, it’s developer-friendly and easy to code. Its simpler syntax uses plain English with less complexity.

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