Python Libraries

Python is currently one of the best programming languages which are used all around the world. However, based on its number of users or the various areas where Python get used is incomparable. So it would be safe for us to say that it is the primary need of every developer and organization.

The reason for its popularity is because of its unique features. It is open-source, and also it has an extensive package library. Therefore, everyone can contribute to its packages, and all can create their own.

Let’s learn about some of the famous python libraries that one should know.

1. TensorFlow: TensorFlow is one of the top libraries of Python that get used for both deep learning and machine learning. So, if you are working on building a vast machine learning application or building a neural network, then TensorFlow is undoubtedly the best option that you can choose. It also has a massive range of options to choose from when building a machine learning language model. Moreover, it gets used to handling a neural network arduously without any data problem. So, it is still considered the very preferred library in 2021 to go for.
   

   Python Libraries – TensorFlow

2. Numpy: Numpy is the short form of Numerical Python. For someone who has started their career in the field of data analytics, then you might have heard about this Python library. The main job of this library is to make mathematics in Python easy. So, if you are working on something on the machine learning or data analytics side, it becomes necessary to understand mathematics comprehensively. It would help if you had things like statistics, linear algebra, etc. Here what Numpy does for you is that it embeds every maths function as a python function so that you can perform all those mathematical operations efficiently. So, it is an instrumental and reliable Python library for anyone looking to start their career in data analytics.
   

   Python Libraries – NumPy

3. Pandas: Pandas is another modern and functional Python library used to handle and manage data. It is for someone working on the data side, and if you are working on excel or CSV files, you need this library mandatorily. Because Pandas is used to handle any data, you can organize the data in the CSV file, claim the data, import the column from the CSV file and organize that, make analytics out of the data set, etc. So it is a very go-to library to get analytics and insights about the data set.
   

   Python Libraries – pandas

4. Matplotlib: Matplotlib is one of the very famous Python packages used for data visualizations that one can use to get insights from the data. You can also use this library with a combination of Numpy or Pandas. It helps you get high-level insights from that, which can get used in creating graphs and pie charts. You can also create different types of charts using Matplotlib very conveniently. Also, it is open-source, and hence it can get used freely.
   

   Python Libraries – matplotlib

5. PyTorch: PyTorch is a Python library based on the Torch library. It can also be called an alternative to TensorFlow. It got developed by Facebook and is mainly used by that only. So basically, it does the same operations which TensorFlow does. Therefore, it is beneficial to deal with neural networks and all those kinds mentioned earlier. So if you are someone who is fancy about building a machine learning model with the help of advanced URL nets and you are very comfortable with TensorFlow, then you can happily go with this library.
   

   Python Libraries – PyTorch

6. OpenCV: This is a very fancy library initially developed by intel. It is allowed by most developers, and it is a computer vision package that can get used in many (almost all) image processing tasks. Whether it is an object detection model, biometric, self-driving car, face detection model, etc., in short, everything that involves computer vision application can be get treated with this Python library. You can use this library to build all those models you want. You can create an object detection classifier, face detection model from scratch. So, in a nutshell, you can use OpenCV at any advanced level to build all those image processing applications.
   

   Python Libraries – OpenCV

7. TextBlob: TextBlob is another famous Python library, and it is one of the most popular NLP libraries. Nlp stands for Natural Language Processing, where users deal with natural language. So, TextBlob is an excellent pick for processing textual data. NLP is also gaining a lot of attention because of its increasing number of applications such as machine translation, chatbots, etc. The part of speech tagging is one of the most potent aspects of TextBlob. You can perform NLP tasks using this package, such as limitation, stemming, extracting sentiment analysis out of data. It is undoubtedly one of the finest Python libraries to go for if working on natural language processing.
   

   Python Libraries – TextBlob

8. Gensim: Gensim is a language processing library whose target audience is the natural language processing and information retrieval communities. It has a simple interface memory, independent algorithms, and efficient multi-core implementations of popular algorithms like LDA, LSA, and RP. It is straightforward to pick up from the library, and it also comes with extensive documentation and Jupiter notebook tutorials.
   

   Python Libraries – Gensim

9. Requests: Requests is the most popular Python HTTP library, and it gets used to sending HTTP requests. It has tons of features and is especially great for beginners in this field. For example, you can add parameters, headers, multipart files, and form data to HTTP Requests. In addition, this lassie program uses the Requests library to retrieve actual content from websites. For example, if you input the URL of a Youtube video, it will retrieve information like the title description and keywords.
   

   Python Libraries – Requests

10. Beautiful Soup: Beautiful is a Python library often referred to by bs4. It is used for parsing HTML and XML documents. It is also one of the best web scrapping packages that one can use. You can scrap data from any website using this fancy package called bs4. It also provides an idiomatic way of searching, modifying, and navigating the parse tree while working with your favourite parser. It is still one of the best packages in web scraping, and it is allowed by the developers because it is easy to get data from any website using this library called Beautiful Soup. It can also get used as a cleaner for most people.
11. Tkinter: If you have a keen interest in building GUI-based applications in Python, then Tkinter is the best option for you to choose. It allows you to make a Python application in GUI interfaces. The task becomes very easy when using Tkinter to create a GUI application. So, you can use this Python Package to build any application, and you don’t even need a web server for that. It is allowed by many people, and it has several strengths.
    

    Python Libraries – Tkinter

12. Pillow: Pillow is known for Python Imagining Library, a free and open-source library. It is similar to Open CV, but it gets used for various image processing applications. This Python package allows you to create and manipulate digital images. So, wherever there is a requirement with image data, you can use this library to control the size of the photos and handle the image data set and any other image-related task that you wish to get done. Also, its current version reads and identifies a lot of formats.
    

    Python Libraries – pillow

13. FlashText: FlashText is a Python package mainly used to extract, replace, and remove keywords in a given text data. One of its vast benefits is its speed. Using a tree data structure, FlashText can perform super fast on large pieces of data. You can also see that it outperforms regex for text more significant than 500 words, and it is significantly faster for even larger readers. However, one downside of this library is that it cannot search for special characters. Nevertheless, FlashText is the go-to library for vision data.
14. Pygame: Pygame is a super easy-to-learn wrapper module for writing video games. It contains computer graphics and a sound library to create dynamic games fast. Programs written with Pygame are compatible with all SDL-supported operating systems, and they can also run on android and tablets. Features like pixel camera manipulation, midi, and collision detection are also supported. You can use it to create games like space shooter and t-rex rush, and if you ever need inspiration, you can check its website for thousands of games it has made.
15. Pyglet: If you want to create a 3d game, Pyglet is your go-to library. Unlike Pygame, Pyglet is bale to create a 3-d guise. On top of that, Pygket has no internal dependencies or installation requirements that allow you to use as many windows as you need and loads images, music, sound, video in almost any format.
    

    Python Libraries – Pyglet

16. wxPython: This is a GUI toolkit for the Python language commonly used as an alternative to Tkinter. It is an excellent choice for cross-platform Python as it supports Windows, Linux, and Mac. Apart from these, wxPython is easy to use, and it offers a sophisticated design layout for developers. Outlier is one program developed using Python that stores notes in a tree.