Top 40 Python Libraries with Kalyn from Kite

Natural Language Processing

NLTK (Natural Language Toolkit)

• Widely popular for NLP tasks.
• Functions: Tokenizing, tagging, stemming.
• Tokenizing separates words or sentences.
• Part of speech tagging labels each word.
• Stemming simplifies words to their root form.

Gensim

• For NLP and information retrieval.
• Simple interface and memory-efficient algorithms.
• Supports LSA, LDA, RP.
• Extensive documentation and tutorials.

FlashText

• Quick keyword extraction and replacement.
• Uses a tree data structure for speed.
• Faster than regex for text > 500 words.
• Doesn’t handle special characters.

Computer Vision

OpenCV

• Largest computer vision library.
• Functions: Read/write images, edge detection, filtering.
• Enables complex programs like face detectors.

SimpleCV

• Beginner-friendly framework for computer vision.
• Access to high-powered libraries like OpenCV.
• Good for projects like pedestrian walk sign programs.
• Limited to Python 2.7.

Graphical User Interface (GUI)

Tkinter

• Standard Python interface to Tk GUI toolkit.
• Offers frames, labels, buttons, and more.
• Customizable attributes for quick GUI creation.
• Recommended for simple projects.

wxPython

• Cross-platform GUI toolkit (Windows, Mac, Linux).
• Offers sophisticated design layouts.
• Example: Outliner for note storage.

PyQt

• Flexible cross-platform GUI toolkit.
• Rich collection of widgets and functionality.
• Suitable for complex projects.

Game Development

Pygame

• Easy to learn for video game creation.
• Supports computer graphics and sound libraries.
• Compatible with all SDL-supported OS.
• Example games: Space Shooter, T-Rex Rush.

Pyglet

• For 3D game creation.
• No external dependencies or installation required.
• Handles multiple windows and various media formats.

Panda3D

• Open source 3D game engine.
• Capable of stunning 3D graphics.

Web Development

Requests

• Popular HTTP library for sending requests.
• User-friendly, adds parameters, headers.
• Example: Lassie for retrieving website content.

Scrapy

• Web scraping framework.
• Used for data mining and automated testing.
• Example: CareerBuilder for scraping job postings.

BeautifulSoup

• Web scraping and parsing library.
• Ideal for beginners, parses broken HTML/XML.
• Example: Sports prediction project.

Zappa

• Simplifies deploying Python apps on AWS Lambda and API Gateway.
• Provides infinite scaling and zero downtime.

Django

• Comprehensive web framework.
• Handles authentication, administration, and more.
• Used by companies like Instagram, Spotify, YouTube.

Flask

• Lightweight WSGI web framework.
• Flexible, handles URL routing, cookies, and testing.
• Used by Airbnb, Netflix, Lyft.

Mathematics

NumPy

• Advanced math functionalities: Arrays, matrices.
• Supports shape manipulation, Fourier transforms, linear algebra.

SciPy

• Often used with NumPy.
• Functions: Numerical integration, interpolation, optimization.
• Strong community support.

SymPy

• Symbolic mathematics library.
• Basic arithmetic to complex operations like the Taylor series and cryptography.

Data Science

Pandas

• Essential for organizing, exploring, and manipulating data.
• Handles various data structures, databases, web services.

Orange

• Machine learning and data visualization software built on Pandas.

SQLAlchemy

• SQL toolkit and ORM for Python.
• Facilitates communication between Python and SQL databases.

Matplotlib

• Graph and plot creation library.
• Active issue tracker and GitHub page.

Plotly

• Advanced plotting library for complex visuals.
• Great for multi-axis and 3D plots.

Scikit-Learn

• Library for working with complex data.
• Features: Classification, regression, clustering, dimensionality reduction, model selection, preprocessing.

Imbalance-Learn

• Manages imbalanced datasets.
• Compatible with Scikit-Learn.

Theano

• For optimizing and evaluating mathematical expressions.
• Integrates with NumPy; supports GPU.

Bokeh

• Data visualization using HTML and JavaScript.
• Ideal for web-based dashboards and applications.

PyMC3

• Bayesian statistical modeling and probabilistic machine learning.
• Built on Theano.

LightGBM

• Framework for gradient boosting with tree-based algorithms.
• Efficient with faster training, lower memory usage.

LIME (Local Interpretable Model-agnostic Explanations)

• Debugs machine learning classifiers.
• Inspects model predictions globally and individually.

Machine Learning

Keras

• Deep neural network library for fast experimentation.
• Runs on TensorFlow, CNTK, Theano.
• Easy to use, suitable for both experts and beginners.

TensorFlow

• End-to-end ML platform.
• Supports intuitive high-level APIs, deployment on various platforms.

PyTorch

• Tensor computation package with strong GPU acceleration.
• Popular among AI researchers (e.g., Facebook AI Research).
• Active community support.

Miscellaneous Libraries

Twisted

• Event-based framework for internet applications.
• Modules for HTTP, SSH, IM protocols, etc.

IPython

• Interactive Python command-line shell.
• Works on Windows, Mac, Linux.

Pillow

• Modern fork of the Python Imaging Library (PIL).
• Supports many file types and image manipulation functions.

Poetry

• Eases Python packaging and dependency management.
• Useful for projects with multiple library dependencies.

PyWin32

• Includes methods and classes for interacting with Windows OS.
• Facilitates control over Microsoft applications.

Kivy

• Open source Python library for multi-touch app development.
• Cross-platform and supports various operating systems.
• Suitable for commercial products.

Pendulum

• Simplifies date/time manipulation in Python.
• Handles time zones automatically and correctly.

Loguru

• Aims to make logging in Python enjoyable.
• Adds useful functionalities like customizable levels, colors, unified add function.