Python is among the most popular programming languages thanks to its wide range of use cases, including web development, machine learning, data science, and more. Despite having many use cases, python is also popular because of having plenty of libraries that developers can use to implement specific functionalities in their code.
Python has over 130,000 libraries that developers can use to execute different tasks in their programs. In today’s article, we will look at ten of the commonly used python libraries that every python developer out there needs to know about. Let’s jump right in!
1. NumPy
This is one of the commonly used open-source libraries in Python. It contains many mathematical functions that developers can use to implement certain computations in their programs. Some of the common functions within this Python library include arcsin(), arccos(), tan(), radians(), and more. There are not so many python programs out there that don’t use any of these functions.
Features of the NumPy Library
Some of the core features of this library include the following;
- High-performance N-dimensional array object: In python programming, NumPy Array objects are preferred over lists because they take up less memory and are faster and more convenient to use.
- Multimedia container for generic data: This enables performing functions on certain generic data types.
- Broadcasting functions: These are useful when working with arrays of uneven shapes.
- Interactive: This library is very interactive and user-friendly for even first-time programmers.
2. Keras
Keras is another open-source Python library that provides programmers with an interface for artificial neural networks. It is one of the most commonly used libraries by AI, deep learning, and machine learning developers. This library has become very popular in the last couple of years, thanks to the huge adaptation of the above fundamental technologies. For a seamless experience, it is recommended that you install TensorFlow in the backend engine before installing Kera.
Features of Kera library
Here are some of the core features that make this library very useful to programmers;
- It is a python-native library, so it uses all the fundamental concepts of python.
- It contains a wide range of pre-defined datasets.
- Train from NumPy data. This library allows developers to use the NumPy array to train and evaluate the model.
- It runs without using a lot of GPU and CPU resources, making it an efficient library.
- Keras supports all the popular neural models, including fully connected, convolutional, pooling, recurrent, embedding, and more.
- It uses a modular design, making it expressive and adaptable.
3. TensorFlow
TensorFlow is also an open-source and high-performance numerical calculation python library created by the Google AI team back in 2015. This library is now being used by Ai and machine learning researchers and developers to solve complicated mathematical computations. TensorFlow uses techniques such as XLA or Accelerated Linear Algebra to do fast linear algebra computations.
Features of the TensorFlow library
- Eases the training of machine learning models. With TensorFlow, you can easily train machine-learning models on either the GPU or CPU.
- Open source and community-based. As we shared earlier, this library was created by Google engineers and is constantly being improved by several other smart software engineers since it is open source.
- Parallel Neural Network Training: This library allows simultaneous training of neural networks and GPUs.
- Responsive contrast: It is pretty easy to visualize the different sections of the graph with TensorFlow, which may not be the case for other libraries like NumPy.
4. Requests
The primary intent of this library is to make HTTP requests easier and more human-friendly. Unlike most libraries on this list, Requests is licensed under the Apache2 license, so it is not open source. This library is the most commonly used library by developers when implementing HTTPs requests in their code.
Besides sending HTTP requests to a server, this library also allows adding form data, content, header, multi-part files, and more. This library abstracts the code for making server requests in a simple API, allowing developers to focus more on interacting with the service.
Features of the Requests library
- It allows browser-style SSL verification
- It supports international domains and URLs
- This library also allows multipart file uploads and downloads.
- It allows developers to read, update or send new headers per their requirements.
- It makes it easier to add timeouts to the URL
- This library also enables easy handling of cookies and sessions.
5. Scrappy
It is a free, open-source python library mainly used for automated testing, data mining, and web crawling. In its early days, scrappy was mainly used for web scrapping. However, it has evolved over the years and is now being used for several other purposes, including crawling web pages and extracting structure data from them. Scrappy uses the DRY (don’t repeat yourself) principle, making it easier to build and scale any web crawling project.
Features of the Scrappy library
- You can use the command line to export scrapped data.
- It adopts the DRY principle.
- It eases the process of writing programs for crawling the web.
6. Tkinter
Tkinter is a standard library in python that allows developers to quickly generate Graphical User Interfaces (GUIs) for their applications. It has up to 15 types of widgets, including buttons, labels, and text boxes that developers can use for different purposes while generating a GUI.
Features of Tkinter
- It supports an object-oriented interface.
- It enables displaying of images and text with label widgets
- Allows getting of user inputs with entry widgets
- Allows turning widgets to frameless with Widget frames
- It also allows getting Multiline User Input with Text Widgets
7. Six
This is a python library that was built to fix the compatibility issues between code written in Python 3 and Python 2. The name “Six” was derived from multiplying Python 2 with Python 3. Six is a very powerful library that smoothens the transition from Python 2 to Python 3 and vice versa.
Features of the Six library
- It is contained in a single python file, making it pretty easy to add to any python project.
- Supports all versions since Python 2.6
- It has simple utility functions for making code compatible with Python 2 and Python 3
8. PyGame
This is an open-source library for developing 2D games in python. PyGame is a highly portable library, so games built with this library can run on various platforms and Operating Systems.
Features of PyGame
- It doesn’t demand OpenGL
- It makes it easy to utilize multi-core CPUs
- No GUI is required to use all its functions
9. Bokeh
This is a library for developing visualization-based applications. Bokeh makes the visualization of data in web browsers more meaningful and beautiful. With this library, developers can easily integrate dashboards, data applications, and interactive plots into their applications.
Features of Bokeh
- It can be embedded in most of the popular python frameworks, including Django and Flask.
- It makes it possible to build complex statistical plots with a few commands.
- Supports multiple language bindings
10. Theano
Theano is mainly used in development of machine learning and deep learning models. Most of the users of this library are deep learning and machine learning developers.
Features of Theano
- It easily integrates with NumPy.
- Functions in this library run more efficiently on GPUs than on CPUs.
- It uses multidimensional arrays to create deep-learning models
- It is optimized for speed and stability.
