Top 10 Python Libraries

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • Pytorch

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

    Released in 2016, PyTorch is free, open-source, and the largest machine learning library developed by Facebook’s AI Research Lab. It is based on Torch, an open-source deep-learning library implemented in C with a wrapper in Lua.

  • scikit-learn

    scikit-learn: machine learning in Python

    Scikit-learn is a free and open-source software for data analysis and data mining tasks. It is also used to build machine learning models and works efficiently with complex data. Scikit-learn is built atop other Python libraries, and hence it is interoperable with most of the other Python libraries (NumPy, SciPy, Pandas, etc.)

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  • NumPy

    The fundamental package for scientific computing with Python.

    NumPy is an open-source numerical Python library used for scientific computing and performing basic and advanced array operations. It supports multi-dimensional arrays and matrices along with a collection of high-level mathematical functions. It manipulates this data using complex mathematical operations like Fourier transformation, linear algebra, random number, etc. You can also use NumPy as an efficient multi-dimensional container to treat generic data.

  • Scrapy

    Scrapy, a fast high-level web crawling & scraping framework for Python.

    ScraPy is also a popular open-source Python library for large-scale web scraping by building crawling programs, also known as spiders. BeautifulSoup helps you scrape data from websites but not via CSV or API. ScraPy gathers structured data from the Web (contact info or URLs) and can be used to scrape data from APIs or Python machine learning models, data mining, information processing, and more.

  • Robot Framework

    Generic automation framework for acceptance testing and RPA

    Robot Framework is an open-source test automation framework for process automation and the testing of hardware and software systems under development.

  • matplotlib

    matplotlib: plotting with Python

    Download the latest version of Matplotlib or visit its GitHub repo for more information.

  • Selenium WebDriver

    A browser automation framework and ecosystem.

    Download Selenium or visit its GitHub repository to know more.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  • examples

    TensorFlow examples (by tensorflow)

    TensorFlow is an open-source deep learning and machine learning library developed by Google Brain. It was released in the year 2015 when Theano and Caffe were the popular deep learning frameworks. TensorFlow has gained tremendous popularity in a short span and is a part of most of Google’s AI or ML applications.

  • Pandas

    Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

    Pandas is a machine learning library that offers high-level data structures and a wide variety of tools for data analysis. It provides essential data structures like series, data frames, and panels, which help manipulate data sets and time series. It also offers high-level abstraction and multiple methods for convenient data filtering.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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