Audience

Component Library solution for DevOps teams

About NumPy

Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.

Pricing

Starting Price:
Free
Free Version:
Free Version available.

Integrations

API:
Yes, NumPy offers API access

Ratings/Reviews - 1 User Review

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Company Information

NumPy
numpy.org

Videos and Screen Captures

NumPy Screenshot 1
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Product Details

Platforms Supported
Windows
Mac
Linux
Training
Documentation
Videos
Support
Online

NumPy Frequently Asked Questions

Q: What kinds of users and organization types does NumPy work with?
Q: What languages does NumPy support in their product?
Q: What other applications or services does NumPy integrate with?
Q: Does NumPy have an API?
Q: What type of training does NumPy provide?
Q: How much does NumPy cost?

NumPy Product Features

NumPy Verified User Reviews

Write a Review
  • A NumPy User
    Principal Software Engineer
    Used the software for: 6-12 Months
    Frequency of Use: Daily
    User Role: User
    Company Size: 100 - 499
    Design
    Ease
    Features
    Pricing
    Support
    Probability You Would Recommend?
    1 2 3 4 5 6 7 8 9 10

    "Excellent Python math library"

    Posted 2022-08-03

    Pros: - used for scientific computing
    - huge variety of mathematical functions, random number generators, etc.
    - supports a wide variety of hardware and GPU acceleration
    - very fast code that runs in C, despite working with Python
    - simple syntax makes it easy to learn
    - good documentation
    - free and open source

    Cons: - there aren't many cons to using NumPy; it's a mainstay of the Python computing community for a reason

    Overall: NumPy is an essential part of the Python ecosystem. It provides a huge variety of mathematical functions in a very performant library for free.

    Read More...
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