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NumPy VS Requestly

Compare NumPy VS Requestly and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Requestly logo Requestly

A Powerful API Mocking and Testing Tool
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Requestly Requestly
    Requestly //
    2025-02-12
  • Requestly Rest Client
    Rest Client //
    2025-02-12
  • Requestly HTTP Interceptor
    HTTP Interceptor //
    2025-02-12
  • Requestly API Mocking
    API Mocking //
    2025-02-12
  • Requestly Requestly
    Requestly //
    2025-02-12

Requestly is a modern and powerful companion for API Development and Testing. It is an open-source tool purpose-built to speed up and simplify API development workflow for developers and QAs. It is a combination of API Client and HTTP Interceptor that helps create and share API Contracts, testing APIs, and easily mock and integrate them into web and mobile apps.

NumPy

Website
numpy.org
Pricing URL
-
$ Details
Platforms
-
Release Date
-
Edit details

Requestly

Website
requestly.com
Pricing URL
Official Requestly Pricing
$ Details
freemium
Platforms
Google Chrome Firefox Edge Safari Brave Opera Vivaldi Android Windows Linux Mac OSX MacOS
Release Date
2021 January
Startup details
Country
United States
State
California
City
San Francisco
Founder(s)
Sachin Jain, Sagar Soni, Sahil Gupta
Employees
20 - 49
Edit details

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Requestly features and specs

  • Redirect URL
  • Block Network Requests
  • Modify Request & Response Header
  • Modify Response
  • Supercharge Selenium
  • Session Replay
  • Modify Query Params
  • Team Workspace
  • API Client
  • API Mocks
  • GraphQL Support
  • Zero Setup
  • Auto Capture Sessions
  • Network Logs
  • Console Logs

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Analysis of Requestly

Overall verdict

  • Requestly is generally regarded as a good tool due to its comprehensive functionalities and ease of use. Its ability to seamlessly manage network requests makes it suitable for both beginners and experienced developers.

Why this product is good

  • Requestly is widely considered a valuable tool because it offers robust and flexible features for intercepting and modifying network requests. Developers and QA testers appreciate it for its ability to simulate and debug API calls efficiently. It is particularly useful for testing changes without altering the codebase and for working with web applications in development and production environments.

Recommended for

  • Developers looking to debug and test API endpoints.
  • Quality Assurance (QA) teams that require reliable testing tools for web applications.
  • Technical professionals who manage network traffic and need to modify or redirect requests effortlessly.
  • Anyone involved in web development who needs to simulate network conditions or test application behavior under different scenarios.

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Requestly videos

+ Add

Session Replays by Requestly

More videos:

  • Demo - Get Started with Requestly
  • Tutorial - Modify API Response using Requestly Chrome Extension
  • Tutorial - How to load local JS file in production sites for faster debugging (Map Local Tool)
  • Tutorial - Report Quality Bugs with Video, Network logs, Console logs & Environment details

Category Popularity

0-100% (relative to NumPy and Requestly)

NumPy

Requestly

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Testing
0 0%
Testing
100% 100

Questions & Answers

As answered by people managing NumPy and Requestly.

Who are some of the biggest customers of your product?

Requestly's answer:

  • Verizon
  • AT&T
  • Adobe
  • Salesforce
  • Telegraph
  • Intuit
  • Verizon

How would you describe the primary audience of your product?

Requestly's answer:

Front-end developers, QAs, PMs, Digital Marketers

What makes your product unique?

Requestly's answer:

Requestly is an open-source API development and testing tool that combines the capabilities of an API Client and HTTP Interceptor, making it a better alternative to Postman + Charles Proxy. It simplifies API mocking, request modification, and debugging with an intuitive no-code interface, enabling developers and QAs to test APIs efficiently.

User comments

Share your experience with using NumPy and Requestly. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare NumPy and Requestly

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Requestly Reviews

Comparing Charles Proxy, Fiddler, Wireshark, and Requestly
On the pricing front, Requestly strikes a balance between affordability and functionality. It is an open-source tool, offering freemium to individual developers and affordable pricing plans for team collaboration. We have also clearly differentiated how Requestly differs from Wireshark and other web debugging tools like Proxyman, Modheader, and HTTP ToolKit separately.
Source: dev.to

Social recommendations and mentions

Based on our record, NumPy should be more popular than Requestly. It has been mentiond 122 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

NumPy mentions (122)

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Requestly mentions (35)

  • Why You Need a Local-First API Client (With Hands-On Example)
    If you want to try a local-first workflow, you can start using Requestly here: https://requestly.com. - Source: dev.to / 9 months ago
  • How to use Cursor to Generate API Testcases in Requestly
    That’s where automation changes the game. By pairing Cursor, an AI-powered coding assistant, with Requestly's local-first API testing and mocking platform, you can offload the grunt work of writing tests to AI while keeping execution secure and reproducible on your own system. In this article, we’ll walk through how to set up Cursor with Requestly, generate test cases automatically, and run them end-to-end so that... - Source: dev.to / 9 months ago
  • These 20 Awesome API Clients Will Change How You Work with APIs
    Requestly is a versatile browser extension and web client used to intercept, mock, and debug APIs in real-time—perfect for frontend developers. - Source: dev.to / about 1 year ago
  • Best Tools for GraphQL Development in 2025
    Requestly is a powerful tool for modifying GraphQL responses, intercepting requests, and debugging API interactions. It allows developers to tweak request bodies, capture GraphQL traffic, and share sessions for easier debugging and collaboration. - Source: dev.to / over 1 year ago
  • How Not to Use AI in Software Development
    Learn more at https://requestly.com/. - Source: dev.to / over 1 year ago
View more

What are some alternatives?

When comparing NumPy and Requestly, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Proxyman.io - Proxyman is a high-performance macOS app, which enables developers to view HTTP/HTTPS requests from apps and domains.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Postman - The Collaboration Platform for API Development

OpenCV - OpenCV is the world's biggest computer vision library

Hoppscotch - Open source API development ecosystem

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