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Sauce Labs VS NumPy

Compare Sauce Labs VS NumPy and see what are their differences

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LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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Sauce Labs logo Sauce Labs

Test mobile or web apps instantly across 700+ browser/OS/device platform combinations - without infrastructure setup.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Sauce Labs Landing page
    Landing page //
    2023-10-23
  • NumPy Landing page
    Landing page //
    2023-05-13

Sauce Labs features and specs

  • Extensive Browser and OS Coverage
    Sauce Labs offers a wide range of browser and operating system combinations, allowing for comprehensive cross-browser testing.
  • Real Device Testing
    Provides access to a large number of real mobile devices for testing, ensuring accurate results compared to emulators.
  • Integration with CI/CD Tools
    Seamlessly integrates with popular Continuous Integration and Continuous Deployment tools like Jenkins, CircleCI, and Travis CI.
  • Detailed Reporting
    Offers in-depth test reports, screenshots, and videos, which help in debugging and improving the quality of tests.
  • Parallel Test Execution
    Supports running multiple tests in parallel, significantly reducing test execution time and speeding up the development cycle.
  • Scalability
    Highly scalable platform that can cater to both small projects and large enterprises, making it flexible for various needs.

Possible disadvantages of Sauce Labs

  • Cost
    The pricing can be quite high, especially for small teams or individual developers, making it less accessible for budget-constrained projects.
  • Learning Curve
    There can be a steep learning curve for new users who are not familiar with automated testing platforms.
  • Latency Issues
    Some users have reported latency issues and slower test execution times compared to local testing environments.
  • Complexity
    Setting up and configuring tests to run on Sauce Labs can be complex and time-consuming, requiring a good understanding of the platform and automated testing best practices.
  • Dependency on Internet Speed
    As a cloud-based service, the performance can be heavily dependent on the tester's internet speed, potentially affecting test execution and debugging processes.

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.

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.

Sauce Labs videos

+ Add

Overview of Sauce Labs

More videos:

  • Review - How an Automated Test Works With Sauce Labs
  • Review - Sauce Labs Analytics

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

Category Popularity

0-100% (relative to Sauce Labs and NumPy)

Sauce Labs

NumPy

Website Testing
100 100%
Website Testing
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Automated Testing
100 100%
Automated Testing
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Sauce Labs and NumPy. 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 Sauce Labs and NumPy

Sauce Labs Reviews

Top Selenium Alternatives
Sauce Labs is a cloud-based platform that offers automated testing tools for web and mobile applications. It provides a secure and scalable environment for running tests across a wide range of browsers and operating systems. With features like parallel testing, real device testing, and live debugging, Sauce Labs focuses on improving test execution times and overall efficiency.
Source: bugbug.io
Top 20 Best Automation Testing Tools in 2018 (Comprehensive List)
Sauce Labs is a selenium cloud-based solution that offers automated testing over cross-browsers and multiple platforms. It has support for both mobile and desktop apps. It is known for significantly accelerating test cycles.
Source: www.softwaretestinghelp.com

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

Social recommendations and mentions

Based on our record, NumPy should be more popular than Sauce Labs. It has been mentiond 119 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.

Sauce Labs mentions (18)

  • Top 10 AI Testing Tools You Need In 2025
    Sauce Labs is a cloud-based testing platform that provides comprehensive coverage for web and mobile applications. It leverages AI to optimize test execution and analysis, helping teams identify issues faster. Sauce Labs also offers real-time analytics, making it easier to monitor and improve your testing processes. - Source: dev.to / 10 days ago
  • 11 Most Popular Tools for Logging and Monitoring API Calls
    Sauce Labs used to be called API Fortress, and under that name, it generated a bit of a reputation as a cloud-based REST API monitoring solution. Setting up Sauce Labs for monitoring involves establishing secure connections to ensure data integrity and security. Sauce Labs continues this success by providing testing, monitoring, and reporting, but for those looking principally for API log tooling, Sauce Labs can... - Source: dev.to / 3 months ago
  • Top 10 iOS Automation Testing Tools for 2025 (with Key Features)
    #2 SauceLabs SauceLabs also offers a cloud-based platform for testing iOS apps, as well as capabilities to build, organize, and run tests for delivering high-quality applications. - Source: dev.to / 7 months ago
  • Free Cross Browser Testing Tools to pick in 2025
    5. Sauce Labs (Free Plan) Sauce Labs provides a cloud-based testing platform that includes real device testing and supports Selenium, Appium, and other popular automation frameworks. While its free tier limits access to testing minutes and device options, it’s ideal for smaller testing needs and early-phase bug hunting. Paid plans enable larger teams to scale with access to additional device environments. - Source: dev.to / 7 months ago
  • 🛑 Stop resizing your browser: improve testing for responsiveness
    Platforms like Browserstack or SauceLabs offer virtual instances of real devices and browsers for manual and end-to-end testing. Caveat: subscriptions cost money and are on a per-seat basis. - Source: dev.to / about 1 year ago
View more

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 5 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 9 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
View more

What are some alternatives?

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

BrowserStack - BrowserStack is a software testing platform for developers to comprehensively test websites and mobile applications for quality.

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

LambdaTest - Perform Web Testing on 2000+ Browsers & OS

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

TestComplete - TestComplete Desktop, Web, and Mobile helps you create repeatable and accurate automated tests across multiple devices, platforms, and environments easily and quickly.

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

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