Software Alternatives, Accelerators & Startups
Register | Login

Cucumber VS NumPy

Compare Cucumber VS NumPy and see what are their differences

LibHunt
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
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Cucumber logo Cucumber

Cucumber is a BDD tool for specification of application features and user scenarios in plain text.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Cucumber Landing page
    Landing page //
    2022-01-19
  • NumPy Landing page
    Landing page //
    2023-05-13

Cucumber videos

+ Add

Madam Kilay Skin Magical Review / Orange cucumber review

More videos:

  • Review - Puff Bar - Cucumber Review (Best Disposable Vape Brand)
  • Review - THE CUCUMBER CHALLENGE! (1 MILLION SUBSCRIBER SPECIAL)
  • Tutorial - Cucumber automation suit

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 Cucumber and NumPy)

Cucumber

NumPy

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

User comments

Share your experience with using Cucumber and NumPy. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

Cucumber Reviews

Top Selenium Alternatives
Cucumber itself is not a test automation tool but a framework that supports BDD. It is often used in conjunction with Selenium to provide a layer where test scenarios are written in a way that is understandable by all team members. Unlike Selenium, which focuses on automating browser actions, Cucumber focuses on defining behavior and can be used to drive Selenium tests.
Source: bugbug.io
5 Selenium Alternatives to Fill in Your Top Testing Gaps
Business testers are likely to prefer to use Cucumber over Selenium since script Cucumber lets you write test scenarios using a plain-English scripting language called Gherkin. Using Gherkin instead of code makes test script creation a much simpler process, since anyone can read, write, and understand the scripts regardless of testing experience.
Source: www.perfecto.io
Top 20 Best Automation Testing Tools in 2018 (Comprehensive List)
Cucumber is an open-source tool that is designed over the concept of BDD (Behavior-driven development). It is used to perform the automated acceptance testing by running the examples that best describe the behavior of the application. It gets you a single up-to-date living document that is having both specification and test documentation.
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 seems to be a lot more popular than Cucumber. While we know about 111 links to NumPy, we've tracked only 1 mention of Cucumber. 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.

Cucumber mentions (1)

NumPy mentions (111)

  • Documenting my pin collection with Segment Anything: Part 3
    NumPy: This library is fundamental for handling arrays and matrices, such as for operations that involve image data. NumPy is used to manipulate image data and perform calculations for image transformations and mask operations. - Source: dev.to / about 5 hours ago
  • Awesome List
    NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 6 days ago
  • NumPy for Beginners: A Basic Guide to Get You Started
    This guide covers the basics of NumPy, and there's much more to explore. Visit numpy.org for more information and examples. - Source: dev.to / 8 days ago
  • 2 Minutes to JupyterLab Notebook on Docker Desktop
    Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 9 months ago
  • Element-wise vs Matrix vs Dot multiplication
    In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 3 months ago
View more

What are some alternatives?

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

Selenium - Selenium automates browsers. That's it! What you do with that power is entirely up to you. Primarily, it is for automating web applications for testing purposes, but is certainly not limited to just that.

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

Robot framework - Robot Framework is a generic test automation framework for acceptance testing and acceptance...

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

JUnit - JUnit is a simple framework to write repeatable tests.

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

Loading...