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NumPy VS Robot framework

Compare NumPy VS Robot framework 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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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Robot framework logo Robot framework

Robot Framework is a generic test automation framework for acceptance testing and acceptance...
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Robot framework Landing page
    Landing page //
    2023-06-20

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.

Robot framework features and specs

  • Open Source
    Robot Framework is open-source, which means it is free to use and has a large community of users and contributors who continuously improve the tool and provide support.
  • Extensible
    Its extensible nature allows easy integration with various libraries and tools. Custom libraries can also be added to extend its functionality further.
  • Keyword-Driven Testing
    Utilizes a keyword-driven testing approach, making tests readable and simple to create even for non-programmers. This encourages collaboration between developers and non-technical stakeholders.
  • Platform Independent
    Robot Framework is platform-independent and can be run on different operating systems like Windows, macOS, and Linux.
  • Selenium Integration
    Offers seamless integration with Selenium, empowering it to be used for a wide range of web application testing tasks, from simple UI checks to complex automated workflows.
  • Rich Reporting
    Generates comprehensive logs and reports that help in the easy identification of test results and issues. The reports are user-friendly and provide detailed execution flow.
  • Data-Driven Testing
    Supports data-driven test cases, allowing tests to be executed with multiple sets of input data, enhancing test coverage.

Possible disadvantages of Robot framework

  • Learning Curve
    For those unfamiliar with keyword-driven testing or the framework itself, there can be a learning curve, particularly in understanding how to best structure test cases and use the available libraries.
  • Performance Overhead
    The high level of abstraction can introduce some performance overhead, making it less suitable for extremely performance-sensitive or low-level testing scenarios.
  • Limited Mobile Testing
    While it supports mobile testing through Appium, the support and community resources for mobile testing are not as robust as for web application testing.
  • Python Dependency
    It primarily relies on Python, which means that some organizations that use different programming languages might find it less straightforward to integrate and utilize effectively.
  • Debugging Complexity
    Debugging can be less intuitive compared to traditional code-based frameworks. Errors can sometimes be harder to trace due to the abstraction layer provided by keyword-driven scripting.

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

Robot framework videos

+ Add

Robot Framework Tutorial | Robot Framework With Python | Python Robot Framework | Edureka

More videos:

  • Review - The Robot Framework – Top 7 Things You Need to Know
  • Review - Robot Class vs Robot Framework Vs Robotic Process Automation

Category Popularity

0-100% (relative to NumPy and Robot framework)

NumPy

Robot framework

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

User comments

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Reviews

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

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

Robot framework Reviews

Top 5 Selenium Alternatives for Less Maintenance
Robot Framework is an open-source automation framework that uses a keyword-driven approach, making it easy to create and maintain test cases. It supports both codeless and script-based automation, making it versatile for various testing needs.
Source: www.leapwork.com
Best Automation Testing Tools (Free and Paid) | July 2022
Selenium is an open-source test automation framework that automates web browsers. It becomes a favorite automation tool of choice for automation testers. It acts as a core framework for open-source test automation software such as Watir, Robot Framework, Katalon Studio, and Protractor.
Source: www.softwaretestingmaterial.com
Top 10 Best Selenium Alternatives You Should Try
Robot Framework is an open-source test automation framework used for acceptance test-driven development (ATDD) and acceptance testing. Robot Framework is standard and uses a keyword-driven testing approach and behavior-driven.
Source: www.softwaretestinghelp.com
Best Selenium Alternatives (Free and Paid) in 2021
Robot Framework is an open-source automation framework that implements the keyword-driven approach for acceptance testing and acceptance test-driven development (ATDD). Robot Framework provides frameworks for different test automation needs. But its test capability can be further extended by implementing additional test libraries using Python and Java. Selenium WebDriver is...
Source: www.softwaretestingmaterial.com
5 Selenium Alternatives to Fill in Your Top Testing Gaps
Robot Framework is an open-source Selenium alternative primarily for acceptance test-driven development (ATDD) and acceptance testing. Using the keyword-driven methodology, testers and developers can use Robot Framework as an automation system for web and mobile test automation.
Source: www.perfecto.io

Social recommendations and mentions

Based on our record, NumPy should be more popular than Robot framework. 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.

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 / 3 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 / 7 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 / 8 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 / 9 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 / 9 months ago
View more

Robot framework mentions (32)

  • Most Effective Approaches for Debugging Applications
    Fixing a bug is incomplete without preventing its recurrence. Root cause analysis (RCA), coupled with regression testing and documentation, ensures long-term reliability. Antony Marceles, Founder of Pumex Computing, emphasizes, “Fixing a bug is only part of the solution, preventing it from happening again is the real goal.” Marceles’ team uses regression tests via Robot Framework and code reviews with Gerrit to... - Source: dev.to / 12 days ago
  • Robot Framework Using the Browser Library: Advantages, Disadvantages, and Practical Tips
    Documentation is your best friend. It provides comprehensive guides, examples, and API references to help you navigate the library effectively. Here you can access it, as well as the Robot Framework documentation. - Source: dev.to / 5 months ago
  • Automated Acceptance Testing with Robot Framework and Testkube
    The Robot Framework is an acceptance testing tool that is easy to write and manage due to its key-driven approach. Let us learn more about the Robot Framework to enable acceptance testing. - Source: dev.to / 11 months ago
  • Beautiful is better than ugly, but my beginner code is horrible
    Well, I work with software quality and despite not having a strong foundation in automation, one fine day I decided to make a change. I have been working with Robot Framework for a few months - and that's when I got a taste of the power of python. Some time later, I dabbled a little with Cypress and Playwright, always using javascript. - Source: dev.to / over 1 year ago
  • Embedded professionals, what kind of 'github' projects would make you hire a developer?
    I've used Lua/Busted in a data-heavy environment (telemetry from hospital ventilators). I've also used robot: https://robotframework.org/. Source: almost 2 years ago
View more

What are some alternatives?

When comparing NumPy and Robot framework, 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.

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.

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

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

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

Cypress.io - Slow, difficult and unreliable testing for anything that runs in a browser. Install Cypress in seconds and take the pain out of front-end testing.

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