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Robot framework VS SciPy

Compare Robot framework VS SciPy and see what are their differences

Flagsmith
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Robot framework logo Robot framework

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

SciPy logo SciPy

SciPy is a Python-based ecosystem of open-source software for mathematics, science, and engineering. 
  • Robot framework Landing page
    Landing page //
    2023-06-20
  • SciPy Landing page
    Landing page //
    2023-07-26

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.

SciPy features and specs

  • Comprehensive Library
    SciPy provides a wide range of scientific and technical computing tools, including modules for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, statistics, and more.
  • Interoperability
    SciPy is built on top of NumPy, which means it naturally dovetails with other scientific computing libraries in the Python ecosystem, facilitating ease of integration and use in conjunction with libraries like Matplotlib and Pandas.
  • Active Community
    SciPy boasts a large, active community of developers and users, which provides extensive documentation, forums, and regular updates and improvements to the library.
  • Open-source
    Being an open-source library, SciPy promotes collaboration and adaptation, allowing users to contribute to its development and modify its tools to suit specific needs.

Possible disadvantages of SciPy

  • Complexity
    For beginners in scientific computing or programming, the comprehensive nature of SciPy can be overwhelming due to its broad range of functionalities and somewhat steep learning curve.
  • Performance Limitations
    Being a high-level library, SciPy may not be as performant as low-level implementations or specialized tools for very demanding computational tasks or large-scale data processing.
  • Dependency on NumPy
    While SciPy's reliance on NumPy ensures compatibility and ease of use within the Python ecosystem, it also means that its performance and limits are tied to those of NumPy.
  • Windows Limitations
    Some functions and modules of SciPy may not work as efficiently or might encounter compatibility issues when run on Windows operating systems compared to Unix-based systems.

Analysis of Robot framework

Overall verdict

  • Yes, Robot Framework is a good choice for automating tests and processes, especially if you are looking for an open-source solution with strong community support and flexibility.

Why this product is good

  • Robot Framework is considered good because it is an open-source automation framework that supports both keyword and behavior-driven development (BDD). It is versatile and can be used for test automation and robotic process automation (RPA). It has a simple, human-readable syntax, making it accessible for non-programmers. The framework is extensible, allowing users to create custom libraries. It also integrates well with various tools and environments, which enhances its functionality.

Recommended for

  • QA engineers and testers looking for a robust test automation framework.
  • Organizations seeking an open-source tool for robotic process automation.
  • Teams that need a scalable solution that integrates with other tools.
  • Non-programmers who require a framework with an easy-to-understand syntax.

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

SciPy videos

+ Add

Numerical Computing With NumPy Tutorial | SciPy 2020 | Eric Olsen

More videos:

  • Tutorial - Land on Vector Spaces: Practical Linear Algebra with Python | SciPy 2019 Tutorial | L Barba, T Wang

Category Popularity

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

Robot framework

SciPy

Automated Testing
100 100%
Automated Testing
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Browser Testing
100 100%
Browser Testing
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Robot framework and SciPy

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

SciPy 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
SciPy is primarily used for mathematical and scientific computations, but sometimes it can also be used for basic image manipulation and processing tasks using the submodule scipy.ndimage.At the end of the day, images are just multidimensional arrays, SciPy provides a set of functions that are used to operate n-dimensional Numpy operations. SciPy provides some basic image...
Source: www.analyticsvidhya.com

Social recommendations and mentions

Based on our record, Robot framework should be more popular than SciPy. It has been mentiond 32 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.

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 / about 2 months 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 / 7 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 / about 1 year 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: about 2 years ago
View more

SciPy mentions (17)

  • 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
  • Video Generation with Python
    Python has become a popular programming language for different applications, including data science, artificial intelligence, and web development. But, did you know creating and rendering fully customized videos with Python is also possible? At Stack Builders, we have successfully used Python libraries such as MoviePy, SciPy, and ImageMagick to generate videos with animations, text, and images. In this article, we... - Source: dev.to / over 1 year ago
  • Beginning Python: Project Management With PDM
    A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / over 1 year ago
  • Understanding Cosine Similarity in Python with Scikit-Learn
    SciPy: a library used for scientific and technical computing. It has a function that can calculate the cosine distance, which equals 1 minus the cosine similarity. - Source: dev.to / about 2 years ago
  • PSA: You don't need fancy stuff to do good work.
    Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: about 2 years ago
View more

What are some alternatives?

When comparing Robot framework and SciPy, 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.

NumPy - NumPy is the fundamental package for scientific computing with Python

Katalon - Built on the top of Selenium and Appium, Katalon Studio is a free and powerful automated testing tool for web testing, mobile testing, and API testing.

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

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.

Matplotlib - matplotlib is a python 2D plotting library which produces publication quality figures in a variety...

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