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Scikit-learn VS Robot framework

Compare Scikit-learn 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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  3. » Reviews
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Scikit-learn logo Scikit-learn

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

Robot framework logo Robot framework

Robot Framework is a generic test automation framework for acceptance testing and acceptance...
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Robot framework Landing page
    Landing page //
    2023-06-20

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

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.

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

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 Scikit-learn and Robot framework)

Scikit-learn

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 Scikit-learn and Robot framework

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...
Source: searchbusinessanalytics.techtarget.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

Robot framework might be a bit more popular than Scikit-learn. We know about 32 links to it since March 2021 and only 31 links to Scikit-learn. 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.

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 11 months ago
  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / about 1 year ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / almost 2 years 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 / 13 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 Scikit-learn 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.

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

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

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

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