Software Alternatives, Accelerators & Startups

Scikit-learn VS Selenium

Compare Scikit-learn VS Selenium and see what are their differences

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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.

Selenium logo 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 Landing page
    Landing page //
    2022-05-06
  • Selenium Landing page
    Landing page //
    2024-08-22

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.

Selenium features and specs

  • Open Source
    Selenium is an open-source tool, which means it is freely available for anyone to use, modify, and distribute. This makes it a cost-effective choice for companies of all sizes.
  • Cross-Browser Compatibility
    Selenium supports multiple browsers like Chrome, Firefox, Safari, and Edge. This allows testers to ensure that web applications work seamlessly across different browsers.
  • Cross-Platform Support
    Selenium can run on various operating systems including Windows, macOS, and Linux. This provides flexibility to test on multiple platforms to ensure consistent user experience.
  • Supports Multiple Programming Languages
    Selenium supports multiple programming languages such as Java, C#, Python, and JavaScript. This allows testers to write their scripts in the language they are most comfortable with.
  • Rich Community and Documentation
    Being a widely-used tool, Selenium has extensive community support and a wealth of documentation and tutorials available. This makes it easier for new users to get started and find solutions to problems.
  • Integration with Other Tools
    Selenium integrates well with various testing frameworks and tools like TestNG, JUnit, and Maven, as well as CI/CD tools like Jenkins and Docker. This makes it a versatile and comprehensive automation solution.

Possible disadvantages of Selenium

  • Steep Learning Curve
    Selenium requires knowledge of programming to create and maintain test scripts. For those new to automation or coding, the learning curve can be quite steep.
  • No Built-in Reporting
    Selenium does not come with built-in reporting features. Testers must rely on third-party tools or build custom reporting solutions to generate test reports.
  • Limited Support for Desktop Applications
    Selenium is designed primarily for web application testing and offers limited support for desktop applications. This limits its use in scenarios where desktop application testing is needed.
  • Manual Effort for Maintenance
    Test scripts require regular maintenance to accommodate changes in the web application, such as updates to the UI or changes in element identifiers. This can lead to significant manual effort.
  • Performance Issues
    Selenium can be slower compared to other automation tools, especially when running extensive test suites. This can affect the speed of the overall testing process.
  • Browser Compatibility Issues
    Although Selenium supports multiple browsers, each browser's implementation of WebDriver may have unique quirks and bugs. This occasionally leads to test script compatibility issues across different browsers.

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

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

Selenium videos

What is Selenium | Selenium Explained in 2-minutes | Introduction to Selenium | Intellipaat

Category Popularity

0-100% (relative to Scikit-learn and Selenium)
Data Science And Machine Learning
Automated Testing
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Browser Testing
0 0%
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 Selenium

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...

Selenium Reviews

Top Selenium Alternatives
Nightwatch.js simplifies the setup and use of Selenium WebDriver, providing an abstraction layer that is easier to work with for JavaScript developers. While it offers the broad compatibility and standardization of Selenium WebDriver, it aims to improve the development experience with its simplified syntax and support for the Page Object pattern, making it a middle ground...
Source: bugbug.io
Top 5 Selenium Alternatives for Less Maintenance
And that’s why code-free test automation is important. Implementing codeless Selenium alternatives can address the challenges posed by traditional Selenium testing. They help testers with various skill sets to contribute to the testing process, enhancing collaboration and accelerating the testing lifecycle. For an in-depth discussion on the significance of codeless Selenium,...
Best Automation Testing Tools (Free and Paid) | July 2022
Automation testing is the process of testing the software using an automation tool to find the defects. In this process, executing the test scripts and generating the results are performed automatically by automation tools. Some most popular tools to do automation testing are HP QTP/UFT, Selenium WebDriver, etc.,
20 BEST Selenium Alternatives in 2021
Selenium is an open-source automated testing tool. It can perform functional, regression, load testing on web applications across different browsers and platforms. Selenium is one of the finest tools, but it does have some drawbacks.
Source: www.guru99.com
Top 10 Best Selenium Alternatives You Should Try
Selenium is a convenient and portable software testing tool specifically used for testing web applications. It acts as an API (Application Program Interface) for browser automation. Selenium is the widely used free and open-source tool used for automation testing of web applications through various browsers and platforms.

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Selenium. It has been mentiond 31 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.

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
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Selenium mentions (8)

  • How to write tests in Django for JavaScript fetch
    You won't be able to test the javascript function itself from within python, but you can exercise the front-end code using something like cypress (https://cypress.io) or the older but still respectable selenium (https://selenium.dev). Source: about 2 years ago
  • Having Issues with selenium
    In addition, .find_element_by_class_name is deprecated since selenium 4.3.0 and the replacement is .find_element(By.CLASS_NAME, "class"). Check selenium's site for more info. Source: over 2 years ago
  • Issues with Selenium 4.8.0
    This is the code again after checking selenium's official site :. Source: over 2 years ago
  • Having Issues with selenium
    I also tried the following code seen on the selenium.dev website. Source: over 2 years ago
  • Document Object Model Specification
    The following functions are defined within the Selenium project, at revision 1721e627e3b5ab90a06e82df1b088a33a8d11c20. - Source: dev.to / about 3 years ago
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What are some alternatives?

When comparing Scikit-learn and Selenium, 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.

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.

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

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.

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

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