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Matplotlib VS Jest

Compare Matplotlib VS Jest and see what are their differences

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

Matplotlib logo Matplotlib

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

Jest logo Jest

Jest is a delightful JavaScript Testing Framework with a focus on simplicity.
  • Matplotlib Landing page
    Landing page //
    2023-06-14
  • Jest Landing page
    Landing page //
    2023-09-10

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Jest features and specs

  • Easy Setup
    Jest provides an out-of-the-box configuration which makes it easy to set up and start testing quickly without needing extensive configuration.
  • Snapshot Testing
    Jest supports snapshot testing, allowing developers to capture the state of UI components, making regression testing easier.
  • Mocking Capabilities
    Jest offers powerful mocking capabilities for functions, modules, and timers, enabling isolated and independent unit tests.
  • Parallel Test Execution
    Jest runs tests in parallel, utilizing multiple workers to speed up test execution and improve performance.
  • Comprehensive Documentation
    Jest has thorough and well-maintained documentation which helps developers easily understand and utilize its features.
  • Watch Mode
    Jest has a watch mode feature that automatically re-runs tests when files are updated, improving development workflow.
  • Built-in Code Coverage
    Jest provides built-in code coverage reports, giving developers insights into which parts of their code are covered by tests.

Possible disadvantages of Jest

  • Performance Overhead
    Jest's parallel test execution can sometimes introduce performance overhead, especially in large projects with many workers firing at once.
  • Test Initialization
    Tests can take longer to initialize due to the need for Jest to transform code from modern JavaScript syntax down to older syntax versions.
  • Limited Browser Testing
    Jest is primarily designed for testing Node.js applications and may require additional configuration or tools for full-featured browser testing.
  • Learning Curve
    For developers unfamiliar with JavaScript testing frameworks, understanding Jest's extensive feature set and configuration options can be challenging.
  • Specific to JavaScript
    Jest is specifically designed for JavaScript and may not be suitable for projects that involve multiple programming languages.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

Analysis of Jest

Overall verdict

  • Jest is considered a good choice for modern JavaScript development, particularly for projects involving React, due to its robustness, ease of use, and active community support. Its ability to run tests in parallel and produce detailed diagnostics contributes significantly to improving testing efficiency.

Why this product is good

  • Jest is a popular testing framework for JavaScript that provides a simple and highly effective environment for unit testing, especially for applications built with React. It comes with an extensive set of features including a zero configuration setup, a powerful mocking library, and coverage reports, all without needing additional tools. Jest's ease of use and speed make it a preferred choice for developers looking for seamless integration in their development process.

Recommended for

  • Developers working with React and looking for easy integration with minimal configuration.
  • Teams that require a fast and reliable testing tool with excellent community support and active development.
  • Projects that demand comprehensive testing capabilities including unit tests, integration tests, and snapshot testing.

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Jest videos

+ Add

60 Second Book Review: โ€œInfinite Jestโ€ by David Foster Wallace

More videos:

  • Review - How I Get Through Tough Books - Infinite Jest and Proust
  • Review - David Foster Wallace interview on "Infinite Jest" with Leonard Lopate (03/1996)

Category Popularity

0-100% (relative to Matplotlib and Jest)

Matplotlib

Jest

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Technical Computing
100 100%
Technical Computing
0% 0
JavaScript Framework
0 0%
JavaScript Framework
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 Matplotlib and Jest

Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
Source: www.technotification.com
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Source: searchbusinessanalytics.techtarget.com
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Source: www.analyticsvidhya.com
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...
Source: www.geeksforgeeks.org

Jest Reviews

We have no reviews of Jest yet.
Be the first one to post

Social recommendations and mentions

Matplotlib might be a bit more popular than Jest. We know about 114 links to it since March 2021 and only 87 links to Jest. 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.

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 10 months ago
View more

Jest mentions (87)

  • 7 Free Tools for Testing AI-Generated Code Before It Ships
    Jest is the dominant testing framework for JavaScript and TypeScript. It supports unit tests, integration tests, and snapshot tests out of the box, with no configuration required for most projects. - Source: dev.to / 3 months ago
  • Three Ways to Convert JSON to TypeScript. Only One Is Deterministic.
    Test fixtures. If you write tests with Jest or Vitest, converting fixture files ensures your mocks match production shapes. - Source: dev.to / 3 months ago
  • JavaScript Awesome Package
    Jest - Delightful JavaScript Testing Framework with a focus on simplicity. - Source: dev.to / 6 months ago
  • Mastering Testing: My journey with Jest in my project
    For my Repository Context Packager project (a CLI tool for packaging repository content), I had to chose among a variety of testing frameworks like Cypress, Jest, Vitest one that will best work and enable me write, organize and execute test cases for my project. I chose Jest because it is a popular and zero-configuration testing library that supports several options. Furthermore, it was my best choice because of... - Source: dev.to / 9 months ago
  • Setting Up Testing for My CLI Tool
    I just finished adding tests to my Repository-Context-Packager project, I went with Jest as my testing framework. Jest is probably the most popular JavaScript testing framework out there and it comes with everything built-in, mocking, coverage reports. I didn't need to install a bunch of separate packages like you would with some other frameworks. Plus, Jest has really good documentation and a huge community, so... - Source: dev.to / 9 months ago
View more

What are some alternatives?

When comparing Matplotlib and Jest, 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.

react-testing-library - [`React Testing Library`][gh] builds on top of `DOM Testing Library` by adding

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

Vitest - A blazing fast unit test framework powered by Vite

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.

Mochajs - Mocha is a JavaScript test framework running on Node.js and the browser, making asynchronous testing simple.

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