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Jupyter VS Web.dev by Google

Compare Jupyter VS Web.dev by Google and see what are their differences

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Jupyter logo Jupyter

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Web.dev by Google logo Web.dev by Google

Learn how to build for the web and see where you stand 🌟
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • Web.dev by Google Landing page
    Landing page //
    2023-06-20

Jupyter features and specs

  • Interactive Computing
    Jupyter allows real-time interaction with the data and code, providing immediate feedback and making it easier to experiment and iterate.
  • Rich Media Output
    It supports output in various formats including HTML, images, videos, LaTeX, and more, enhancing the ability to visualize and interpret results.
  • Language Agnostic
    Jupyter supports multiple programming languages through its kernel system (e.g., Python, R, Julia), allowing flexibility in the choice of tools.
  • Collaborative Features
    It enables collaboration through shared notebooks, version control, and platform integrations like GitHub.
  • Educational Tool
    Jupyter is widely used for teaching, thanks to its easy-to-use interface and ability to combine narrative text with code, making it ideal for assignments and tutorials.
  • Extensibility
    Jupyter is highly extensible with a large ecosystem of plugins and extensions available for various functionalities.

Possible disadvantages of Jupyter

  • Performance Issues
    For larger datasets and more complex computations, Jupyter can be slower compared to running scripts directly in a dedicated IDE.
  • Version Control Challenges
    Managing version control for Jupyter notebooks can be cumbersome, as they are not plain text files and include metadata that can make diffing and merging complex.
  • Resource Intensive
    Running Jupyter notebooks can be resource-intensive, especially when working with multiple large notebooks simultaneously.
  • Security Concerns
    Because Jupyter allows code execution in the browser, it can be a potential security risk if notebooks from untrusted sources are run without restrictions.
  • Dependency Management
    Managing dependencies and ensuring that the notebook runs consistently across different environments can be challenging.
  • Less Suitable for Production
    Jupyter is often considered more as a research and educational tool rather than a production environment; transitioning from a notebook to production code can require significant refactoring.

Web.dev by Google features and specs

  • Comprehensive Guides
    Web.dev offers an extensive range of articles and tutorials that cover various aspects of web development, from performance optimization to accessibility improvements.
  • Lighthouse Integration
    The site integrates with Lighthouse, an open-source tool that audits web pages for performance, accessibility, SEO, and more, providing actionable insights.
  • Regular Updates
    Content is consistently updated to align with the latest web standards and practices, ensuring developers get current and relevant information.
  • Interactive Learning
    Offers interactive assessments and code labs that allow developers to practice and implement what they have learned in a hands-on manner.
  • Expert Contributors
    Content on Web.dev is often contributed by industry experts and Google engineers, ensuring a high level of credibility and insight.

Possible disadvantages of Web.dev by Google

  • Google-Centric
    While the information is high-quality, it often reflects Google's specific views and technologies, which may not always align with other standards or practices.
  • Overwhelming for Beginners
    The sheer amount of information can be overwhelming for novice developers who may not know where to start.
  • Performance Over Focus
    The strong emphasis on performance might sometimes underplay other critical aspects such as backend development or advanced JavaScript frameworks.
  • Tool Dependence
    Heavy reliance on tools like Lighthouse could lead developers to become dependent on these tools rather than understanding the underlying principles.
  • Surface-Level Coverage
    Some topics may receive only surface-level coverage, leaving those seeking in-depth knowledge to look elsewhere.

Analysis of Web.dev by Google

Overall verdict

  • Yes, Web.dev by Google is highly regarded for its thorough and actionable resources designed to enhance web development practices. It's considered a valuable tool for developers aiming to build fast, reliable, and accessible web applications.

Why this product is good

  • Web.dev by Google provides comprehensive resources and tools to help developers improve the performance, accessibility, and best practices of their web applications. It offers up-to-date documentation, practical guides, and actionable insights that are aligned with industry standards. The platform is developed by Google, a leader in web technology, ensuring that the information is credible and relevant. Web.dev also includes tools like Lighthouse for site audits, enabling developers to optimize their web platforms effectively.

Recommended for

    Web.dev is recommended for web developers, designers, and SEO professionals looking to improve their website's performance, accessibility, and compliance with best practices. It's also useful for educators and students in web development programs who need a reliable source of information and tools for learning and teaching modern web technologies.

Jupyter videos

+ Add

What is Jupyter Notebook?

More videos:

  • Tutorial - Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough
  • Review - JupyterLab: The Next Generation Jupyter Web Interface

Web.dev by Google videos

No Web.dev by Google videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Jupyter and Web.dev by Google)

Jupyter

Web.dev by Google

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Online Services
0 0%
Online Services
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Developer Tools
0 0%
Developer 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 Jupyter and Web.dev by Google

Jupyter Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Once you install nteract, you can open your notebook without having to launch the Jupyter Notebook or visit the Jupyter Lab. The nteract environment is similar to Jupyter Notebook but with more control and the possibility of extension via libraries like Papermill (notebook parameterization), Scrapbook (saving your notebook’s data and photos), and Bookstore (versioning).
Source: lakefs.io
7 best Colab alternatives in 2023
JupyterLab is the next-generation user interface for Project Jupyter. Like Colab, it's an interactive development environment for working with notebooks, code, and data. However, JupyterLab offers more flexibility as it can be self-hosted, enabling users to use their own hardware resources. It also supports extensions for integrating other services, making it a highly...
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Jupyter Notebook is a widely popular tool for data scientists to work on data science projects. This article reviews the top 12 alternatives to Jupyter Notebook that offer additional features and capabilities.
Source: noteable.io
15 data science tools to consider using in 2021
Jupyter Notebook's roots are in the programming language Python -- it originally was part of the IPython interactive toolkit open source project before being split off in 2014. The loose combination of Julia, Python and R gave Jupyter its name; along with supporting those three languages, Jupyter has modular kernels for dozens of others.
Source: searchbusinessanalytics.techtarget.com
Top 4 Python and Data Science IDEs for 2021 and Beyond
Yep — it’s the most popular IDE among data scientists. Jupyter Notebooks made interactivity a thing, and Jupyter Lab took the user experience to the next level. It’s a minimalistic IDE that does the essentials out of the box and provides options and hacks for more advanced use.
Source: towardsdatascience.com

Web.dev by Google Reviews

We have no reviews of Web.dev by Google yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Jupyter should be more popular than Web.dev by Google. It has been mentiond 216 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.

Jupyter mentions (216)

  • The 3 Best Python Frameworks To Build UIs for AI Apps
    Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / 3 months ago
  • LangChain: From Chains to Threads
    LangChain wasn’t designed in isolation — it was built in the data pipeline world, where every data engineer’s tool of choice was Jupyter Notebooks. Jupyter was an innovative tool, making pipeline programming easy to experiment with, iterate on, and debug. It was a perfect fit for machine learning workflows, where you preprocess data, train models, analyze outputs, and fine-tune parameters — all in a structured,... - Source: dev.to / 4 months ago
  • Applied Artificial Intelligence & its role in an AGI World
    Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 5 months ago
  • Jupyter Notebook for Java
    Lately I've been working on Langgraph4J which is a Java implementation of the more famous Langgraph.js which is a Javascript library used to create agent and multi-agent workflows by Langchain. Interesting note is that [Langchain.js] uses Javascript Jupyter notebooks powered by a DENO Jupiter Kernel to implement and document How-Tos. So, I faced a dilemma on how to use (or possibly simulate) the same approach in... - Source: dev.to / 9 months ago
  • JIRA Analytics with Pandas
    One of the most convenient ways to play with datasets is to utilize Jupyter. If you are not familiar with this tool, do not worry. I will show how to use it to solve our problem. For local experiments, I like to use DataSpell by JetBrains, but there are services available online and for free. One of the most well-known services among data scientists is Kaggle. However, their notebooks don't allow you to make... - Source: dev.to / 12 months ago
View more

Web.dev by Google mentions (130)

  • Eating the toast
    Toast is a fairly common component which is often used to display a message or sometimes feedback of an action on the screen. A more formal definition by https://web.dev state is this way:. - Source: dev.to / 3 months ago
  • Understanding the Critical Render Path and Its Role in Web Performance
    Here is a sample video clip of FOUC taken from web.dev where you can see the page without any styling and all styles are applied once the page's CSS has finished loading from the network. Example of FOUC. - Source: dev.to / 6 months ago
  • A Comprehensive Guide to Web Vitals: Metrics That Matter for Performance
    In this article, we have learned about What are Web Vitals, Core Web Vitals and how these matrices are used to measure web performance. To learn more about them check out the web.dev performance section here. If you like this blog and you want to learn more about Frontend Development and Software Engineering you can follow me on Dev.to. - Source: dev.to / 6 months ago
  • Is Chrome the New IE?
    Another piece of evidence is Google tries at nearly every turn to help people write portable code, use best practices like feature detection instead of browser version sniffing, etc... They run https://web.dev/ and the founded baseline https://web.dev/baseline and the web platform dashboard https://web.dev/blog/web-platform-dashboard MS in their IE days did the exact opposite, trying to make as many proprietary IE... - Source: Hacker News / 7 months ago
  • Old Dogs, New CSS Tricks
    It may be ran by Google, but https://web.dev/ is one good source for keeping up with new web technologies. - Source: Hacker News / about 1 year ago
View more

What are some alternatives?

When comparing Jupyter and Web.dev by Google, you can also consider the following products

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

cutestat - Website Stats and Valuation. CuteStat.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Rankchart - Rankchart is one of the unique websites that allows you to examine your websites or watch competitors and locate rich information about website technologies, site reputation, errors, SEO, and ad-word recommendations.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

WebsiteOutlook - WebsiteOutlook is an all-in-one website that provides you detailed information on famous websites based on various data sources like traffic, page rank, and estimated ad revenue.

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