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Jupyter VS GraphQL Playground

Compare Jupyter VS GraphQL Playground 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.

GraphQL Playground logo GraphQL Playground

GraphQL IDE for better development workflows
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • GraphQL Playground Landing page
    Landing page //
    2023-10-09

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.

GraphQL Playground features and specs

  • Interactive Interface
    GraphQL Playground provides a user-friendly, interactive interface for exploring and testing GraphQL queries and mutations. This allows developers to quickly experiment with their GraphQL API.
  • Auto-Completion and Syntax Highlighting
    It offers auto-completion and syntax highlighting which increases productivity by helping developers write correct GraphQL queries faster.
  • Built-in Documentation
    The built-in documentation explorer helps developers easily navigate and understand the GraphQL schemas, types, and fields available in their API.
  • Real-time Error Feedback
    Provides real-time error feedback, making it easier to identify and fix issues while writing queries, resulting in smoother development workflows.
  • Request History
    GraphQL Playground maintains a history of queries and mutations executed, allowing developers to quickly revisit and reuse previous work.
  • Customizable Settings
    It is highly customizable, allowing developers to set endpoint URLs, headers, and other configurations to match various environments (development, staging, production).

Possible disadvantages of GraphQL Playground

  • Performance
    GraphQL Playground can be resource-intensive, consuming significant amounts of memory and CPU, which might slow down the development environment, especially with large schemas.
  • Security Concerns
    As an interactive playground embedded in web interfaces, it may expose sensitive data or operations if not properly secured, necessitating careful configuration and access control.
  • Limited Offline Use
    Since it relies on an active endpoint to fetch schema details and execute queries, its utility is limited when working offline.
  • Deprecated Maintenance
    As of 2020, the GraphQL Playground repository is not actively maintained anymore, which means it may not receive updates, bug fixes, or new features.
  • Complex Configuration
    In comparison to simpler alternatives, setting up and configuring GraphQL Playground can be more complex and time-consuming.

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

GraphQL Playground videos

+ Add

Graphql playground review completa parte 1

More videos:

  • Review - Create Local GraphQL Playground
  • Review - Graphql playground review completa parte 2

Category Popularity

0-100% (relative to Jupyter and GraphQL Playground)

Jupyter

GraphQL Playground

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
GraphQL
0 0%
GraphQL
100% 100

User comments

Share your experience with using Jupyter and GraphQL Playground. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Jupyter and GraphQL Playground

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

GraphQL Playground Reviews

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

Social recommendations and mentions

Based on our record, Jupyter seems to be a lot more popular than GraphQL Playground. While we know about 216 links to Jupyter, we've tracked only 12 mentions of GraphQL Playground. 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 / about 2 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 / 3 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 / 4 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 / 8 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 / 11 months ago
View more

GraphQL Playground mentions (12)

  • Show HN: API Parrot – Automatically Reverse Engineer HTTP APIs"
    Have you tried something like GraphQL playground before? https://github.com/graphql/graphql-playground There's other tools out there that can generate similar docs or playgrounds, given you have a schema/spec of some type. - Source: Hacker News / 4 months ago
  • Exploring GraphiQL 2 Updates and New Features
    GraphiQL is a tool that was created to help developers explore GraphQL APIs, maintained by the GraphQL Foundation. But when GraphiQL became more and more popular, developers started to create additional GraphQL IDEs. A good example of this was GraphQL Playground, which quickly became the most popular GraphQL IDE. It was loosely based on GraphiQL, but had more features and a better UI. - Source: dev.to / over 2 years ago
  • Why Is It So Important To Go To Meetups
    I went to a GraphQL meetup and they used the gql playground and a similar schema generator to what I was using, and it made me feel relevant. - Source: dev.to / about 3 years ago
  • GraphQL subscriptions at scale with NATS
    Here, we'll create a simple GraphQL server and subscribe to a subject from our resolver. We'll use GraphQL playground to mock client side behavior. Once we're connected we'll use NATS CLI to send a payload to our subject and see the changes on the client. - Source: dev.to / over 3 years ago
  • GraphQL vs REST in .NET Core
    Now we can consume created GraphQL API. In the GitHub Repo same functionality has been added with REST approach and GraphQL endpoint. Also widely used Swagger configured for Web API Endpoints as well as AltairUI added for GraphQL endpoint testing. Naturally, AltairUI it not a must for GraphQL, you can also use Swagger, GraphiQL, or GraphQL Playground. - Source: dev.to / over 3 years ago
View more

What are some alternatives?

When comparing Jupyter and GraphQL Playground, 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.

How to GraphQL - Open-source tutorial website to learn GraphQL development

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

GraphQl Editor - Editor for GraphQL that lets you draw GraphQL schemas using visual nodes

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

Stellate.co - Everything you need to run your GraphQL API at scale

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