nteract/hydrogen

:atom: Run code interactively, inspect data, and plot. All the power of Jupyter kernels, inside your favorite text editor.

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Summary Information

Updated 1 hour ago
Added to GitGenius on September 17th, 2026
Created on May 11th, 2015
Open Issues & Pull Requests: 180 (+0)
GitHub issues: Enabled
Number of forks: 339
Total Stargazers: 4,021 (+0)
Total Subscribers: 74 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 19.6 days
Mean response time: 476.2 days
90th percentile: 1783.6 days
Tracked items: 4

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Issue Activity (beta)

Open issues: 1
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,041 days
Stale 30+ days: 1
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug :bug: (1)
  • enhancement :star2: (1)
  • language specific (1)
  • pull-request-welcome (1)
  • wontfix (1)

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Detailed Description

Hydrogen is an Atom package that brings interactive code execution and Jupyter kernel functionality directly into a text editor.

The tool solves the friction of switching between a code editor and a separate notebook environment by embedding Jupyter kernel capabilities within Atom itself. It allows developers to run code interactively, inspect variables, and generate plots without leaving their editor. The approach works by connecting to Jupyter kernels, which handle the actual code execution and provide the computational backend that powers interactive workflows.

Hydrogen suits developers who prefer working in a traditional text editor but want the interactive capabilities of notebook environments. It works well for data science tasks, exploratory programming, and any workflow where rapid iteration and inline result inspection are valuable. The tool is particularly useful for those already invested in Atom as their primary editor and who want to avoid context-switching between separate applications.

The project shows signs of sustained maintenance with regular updates addressing user-reported issues and compatibility concerns. Development activity includes ongoing refinement of the kernel connection mechanism and improvements to how results are displayed within the editor. The maintainers actively respond to bug reports and pull requests, indicating continued engagement with the user base. Work continues on supporting multiple programming languages through different Jupyter kernel backends, expanding the tool's applicability beyond Python-only workflows.