Real-time collaboration in Jupyter

Coming soon. Explore other notebooks in the meantime.

Data science is a team sport. We share our findings, consult domain knowledge and need a second pair of eyes for our code. However, the number one tool used by 95% of data scientists works best when used solo.

People share .ipynb files by sending them back and forth. They send static screenshots of charts to ask questions. Code reviews get done on messy JSON structures or involve transformations before comitting. Often, these hurdles lead to less sharing, less talking, and almost no code review.

A new generation of tools aims to solve these problems. They promote notebooks to a first class citizen among company documents, accessible by everyone.

Deepnote

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Deepnote is a new kind of data science notebook. Jupyter-compatible with real-time collaboration and running in the cloud. Oh, and it's free.

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CoCalc

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Your best choice for teaching remote scientific courses!

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Nextjournal

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Runs anything you can put into a Docker container. Improve your workflow with polyglot notebooks, automatic versioning and real-time collaboration. Save time and money with on-demand provisioning, including GPU support.

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Zepl

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Notebook-powered analytics for enterprise teams.

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Databricks Notebooks

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A notebook is a web-based interface to a document that contains runnable code, visualizations, and narrative text.

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Hex

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The Data Workspace for Teams. Work with data in collaborative SQL and Python notebooks. Share as interactive data apps that anyone can use.

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Jetbrains Datalore

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A powerful online environment for Jupyter notebooks. Use smart coding assistance for Python in online Jupyter notebooks, run code on powerful CPUs and GPUs, collaborate in real-time, and easily share the results.

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Count

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The BI notebook built for analysts. Simplify your workflow, collaborate with others and create the analysis your company craves in record time.

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