● Covered by 1 source · 1 reportLow impact1 neutral
Tithon enables persistent Jupyter kernel execution and live output streaming in VSCode
Key points
- Jupyter kernels persist independently of client connection.
- Live output streaming continues even after disconnects.
- Addresses limitations in JupyterLab and VSCode Jupyter.
- Converts .ipynb to cleaner .py files and stores outputs as real files.
Persistent Jupyter Sessions
Tithon is an alpha-stage tool designed to maintain Jupyter kernel execution and output streaming even when the client connection is lost. This addresses a common problem where closing an editor or experiencing a network disconnect terminates the Jupyter kernel and its associated session, leading to loss of progress and output.
Addressing Current Limitations
Existing Jupyter environments like JupyterLab and VSCode Jupyter often lose output or terminate kernels upon client disconnection. JupyterLab does not persist iopub output server-side, while VSCode Jupyter ties the kernel to the extension-host process. Tithon moves the source of truth for the session to the host, ensuring continuity.
Improved Data Handling
Beyond persistence, Tithon also processes Jupyter notebooks differently. It converts the verbose JSON format of .ipynb files into cleaner .py files. Output images are stored as actual files rather than base64 encoded strings within the notebook, which can be beneficial for AI agents that process visual data.
System Requirements and Installation
Tithon requires Python 3.11+ and a Unix-like host for its daemon and CLI components. It is developed and tested on Linux, with support for Windows users via WSL. Installation involves `pip install tithon` and installing the Tithon extension from the VSCode Marketplace.
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Primary sources
GitHub cmc_internal/api GitHub github/collect GitHub rnoro/tithon GitHub _private/browser GitHub get-started/accessibility GitHub open-source/sponsorsReporting from
Tithon, an alpha-stage tool, allows Jupyter kernels and their output to persist independently of the client connection, addressing issues where closing an editor or losing connection terminates the kernel and its session. This enables continuous execution and output streaming even after disconnects, improving workflow for long-running tasks in environments like VSCode and JupyterLab.