# deepklarity/jupyter-text2code

A proof-of-concept jupyter extension which converts english queries into relevant python code

Repository: https://github.com/deepklarity/jupyter-text2code
Canonical: https://ross.abutalabs.com/products/jupyter-text2code
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: jupyter-notebook, machine-learning, python
Last push: 2025-10-22T03:15:15+00:00

## Health v2 (maintenance only)
Score: 54/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 48, release rhythm 35, longevity 100
- inputs: {"age_days": 2187, "days_push": 315, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2082, forks 354 (observed 2026-08-28T04:06:11.733868+00:00)

## What it is
A proof-of-concept Jupyter Notebook extension that converts English queries into relevant Python code using sentence embedding models. It supports pandas commands and snippet insertion from popular integrations via a terminal-style UI in the notebook menu.

## Use cases
- generate python code from english queries in jupyter
- convert natural language to pandas commands
- insert code snippets for twitter or instagram integrations in a notebook
- make data analysis easier by typing what i want instead of writing code
- jupyter notebook extension for text to code

## When to choose
- you want to try natural-language code generation inside classic Jupyter Notebook
- you frequently write pandas commands and want a conversational shortcut
- you want quick snippet insertion from awesome-notebooks integrations

## When to avoid
- you need production-grade, reliable code generation from modern LLMs
- you use JupyterLab instead of classic Jupyter Notebook
- you need Windows support or a maintained, actively developed tool

## Facets
- artifact type: plugin
- maturity: experimental
- function: nlp, machine-learning, developer-tools
- domain: developer-tools, data-science
- platform: python
- tags: jupyter-extension, text-to-code, nbextension, code-generation, proof-of-concept, natural-language-processing, linux, macos, jupyter

## Member repositories
- deepklarity/jupyter-text2code (main) score 54

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:11.733868+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:55:55.429834+00:00, confidence not recorded.
  - readme: https://github.com/deepklarity/jupyter-text2code (fetched 2026-08-28T04:06:11.733868+00:00, sha d913fe1ad82e)
- Data as of 2026-08-30T08:39:29.467469+00:00.