Skip to main content

A Swarmauri tool designed to export Jupyter Notebooks to Markdown.

Project description

Swarmauri Logo

PyPI - Downloads Hits PyPI - Python Version PyPI - License PyPI - swarmauri_tool_jupyterexportmarkdown


Swarmauri Tool Jupyter Export Markdown

Converts a Jupyter NotebookNode to Markdown using nbconvert’s MarkdownExporter. Injectable CSS and JS snippets let you tweak the output for static publishing.

Features

  • Accepts a notebook JSON string and returns rendered Markdown.
  • Optional inline CSS/JS injection to customize the exported document.
  • Returns a dict with exported_markdown or error if conversion fails.

Prerequisites

  • Python 3.10 or newer.
  • nbconvert/nbformat installed (pulled in automatically).

Installation

# pip
pip install swarmauri_tool_jupyterexportmarkdown

# poetry
poetry add swarmauri_tool_jupyterexportmarkdown

# uv (pyproject-based projects)
uv add swarmauri_tool_jupyterexportmarkdown

Quickstart

import json
import nbformat
from swarmauri_tool_jupyterexportmarkdown import JupyterExportMarkdownTool

notebook = nbformat.read("notebooks/example.ipynb", as_version=4)
notebook_json = json.dumps(notebook)

exporter = JupyterExportMarkdownTool()
response = exporter(
    notebook_json=notebook_json,
    extra_css="blockquote { color: gray; }",
    extra_js="console.log('Markdown ready');",
)

if "exported_markdown" in response:
    Path("notebooks/example.md").write_text(response["exported_markdown"], encoding="utf-8")
else:
    print("Error:", response["error"])

Tips

  • Use Markdown export when preparing notebooks for static docs, blogs, or README content.
  • Apply lightweight CSS/JS to adjust styling when the Markdown is embedded in HTML environments.
  • Combine with notebook execution tools to build pipelines (execute → convert to Markdown → publish).

Want to help?

If you want to contribute to swarmauri-sdk, read up on our guidelines for contributing that will help you get started.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file swarmauri_tool_jupyterexportmarkdown-1.4.0.dev7.tar.gz.

File metadata

  • Download URL: swarmauri_tool_jupyterexportmarkdown-1.4.0.dev7.tar.gz
  • Upload date:
  • Size: 8.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.12 {"installer":{"name":"uv","version":"0.10.12","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for swarmauri_tool_jupyterexportmarkdown-1.4.0.dev7.tar.gz
Algorithm Hash digest
SHA256 76bdcad972b5c06ca167c7311c78f888d4b67149395b7dd50fb902c2d0f8badf
MD5 778217e1cac57618fb6226981a97072c
BLAKE2b-256 3924f8b0a1780d578b0ef820a06b754df1797f3b0e54a438893ab9442255db37

See more details on using hashes here.

File details

Details for the file swarmauri_tool_jupyterexportmarkdown-1.4.0.dev7-py3-none-any.whl.

File metadata

  • Download URL: swarmauri_tool_jupyterexportmarkdown-1.4.0.dev7-py3-none-any.whl
  • Upload date:
  • Size: 9.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.12 {"installer":{"name":"uv","version":"0.10.12","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for swarmauri_tool_jupyterexportmarkdown-1.4.0.dev7-py3-none-any.whl
Algorithm Hash digest
SHA256 87fa99ec6f75e2a29c9a9a266996531a9a682a6d59df09cce4c53aaa08515bee
MD5 8aa4e887eb832de1b049c8d55ccf2a1d
BLAKE2b-256 9ea6599840d5ddf0ce90fb5d93feaa2754220ff2e9e7e3f6c4e31c66a636f261

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page