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.dev3.tar.gz.

File metadata

  • Download URL: swarmauri_tool_jupyterexportmarkdown-1.4.0.dev3.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.dev3.tar.gz
Algorithm Hash digest
SHA256 6d01976903cbab63cda76d2e1c31606b20ae1727b52b101873caaaea5143b012
MD5 6a98671fea9da38cb8632e6dc8f65122
BLAKE2b-256 8ed3436441444deb0ff0a7baeabed2b3935d3ffc49e2af4a2ecf335b725cb78d

See more details on using hashes here.

File details

Details for the file swarmauri_tool_jupyterexportmarkdown-1.4.0.dev3-py3-none-any.whl.

File metadata

  • Download URL: swarmauri_tool_jupyterexportmarkdown-1.4.0.dev3-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.dev3-py3-none-any.whl
Algorithm Hash digest
SHA256 de60be4fbff89b72ec7d270ac5fb603ab9b3f2d2f6990d661845c8836116bc48
MD5 7021c7cdaa2b359eee3d8a5e558beba7
BLAKE2b-256 a247c446138c5a382df0e0a5e391ffe464052b80cb1696e1d25217a105b744c1

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