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-1.4.1.dev3.tar.gz.

File metadata

  • Download URL: swarmauri_tool_jupyterexportmarkdown-1.4.1.dev3.tar.gz
  • Upload date:
  • Size: 8.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.15 {"installer":{"name":"uv","version":"0.11.15","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-1.4.1.dev3.tar.gz
Algorithm Hash digest
SHA256 b5aef5983684115ee121bd5c5357923779f5478be4974128fb4de2d4abf47145
MD5 b5b6df78b243bffc3c3dbfaa5b6344ec
BLAKE2b-256 cccee0a557d847c49fc72ed84bec1a8ed56b8cfddd75582f2afea4723e9f5c61

See more details on using hashes here.

File details

Details for the file swarmauri_tool_jupyterexportmarkdown-1.4.1.dev3-py3-none-any.whl.

File metadata

  • Download URL: swarmauri_tool_jupyterexportmarkdown-1.4.1.dev3-py3-none-any.whl
  • Upload date:
  • Size: 9.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.15 {"installer":{"name":"uv","version":"0.11.15","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-1.4.1.dev3-py3-none-any.whl
Algorithm Hash digest
SHA256 6bfa16ab62709538de66505a6fe1c6bdd15b37030fce972e26bc88ad05de4ded
MD5 35028f68dea5712fdee5c6dd7483d34d
BLAKE2b-256 bb8fdb3f603691ef1e312c37e3b11d9402c6426ac732732ab76671e46387f7cd

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