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-1.3.3.dev4.tar.gz.

File metadata

  • Download URL: swarmauri_tool_jupyterexportmarkdown-1.3.3.dev4.tar.gz
  • Upload date:
  • Size: 8.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.3 {"installer":{"name":"uv","version":"0.10.3","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-1.3.3.dev4.tar.gz
Algorithm Hash digest
SHA256 3ba7c28185df639d5c2e5b6a6f17fdc265a6e53867c7d76d9b7804f30ff36fa0
MD5 c2484f8ad83ba92ebab733e4ab0a0543
BLAKE2b-256 46e2d2a6fb56f5326d3f72c06568d94a9be70a5b168e6e5cb315f4e9056ce01f

See more details on using hashes here.

File details

Details for the file swarmauri_tool_jupyterexportmarkdown-1.3.3.dev4-py3-none-any.whl.

File metadata

  • Download URL: swarmauri_tool_jupyterexportmarkdown-1.3.3.dev4-py3-none-any.whl
  • Upload date:
  • Size: 9.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.10.3 {"installer":{"name":"uv","version":"0.10.3","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-1.3.3.dev4-py3-none-any.whl
Algorithm Hash digest
SHA256 9297632d118d790adf4d89ccc6617dfce14eaf15380c98c1e0f13ce227df9281
MD5 ba30ec8df64b7924b66c06f2691290fe
BLAKE2b-256 965e25232db77dc176da132f7c2c4d084ed3623170e4b5a209ae50d20310baac

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