labpaper 1.0.10

LabPaper - A Jupyter notebook extension for exporting notebooks to academic papers.

LabPaper

A sophisticated Jupyter notebook exporter designed for creating academic papers. This package provides a seamless integration between Jupyter notebooks and professional academic paper formats.

Features

• Export Jupyter notebooks to professional academic paper formats
• Support for Nature journal format
• Customizable templates and exporters
• Advanced preprocessing capabilities
• Flexible filtering system

Installation

pip install labpaper

Quick Start

Basic usage example:

jupyter nbconvert --to nature your_notebook.ipynb

Documentation

• Exporters - Document conversion and output generation
• Filters - Content transformation and processing
• Preprocessors - Pre-conversion notebook manipulation
• Templates - Document layout and styling
• Embedded Resources - Any additional resources required by your exporter or template

Requirements

• Python ≥ 3.11
• Jupyter ≥ 7.0.0
• nbconvert ≥ 7.16.0
• pandoc >= 3.6
• A LaTeX distribution (e.g., MikTeX, TeX Live, etc.)
• Other dependencies are handled automatically during installation

Development

1. Clone the repository:

   git clone https://github.com/yourusername/labpaper.git
   cd labpaper
   

2. Create and activate a virtual environment:

   python -m venv env
   source env/bin/activate  # On Windows use `env\Scripts\activate`
   

3. Install the package in development mode along with development dependencies:

   pip install -e .[dev]
   

4. Install pre-commit hooks:

   pre-commit install
   

5. Add New Exporters:

   • Create a new Python file for your exporter in the labpaper/exporters directory.
   • Implement your exporter class by inheriting from the base exporter class provided by LabPaper.
   • Ensure your exporter handles the conversion logic specific to the desired output format.
   • Register your new exporter in the pyproject.toml file under the [tool.labpaper.exporters] section to make it available for use.

6. Add New Filters:

   • Create a new Python file for your filter in the labpaper/filters directory.
   • Implement your filter function or class, ensuring it processes the content as required.
   • Register your new filter in the pyproject.toml file under the [tool.labpaper.filters] section to integrate it into the conversion pipeline.

7. Add New Preprocessors:

   • Create a new Python file for your preprocessor in the labpaper/preprocessors directory.
   • Implement your preprocessor class by inheriting from nbconvert.preprocessors.Preprocessor.
   • Define the preprocess method to modify notebook content before conversion.
   • Register your new preprocessor in the labpaper/preprocessors/__init__.py file to include it in the available preprocessors list. Note that preprocessors will be refactored in a later release for better modularity.

8. Create New Templates:

   • Create a new subdirectory for your template in the templates directory.
   • Add the necessary Jinja2 template files (.tex.j2) to define the document structure and styling.
   • Include a conf.json file in your template subdirectory to specify template metadata and configuration options, following the nbconvert documentation.
   • Register your new template in the pyproject.toml file under the [tool.labpaper.templates] section to make it available for use.

9. Place Resources in the Appropriate texmf Subdirectory:

   • Organize any additional resources (e.g., .bst files, .cls files, custom style files) required for TeX/LaTeX compilation in the texmf directory.
   • Follow the existing directory structure within texmf to ensure resources are correctly located and accessible during the PDF generation process.
   • Update any relevant documentation or configuration files to reference the new resources as needed.

Contributing

We welcome contributions to LabPaper! Here's how you can help:

• Report Bugs: If you find a bug, please open an issue
• Suggest Features: Have an idea for a new feature? Create a feature request
• Submit Pull Requests: Want to contribute code? Fork the repository and submit a pull request

Please read our Contributing Guidelines before submitting any contributions.

License

This project is licensed under the BSD License - see the LICENSE file for details.