shared-summary/
├── README.md                          # Brief overview
├── analysis-YYYY-MM-DD.pdf           # Notebook as PDF
└── results/
    ├── figures/
    │   ├── fig1-main-result.png
    │   └── fig2-comparison.png
    └── tables/
        └── summary-statistics.csv

shared-reproducible/
├── README.md                          # Setup and reproduction instructions
├── MANIFEST.md                        # File descriptions
├── environment.yml                    # Conda environment OR requirements.txt
├── notebooks/
│   ├── 01-data-processing.ipynb      # Cleaned, outputs cleared
│   ├── 02-analysis.ipynb
│   └── 03-visualization.ipynb
├── scripts/
│   ├── generate_figures.py           # Standalone scripts
│   └── utils.py
└── data/
    ├── processed/
    │   ├── cleaned_data.csv
    │   └── processed_results.tsv
    └── README.md                      # Data provenance

shared-complete/
├── README.md                          # Complete project guide
├── MANIFEST.md                        # Comprehensive file listing
├── environment.yml
├── data/
│   ├── raw/                          # Original, unmodified data
│   │   ├── sample_A_reads.fastq.gz
│   │   └── README.md                 # Data source, download date
│   ├── intermediate/                 # Processing steps
│   │   ├── 01-filtered/
│   │   ├── 02-aligned/
│   │   └── README.md
│   └── processed/                    # Final analysis-ready
│       └── final_dataset.csv
├── scripts/
│   ├── 01-download-data.sh
│   ├── 02-quality-control.py
│   ├── 03-filtering.py
│   ├── 04-analysis.py
│   └── utils/
├── notebooks/
│   ├── exploratory/                  # Early exploration
│   └── final/                        # Publication analyses
├── results/
│   ├── figures/
│   ├── tables/
│   └── supplementary/
└── documentation/
    ├── methods.md                    # Detailed methodology
    ├── changelog.md                  # Processing decisions
    └── data-dictionary.md            # Variable definitions

Which sharing level do you need?

1. Summary Only - PDF + final results (quick sharing)
2. Reproducible - Notebooks + scripts + data (standard sharing)
3. Full Traceability - Everything from raw data (archival/compliance)

Additional questions:
- Who is the audience? (colleagues, reviewers, public)
- Are there size constraints?
- Any sensitive data to handle?
- Timeline for sharing?

undefined

undefined

import nbformat
from nbconvert.preprocessors import ClearOutputPreprocessor

def clean_notebook(input_path, output_path):
    """Clean notebook: clear outputs, remove debug cells."""

    # Read notebook
    with open(input_path, 'r') as f:
        nb = nbformat.read(f, as_version=4)

    # Clear outputs
    clear_output = ClearOutputPreprocessor()
    nb, _ = clear_output.preprocess(nb, {})

    # Remove cells tagged as 'debug' or 'remove'
    nb.cells = [cell for cell in nb.cells
                if 'debug' not in cell.metadata.get('tags', [])
                and 'remove' not in cell.metadata.get('tags', [])]

    # Write cleaned notebook
    with open(output_path, 'w') as f:
        nbformat.write(nb, f)

undefined

undefined

undefined

undefined

import hashlib

def anonymize_ids(df, id_column='subject_id'):
    """Replace IDs with hashed values."""
    df[id_column] = df[id_column].apply(
        lambda x: hashlib.sha256(str(x).encode()).hexdigest()[:8]
    )
    return df

undefined

**For larger packages:**
```bash

**Document package contents:**
- Total size
- Number of files
- Compression method
- How to extract

undefined

---

undefined

**For conda:**
```bash

---

#!/usr/bin/env python3
"""Create sharing package for project."""

import shutil
from pathlib import Path
from datetime import date
import nbformat
from nbconvert.preprocessors import ClearOutputPreprocessor

def create_sharing_package(level='reproducible', output_dir=None):
    """
    Create sharing package.

    Args:
        level: 'summary', 'reproducible', or 'full'
        output_dir: Output directory name (auto-generated if None)
    """

    # Create output directory
    if output_dir is None:
        output_dir = f"shared-{date.today():%Y%m%d}-{level}"

    share_path = Path(output_dir)
    share_path.mkdir(exist_ok=True)

    print(f"Creating {level} sharing package in {share_path}")

    # Create structure based on level
    if level == 'summary':
        create_summary_package(share_path)
    elif level == 'reproducible':
        create_reproducible_package(share_path)
    elif level == 'full':
        create_full_package(share_path)

    print(f"✓ Package created: {share_path}")
    print(f"  Review and compress: tar -czf {share_path}.tar.gz {share_path}")

def clean_notebook(input_path, output_path):
    """Clean notebook outputs and debug cells."""
    with open(input_path) as f:
        nb = nbformat.read(f, as_version=4)

    # Clear outputs
    clear = ClearOutputPreprocessor()
    nb, _ = clear.preprocess(nb, {})

    # Remove debug cells
    nb.cells = [c for c in nb.cells
                if 'debug' not in c.metadata.get('tags', [])]

    with open(output_path, 'w') as f:
        nbformat.write(nb, f)

---