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Package to extract parliamentary protocols from the German Bundestag in structured form.

Project description

Bundestag Protocol Extractor

PyPI version Python Versions License Tests

Extract and structure data from the German Bundestag's parliamentary protocols using the official DIP API.

🚀 Quick Start

Installation

pip install bundestag-protocol-extractor

Command Line Usage

# Extract protocols from the 20th legislative period, limit to 5
bpe --period 20 --limit 5 --output-dir ./data

# Export to both CSV and JSON format
bpe --period 20 --limit 5 --format both

# Use a specific API key (optional, package includes a public key)
bpe --api-key YOUR_API_KEY --period 20 --limit 5

🔍 Overview

This package allows researchers, journalists, and political analysts to access German parliamentary protocols (plenarprotokolle) in a structured format suitable for analysis. It extracts speeches, speaker metadata, topics, and related information from the Bundestag's official API.

✨ Features

  • Extract Protocols: Access plenarprotokolle from all legislative periods
  • Structure Content: Extract individual speeches with rich metadata
  • Speaker Metadata: Get information about speakers (name, party, role)
  • Topic Analysis: Access topic information and related proceedings
  • Multiple Export Formats: Export to CSV and JSON for easy analysis
  • Automatic Rate Limiting: Robust handling of API limits with exponential backoff
  • Progress Tracking: Resume long-running extractions if interrupted
  • Flexible Configuration: Fine-tune extraction parameters based on your needs
  • Multi-strategy Extraction: Tiered extraction approach with automatic fallbacks
  • Quality Tracking: Detailed extraction metadata for research transparency
  • XML Caching: Efficient storage and retrieval of previously downloaded documents
  • Pattern Recognition: Sophisticated text pattern matching for speech extraction

📋 Detailed Usage

Command Line Interface

# Basic usage
bpe --period 20 --limit 5 --output-dir ./data

# List help and all available options
bpe --help

# Extract all protocols from the current legislative period
bpe --period 20 --output-dir ./data

# Enable XML caching for faster subsequent runs (default)
bpe --period 20 --enable-xml-cache

# Disable XML caching
bpe --period 20 --disable-xml-cache

# Specify a custom cache directory
bpe --period 20 --cache-dir /path/to/cache/dir

# Enable automatic repair of malformed XML (default)
bpe --period 20 --repair-xml

# Disable XML repair
bpe --period 20 --no-repair-xml

Control Output Format

# Export to CSV (default)
bpe --period 20 --format csv

# Export to JSON
bpe --period 20 --format json

# Export to both formats
bpe --period 20 --format both

# Exclude full speech text to reduce file size
bpe --period 20 --exclude-speech-text

# Include full protocol text (large files)
bpe --period 20 --include-full-protocols

Logging Options

# Enable verbose output (INFO to console, DEBUG to log file)
bpe --period 20 --verbose

# Enable full debug logging (DEBUG to both console and log file)
bpe --period 20 --debug

# Quiet mode (WARNING to console, INFO to log file)
bpe --period 20 --quiet

# Specify custom log file
bpe --period 20 --log-file /path/to/custom/log/file.log

Progress Tracking & Resumption

# List available progress files
bpe --list-progress

# Resume from a specific progress file
bpe --resume /path/to/progress_file.json

# Resume from a specific protocol
bpe --resume-from "20/123"

# Skip first N protocols
bpe --offset 25

Python API

You can also use the package directly in your Python code:

from bundestag_protocol_extractor import BundestagExtractor
import logging

# Initialize the extractor (uses default public API key)
extractor = BundestagExtractor()

# Or with your own API key and XML options
# extractor = BundestagExtractor(
#     api_key="YOUR_API_KEY",
#     enable_xml_cache=True,
#     cache_dir="./cache",
#     repair_xml=True
# )

# Fetch protocols for a specific legislative period (20th Bundestag)
protocols = extractor.get_protocols(period=20, limit=5)

# Export to CSV (creates separate files for protocols, speeches, etc.)
exported_files = extractor.export_to_csv(
    protocols,
    output_dir="./data",
    include_speech_text=True
)

# Export to JSON (creates a single JSON file with all data)
json_path = extractor.export_to_json(protocols, output_dir="./data")

📊 Data Structure

The extracted data is organized in a relational format with multiple CSV files:

Core Files

  1. protocols.csv: Basic protocol metadata (date, title, etc.)
  2. speeches.csv: Individual speeches with speaker references
  3. persons.csv: Speaker information (name, party, role)
  4. proceedings.csv: Related parliamentary proceedings
  5. speech_topics.csv: Topics associated with each speech

Detailed Files (XML-based)

  1. paragraphs.csv: Individual paragraphs for detailed text analysis
  2. comments.csv: Comments and interjections
  3. agenda_items.csv: Agenda items for each session
  4. toc.csv: Table of contents with document structure

Extraction Quality Metadata

Each extracted speech includes quality metadata fields:

  • extraction_method: The method used to extract the speech text:

    • xml: Extracted from structured XML (highest quality)
    • pattern: Extracted using pattern matching from text
    • page: Extracted from page references only (lower quality)
    • none: No text extraction was possible
  • extraction_status: The status of the extraction:

    • complete: Successfully extracted full text
    • partial: Only partial text was extracted
    • failed: Extraction failed
  • extraction_confidence: A confidence score from 0.0 to 1.0:

    • 1.0: High confidence (XML extraction)
    • 0.6-0.8: Medium confidence (pattern matching)
    • 0.1-0.5: Low confidence (page-based extraction)
    • 0.0: No confidence (extraction failed)

These fields allow researchers to filter speeches based on extraction quality for their analyses.

Data Science Integration

The package includes tools specifically designed for data science workflows:

  • Quality Reports: Comprehensive reports on extraction quality with detailed statistics
  • Interactive Visualizations: Charts and graphs for analyzing extraction quality
  • Pandas Integration: Helper functions for working with extracted data in pandas
  • Jupyter Notebook Example: Example workflow for analyzing extraction data

Each export automatically includes:

  1. HTML Quality Report: Interactive report with visualizations
  2. JSON Quality Data: Machine-readable quality statistics
  3. Quality Visualizations: PNG charts showing extraction distributions
  4. Helper Columns: Boolean fields for easy filtering in pandas

See the examples/data_science_workflow.ipynb notebook for a detailed demonstration of how to work with the data in a research context.

🔑 API Key

The package includes a public API key with limited rate allowance. For extensive usage, register for your own API key from the Bundestag DIP API:

Visit: Dokumentations- und Informationssystems für Parlamentsmaterialien (DIP) API Documentation

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Development Setup

  1. Clone the repository:

    git clone https://github.com/maxboettinger/bundestag-protocol-extractor.git
    cd bundestag-protocol-extractor
    
  2. Create a conda environment:

    conda env create -f environment.yml
    conda activate bundestag-protocol-extractor
    
  3. Install the package in development mode:

    pip install -e ".[dev]"
    
  4. Run tests:

    pytest
    

Making a Release

The package includes a comprehensive release script that verifies package integrity:

python scripts/release.py [major|minor|patch]

The release process:

  1. Runs all tests including import verification
  2. Builds distribution packages
  3. Verifies the built package in a virtual environment
  4. Ensures critical modules like utils.logging are included
  5. Uploads to PyPI (with confirmation)

📄 License

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

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