| Name | ddex-parser JSON |
| Version |
0.4.0
JSON |
| download |
| home_page | None |
| Summary | High-performance DDEX XML parser for Python |
| upload_time | 2025-09-15 01:26:54 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT |
| keywords |
ddex
xml
parser
music
metadata
ern
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
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| Travis-CI |
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| coveralls test coverage |
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# DDEX Parser - Python Bindings
[](https://pypi.org/project/ddex-parser/)
[](https://pypi.org/project/ddex-parser/)
[](https://pypi.org/project/ddex-parser/)
[](https://opensource.org/licenses/MIT)
High-performance DDEX XML parser for Python with built-in security features and comprehensive metadata extraction. Parse DDEX files 10x faster than traditional XML parsers with full support for all DDEX versions and profiles.
## Installation
```bash
pip install ddex-parser
```
## Security Notice
**v0.4.0 fixes a critical security vulnerability (RUSTSEC-2025-0020).**
All users should upgrade immediately for PyO3 0.24 compatibility and enhanced security.
## Quick Start
```python
from ddex_parser import DDEXParser
import pandas as pd
# Parse DDEX file
parser = DDEXParser()
result = parser.parse_file("release.xml")
# Access parsed data
print(f"Release: {result.release_title}")
print(f"Artist: {result.main_artist}")
print(f"Tracks: {len(result.tracks)}")
# Convert to DataFrame for analysis
tracks_df = result.to_dataframe()
print(tracks_df.head())
```
## Features
### 🚀 High Performance
- **10x faster** than standard XML parsers
- Streaming support for large files (>100MB)
- Memory-efficient processing
- Native Rust implementation with Python bindings
### 🔒 Security Built-in
- XXE (XML External Entity) attack protection
- Entity expansion limits
- Memory-bounded parsing
- Deep nesting protection
### 📊 Data Science Ready
- Direct pandas DataFrame export
- Structured metadata extraction
- JSON serialization support
- Type hints for better IDE experience
### 🎵 Music Industry Focused
- Support for all DDEX versions (3.2, 3.3, 4.0+)
- Release, track, and artist metadata
- Rights and usage information
- Territory and deal terms
- Image and audio resource handling
## API Reference
### DDEXParser
```python
from ddex_parser import DDEXParser
parser = DDEXParser(
max_entity_expansions=1000, # Limit entity expansions for security
max_depth=100, # Maximum XML nesting depth
streaming=True # Enable streaming for large files
)
```
### Parsing Methods
#### `parse_file(path: str) -> DDEXResult`
Parse a DDEX XML file from disk.
```python
result = parser.parse_file("path/to/release.xml")
```
#### `parse_string(xml: str) -> DDEXResult`
Parse DDEX XML from a string.
```python
with open("release.xml", "r") as f:
xml_content = f.read()
result = parser.parse_string(xml_content)
```
#### `parse_async(path: str) -> Awaitable[DDEXResult]`
Asynchronous parsing for non-blocking operations.
```python
import asyncio
async def parse_ddex():
result = await parser.parse_async("release.xml")
return result
# Usage
result = asyncio.run(parse_ddex())
```
## DataFrame Integration
Perfect for data analysis workflows:
```python
import pandas as pd
from ddex_parser import DDEXParser
parser = DDEXParser()
result = parser.parse_file("catalog.xml")
# Get tracks as DataFrame
tracks_df = result.to_dataframe("tracks")
print(tracks_df.columns)
# ['track_id', 'title', 'artist', 'duration', 'isrc', 'genre', ...]
# Analyze your catalog
genre_counts = tracks_df['genre'].value_counts()
avg_duration = tracks_df['duration'].mean()
# Export for further analysis
tracks_df.to_csv("catalog_analysis.csv")
tracks_df.to_parquet("catalog_analysis.parquet")
```
## Performance Benchmarks
Performance comparison on a MacBook Pro M2:
| File Size | ddex-parser | lxml | xml.etree | Speedup |
|-----------|-------------|------|-----------|----------|
| 10KB | 0.8ms | 8ms | 12ms | 10x-15x |
| 100KB | 3ms | 45ms | 78ms | 15x-26x |
| 1MB | 28ms | 380ms| 650ms | 13x-23x |
| 10MB | 180ms | 3.2s | 5.8s | 18x-32x |
Memory usage is consistently 60-80% lower than traditional parsers.
## Integration with ddex-builder
Round-trip compatibility with ddex-builder for complete workflows:
```python
from ddex_parser import DDEXParser
from ddex_builder import DDEXBuilder
# Parse existing DDEX file
parser = DDEXParser()
original = parser.parse_file("input.xml")
# Modify data
modified_data = original.to_dict()
modified_data['tracks'][0]['title'] = "New Title"
# Build new DDEX file
builder = DDEXBuilder()
new_xml = builder.build_from_dict(modified_data)
# Verify round-trip integrity
new_result = parser.parse_string(new_xml)
assert new_result.tracks[0].title == "New Title"
```
## Requirements
- Python 3.8+
- pandas (optional, for DataFrame support)
- PyO3 0.24 compatible runtime
## License
This project is licensed under the MIT License - see the [LICENSE](https://github.com/daddykev/ddex-suite/blob/main/LICENSE) file for details.
## Related Projects
- **[ddex-builder](https://pypi.org/project/ddex-builder/)** - Build deterministic DDEX XML files
- **[ddex-parser (npm)](https://www.npmjs.com/package/ddex-parser)** - JavaScript/TypeScript bindings
- **[DDEX Suite](https://ddex-suite.org)** - Complete DDEX processing toolkit
---
Built for the music industry. Powered by Rust for maximum performance and safety.
Raw data
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"description": "# DDEX Parser - Python Bindings\n\n[](https://pypi.org/project/ddex-parser/)\n[](https://pypi.org/project/ddex-parser/)\n[](https://pypi.org/project/ddex-parser/)\n[](https://opensource.org/licenses/MIT)\n\nHigh-performance DDEX XML parser for Python with built-in security features and comprehensive metadata extraction. Parse DDEX files 10x faster than traditional XML parsers with full support for all DDEX versions and profiles.\n\n## Installation\n\n```bash\npip install ddex-parser\n```\n\n## Security Notice\n**v0.4.0 fixes a critical security vulnerability (RUSTSEC-2025-0020).** \nAll users should upgrade immediately for PyO3 0.24 compatibility and enhanced security.\n\n## Quick Start\n\n```python\nfrom ddex_parser import DDEXParser\nimport pandas as pd\n\n# Parse DDEX file\nparser = DDEXParser()\nresult = parser.parse_file(\"release.xml\")\n\n# Access parsed data\nprint(f\"Release: {result.release_title}\")\nprint(f\"Artist: {result.main_artist}\")\nprint(f\"Tracks: {len(result.tracks)}\")\n\n# Convert to DataFrame for analysis\ntracks_df = result.to_dataframe()\nprint(tracks_df.head())\n```\n\n## Features\n\n### \ud83d\ude80 High Performance\n- **10x faster** than standard XML parsers\n- Streaming support for large files (>100MB)\n- Memory-efficient processing\n- Native Rust implementation with Python bindings\n\n### \ud83d\udd12 Security Built-in\n- XXE (XML External Entity) attack protection\n- Entity expansion limits\n- Memory-bounded parsing\n- Deep nesting protection\n\n### \ud83d\udcca Data Science Ready\n- Direct pandas DataFrame export\n- Structured metadata extraction\n- JSON serialization support\n- Type hints for better IDE experience\n\n### \ud83c\udfb5 Music Industry Focused\n- Support for all DDEX versions (3.2, 3.3, 4.0+)\n- Release, track, and artist metadata\n- Rights and usage information\n- Territory and deal terms\n- Image and audio resource handling\n\n## API Reference\n\n### DDEXParser\n\n```python\nfrom ddex_parser import DDEXParser\n\nparser = DDEXParser(\n max_entity_expansions=1000, # Limit entity expansions for security\n max_depth=100, # Maximum XML nesting depth\n streaming=True # Enable streaming for large files\n)\n```\n\n### Parsing Methods\n\n#### `parse_file(path: str) -> DDEXResult`\n\nParse a DDEX XML file from disk.\n\n```python\nresult = parser.parse_file(\"path/to/release.xml\")\n```\n\n#### `parse_string(xml: str) -> DDEXResult`\n\nParse DDEX XML from a string.\n\n```python\nwith open(\"release.xml\", \"r\") as f:\n xml_content = f.read()\nresult = parser.parse_string(xml_content)\n```\n\n#### `parse_async(path: str) -> Awaitable[DDEXResult]`\n\nAsynchronous parsing for non-blocking operations.\n\n```python\nimport asyncio\n\nasync def parse_ddex():\n result = await parser.parse_async(\"release.xml\")\n return result\n\n# Usage\nresult = asyncio.run(parse_ddex())\n```\n\n## DataFrame Integration\n\nPerfect for data analysis workflows:\n\n```python\nimport pandas as pd\nfrom ddex_parser import DDEXParser\n\nparser = DDEXParser()\nresult = parser.parse_file(\"catalog.xml\")\n\n# Get tracks as DataFrame\ntracks_df = result.to_dataframe(\"tracks\")\nprint(tracks_df.columns)\n# ['track_id', 'title', 'artist', 'duration', 'isrc', 'genre', ...]\n\n# Analyze your catalog\ngenre_counts = tracks_df['genre'].value_counts()\navg_duration = tracks_df['duration'].mean()\n\n# Export for further analysis\ntracks_df.to_csv(\"catalog_analysis.csv\")\ntracks_df.to_parquet(\"catalog_analysis.parquet\")\n```\n\n## Performance Benchmarks\n\nPerformance comparison on a MacBook Pro M2:\n\n| File Size | ddex-parser | lxml | xml.etree | Speedup |\n|-----------|-------------|------|-----------|----------|\n| 10KB | 0.8ms | 8ms | 12ms | 10x-15x |\n| 100KB | 3ms | 45ms | 78ms | 15x-26x |\n| 1MB | 28ms | 380ms| 650ms | 13x-23x |\n| 10MB | 180ms | 3.2s | 5.8s | 18x-32x |\n\nMemory usage is consistently 60-80% lower than traditional parsers.\n\n## Integration with ddex-builder\n\nRound-trip compatibility with ddex-builder for complete workflows:\n\n```python\nfrom ddex_parser import DDEXParser\nfrom ddex_builder import DDEXBuilder\n\n# Parse existing DDEX file\nparser = DDEXParser()\noriginal = parser.parse_file(\"input.xml\")\n\n# Modify data\nmodified_data = original.to_dict()\nmodified_data['tracks'][0]['title'] = \"New Title\"\n\n# Build new DDEX file\nbuilder = DDEXBuilder()\nnew_xml = builder.build_from_dict(modified_data)\n\n# Verify round-trip integrity\nnew_result = parser.parse_string(new_xml)\nassert new_result.tracks[0].title == \"New Title\"\n```\n\n## Requirements\n- Python 3.8+\n- pandas (optional, for DataFrame support)\n- PyO3 0.24 compatible runtime\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](https://github.com/daddykev/ddex-suite/blob/main/LICENSE) file for details.\n\n## Related Projects\n\n- **[ddex-builder](https://pypi.org/project/ddex-builder/)** - Build deterministic DDEX XML files\n- **[ddex-parser (npm)](https://www.npmjs.com/package/ddex-parser)** - JavaScript/TypeScript bindings\n- **[DDEX Suite](https://ddex-suite.org)** - Complete DDEX processing toolkit\n\n---\n\nBuilt for the music industry. Powered by Rust for maximum performance and safety.\n",
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