# IDTAP Python API
[](https://badge.fury.io/py/idtap-api)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
Python client library for **IDTAP** (Interactive Digital Transcription and Analysis Platform) - a web-based research platform developed at UC Santa Cruz for transcribing, analyzing, and archiving Hindustani (North Indian classical) music recordings using trajectory-based notation designed specifically for oral melodic traditions.
## About IDTAP
IDTAP represents a paradigm shift in musical transcription and analysis. Rather than forcing oral traditions into Western notational frameworks, it uses **trajectories** as the fundamental musical unit—archetypal paths between pitches that capture the continuous melodic movement central to Hindustani music.
**Key Innovation**: Instead of discrete notes, IDTAP models music through:
- **Trajectory-based notation** - Continuous pitch contours rather than fixed notes
- **Microtonal precision** - Cent-based tuning with flexible raga systems
- **Idiomatic articulations** - Performance techniques specific to each instrument
- **Hierarchical segmentation** - Phrases, sections, and formal structures
## Features
- **Trajectory-Based Data Access** - Load and analyze transcriptions using the trajectory notation system
- **Hindustani Music Analysis** - Work with raga-aware transcriptions and microtonal pitch data
- **Audio Download** - Retrieve associated audio recordings in multiple formats
- **Secure Authentication** - OAuth integration with encrypted token storage
## Installation
```bash
pip install idtap-api
```
### Optional Dependencies
For enhanced Linux keyring support:
```bash
pip install idtap-api[linux]
```
For development:
```bash
pip install idtap-api[dev]
```
## Quick Start
### Authentication & Basic Usage
```python
from idtap_api import SwaraClient, Piece, Instrument
# Initialize client - connects to swara.studio platform
client = SwaraClient() # Automatic OAuth via Google
# Browse available transcriptions
transcriptions = client.get_viewable_transcriptions()
print(f"Found {len(transcriptions)} transcriptions")
# Load a Hindustani music transcription
piece_data = client.get_piece("transcription-id")
piece = Piece.from_json(piece_data)
print(f"Transcription: {piece.title}")
print(f"Raga: {piece.raga.name if piece.raga else 'Unknown'}")
print(f"Instrument: {piece.instrumentation}")
print(f"Trajectories: {sum(len(p.trajectories) for p in piece.phrases)}")
```
### Working with Trajectory-Based Transcriptions
```python
# Analyze trajectory-based musical structure
for phrase in piece.phrases:
print(f"Phrase {phrase.phrase_number}: {len(phrase.trajectories)} trajectories")
# Examine individual trajectories (fundamental units of IDTAP)
for traj in phrase.trajectories:
if traj.pitch_array:
# Each trajectory contains continuous pitch movement
start_pitch = traj.pitch_array[0].pitch_number
end_pitch = traj.pitch_array[-1].pitch_number
print(f" Trajectory {traj.traj_number}: {start_pitch:.2f} → {end_pitch:.2f}")
# Check for articulations (performance techniques)
if traj.articulation:
techniques = [art.stroke for art in traj.articulation if art.stroke]
print(f" Articulations: {', '.join(techniques)}")
# Raga analysis (theoretical framework)
if piece.raga:
print(f"Raga: {piece.raga.name}")
if hasattr(piece.raga, 'aroha') and piece.raga.aroha:
print(f"Aroha (ascending): {piece.raga.aroha}")
if hasattr(piece.raga, 'avaroha') and piece.raga.avaroha:
print(f"Avaroha (descending): {piece.raga.avaroha}")
```
### Audio Handling
```python
# Download audio in different formats
audio_bytes = client.download_audio("audio-id", format="wav")
with open("recording.wav", "wb") as f:
f.write(audio_bytes)
# Download all audio associated with a transcription
client.download_and_save_transcription_audio(piece, directory="./audio/")
```
### Data Export
```python
# Export transcription data
excel_data = client.excel_data(piece_id)
with open("analysis.xlsx", "wb") as f:
f.write(excel_data)
json_data = client.json_data(piece_id)
with open("transcription.json", "wb") as f:
f.write(json_data)
```
### Working with Hindustani Music Data
```python
from idtap_api import Piece, Phrase, Trajectory, Pitch, Raga, Instrument
# Example: Analyze a sitar transcription
sitar_pieces = [t for t in transcriptions if t.get('instrumentation') == 'Sitar']
for trans_meta in sitar_pieces[:3]: # First 3 sitar pieces
piece = Piece.from_json(client.get_piece(trans_meta['_id']))
# Count different types of trajectories (IDTAP's innovation)
trajectory_types = {}
for phrase in piece.phrases:
for traj in phrase.trajectories:
traj_type = getattr(traj, 'curve_type', 'straight')
trajectory_types[traj_type] = trajectory_types.get(traj_type, 0) + 1
print(f"{piece.title}:")
print(f" Raga: {piece.raga.name if piece.raga else 'Unknown'}")
print(f" Trajectory types: {trajectory_types}")
# Analyze articulation patterns (performance techniques)
articulations = []
for phrase in piece.phrases:
for traj in phrase.trajectories:
if traj.articulation:
articulations.extend([art.stroke for art in traj.articulation])
unique_arts = list(set(articulations))
print(f" Articulations used: {', '.join(unique_arts[:5])}") # First 5
```
## Key Classes
### SwaraClient
The main HTTP client for interacting with the IDTAP server.
**Key Methods:**
- `get_viewable_transcriptions()` - List accessible transcriptions
- `get_piece(id)` - Load transcription data
- `save_piece(data)` - Save transcription
- `excel_data(id)` / `json_data(id)` - Export data
- `download_audio(id, format)` - Download audio files
- `get_waiver_text()` - Display the research waiver text that must be read
- `agree_to_waiver(i_agree=True)` - Accept research waiver (required for first-time users)
- `has_agreed_to_waiver()` - Check if waiver has been accepted
### Musical Data Models
- **`Piece`** - Central transcription container with metadata, audio association, and musical content
- **`Phrase`** - Musical phrase containing trajectory data and categorizations
- **`Trajectory`** - Detailed pitch movement data with timing and articulations
- **`Pitch`** - Individual pitch points with frequency and timing information
- **`Raga`** - Indian musical scale/mode definitions with theoretical rules
- **`Section`** - Large structural divisions (alap, composition, etc.)
- **`Meter`** - Rhythmic cycle and tempo information
- **`Articulation`** - Performance technique annotations (meend, andolan, etc.)
### Specialized Features
- **Microtonal Pitch System** - Precise cent-based pitch representation
- **Hindustani Music Theory** - Raga rules, sargam notation, gharana traditions
- **Performance Analysis** - Ornament detection, phrase categorization
- **Multi-Track Support** - Simultaneous transcription of melody and drone
## Authentication
The client uses OAuth 2.0 flow with Google authentication. On first use, it will:
1. Open a browser for Google OAuth login
2. Securely store the authentication token using:
- OS keyring (preferred)
- Encrypted local file (fallback)
- Plain text (legacy, discouraged)
### Research Waiver Requirement
**First-time users must agree to a research waiver** before accessing transcription data. If you haven't agreed yet, you'll see an error when trying to access transcriptions:
```python
client = SwaraClient()
transcriptions = client.get_viewable_transcriptions() # Will raise RuntimeError
# First, read the waiver text
waiver_text = client.get_waiver_text()
print("Research Waiver:")
print(waiver_text)
# After reading, agree to the waiver
client.agree_to_waiver(i_agree=True)
transcriptions = client.get_viewable_transcriptions() # Now works
# Check waiver status
if client.has_agreed_to_waiver():
print("Waiver agreed - full access available")
```
### Manual Token Management
```python
# Initialize without auto-login
client = SwaraClient(auto_login=False)
# Login manually when needed
from idtap_api import login_google
login_google()
```
## Advanced Usage
### Batch Processing
```python
# Process multiple transcriptions
transcriptions = client.get_viewable_transcriptions()
for trans in transcriptions:
if trans.get('instrumentation') == 'Sitar':
piece = Piece.from_json(client.get_piece(trans['_id']))
# Analyze sitar-specific features
total_meends = sum(
len([art for art in traj.articulation if art.stroke == 'meend'])
for phrase in piece.phrases
for traj in phrase.trajectories
)
print(f"{piece.title}: {total_meends} meends")
```
### Research Applications
```python
# Raga analysis across corpus
raga_stats = {}
for trans in transcriptions:
piece = Piece.from_json(client.get_piece(trans['_id']))
if piece.raga:
raga_name = piece.raga.name
raga_stats[raga_name] = raga_stats.get(raga_name, 0) + 1
print("Raga distribution:", raga_stats)
```
## Development
### Running Tests
```bash
# Unit tests
pytest idtap_api/tests/
# Integration tests (requires authentication)
python api_testing/api_test.py
```
### Contributing
1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Ensure all tests pass
5. Submit a pull request
## Documentation
- **API Reference**: Full documentation of all classes and methods
- **Musical Concepts**: Guide to Hindustani music terminology and theory
- **Research Examples**: Academic use cases and analysis workflows
## Platform Access
- **IDTAP Web Platform**: [swara.studio](https://swara.studio)
- **Source Code**: [github.com/jon-myers/idtap](https://github.com/jon-myers/idtap)
- **Research Paper**: "Beyond Notation: A Digital Platform for Transcribing and Analyzing Oral Melodic Traditions" (ISMIR 2025)
## Support
- **GitHub Issues**: [Report bugs and request features](https://github.com/jon-myers/idtap/issues)
- **Research Contact**: Jonathan Myers & Dard Neuman, UC Santa Cruz
- **Platform**: [swara.studio](https://swara.studio)
## License
MIT License - see LICENSE file for details.
## Citation
If you use IDTAP in academic research, please cite the ISMIR 2025 paper:
```bibtex
@inproceedings{myers2025beyond,
title={Beyond Notation: A Digital Platform for Transcribing and Analyzing Oral Melodic Traditions},
author={Myers, Jonathan and Neuman, Dard},
booktitle={Proceedings of the 26th International Society for Music Information Retrieval Conference},
pages={},
year={2025},
address={Daejeon, South Korea},
url={https://swara.studio}
}
```
---
**IDTAP** was developed at UC Santa Cruz with support from the National Endowment for the Humanities. The platform challenges Western-centric approaches to music representation by creating tools designed specifically for oral melodic traditions, enabling scholars to study Hindustani music on its own terms while applying cutting-edge computational methodologies.
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"description": "# IDTAP Python API\n\n[](https://badge.fury.io/py/idtap-api)\n[](https://www.python.org/downloads/)\n[](https://opensource.org/licenses/MIT)\n\nPython client library for **IDTAP** (Interactive Digital Transcription and Analysis Platform) - a web-based research platform developed at UC Santa Cruz for transcribing, analyzing, and archiving Hindustani (North Indian classical) music recordings using trajectory-based notation designed specifically for oral melodic traditions.\n\n## About IDTAP\n\nIDTAP represents a paradigm shift in musical transcription and analysis. Rather than forcing oral traditions into Western notational frameworks, it uses **trajectories** as the fundamental musical unit\u2014archetypal paths between pitches that capture the continuous melodic movement central to Hindustani music.\n\n**Key Innovation**: Instead of discrete notes, IDTAP models music through:\n- **Trajectory-based notation** - Continuous pitch contours rather than fixed notes\n- **Microtonal precision** - Cent-based tuning with flexible raga systems \n- **Idiomatic articulations** - Performance techniques specific to each instrument\n- **Hierarchical segmentation** - Phrases, sections, and formal structures\n\n## Features\n\n- **Trajectory-Based Data Access** - Load and analyze transcriptions using the trajectory notation system\n- **Hindustani Music Analysis** - Work with raga-aware transcriptions and microtonal pitch data\n- **Audio Download** - Retrieve associated audio recordings in multiple formats\n- **Secure Authentication** - OAuth integration with encrypted token storage\n\n## Installation\n\n```bash\npip install idtap-api\n```\n\n### Optional Dependencies\n\nFor enhanced Linux keyring support:\n```bash\npip install idtap-api[linux]\n```\n\nFor development:\n```bash\npip install idtap-api[dev]\n```\n\n## Quick Start\n\n### Authentication & Basic Usage\n\n```python\nfrom idtap_api import SwaraClient, Piece, Instrument\n\n# Initialize client - connects to swara.studio platform\nclient = SwaraClient() # Automatic OAuth via Google\n\n# Browse available transcriptions\ntranscriptions = client.get_viewable_transcriptions()\nprint(f\"Found {len(transcriptions)} transcriptions\")\n\n# Load a Hindustani music transcription\npiece_data = client.get_piece(\"transcription-id\")\npiece = Piece.from_json(piece_data)\n\nprint(f\"Transcription: {piece.title}\")\nprint(f\"Raga: {piece.raga.name if piece.raga else 'Unknown'}\")\nprint(f\"Instrument: {piece.instrumentation}\")\nprint(f\"Trajectories: {sum(len(p.trajectories) for p in piece.phrases)}\")\n```\n\n### Working with Trajectory-Based Transcriptions\n\n```python\n# Analyze trajectory-based musical structure\nfor phrase in piece.phrases:\n print(f\"Phrase {phrase.phrase_number}: {len(phrase.trajectories)} trajectories\")\n \n # Examine individual trajectories (fundamental units of IDTAP)\n for traj in phrase.trajectories:\n if traj.pitch_array:\n # Each trajectory contains continuous pitch movement\n start_pitch = traj.pitch_array[0].pitch_number\n end_pitch = traj.pitch_array[-1].pitch_number\n print(f\" Trajectory {traj.traj_number}: {start_pitch:.2f} \u2192 {end_pitch:.2f}\")\n \n # Check for articulations (performance techniques)\n if traj.articulation:\n techniques = [art.stroke for art in traj.articulation if art.stroke]\n print(f\" Articulations: {', '.join(techniques)}\")\n\n# Raga analysis (theoretical framework)\nif piece.raga:\n print(f\"Raga: {piece.raga.name}\")\n if hasattr(piece.raga, 'aroha') and piece.raga.aroha:\n print(f\"Aroha (ascending): {piece.raga.aroha}\")\n if hasattr(piece.raga, 'avaroha') and piece.raga.avaroha: \n print(f\"Avaroha (descending): {piece.raga.avaroha}\")\n```\n\n### Audio Handling\n\n```python\n# Download audio in different formats\naudio_bytes = client.download_audio(\"audio-id\", format=\"wav\")\nwith open(\"recording.wav\", \"wb\") as f:\n f.write(audio_bytes)\n\n# Download all audio associated with a transcription\nclient.download_and_save_transcription_audio(piece, directory=\"./audio/\")\n```\n\n### Data Export\n\n```python\n# Export transcription data\nexcel_data = client.excel_data(piece_id)\nwith open(\"analysis.xlsx\", \"wb\") as f:\n f.write(excel_data)\n\njson_data = client.json_data(piece_id)\nwith open(\"transcription.json\", \"wb\") as f:\n f.write(json_data)\n```\n\n### Working with Hindustani Music Data\n\n```python\nfrom idtap_api import Piece, Phrase, Trajectory, Pitch, Raga, Instrument\n\n# Example: Analyze a sitar transcription\nsitar_pieces = [t for t in transcriptions if t.get('instrumentation') == 'Sitar']\n\nfor trans_meta in sitar_pieces[:3]: # First 3 sitar pieces\n piece = Piece.from_json(client.get_piece(trans_meta['_id']))\n \n # Count different types of trajectories (IDTAP's innovation)\n trajectory_types = {}\n for phrase in piece.phrases:\n for traj in phrase.trajectories:\n traj_type = getattr(traj, 'curve_type', 'straight')\n trajectory_types[traj_type] = trajectory_types.get(traj_type, 0) + 1\n \n print(f\"{piece.title}:\")\n print(f\" Raga: {piece.raga.name if piece.raga else 'Unknown'}\")\n print(f\" Trajectory types: {trajectory_types}\")\n \n # Analyze articulation patterns (performance techniques) \n articulations = []\n for phrase in piece.phrases:\n for traj in phrase.trajectories:\n if traj.articulation:\n articulations.extend([art.stroke for art in traj.articulation])\n \n unique_arts = list(set(articulations))\n print(f\" Articulations used: {', '.join(unique_arts[:5])}\") # First 5\n```\n\n## Key Classes\n\n### SwaraClient\nThe main HTTP client for interacting with the IDTAP server.\n\n**Key Methods:**\n- `get_viewable_transcriptions()` - List accessible transcriptions\n- `get_piece(id)` - Load transcription data\n- `save_piece(data)` - Save transcription\n- `excel_data(id)` / `json_data(id)` - Export data\n- `download_audio(id, format)` - Download audio files\n- `get_waiver_text()` - Display the research waiver text that must be read\n- `agree_to_waiver(i_agree=True)` - Accept research waiver (required for first-time users)\n- `has_agreed_to_waiver()` - Check if waiver has been accepted\n\n### Musical Data Models\n\n- **`Piece`** - Central transcription container with metadata, audio association, and musical content\n- **`Phrase`** - Musical phrase containing trajectory data and categorizations\n- **`Trajectory`** - Detailed pitch movement data with timing and articulations\n- **`Pitch`** - Individual pitch points with frequency and timing information\n- **`Raga`** - Indian musical scale/mode definitions with theoretical rules\n- **`Section`** - Large structural divisions (alap, composition, etc.)\n- **`Meter`** - Rhythmic cycle and tempo information\n- **`Articulation`** - Performance technique annotations (meend, andolan, etc.)\n\n### Specialized Features\n\n- **Microtonal Pitch System** - Precise cent-based pitch representation\n- **Hindustani Music Theory** - Raga rules, sargam notation, gharana traditions\n- **Performance Analysis** - Ornament detection, phrase categorization\n- **Multi-Track Support** - Simultaneous transcription of melody and drone\n\n## Authentication\n\nThe client uses OAuth 2.0 flow with Google authentication. On first use, it will:\n\n1. Open a browser for Google OAuth login\n2. Securely store the authentication token using:\n - OS keyring (preferred)\n - Encrypted local file (fallback)\n - Plain text (legacy, discouraged)\n\n### Research Waiver Requirement\n\n**First-time users must agree to a research waiver** before accessing transcription data. If you haven't agreed yet, you'll see an error when trying to access transcriptions:\n\n```python\nclient = SwaraClient()\ntranscriptions = client.get_viewable_transcriptions() # Will raise RuntimeError\n\n# First, read the waiver text\nwaiver_text = client.get_waiver_text()\nprint(\"Research Waiver:\")\nprint(waiver_text)\n\n# After reading, agree to the waiver\nclient.agree_to_waiver(i_agree=True)\ntranscriptions = client.get_viewable_transcriptions() # Now works\n\n# Check waiver status\nif client.has_agreed_to_waiver():\n print(\"Waiver agreed - full access available\")\n```\n\n### Manual Token Management\n\n```python\n# Initialize without auto-login\nclient = SwaraClient(auto_login=False)\n\n# Login manually when needed\nfrom idtap_api import login_google\nlogin_google()\n```\n\n## Advanced Usage\n\n### Batch Processing\n\n```python\n# Process multiple transcriptions\ntranscriptions = client.get_viewable_transcriptions()\n\nfor trans in transcriptions:\n if trans.get('instrumentation') == 'Sitar':\n piece = Piece.from_json(client.get_piece(trans['_id']))\n \n # Analyze sitar-specific features\n total_meends = sum(\n len([art for art in traj.articulation if art.stroke == 'meend'])\n for phrase in piece.phrases\n for traj in phrase.trajectories\n )\n print(f\"{piece.title}: {total_meends} meends\")\n```\n\n### Research Applications\n\n```python\n# Raga analysis across corpus\nraga_stats = {}\nfor trans in transcriptions:\n piece = Piece.from_json(client.get_piece(trans['_id']))\n if piece.raga:\n raga_name = piece.raga.name\n raga_stats[raga_name] = raga_stats.get(raga_name, 0) + 1\n\nprint(\"Raga distribution:\", raga_stats)\n```\n\n## Development\n\n### Running Tests\n\n```bash\n# Unit tests\npytest idtap_api/tests/\n\n# Integration tests (requires authentication)\npython api_testing/api_test.py\n```\n\n### Contributing\n\n1. Fork the repository\n2. Create a feature branch\n3. Add tests for new functionality\n4. Ensure all tests pass\n5. Submit a pull request\n\n## Documentation\n\n- **API Reference**: Full documentation of all classes and methods\n- **Musical Concepts**: Guide to Hindustani music terminology and theory\n- **Research Examples**: Academic use cases and analysis workflows\n\n## Platform Access\n\n- **IDTAP Web Platform**: [swara.studio](https://swara.studio)\n- **Source Code**: [github.com/jon-myers/idtap](https://github.com/jon-myers/idtap)\n- **Research Paper**: \"Beyond Notation: A Digital Platform for Transcribing and Analyzing Oral Melodic Traditions\" (ISMIR 2025)\n\n## Support\n\n- **GitHub Issues**: [Report bugs and request features](https://github.com/jon-myers/idtap/issues)\n- **Research Contact**: Jonathan Myers & Dard Neuman, UC Santa Cruz\n- **Platform**: [swara.studio](https://swara.studio)\n\n## License\n\nMIT License - see LICENSE file for details.\n\n## Citation\n\nIf you use IDTAP in academic research, please cite the ISMIR 2025 paper:\n\n```bibtex\n@inproceedings{myers2025beyond,\n title={Beyond Notation: A Digital Platform for Transcribing and Analyzing Oral Melodic Traditions},\n author={Myers, Jonathan and Neuman, Dard},\n booktitle={Proceedings of the 26th International Society for Music Information Retrieval Conference},\n pages={},\n year={2025},\n address={Daejeon, South Korea},\n url={https://swara.studio}\n}\n```\n\n---\n\n**IDTAP** was developed at UC Santa Cruz with support from the National Endowment for the Humanities. The platform challenges Western-centric approaches to music representation by creating tools designed specifically for oral melodic traditions, enabling scholars to study Hindustani music on its own terms while applying cutting-edge computational methodologies.\n",
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]
},
{
"name": "pyhumps",
"specs": [
[
">=",
"3.8.0"
]
]
},
{
"name": "keyring",
"specs": [
[
">=",
"24.0.0"
]
]
},
{
"name": "cryptography",
"specs": [
[
">=",
"41.0.0"
]
]
},
{
"name": "PyJWT",
"specs": [
[
">=",
"2.8.0"
]
]
},
{
"name": "secretstorage",
"specs": [
[
">=",
"3.3.0"
]
]
}
],
"lcname": "idtap-api"
}
JSON
