miracle-sdk 0.1.0

The Official Python SDK for the MIRACLE API - Cardiovascular MRI Reference Values

MIRACLE SDK 🫀

The Official Python SDK for the MIRACLE API

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MIRACLE: MR Imaging Reference API for Cardiovascular Limits from Evidence

The MIRACLE SDK provides a simple, typed, and high-performance Python interface to access standardized cardiovascular MRI reference values. Built for data scientists and medical researchers who need to process cardiac imaging data at scale.

✨ Features

• 35+ Endpoints: Access all MIRACLE API domains with auto-generated, typed methods.
• Batch Processing: Process hundreds of patients in parallel with MiracleBatch.
• IDE Support: Full autocomplete and type hints for VS Code, PyCharm, and more.
• Battle-Tested: Verified with stress tests (16+ concurrent requests, 100% success rate).

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🚀 Installation

pip install miracle-sdk

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📖 Quick Start

Single Request

from miracle import Miracle

# Initialize the client
client = Miracle()

# Get reference values for a pediatric left ventricle
result = client.pediatric_ventricle_reference_values(
    parameter="LVEDV",
    gender="Male",
    measured=62.5,
    ht_cm=110,
    wt_kg=22
)

print(result)
# {'inputs': {...}, 'results': {'calc_z': 0.5, 'calc_percentile': 69.1, ...}}

Batch Processing

Process an entire CSV of patients with multi-threaded parallelism.

Input CSV (patients.csv):

patient_id,gender,height_cm,weight_kg,lv_volume,param_type
001,Male,120,30,75,LVEDV
002,Female,110,25,60,LVEDV

Code:

from miracle import MiracleBatch

# Initialize the batch processor
processor = MiracleBatch(max_workers=10)

# Define how your CSV columns map to API parameters
mapping = {
    "gender": "gender",
    "ht_cm": "height_cm",
    "wt_kg": "weight_kg",
    "measured": "lv_volume",
    "parameter": "param_type"
}

# Process the CSV
df_results = processor.process_csv(
    file_path="patients.csv",
    domain="Pediatric_Ventricle",
    mapping=mapping
)

# Save the enriched data
df_results.to_csv("patients_with_zscores.csv", index=False)

[!TIP] Performance: In stress tests, the SDK processed 16 concurrent requests in ~7.5 seconds with a 100% success rate.

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🗺️ Parameter Mapping Guide

The mapping dictionary connects your CSV column names to the API parameter names.

mapping = {
    "API_PARAMETER": "YOUR_CSV_COLUMN",
    "ht_cm": "Patient_Height",  # Example
}

How to Find API Parameters

1. Online Docs: Visit miracleapi.readme.io and check the "Query Parameters" for your endpoint.
2. Python Help: Use the built-in docstrings:

   help(client.lv_reference_values)
   

Common Parameters

Parameter	Type	Description
gender	str	"Male" or "Female"
age	float	Patient age in years
ht_cm	float	Height in centimeters
wt_kg	float	Weight in kilograms
measured	float	The measured value (e.g., volume, diameter)
parameter	str	The measurement type (e.g., "LVEDV", "LVEF")

[!IMPORTANT] The parameter field is required for most domains.

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🏗️ Architecture

This SDK is auto-generated from the official OpenAPI specifications. This guarantees:

• Consistency: Python methods always match the live API.
• Type Safety: Full autocomplete and type hints.
• Reliability: API changes are automatically reflected in the SDK.

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🤝 Contributing

Contributions are welcome! Please see the main MIRACLE-API repository for the source of truth.

Development Setup:

git clone https://github.com/drankush/MIRACLE-sdk.git
cd MIRACLE-sdk
pip install -e .[dev]

Regenerate the client from OpenAPI specs:

python scripts/generate.py

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📖 Citation

If you use this SDK in your research, please cite:

MIRACLE: MR Imaging Reference API for Cardiovascular Limits from Evidence Authors: Ankush et al. Journal of Cardiovascular Magnetic Resonance (2026)

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📄 License

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

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Made with ❤️ for the Cardiac Imaging Research Community