# FHIR for Data Science (FHIR4DS)
Production-ready healthcare analytics platform providing 100% SQL-on-FHIR v2.0 compliance with dual database support (DuckDB + PostgreSQL).
**Current Version**: 0.5.0 (Complete FHIRPath Specification Implementation)
**Test Compliance**: 100% (117/117 tests passing)
**Database Support**: DuckDB 100% + PostgreSQL 100%
**User Experience**: One-line setup, multi-format export, batch processing
## Key Features
- **100% SQL-on-FHIR v2.0 compliance** - All 117 official tests passing
- **Dual database support** - DuckDB and PostgreSQL with identical functionality
- **Advanced FHIRPath parsing** - Complete parser with 187 choice type mappings
- **CTE-based SQL generation** - 95% reduction in SQL complexity
- **Parallel processing** - High-performance data loading and query execution
- **Multi-format export** - Pandas, JSON, CSV, Excel, Parquet
- **Database object creation** - Views, tables, schemas from ViewDefinitions
## Quick Start
### Installation
```bash
pip install fhir4ds
```
### Database Setup
```python
from fhir4ds.datastore import QuickConnect
# DuckDB (recommended for analytics)
db = QuickConnect.duckdb("./healthcare_data.db")
# PostgreSQL (enterprise-grade)
db = QuickConnect.postgresql("postgresql://user:pass@host:5432/db")
# Auto-detect from connection string
db = QuickConnect.auto("./local.db") # → DuckDB
```
### Load Data
```python
# Load FHIR resources with parallel processing
db.load_resources(fhir_resources, parallel=True)
# Load from JSON files (optimized for large files)
db.load_from_json_file("fhir_bundle.json", use_native_json=True)
```
### Execute Queries and Export
```python
# Execute ViewDefinitions with immediate export
df = db.execute_to_dataframe(view_definition)
db.execute_to_excel([query1, query2], "report.xlsx", parallel=True)
db.execute_to_parquet(analytics_query, "dataset.parquet")
# Batch processing with progress monitoring
results = db.execute_batch(queries, parallel=True, show_progress=True)
```
### Create Database Objects
```python
# Create analytics infrastructure
db.create_schema("clinical_analytics")
db.create_view(patient_view, "patient_demographics")
db.create_table(observation_view, "vital_signs_table")
# List created objects
tables = db.list_tables()
views = db.list_views()
```
For more details, please see the [documentation](./docs/README.md).
## Testing
Run the comprehensive test suite:
```bash
# Test both DuckDB and PostgreSQL dialects
python tests/run_tests.py --dialect all
# Test specific dialect
python tests/run_tests.py --dialect duckdb
python tests/run_tests.py --dialect postgresql
```
Test results: 117/117 tests passing on both DuckDB and PostgreSQL.
## License
GNU General Public License v3 (GPLv3)
## Related Projects
- [SQL-on-FHIR Specification](https://github.com/FHIR/sql-on-fhir-v2) - Official specification
- [FHIR R4 Specification](https://hl7.org/fhir/R4/) - FHIR standard
- [DuckDB](https://duckdb.org/) - High-performance analytics database
- [PostgreSQL](https://www.postgresql.org/) - Enterprise-grade relational database
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"description": "# FHIR for Data Science (FHIR4DS)\n\nProduction-ready healthcare analytics platform providing 100% SQL-on-FHIR v2.0 compliance with dual database support (DuckDB + PostgreSQL).\n\n**Current Version**: 0.5.0 (Complete FHIRPath Specification Implementation) \n**Test Compliance**: 100% (117/117 tests passing)\n**Database Support**: DuckDB 100% + PostgreSQL 100% \n**User Experience**: One-line setup, multi-format export, batch processing\n\n## Key Features\n\n- **100% SQL-on-FHIR v2.0 compliance** - All 117 official tests passing\n- **Dual database support** - DuckDB and PostgreSQL with identical functionality\n- **Advanced FHIRPath parsing** - Complete parser with 187 choice type mappings\n- **CTE-based SQL generation** - 95% reduction in SQL complexity\n- **Parallel processing** - High-performance data loading and query execution\n- **Multi-format export** - Pandas, JSON, CSV, Excel, Parquet\n- **Database object creation** - Views, tables, schemas from ViewDefinitions\n\n## Quick Start\n\n### Installation\n```bash\npip install fhir4ds\n```\n\n### Database Setup\n```python\nfrom fhir4ds.datastore import QuickConnect\n\n# DuckDB (recommended for analytics)\ndb = QuickConnect.duckdb(\"./healthcare_data.db\")\n\n# PostgreSQL (enterprise-grade)\ndb = QuickConnect.postgresql(\"postgresql://user:pass@host:5432/db\")\n\n# Auto-detect from connection string\ndb = QuickConnect.auto(\"./local.db\") # \u2192 DuckDB\n```\n\n### Load Data\n```python\n# Load FHIR resources with parallel processing\ndb.load_resources(fhir_resources, parallel=True)\n\n# Load from JSON files (optimized for large files)\ndb.load_from_json_file(\"fhir_bundle.json\", use_native_json=True)\n```\n\n### Execute Queries and Export\n```python\n# Execute ViewDefinitions with immediate export\ndf = db.execute_to_dataframe(view_definition)\ndb.execute_to_excel([query1, query2], \"report.xlsx\", parallel=True)\ndb.execute_to_parquet(analytics_query, \"dataset.parquet\")\n\n# Batch processing with progress monitoring\nresults = db.execute_batch(queries, parallel=True, show_progress=True)\n```\n\n### Create Database Objects\n```python\n# Create analytics infrastructure\ndb.create_schema(\"clinical_analytics\")\ndb.create_view(patient_view, \"patient_demographics\")\ndb.create_table(observation_view, \"vital_signs_table\")\n\n# List created objects\ntables = db.list_tables()\nviews = db.list_views()\n```\n\nFor more details, please see the [documentation](./docs/README.md).\n\n## Testing\n\nRun the comprehensive test suite:\n\n```bash\n# Test both DuckDB and PostgreSQL dialects\npython tests/run_tests.py --dialect all\n\n# Test specific dialect\npython tests/run_tests.py --dialect duckdb\npython tests/run_tests.py --dialect postgresql\n```\n\nTest results: 117/117 tests passing on both DuckDB and PostgreSQL.\n\n## License\n\nGNU General Public License v3 (GPLv3)\n\n## Related Projects\n\n- [SQL-on-FHIR Specification](https://github.com/FHIR/sql-on-fhir-v2) - Official specification\n- [FHIR R4 Specification](https://hl7.org/fhir/R4/) - FHIR standard\n- [DuckDB](https://duckdb.org/) - High-performance analytics database\n- [PostgreSQL](https://www.postgresql.org/) - Enterprise-grade relational database",
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