fhirpathrs
A high-performance FHIRPath engine written in Rust with Python bindings.
FHIRPath is a path-based navigation and extraction language for FHIR (Fast Healthcare Interoperability Resources) data, widely used in healthcare systems for querying clinical data, validating resources, and implementing decision support logic.
Key Features
- Fast — Rust-powered parser and interpreter, 10-600x faster than pure-Python alternatives
- Safe — Fully iterative evaluation (no call-stack recursion)
- Complete — 100+ FHIRPath functions including collections, math, strings, dates, types, and higher-order functions
- Python-native — Install with pip, pass dicts and lists, get dicts and lists back
Installation
pip install fhirpathrs
Build from source
# Rust toolchain required
pip install maturin
maturin develop --release --manifest-path crates/python/Cargo.toml
Quick Start
from fhirpathrs import evaluate
patient = {
"resourceType": "Patient",
"id": "pat-42",
"active": True,
"name": [
{"family": "Jetson", "given": ["George", "Astro"]},
{"family": "Jetson-Spacely", "given": ["Elroy"]},
],
"address": [
{"city": "Orbit City", "state": "Space"}
],
}
# Navigate fields
evaluate("name.family", patient)
# → ["Jetson", "Jetson-Spacely"]
# Filter collections
evaluate("name.where(family = 'Jetson').given", patient)
# → ["George", "Astro"]
# Boolean logic
evaluate("name.exists() and active", patient)
# → True
# Count results
evaluate("name.count()", patient)
# → 2
Python API
evaluate(expression: str, data: Any = None, constants: dict | None = None) -> Any
| Parameter | Description |
|---|---|
expression |
FHIRPath expression string |
data |
Input data — any combination of dicts, lists, strings, numbers, bools, and None |
constants |
Optional external constants, accessible as %name in expressions |
Returns the evaluation result as a Python object. Raises ValueError on parse errors and RuntimeError on evaluation errors.
Examples
Path Navigation
data = {"a": {"b": {"c": 42}}}
evaluate("a.b.c", data) # → 42
Filtering with where()
bundle = {
"entry": [
{"resource": {"resourceType": "Observation", "status": "final", "value": 120}},
{"resource": {"resourceType": "Condition", "status": "active"}},
{"resource": {"resourceType": "Observation", "status": "final", "value": 80}},
]
}
evaluate(
"entry.resource.where(resourceType = 'Observation').value",
bundle,
)
# → [120, 80]
QuestionnaireResponse Navigation
data = {
"QuestionnaireResponse": {
"resourceType": "QuestionnaireResponse",
"status": "completed",
"item": [
{
"linkId": "blood-pressure",
"item": [
{"linkId": "systolic", "answer": [{"valueInteger": 120}]},
{"linkId": "diastolic", "answer": [{"valueInteger": 80}]},
],
},
{
"linkId": "heart-rate",
"answer": [{"valueInteger": 72}],
},
],
}
}
# %QuestionnaireResponse resolves from the data context
evaluate(
"%QuestionnaireResponse.repeat(item).where(linkId = 'systolic').answer.valueInteger",
data,
)
# → [120]
evaluate(
"%QuestionnaireResponse.repeat(item).where(linkId = 'heart-rate').answer.valueInteger",
data,
)
# → [72]
# Collect all answers across nesting levels
evaluate("%QuestionnaireResponse.repeat(item).answer.valueInteger", data)
# → [72, 120, 80]
External Constants
data = {"items": [{"value": 10}, {"value": 50}, {"value": 90}]}
evaluate(
"items.where(value > %threshold).count()",
data,
constants={"threshold": 25},
)
# → 2
Arithmetic and String Functions
evaluate("1 + 2 * 3") # → 7
evaluate("name.length()", {"name": "hello"}) # → 5
evaluate("name.upper()", {"name": "hello"}) # → "HELLO"
Aggregation
data = {"scores": [10, 20, 30, 40, 50]}
evaluate("scores.sum()", data) # → 150
evaluate("scores.avg()", data) # → 30.0
evaluate("scores.min()", data) # → 10
evaluate("scores.max()", data) # → 50
# Custom aggregation
evaluate("scores.aggregate($total + $this, 0)", data) # → 150
FHIR Date and Quantity Literals
evaluate("@2024-01-15") # → "2024-01-15"
evaluate("@T14:30:00") # → "14:30:00"
evaluate("10 'mg'") # → {"value": 10.0, "unit": "mg"}
Pydantic Models
from pydantic import BaseModel
class Patient(BaseModel):
resourceType: str = "Patient"
id: str
active: bool
patient = Patient(id="pat-42", active=True)
evaluate("active", patient.model_dump()) # → True
Type Testing and Conversion
evaluate("(1).is(Integer)") # → True
evaluate("(1.5).is(Decimal)") # → True
evaluate("42.toString()") # → "42"
evaluate("'123'.toInteger()") # → 123
Supported Functions
Collection
empty() exists() count() first() last() single() tail() take() skip() combine() distinct() isDistinct() intersect() exclude() subsetOf() supersetOf() not() hasValue() union() children() descendants() ofType()
Higher-Order
where() select() all() repeat() repeatAll() sort() iif() coalesce() aggregate() defineVariable()
Math
abs() ceiling() floor() round() truncate() sqrt() exp() ln() log() power()
String
indexOf() substring() startsWith() endsWith() contains() upper() lower() replace() matches() matchesFull() replaceMatches() length() toChars() split() join() trim() lastIndexOf() encode() decode() escape() unescape()
Type Conversion
toString() toInteger() toDecimal() toBoolean() toDate() toDateTime() toTime() toQuantity() toLong() convertsToInteger() convertsToDecimal() convertsToBoolean() convertsToString() convertsToDate() convertsToDateTime() convertsToTime() convertsToQuantity() convertsToLong()
Aggregate
allTrue() anyTrue() allFalse() anyFalse() sum() avg() min() max()
Utility
now() today() timeOfDay() type() precision() lowBoundary() highBoundary() trace()
Date/Time Components
year() month() day() hour() minute() second() millisecond() timezone() duration() difference() comparable()
Operators
+ - * / div mod = != ~ !~ < > <= >= and or xor implies is as in contains | &
Performance
Benchmarked against fhirpathpy (pure Python, ANTLR-based):
| Benchmark | fhirpathrs | fhirpathpy | Speedup |
|---|---|---|---|
| Field access (small object) | 1.6 us | 73 us | 47x |
Nested path (a.b.c.d.e) |
2.4 us | 268 us | 103x |
Arithmetic (1 + 2 * 3 - 4) |
2.3 us | 1,411 us | 627x |
where() filter (10 items) |
14 us | 745 us | 54x |
where() filter (1000 items) |
1,578 us | 15,504 us | 10x |
| Patient field navigation | 3.8 us | 130 us | 34x |
Patient where().given |
6.3 us | 389 us | 61x |
| Bundle filter+count (100 entries) | 191 us | 2,482 us | 13x |
100-chained .where(true) |
102 us | 50,099 us | 489x |
100-nested iif() |
152 us | crashes | -- |
Architecture
crates/
├── parser/ # FHIRPath string → AST (nom + iterative Pratt parser)
├── interpreter/ # AST + data → result (iterative dispatch loop)
└── python/ # PyO3 bindings exposing evaluate()
All three layers are fully iterative — no call-stack recursion anywhere.
License
MIT
Metadata
Release files for fhirpathrs 0.1.5
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| Size | 1.3 MB |
| Tags | CPython 3.9 Linux glibc 2.17+ ARM64 |
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| Download URL | fhirpathrs-0.1.5-cp39-cp39-macosx_10_12_x86_64.whl |
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