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FHIRPath Normative Release (v2.0.0) implementation in Python, along side it provides support for FHIR Search API and Query (we called it fql(FHIR Query Language)) API to fetch FHIR resources from any data-source(database). This library is built in ORM like approach. Our goal is to make 100% (as much as possible) FHIRPath Normative Release (v2.0.0) specification compliance product.


This library is kind of abstract type, where all specifications from FHIRPath Normative Release (v2.0.0) are implemented rather than completed solution (ready to go). The main reason behind this design pattern, to support multiple database systems as well as well as any framework, there is no dependency.

fhirpath never taking care of creating indexes, mappings (elasticsearch) and storing data, if you want to use this library, you have to go through any of existing providers (see list bellow) or make your own provider (should not too hard work).

Simple example


  1. Elasticsearch server 7.x.x Installed.

  2. Mappings and indexes are handled manually.

  3. Data (document) also are stored manually.

Create Connection and Engine:

>>> from fhirpath.connectors import create_connection
>>> from import ElasticsearchEngine
>>> from fhirpath.engine import dialect_factory
>>> from fhirpath.enums import FHIR_VERSION

>>> host, port = "", 9200
>>> conn_str = "es://@{0}:{1}/".format(host, port)
>>> connection = create_connection(conn_str, "elasticsearch.Elasticsearch")
>>> engine = ElasticsearchEngine(FHIR_VERSION.R4, lambda x: connection, dialect_factory)

Basic Search:

>>> from import Search
>>> from import SearchContext

>>> search_context = SearchContext(engine, "Organization")
>>> params = (
....    ("active", "true"),
....    ("_lastUpdated", "2010-05-28T05:35:56+00:00"),
....    ("_profile", ""),
....    ("identifier", "urn:oid:2.16.528.1|91654"),
....    ("type", "|prov"),
....    ("address-postalcode", "9100 AA"),
....    ("address", "Den Burg"),
.... )
>>> fhir_search = Search(search_context, params=params)
>>> bundle = fhir_search()
>>> len(bundle.entry) == 0

Basic Query:

>>> from fhirpath.enums import SortOrderType
>>> from fhirpath.query import Q_
>>> from fhirpath.fql import T_
>>> from fhirpath.fql import V_
>>> from fhirpath.fql import exists_
>>> query_builder = Q_(resource="Organization", engine=engine)
>>>  query_builder = (
....    query_builder.where(T_("") == V_("true"))
....    .where(T_("Organization.meta.lastUpdated", "2010-05-28T05:35:56+00:00"))
....    .sort(sort_("Organization.meta.lastUpdated", SortOrderType.DESC))
.... )
>>> query_result = query_builder(async_result=False)
>>> for resource in query_result:
....    assert resource.__class__.__name__ == "OrganizationModel"
>>> # test fetch all
>>> result = query_result.fetchall()
>>> result.__class__.__name__ == "EngineResult"

>>> query_builder = Q_(resource="ChargeItem", engine=engine)
>>> query_builder = query_builder.where(exists_("ChargeItem.enteredDate"))
>>> result = query_builder(async_result=False).single()
>>> result is not None
>>> isinstance(result, builder._from[0][1])

>>> query_builder = Q_(resource="ChargeItem", engine=engine)
>>> query_builder = query_builder.where(exists_("ChargeItem.enteredDate"))
>>> result = query_builder(async_result=False).first()
>>> result is not None
>>> isinstance(result, builder._from[0][1])

Available Provider (known)

Currently very few numbers of providers available, however more will coming soon.


A Plone powered provider, like fhirpath-guillotina every thing is included. ready to go, although has a dependency on

  1. Engine: Elasticsearch

  2. PyPi:

  3. Source:


Why are you waiting for? You are welcome to list your provider here! Developing provider should not be so hard, as fhirpath is giving you convenient APIs.

Elasticsearch Custom Analyzer

To get some special search features for reference type field, you will need to setup custom analyzer for your elasticsearch index.

Example Custom Analyzer:

settings = {
    "analysis": {
        "normalizer": {
            "fhir_token_normalizer": {"filter": ["lowercase", "asciifolding"]}
        "analyzer": {
            "fhir_reference_analyzer": {
                "tokenizer": "keyword",
                "filter": ["fhir_reference_filter"],
        "filter": {
            "fhir_reference_filter": {
                "type": "pattern_capture",
                "preserve_original": True,
                "patterns": [r"(?:\w+\/)?(https?\:\/\/.*|[a-zA-Z0-9_-]+)"],
        "char_filter": {},
        "tokenizer": {},

Example Mapping (Reference Field):

"properties": {
  "reference": {
    "type": "text",
    "index": true,
    "store": false,
    "analyzer": "fhir_reference_analyzer"


  1. fhirbase engine aka provider implementation.

  2. All methods/functions are defined in FHIRPath specification, would be completed.

  3. Implement



This package skeleton was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

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