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.. image:: https://www.hl7.org/fhir/assets/images/fhir-logo-www.png :target: https://www.hl7.org/implement/standards/product_brief.cfm?product_id=449 :alt: HL7® FHIR®
*Beware! This is a beta release, so you should be careful using it in production. The sole purpose of this public beta is to get feedback.
FHIR_ (Fast Healthcare Interoperability Resources) is a specification for exchanging healthcare information electronically. It is designed to facilitate the exchange of data between different healthcare systems and applications, and is commonly used to build APIs (Application Programming Interfaces) for healthcare data. It is based on modern web technologies, and is designed to be easy to use and implement. It uses a modular approach, with a set of "resources" that represent different types of healthcare data (such as patients, observations, and diagnoses). These resources can be combined and extended as needed to support a wide range of healthcare use cases.
This "fhir.resources" package is powered by pydantic V2, so it become faster in performance.
Obviously it is written in modern python and has data validation built-in.
It provides tools and classes for all of the FHIR Resources <https://www.hl7.org/fhir/resourcelist.html> defined in the FHIR specification,
and allows you to create and manipulate FHIR resources in Python. You can then use these resources to build FHIR-based APIs or to work with FHIR data in other ways.
ORM <https://en.wikipedia.org/wiki/Object-relational_mapping>_.Experimental XML and YAML serialization and deserialization supports. See [Advanced Usages] section! [currently XML is not available]
FHIR® (Release R5, version 5.0.0) is available as default. Also previous versions are available as Python sub-package
(each release name string becomes sub-package name, i.e R4B ).
From fhir.resources version 7.0.0; there is no FHIR R4 instead of R4B is available as sub-package.
Available Previous Versions:
R4B (4.3.0)STU3 (3.0.2)Just a simple pip install fhir.resources or easy_install fhir.resources is enough. But if you want development
version, just clone from https://github.com/nazrulworld/fhir.resources and pip install -e .[dev].
Example: 1: This example creates a new Organization resource with some of its attributes (id, active, name, address)::
>>> from fhir.resources.organization import Organization
>>> from fhir.resources.address import Address
>>> data = {
... "id": "f001",
... "active": True,
... "name": "Acme Corporation",
... "address": [{"country": "Switzerland"}]
... }
>>> org = Organization(**data)
>>> org.get_resource_type() == "Organization"
True
>>> isinstance(org.address[0], Address)
True
>>> org.address[0].country == "Switzerland"
True
>>> org.model_dump()['active'] is True
TrueExample: 2: This example creates a new Organization resource from json string::
>>> from fhir.resources.organization import Organization
>>> from fhir.resources.address import Address
>>> json_str = '''{"resourceType": "Organization",
... "id": "f001",
... "active": True,
... "name": "Acme Corporation",
... "address": [{"country": "Switzerland"}]
... }'''
>>> org = Organization.model_dump_json(json_str)
>>> isinstance(org.address[0], Address)
True
>>> org.address[0].country == "Switzerland"
True
>>> org.dict()['active'] is True
TrueExample: 3: This example creates a new Patient resource from json object(py dict)::
>>> from fhir.resources.patient import Patient
>>> from fhir.resources.humanname import HumanName
>>> from datetime import date
>>> json_obj = {"resourceType": "Patient",
... "id": "p001",
... "active": True,
... "name": [
... {"text": "Adam Smith"}
... ],
... "birthDate": "1985-06-12"
... }
>>> pat = Patient.model_validate(json_obj)
>>> isinstance(pat.name[0], HumanName)
True
>>> pat.birthDate == date(year=1985, month=6, day=12)
True
>>> pat.active is True
TrueExample: 4: This example creates a new Patient resource from json file::
>>> from fhir.resources.patient import Patient
>>> import os
>>> import pathlib
>>> filename = pathlib.Path("foo/bar.json")
>>> pat = Patient.model_validate_json(filename.read_bytes())
>>> pat.get_resource_type() == "Patient"
TrueExample: 5: This example creates a new Organization resource in python way::
>>> from fhir.resources.organization import Organization
>>> from fhir.resources.address import Address
>>> json_obj = {"resourceType": "Organization",
... "id": "f001",
... "active": True,
... "name": "Acme Corporation",
... "address": [{"country": "Switzerland"}]
... }
>>> org = Organization.model_construct()
>>> org.id = "f001"
>>> org.active = True
>>> org.name = "Acme Corporation"
>>> org.address = list()
>>> address = Address.model_construct()
>>> address.country = "Switzerland"
>>> org.address.append(address)
>>> org.model_dump() == json_obj
True.. note::
Please note that due to the way the validation works, you will run into issues if you are using model_construct() to create
resources that have more than one mandatory field. See this comment in issue#56 <https://github.com/nazrulworld/fhir.resources/issues/56#issuecomment-784520234>_ for details.
Example: 5: Auto validation while providing wrong datatype::
>>> try:
... org = Organization({"id": "fmk", "address": ["i am wrong type"]})
... raise AssertionError("Code should not come here")
... except ValueError:
... passFHIR Comments (JSON)
It is possible to add comments inside json like xml, but need to follow some convention, what is suggested by `Grahame Grieve <http://www.healthintersections.com.au/?p=2569>`_;
is implemented here.
Also it is possible to generate json string output without comments.
Examples::
>>> observation_str = b"""{
... "resourceType": "Observation",
... "id": "f001",
... "fhir_comments": [
... " a specimen identifier - e.g. assigned when the specimen was taken by the orderer/placer use the accession number for the filling lab ",
... " Placer ID "
... ],
... "text": {
... "fhir_comments": [
... " a specimen identifier - e.g. assigned when the specimen was taken by the orderer/placer use the accession number for the filling lab ",
... " Placer ID "
... ],
... "status": "generated",
... "div": "<div xmlns=\"http://www.w3.org/1999/xhtml\">.........</div>"
... },
... "identifier": [
... {
... "use": "official",
... "system": "http://www.bmc.nl/zorgportal/identifiers/observations",
... "value": "6323"
... }
... ],
... "status": "final",
... "_status": {
... "fhir_comments": [
... " EH: Note to balloters - lots of choices for whole blood I chose this. "
... ]
... },
... "code": {
... "coding": [
... {
... "system": "http://loinc.org",
... "code": "15074-8",
... "display": "Glucose [Moles/volume] in Blood"
... }
... ]
... },
... "subject": {
... "reference": "Patient/f001",
... "display": "P. van de Heuvel"
... },
... "effectivePeriod": {
... "start": "2013-04-02T09:30:10+01:00"
... },
... "issued": "2013-04-03T15:30:10+01:00",
... "performer": [
... {
... "reference": "Practitioner/f005",
... "display": "A. Langeveld"
... }
... ],
... "valueQuantity": {
... "value": 6.3,
... "unit": "mmol/l",
... "system": "http://unitsofmeasure.org",
... "code": "mmol/L"
... },
... "interpretation": [
... {
... "coding": [
... {
... "system": "http://terminology.hl7.org/CodeSystem/v3-ObservationInterpretation",
... "code": "H",
... "display": "High"
... }
... ]
... }
... ],
... "referenceRange": [
... {
... "low": {
... "value": 3.1,
... "unit": "mmol/l",
... "system": "http://unitsofmeasure.org",
... "code": "mmol/L"
... },
... "high": {
... "value": 6.2,
... "unit": "mmol/l",
... "system": "http://unitsofmeasure.org",
... "code": "mmol/L"
... }
... }
... ]
... }"""
>>> from fhir.resources.observation import Observation
>>> obj = Observation.model_validate_json(observation_str)
>>> "fhir_comments" in obj.model_dump_json()
>>> # Test comments filtering
>>> "fhir_comments" not in obj.model_dump_json(exclude_comments=True)
Special Case: Missing dataIn some cases <https://www.hl7.org/fhir/extensibility.html#Special-Case>_, implementers might
find that they do not have appropriate data for an element with minimum cardinality = 1.
In this case, the element must be present, but unless the resource or a profile on it has made the
actual value of the primitive data type mandatory, it is possible to provide an extension that
explains why the primitive value is not present.
Example (required intent element is missing but still valid because of extension)::
>>> json_str = b"""{
... "resourceType": "MedicationRequest",
... "id": "1620518",
... "meta": {
... "versionId": "1",
... "lastUpdated": "2020-10-27T11:04:42.215+00:00",
... "source": "#z072VeAlQWM94jpc",
... "tag": [
... {
... "system": "http://www.alpha.alp/use-case",
... "code": "EX20"
... }
... ]
... },
... "status": "completed",
... "_intent": {
... "extension": [
... {
... "url": "http://hl7.org/fhir/StructureDefinition/data-absent-reason",
... "valueCode": "unknown"
... }
... ]
... },
... "medicationReference": {
... "reference": "Medication/1620516",
... "display": "Erythromycin 250 MG Oral Tablet"
... },
... "subject": {
... "reference": "Patient/1620472"
... },
... "encounter": {
... "reference": "Encounter/1620506",
... "display": "Follow up encounter"
... },
... "authoredOn": "2018-06-16",
... "requester": {
... "reference": "Practitioner/1620502",
... "display": "Dr. Harold Hippocrates"
... },
... "reasonReference": [
... {
... "reference": "Condition/1620514",
... "display": "Otitis Media"
... }
... ],
... "dosageInstruction": [
... {
... "text": "250 mg 4 times per day for 10 days",
... "timing": {
... "repeat": {
... "boundsDuration": {
... "value": 10,
... "unit": "day",
... "system": "http://unitsofmeasure.org",
... "code": "d"
... },
... "frequency": 4,
... "period": 1,
... "periodUnit": "d"
... }
... },
... "doseAndRate": [
... {
... "doseQuantity": {
... "value": 250,
... "unit": "mg",
... "system": "http://unitsofmeasure.org",
... "code": "mg"
... }
... }
... ]
... }
... ],
... "priorPrescription": {
... "reference": "MedicationRequest/1620517",
... "display": "Amoxicillin prescription"
... }
... }"""
>>> from fhir.resources.medicationrequest import MedicationRequest
>>> obj = MedicationRequest.model_validate_json(json_str)
>>> "intent" not in obj.model_dump()Custom Validators
**This feature is not available**
``fhir.resources`` is providing the extensive API to create and attach custom validator into any model. See more `about root validator <https://pydantic-docs.helpmanual.io/usage/validators/#root-validators>`_
Some convention you have to follow though, while creating a root validator.
1. Number of arguments are fixed, as well as names are also. i.e ``(cls, values)``.
2. Should return ``values``, unless any exception need to be raised.
3. Validator should be attached only one time for individual Model. Update [from now, it's not possible to attach multiple time same name validator on same class]
Example 1: Validator for Patient::
from typing import Dict
from fhir.resources.patient import Patient
import datetime
def validate_birthdate(cls, values: Dict):
if not values:
return values
if "birthDate" not in values:
raise ValueError("Patient's ``birthDate`` is required.")
minimum_date = datetime.date(2002, 1, 1)
if values["birthDate"] > minimum_date:
raise ValueError("Minimum 18 years patient is allowed to use this system.")
return values
# we want this validator to execute after data evaluating by individual field validators.
Patient.add_root_validator(validate_gender, pre=False)
Example 2: Validator for Patient from Validator Class::
from typing import Dict
from fhir.resources.patient import Patient
import datetime
class MyValidator:
@classmethod
def validate_birthdate(cls, values: Dict):
if not values:
return values
if "birthDate" not in values:
raise ValueError("Patient's ``birthDate`` is required.")
minimum_date = datetime.date(2002, 1, 1)
if values["birthDate"] > minimum_date:
raise ValueError("Minimum 18 years patient is allowed to use this system.")
return values
# we want this validator to execute after data evaluating by individual field validators.
Patient.add_root_validator(MyValidator.validate_gender, pre=False)
**important notes** It is possible add root validator into any base class like ``DomainResource``.
In this case you have to make sure root validator is attached before any import of derived class, other
than validator will not trigger for successor class (if imported before) by nature.
ENUM Validatorfhir.resources is providing API for enum constraint for each field (where applicable), but it-self doesn't
enforce enum based validation! see discussion here <https://github.com/nazrulworld/fhir.resources/issues/23>_.
If you want to enforce enum constraint, you have to create a validator for that.
Example: Gender Enum::
from typing import Dict
from fhir.resources.patient import Patient
def validate_gender(cls, values: Dict):
if not values:
return values
enums = cls.model_fields["gender"].json_schema_extra["enum_values"]
if "gender" in values and values["gender"] not in enums:
raise ValueError("write your message")
return values
Patient.add_root_validator(validate_gender, pre=True)Reference Validator
``fhir.resources`` is also providing enum like list of permitted resource types through json_schema_extra ``enum_reference_types``.
You can get that list by following above (Enum) approaches ``resource_types = cls.model_fields["managingOrganization"].json_schema_extra["enum_reference_types"]``
pydantic_ Field Type SupportAll available fhir resources (types) can be use as pydantic's Field's value types. See issue#46 Support for FastAPI pydantic response models <https://github.com/nazrulworld/fhir.resources/issues/46>.
The module fhirtypes.py contains all fhir resources related types and should trigger validator automatically.
Resource.id aka fhirtypes.Id constraint extensibility
There are a lots of discussion here here i.) https://bit.ly/360HksL ii.) https://bit.ly/3o1fZgl about the length of ``Resource.Id``'s value.
Based on those discussions, we recommend that keep your ``Resource.Id`` size within 64 letters (for the seek of intercompatibility with third party system), but we are also providing freedom
about the length of Id, in respect with others opinion that 64 chr length is not sufficient, so default length is now 255.
But it is offering to customize as your own requirement by doing a monkey patch.
Examples::
# ``patch.py``
>>> import importlib
>>> from fhir_core import constraints
>>> from fhir_core import types as ftypes
>>> constraints.TYPES_ID_MAX_LENGTH = 64
>>> importlib.reload(ftypes)
Note: when you will change that behaviour, that would impact into your whole project.
XML SupportsThis feature is currently not available
Along side with JSON string export, it is possible to export as XML string!
Before using this feature, make sure associated dependent library is installed. Use fhir.resources[xml] or fhir.resources[all] as
your project requirements.
XML schema validator! It is possible to provide custom xmlparser, during load from file or string, meaning that you can validate data against FHIR xml schema(and/or your custom schema).
Example-1 Export::
from fhir.resources.patient import Patient data = {"active": True, "gender": "male", "birthDate": "2000-09-18", "name": [{"text": "Primal Kons"}]} patient_obj = Patient(**data) xml_str = patient_obj.xml(pretty_print=True) print(xml_str) <?xml version='1.0' encoding='utf-8'?>
Example-2 Import from string::
from fhir.resources.patient import Patient data = {"active": True, "gender": "male", "birthDate": "2000-09-18", "name": [{"text": "Primal Kons"}]} patient_obj = Patient(**data) xml_str = patient_obj.xml(pretty_print=True) print(xml_str) data = b"""<?xml version='1.0' encoding='utf-8'?> ...
... """ patient = Patient.parse_raw(data, content_type="text/xml") print(patient.json(indent=2)) { "resourceType": "Patient", "active": true, "name": [ { "text": "Primal Kons", "family": "Kons", "given": [ "Primal" ] } ], "gender": "male", "birthDate": "2000-09-18" }... ... ...... ... ... with xml parser import lxml schema = lxml.etree.XMLSchema(file=str(FHIR_XSD_DIR / "patient.xsd")) xmlparser = lxml.etree.XMLParser(schema=schema) patient2 = Patient.parse_raw(data, content_type="text/xml", xmlparser=xmlparser) patient2 == patient True
Example-3 Import from file::
patient3 = Patient.parse_file("Patient.xml") patient3 == patient and patient3 == patient2 True
XML FAQ
- Although generated XML is validated against ``FHIR/patient.xsd`` and ``FHIR/observation.xsd`` in tests, but we suggest you check output of your production data.
- Comment feature is included, but we recommend you check in your complex usages.YAML Supports
Although there is no official support for YAML documented in FHIR specification, but as an experimental feature, we add this support.
Now it is possible export/import YAML strings.
Before using this feature, make sure associated dependent library is installed. Use ``fhir.resources[yaml]`` or ``fhir.resources[all]`` as
your project requirements.
Example-1 Export::
>>> from fhir.resources.patient import Patient
>>> data = {"active": True, "gender": "male", "birthDate": "2000-09-18", "name": [{"text": "Primal Kons", "family": "Kons", "given": ["Primal"]}]}
>>> patient_obj = Patient(**data)
>>> yml_str = patient_obj.model_dump_yaml(indent=2)
>>> print(yml_str)
resourceType: Patient
active: true
name:
- text: Primal Kons
family: Kons
given:
- Primal
gender: male
birthDate: 2000-09-18
Example-2 Import from YAML string::
>>> from fhir.resources.patient import Patient
>>> data = b"""
... resourceType: Patient
... active: true
... name:
... - text: Primal Kons
... family: Kons
... given:
... - Primal
... gender: male
... birthDate: 2000-09-18
... """
>>> patient_obj = Patient.model_validate_yaml(data)
>>> json_str = patient_obj.model_dump_json(indent=2)
>>> print(json_str)
{
"resourceType": "Patient",
"active": true,
"name": [
{
"text": "Primal Kons",
"family": "Kons",
"given": [
"Primal"
]
}
],
"gender": "male",
"birthDate": "2000-09-18"
}
Example-3 Import from YAML file::
>>> import pathlib
>>> from fhir.resources.patient import Patient
>>> patient_obj = Patient.model_validate_yaml(pathlib.Path("Patient.yml").read_bytes())
>>> json_str = patient_obj.model_dump_json(indent=2)
>>> print(json_str)
{
"resourceType": "Patient",
"active": true,
"name": [
{
"text": "Primal Kons",
"family": "Kons",
"given": [
"Primal"
]
}
],
"gender": "male",
"birthDate": "2000-09-18"
}
**YAML FAQ**
- We are using https://pyyaml.org/ PyYAML library, for serialization/deserialization but if we find more faster library, we could use that. you are welcome to provide us your suggestion.
- YAML based comments is not supported yet, instead json comments syntax is used! Of course this comment feature is in our todo list.
Allow Empty StringAlthough this is not good practice to allow empty string value against FHIR primitive data type String. But
we in real life scenario, is it unavoidable sometimes.
Examples:: Place this code inside your init.py module or any place, just to make sure that this fragment of codes is runtime executed.
>>> # ``__init__.py``
>>> import importlib
>>> from fhir_core import constraints
>>> from fhir_core import types as ftypes
>>> constraints.TYPES_STRING_ALLOW_EMPTY_STR = True
>>> importlib.reload(ftypes)FHIR release R4B is coming with not that much changes over the release of R4. So we decided not to create separate sub-package for R4 like STU3, instead there just overlaps on existing R4. This also means that in future, when we will work on R5; there will be sub-package for R4B and no R4. We suggest you to try make a plan to be upgraded to R4B. Here you could find related information dealing-strategy-R4-R4B_.
You could find full discussion here https://github.com/nazrulworld/fhir.resources/discussions/116
7.X.X to 8.X.X)There is no breaking changes in terms of api/functions. But it is recommended that you should use new functions from Pydantic V2 instead of using deprecated functions.
Replacements and/or new functions.
FHIRAbstractModel::dict to FHIRAbstractModel::model_dumpFHIRAbstractModel::json to FHIRAbstractModel::model_dump_jsonFHIRAbstractModel::yaml to FHIRAbstractModel::model_dump_yamlFHIRAbstractModel::xml to FHIRAbstractModel::model_dump_xml [coming soon]FHIRAbstractModel::parse_obj to FHIRAbstractModel::model_validateFHIRAbstractModel::parse_raw to FHIRAbstractModel::model_validate_jsonFHIRAbstractModel::parse_file to no replacement, we suggest you use pathlib (see examples)FHIRAbstractModel::model_validate_yaml parse YAML string to FHIRAbstractModel.FHIRAbstractModel::model_validate_xml parse XML string to FHIRAbstractModel.6.X.X to 7.0.X)First of all, you have to correct all imports path, if you wish to keep continue using FHIR release R4B or R4, as those resources
are moved under sub-package named R4B. Then if you wish to use current R5 release,
read carefully the following documents.
R4,
then it is important to look at the differences between R4B and R4 here -> https://hl7.org/fhir/R4B/diff.html6.X.X)This migration guide states some underlying changes of API and replacement, those are commonly used from later than 6.X.X version.
fhir.resources.fhirelementfactory.FHIRElementFactory::instantiate
**Replacement:** ``fhir.resources.construct_fhir_element``
- First parameter value is same as previous, the Resource name.
- Second parameter is more flexible than previous! it is possible to provide not only json ``dict`` but also
json string or json file path.
- No third parameter, what was in previous version.
``fhir.resources.fhirabstractbase.FHIRAbstractBase::__init__``Replacement: fhir.resources.fhirabstractmodel.FHIRAbstractModel::parse_obj<classmethod>
First parameter value is same as previous, json dict.
No second parameter, what was in previous version.
fhir.resources.fhirabstractbase.FHIRAbstractBase::as_json
**Replacement:** ``fhir.resources.fhirabstractmodel.FHIRAbstractModel::dict``
- Output are almost same previous, but there has some difference in case of some date type, for example py date,
datetime, Decimal are in object representation.
- It is possible to use ``fhir.resources.fhirabstractmodel.FHIRAbstractModel::json`` as replacement, when
json string is required (so not need further, json dumps from dict)
Note:
All resources/classes are derived from ``fhir.resources.fhirabstractmodel.FHIRAbstractModel`` what was previously
from ``fhir.resources.fhirabstractbase.FHIRAbstractBase``.
Release and Version Policy
--------------------------
Starting from version ``5.0.0`` we are following our own release policy and we although follow Semantic Versioning scheme like FHIR® version.
Unlike previous statement (bellow), releasing now is not dependent on FHIR®.
**removed statement**
This package is following `FHIR® release and versioning policy <https://www.hl7.org/fhir/versions.html>`_, for example say, FHIR releases next version 4.0.1,
we also release same version here.
Credits
-------
All FHIR® Resources (python classes) are generated using fhir-parser_ which is forked from https://github.com/smart-on-fhir/fhir-parser.git.
This package skeleton was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
.. _`fhir-parser`: https://github.com/nazrulworld/fhir-parser
.. _`pydantic`: https://pydantic-docs.helpmanual.io/
.. _`orjson`: https://pypi.org/project/orjson/
.. _`dealing-strategy-R4-R4B`: https://confluence.hl7.org/display/FHIR/Strategies+for+dealing+with+R4+and+R4B
.. _`FHIR`: https://www.hl7.org/implement/standards/product_brief.cfm
© Copyright HL7® logo, FHIR® logo and the flaming fire are registered trademarks
owned by `Health Level Seven International <https://www.hl7.org/legal/trademarks.cfm?ref=https://pypi.org/project/fhir-resources/>`_
.. role:: strike
:class: strike
.. role:: raw-html(raw)
:format: html