FHIR® Resources (R4, STU3, DSTU2)

Experimental XML and YAML serialization and deserialization supports. See [Advanced Usages] section!

Powered by pydantic, all FHIR Resources are available as python class with built-in data validation, faster in performance and optionally orjson support has been included as a performance booster! Written in modern python.

Easy to construct, easy to extended validation, easy to export.
By inheriting behaviour from pydantic, compatible with ORM.
Full support of FHIR® Extensibility for Primitive Data Types are available.
Previous release of FHIR® Resources are available.
Free software: BSD license

FHIR® Version Info

FHIR® (Release R4, version 4.0.1) is available as default. Also previous versions are available as Python sub-package (each release name string becomes sub-package name, i.e STU3 ).

Available Previous Versions:

STU3 (3.0.2)
DSTU2 (1.0.2) [see issue#13][don't have full tests coverage]

Installation

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].

Usages

Example: 1: Construct Resource Model object:

>>> 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.resource_type == "Organization"
True
>>> isinstance(org.address[0], Address)
True
>>> org.address[0].country == "Switzerland"
True
>>> org.dict()['active'] is True
True

Example: 2: Resource object created 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.parse_raw(json_str)
>>> isinstance(org.address[0], Address)
True
>>> org.address[0].country == "Switzerland"
True
>>> org.dict()['active'] is True
True

Example: 3: Resource object created 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.parse_obj(json_obj)
>>> isinstance(pat.name[0], HumanName)
True
>>> pat.birthDate == date(year=1985, month=6, day=12)
True
>>> pat.active is True
True

Example: 4: Construct Resource object from json file:

>>> from fhir.resources.patient import Patient
>>> import os
>>> import pathlib
>>> filename = pathlib.Path("foo/bar.json")
>>> pat = Patient.parse_file(filename)
>>> pat.resource_type == "Patient"
True

Example: 5: Construct resource object 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.construct()
>>> org.id = "f001"
>>> org.active = True
>>> org.name = "Acme Corporation"
>>> org.address = list()
>>> address = Address.construct()
>>> address.country = "Switzerland"
>>> org.address.append(address)
>>> org.dict() == json_obj
True

Note

Please note that due to the way the validation works, you will run into issues if you are using construct() to create resources that have more than one mandatory field. See this comment in issue#56 for details.

Example: 4: Using Resource Factory Function:

>>> from fhir.resources import construct_fhir_element
>>> json_dict = {"resourceType": "Organization",
...     "id": "mmanu",
...     "active": True,
...     "name": "Acme Corporation",
...     "address": [{"country": "Switzerland"}]
... }
>>> org = construct_fhir_element('Organization', json_dict)
>>> org.address[0].country == "Switzerland"
True
>>> org.dict()['active'] is True
True

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:
...     pass

Advanced Usages

FHIR Comments (JSON)

It is possible to add comments inside json like xml, but need to follow some convention, what is suggested by Grahame Grieve; 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.parse_raw(observation_str)
>>> "fhir_comments" in obj.json()
>>> # Test comments filtering
>>> "fhir_comments" not in obj.json(exclude_comments=True)

Special Case: Missing data

In some cases, 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.parse_raw(json_str)
>>> "intent" not in obj.dict()

Custom Validators

fhir.resources is providing the extensive API to create and attach custom validator into any model. See more about root validator Some convention you have to follow though, while creating a root validator.

Number of arguments are fixed, as well as names are also. i.e (cls, values).
Should return values, unless any exception need to be raised.
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 Validator

fhir.resources is providing API for enum constraint for each field (where applicable), but it-self doesn't enforce enum based validation! see discussion here. 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.__fields__["gender"].field_info.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 field property enum_reference_types. You can get that list by following above (Enum) approaches resource_types = cls.__fields__["managingOrganization"].field_info.extra["enum_reference_types"]

Usages of orjson

orjson is one of the fastest Python library for JSON and is more correct than the standard json library (according to their docs). Good news is that fhir.resource has an extensive support for orjson and it's too easy to enable it automatically. What you need to do, just make orjson as your project dependency!

pydantic Field Type Support

All available fhir resources (types) can be use as pydantic's Field's value types. See issue#46 Support for FastAPI pydantic response models. 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. fhirtypes.Id.configure_constraints() is offering to customize as your own requirement.

Examples::

>>> from fhir.resources.fhirtypes import Id
>>> Id.configure_constraints(min_length=16, max_length=128)

Note: when you will change that behaviour, that would impact into your whole project.

XML Supports

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'?>
<Patient xmlns="http://hl7.org/fhir">
  <active value="true"/>
  <name>
    <text value="Primal Kons"/>
  </name>
  <gender value="male"/>
  <birthDate value="2000-09-18"/>
</Patient>

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 xmlns="http://hl7.org/fhir">
...   <active value="true"/>
...   <name>
...     <text value="Primal Kons"/>
...   </name>
...   <gender value="male"/>
...   <birthDate value="2000-09-18"/>
... </Patient>"""
>>> 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.yaml(indent=True)
>>> 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.parse_raw(data, content_type="text/yaml")
>>> json_str = patient_obj.json(indent=True)
>>> 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::

>>> from fhir.resources.patient import Patient
>>> patient_obj = Patient.parse_file("Patient.yml")
>>> json_str = patient_obj.json(indent=True)
>>> 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 String

Although 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.

>>> from fhir.resources.fhirtypes import String
>>> String.configure_empty_str(allow=True)

Migration (from later than `6.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, 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.

Name		Name	Last commit message	Last commit date
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.github		.github
fhir		fhir
script		script
tests		tests
.editorconfig		.editorconfig
.flake8		.flake8
.gitignore		.gitignore
.isort.cfg		.isort.cfg
.travis.yml		.travis.yml
AUTHORS.rst		AUTHORS.rst
CONTRIBUTING.rst		CONTRIBUTING.rst
HISTORY.rst		HISTORY.rst
LICENSE		LICENSE
MANIFEST.in		MANIFEST.in
Makefile		Makefile
README.rst		README.rst
appveyor.yml		appveyor.yml
pyproject.toml		pyproject.toml
setup.cfg		setup.cfg
setup.py		setup.py
tox.ini		tox.ini

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FHIR® Resources (R4, STU3, DSTU2)

FHIR® Version Info

Installation

Usages

Advanced Usages

FHIR Comments (JSON)

Special Case: Missing data

Custom Validators

ENUM Validator

Reference Validator

Usages of orjson

pydantic Field Type Support

`Resource.id aka fhirtypes.Id` constraint extensibility

XML Supports

YAML Supports

Allow Empty String

Migration (from later than `6.X.X`)

`fhir.resources.fhirelementfactory.FHIRElementFactory::instantiate`

`fhir.resources.fhirabstractbase.FHIRAbstractBase::init`

`fhir.resources.fhirabstractbase.FHIRAbstractBase::as_json`

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kshillingstad/fhir.resources

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FHIR® Resources (R4, STU3, DSTU2)

FHIR® Version Info

Installation

Usages

Advanced Usages

FHIR Comments (JSON)

Special Case: Missing data

Custom Validators

ENUM Validator

Reference Validator

Usages of orjson

pydantic Field Type Support

Resource.id aka fhirtypes.Id constraint extensibility

XML Supports

YAML Supports

Allow Empty String

Migration (from later than 6.X.X)

fhir.resources.fhirelementfactory.FHIRElementFactory::instantiate

fhir.resources.fhirabstractbase.FHIRAbstractBase::__init__

fhir.resources.fhirabstractbase.FHIRAbstractBase::as_json

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`Resource.id aka fhirtypes.Id` constraint extensibility

Migration (from later than `6.X.X`)

`fhir.resources.fhirelementfactory.FHIRElementFactory::instantiate`

`fhir.resources.fhirabstractbase.FHIRAbstractBase::init`

`fhir.resources.fhirabstractbase.FHIRAbstractBase::as_json`

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