itaygoren / fhir.resources

FHIR Resources

FHIR® Resources (R4, STU3, DSTU2)

Powered by pydantic, all FHIR Resources are available as python class with built-in data validation, faster in performance and by default orjson is included as 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) [partially see issue#13]

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 .[all].

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": "Swizterland"}]
... }
>>> org = Organization(**data)
>>> org.resource_type == "Organization"
True
>>> isinstance(org.address[0], Address)
>>> True
>>> org.address[0].country == "Swizterland"
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": "Swizterland"}]
... }'''
>>> org = Organization.parse_raw(json_str)
>>> isinstance(org.address[0], Address)
>>> True
>>> org.address[0].country == "Swizterland"
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
>>> org.birthDate == date(year=1985, month=6, day=12)
True
>>> org.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": "Swizterland"}]
... }

>>> org = Organization.construct()
>>> org.id = "f001"
>>> org.active = True
>>> org.name = "Acme Corporation"
>>> org.address = list()
>>> address = Address.construct()
>>> address.country = "Swizterland"
>>> org.address.append(address)
>>> org.dict() == json_obj
True

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": "Swizterland"}]
... }
>>> org = construct_fhir_element('Organization', json_dict)
>>> org.address[0].country == "Swizterland"
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

Custom Validators

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

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)

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"]

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.

© Copyright HL7® logo, FHIR® logo and the flaming fire are registered trademarks owned by Health Level Seven International