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Clients

EHRClient

Bases: BaseClient

Source code in healthchain/clients/ehrclient.py 
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class EHRClient(BaseClient):
    def __init__(
        self,
        func: Callable[..., Any],
        workflow: Workflow,
        strategy: BaseStrategy,
        timeout: Optional[float] = 10.0,
    ):
        """
        Initializes the EHRClient with a data generator function and optional workflow and use case.
        Should be a subclass of BaseUseCase. Example - ClinicalDecisionSupport()

        Parameters:
            func (Callable[..., Any]): A function to generate data for requests.
            workflow ([Workflow]): The workflow context to apply to the data generator.
            strategy (BaseStrategy): The strategy object to construct requests based on the generated data.
            timeout (Optional[float], default=10.0) : The maximum time in seconds to wait for a response from the server. This parameter determines how long the client will wait before considering a request timed out.

        """
        # TODO: Add option to pass in different provider options
        self.data_generator_func: Callable[..., Any] = func
        self.workflow: Workflow = workflow
        self.strategy: BaseStrategy = strategy
        self.vendor = None
        self.request_data: List[CDSRequest] = []
        self.timeout = timeout

    def set_vendor(self, name) -> None:
        self.vendor = name

    def generate_request(self, *args: Any, **kwargs: Any) -> None:
        """
        Generates a request using the data produced by the data generator function,
        and appends it to the internal request queue.

            Parameters:
                *args (Any): Positional arguments passed to the data generator function.
                **kwargs (Any): Keyword arguments passed to the data generator function.

            Raises:
                ValueError: If the use case is not configured.
        """
        data = self.data_generator_func(*args, **kwargs)
        self.request_data.append(self.strategy.construct_request(data, self.workflow))

    async def send_request(self, url: str) -> List[Dict]:
        """
        Sends all queued requests to the specified URL and collects the responses.

            Parameters:
                url (str): The URL to which the requests will be sent.
            Returns:
                List[dict]: A list of JSON responses from the server.
            Notes:
                This method logs errors rather than raising them, to avoid interrupting the batch processing of requests.
        """
        async with httpx.AsyncClient() as client:
            responses: List[Dict] = []
            # TODO: pass timeout as config
            timeout = httpx.Timeout(self.timeout, read=None)
            for request in self.request_data:
                try:
                    if self.strategy.api_protocol == ApiProtocol.soap:
                        headers = {"Content-Type": "text/xml; charset=utf-8"}
                        response = await client.post(
                            url=url,
                            data=request.document,
                            headers=headers,
                            timeout=timeout,
                        )
                        response.raise_for_status()
                        response_model = CdaResponse(document=response.text)
                        responses.append(response_model.model_dump_xml())
                    else:
                        response = await client.post(
                            url=url,
                            json=request.model_dump(exclude_none=True),
                            timeout=timeout,
                        )
                        response.raise_for_status()
                        responses.append(response.json())
                except httpx.HTTPStatusError as exc:
                    log.error(
                        f"Error response {exc.response.status_code} while requesting {exc.request.url!r}."
                    )
                    responses.append({})
                except httpx.TimeoutException as exc:
                    log.error(f"Request to {exc.request.url!r} timed out!")
                    responses.append({})
                except httpx.RequestError as exc:
                    log.error(
                        f"An error occurred while requesting {exc.request.url!r}."
                    )
                    responses.append({})

        return responses

__init__(func, workflow, strategy, timeout=10.0)

Initializes the EHRClient with a data generator function and optional workflow and use case. Should be a subclass of BaseUseCase. Example - ClinicalDecisionSupport()

PARAMETER DESCRIPTION
func

A function to generate data for requests.

TYPE: Callable[..., Any]

workflow

The workflow context to apply to the data generator.

TYPE: [Workflow]

strategy

The strategy object to construct requests based on the generated data.

TYPE: BaseStrategy

timeout

The maximum time in seconds to wait for a response from the server. This parameter determines how long the client will wait before considering a request timed out.

TYPE: Optional[float], default=10.0) DEFAULT: 10.0

Source code in healthchain/clients/ehrclient.py 
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def __init__(
    self,
    func: Callable[..., Any],
    workflow: Workflow,
    strategy: BaseStrategy,
    timeout: Optional[float] = 10.0,
):
    """
    Initializes the EHRClient with a data generator function and optional workflow and use case.
    Should be a subclass of BaseUseCase. Example - ClinicalDecisionSupport()

    Parameters:
        func (Callable[..., Any]): A function to generate data for requests.
        workflow ([Workflow]): The workflow context to apply to the data generator.
        strategy (BaseStrategy): The strategy object to construct requests based on the generated data.
        timeout (Optional[float], default=10.0) : The maximum time in seconds to wait for a response from the server. This parameter determines how long the client will wait before considering a request timed out.

    """
    # TODO: Add option to pass in different provider options
    self.data_generator_func: Callable[..., Any] = func
    self.workflow: Workflow = workflow
    self.strategy: BaseStrategy = strategy
    self.vendor = None
    self.request_data: List[CDSRequest] = []
    self.timeout = timeout

generate_request(*args, **kwargs)

Generates a request using the data produced by the data generator function, and appends it to the internal request queue.

Parameters:
    *args (Any): Positional arguments passed to the data generator function.
    **kwargs (Any): Keyword arguments passed to the data generator function.

Raises:
    ValueError: If the use case is not configured.
Source code in healthchain/clients/ehrclient.py 
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def generate_request(self, *args: Any, **kwargs: Any) -> None:
    """
    Generates a request using the data produced by the data generator function,
    and appends it to the internal request queue.

        Parameters:
            *args (Any): Positional arguments passed to the data generator function.
            **kwargs (Any): Keyword arguments passed to the data generator function.

        Raises:
            ValueError: If the use case is not configured.
    """
    data = self.data_generator_func(*args, **kwargs)
    self.request_data.append(self.strategy.construct_request(data, self.workflow))

send_request(url) async

Sends all queued requests to the specified URL and collects the responses.

Parameters:
    url (str): The URL to which the requests will be sent.
Returns:
    List[dict]: A list of JSON responses from the server.
Notes:
    This method logs errors rather than raising them, to avoid interrupting the batch processing of requests.
Source code in healthchain/clients/ehrclient.py 
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async def send_request(self, url: str) -> List[Dict]:
    """
    Sends all queued requests to the specified URL and collects the responses.

        Parameters:
            url (str): The URL to which the requests will be sent.
        Returns:
            List[dict]: A list of JSON responses from the server.
        Notes:
            This method logs errors rather than raising them, to avoid interrupting the batch processing of requests.
    """
    async with httpx.AsyncClient() as client:
        responses: List[Dict] = []
        # TODO: pass timeout as config
        timeout = httpx.Timeout(self.timeout, read=None)
        for request in self.request_data:
            try:
                if self.strategy.api_protocol == ApiProtocol.soap:
                    headers = {"Content-Type": "text/xml; charset=utf-8"}
                    response = await client.post(
                        url=url,
                        data=request.document,
                        headers=headers,
                        timeout=timeout,
                    )
                    response.raise_for_status()
                    response_model = CdaResponse(document=response.text)
                    responses.append(response_model.model_dump_xml())
                else:
                    response = await client.post(
                        url=url,
                        json=request.model_dump(exclude_none=True),
                        timeout=timeout,
                    )
                    response.raise_for_status()
                    responses.append(response.json())
            except httpx.HTTPStatusError as exc:
                log.error(
                    f"Error response {exc.response.status_code} while requesting {exc.request.url!r}."
                )
                responses.append({})
            except httpx.TimeoutException as exc:
                log.error(f"Request to {exc.request.url!r} timed out!")
                responses.append({})
            except httpx.RequestError as exc:
                log.error(
                    f"An error occurred while requesting {exc.request.url!r}."
                )
                responses.append({})

    return responses

ehr(func=None, *, workflow, num=1)

A decorator that wraps around a data generator function and returns an EHRClient

PARAMETER DESCRIPTION
func

The function to be decorated. If None, this allows the decorator to be used with arguments.

TYPE: Optional[Callable] DEFAULT: None

workflow

The workflow identifier which should match an item in the Workflow enum. This specifies the context in which the EHR function will operate.

TYPE: [str]

num

The number of requests to generate in the queue; defaults to 1.

TYPE: int DEFAULT: 1

RETURNS DESCRIPTION
Callable

A decorated callable that incorporates EHR functionality or the decorator itself if 'func' is None, allowing it to be used as a parameterized decorator.

TYPE: Union[Callable[..., Any], Callable[[F], F]]

RAISES DESCRIPTION
ValueError

If the workflow does not correspond to any defined enum or if use case is not configured.
NotImplementedError

If the use case class is not one of the supported types.
Example

@ehr(workflow='patient-view', num=2) def generate_data(self, config): # Function implementation

Source code in healthchain/clients/ehrclient.py 
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def ehr(
    func: Optional[F] = None, *, workflow: Workflow, num: int = 1
) -> Union[Callable[..., Any], Callable[[F], F]]:
    """
    A decorator that wraps around a data generator function and returns an EHRClient

    Parameters:
        func (Optional[Callable]): The function to be decorated. If None, this allows the decorator to
                                   be used with arguments.
        workflow ([str]): The workflow identifier which should match an item in the Workflow enum.
                                  This specifies the context in which the EHR function will operate.
        num (int): The number of requests to generate in the queue; defaults to 1.

    Returns:
        Callable: A decorated callable that incorporates EHR functionality or the decorator itself
                  if 'func' is None, allowing it to be used as a parameterized decorator.

    Raises:
        ValueError: If the workflow does not correspond to any defined enum or if use case is not configured.
        NotImplementedError: If the use case class is not one of the supported types.

    Example:
        @ehr(workflow='patient-view', num=2)
        def generate_data(self, config):
            # Function implementation
    """

    def decorator(func: F) -> F:
        func.is_client = True

        @wraps(func)
        def wrapper(self, *args: Any, **kwargs: Any) -> EHRClient:
            # Validate function decorated is a use case base class
            assert issubclass(
                type(self), BaseUseCase
            ), f"{self.__class__.__name__} must be subclass of valid Use Case strategy!"

            # Validate workflow is a valid workflow
            try:
                workflow_enum = Workflow(workflow)
            except ValueError as e:
                raise ValueError(
                    f"{e}: please select from {[x.value for x in Workflow]}"
                )

            # Set workflow in data generator if configured
            data_generator_attributes = find_attributes_of_type(self, CdsDataGenerator)
            for i in range(len(data_generator_attributes)):
                attribute_name = data_generator_attributes[i]
                try:
                    assign_to_attribute(
                        self, attribute_name, "set_workflow", workflow_enum
                    )
                except Exception as e:
                    log.error(
                        f"Could not set workflow {workflow_enum.value} for data generator method {attribute_name}: {e}"
                    )
                if i > 1:
                    log.warning("More than one DataGenerator instances found.")

            # Wrap the function in EHRClient with workflow and strategy passed in
            if self.type in UseCaseType:
                method = EHRClient(func, workflow=workflow_enum, strategy=self.strategy)
                # Generate the number of requests specified with method
                for _ in range(num):
                    method.generate_request(self, *args, **kwargs)
            else:
                raise NotImplementedError(
                    f"Use case {self.type} not recognised, check if implemented."
                )
            return method

        return wrapper

    if func is None:
        return decorator
    else:
        return decorator(func)