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BatchJob

Batch job.

Source code in hume/_batch/batch_job.py 
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class BatchJob:
    """Batch job."""

    TIMEOUT_MESSAGE = ("Connection to API has been terminated after {}s, but your job will continue to run. "
                       "Get a reference to your job with `client.get_job('{}')` at any time.")

    def __init__(self, client: "HumeBatchClient", job_id: str):
        """Construct a BatchJob.

        Args:
            client (HumeBatchClient): HumeBatchClient instance.
            job_id (str): Job ID.
        """
        self._client = client
        self.id = job_id

    def get_status(self) -> BatchJobStatus:
        """Get the status of the job.

        Returns:
            BatchJobStatus: The status of the `BatchJob`.
        """
        return self.get_details().state.status

    def get_predictions(self) -> Any:
        """Get `BatchJob` predictions.

        Returns:
            Any: Predictions for the `BatchJob`.
        """
        return self._client.get_job_predictions(self.id)

    def download_predictions(self, filepath: Union[str, Path]) -> None:
        """Download `BatchJob` predictions file.

        Args:
            filepath (Union[str, Path]): Filepath where predictions will be downloaded.
        """
        predictions = self.get_predictions()
        with Path(filepath).open("w") as f:
            json.dump(predictions, f)

    def download_artifacts(self, filepath: Union[str, Path]) -> None:
        """Download `BatchJob` artifacts zip file.

        Args:
            filepath (Optional[Union[str, Path]]): Filepath where artifacts will be downloaded.
        """
        self._client.download_job_artifacts(self.id, filepath)

    def get_details(self) -> BatchJobDetails:
        """Get details for the BatchJob.

        Note that the details for a job may be fetched before the job has completed.
        You may want to use `job.await_complete()` which will wait for the job to
        reach a terminal state before returning.

        Returns:
            BatchJobDetails: Details for the `BatchJob`.
        """
        return self._client.get_job_details(self.id)

    def await_complete(self, timeout: int = 300, raise_on_failed: bool = False) -> BatchJobDetails:
        """Block until the job has reached a terminal status.

        Args:
            timeout (int): Maximum time in seconds to await. If the timeout is reached
                before the job reaches a terminal state the job will continue to be processed,
                but a `HumeClientException` will be raised to the caller of `await_complete`.
            raise_on_failed (bool): If set to True and job fails an exception will be raised.

        Raises:
            ValueError: If the timeout is not valid.
            HumeClientException: If the `BatchJob` has not reached a terminal state within
                the specified timeout. Also can be raised if `raise_on_failed` is set and
                the job reaches a `FAILED` terminal state.

        Returns:
            BatchJobDetails: Details for the `BatchJob`.
        """
        if timeout < 1:
            raise ValueError("timeout must be at least 1 second")

        # pylint: disable=unused-argument
        @retry(timeout_message=self.TIMEOUT_MESSAGE.format(timeout, self.id))
        def _await_complete(timeout: int = timeout) -> BatchJobDetails:
            details = self._client.get_job_details(self.id)
            if not BatchJobStatus.is_terminal(details.state.status):
                raise RetryIterError
            if raise_on_failed and details.state.status == BatchJobStatus.FAILED:
                raise HumeClientException(f"BatchJob {self.id} failed.")
            return details

        return _await_complete(timeout=timeout)

    def __repr__(self) -> str:
        """Get the string representation of the `BatchJob`.

        Returns:
            The the string representation of the `BatchJob`.
        """
        return f'Job(id="{self.id}")'

__init__(client, job_id)

Construct a BatchJob.

Parameters:

Name Type Description Default
client HumeBatchClient

HumeBatchClient instance.

 required
job_id str

Job ID.

 required
Source code in hume/_batch/batch_job.py 
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def __init__(self, client: "HumeBatchClient", job_id: str):
    """Construct a BatchJob.

    Args:
        client (HumeBatchClient): HumeBatchClient instance.
        job_id (str): Job ID.
    """
    self._client = client
    self.id = job_id

__repr__()

Get the string representation of the BatchJob.

Returns:

Type Description
str

The the string representation of the BatchJob.
Source code in hume/_batch/batch_job.py 
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def __repr__(self) -> str:
    """Get the string representation of the `BatchJob`.

    Returns:
        The the string representation of the `BatchJob`.
    """
    return f'Job(id="{self.id}")'

await_complete(timeout=300, raise_on_failed=False)

Block until the job has reached a terminal status.

Parameters:

Name Type Description Default
timeout int

Maximum time in seconds to await. If the timeout is reached before the job reaches a terminal state the job will continue to be processed, but a HumeClientException will be raised to the caller of await_complete.

 300
raise_on_failed bool

If set to True and job fails an exception will be raised.

 False

Raises:

Type Description
ValueError

If the timeout is not valid.
HumeClientException

If the BatchJob has not reached a terminal state within the specified timeout. Also can be raised if raise_on_failed is set and the job reaches a FAILED terminal state.

Returns:

Name Type Description
BatchJobDetails BatchJobDetails

Details for the BatchJob.
Source code in hume/_batch/batch_job.py 
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def await_complete(self, timeout: int = 300, raise_on_failed: bool = False) -> BatchJobDetails:
    """Block until the job has reached a terminal status.

    Args:
        timeout (int): Maximum time in seconds to await. If the timeout is reached
            before the job reaches a terminal state the job will continue to be processed,
            but a `HumeClientException` will be raised to the caller of `await_complete`.
        raise_on_failed (bool): If set to True and job fails an exception will be raised.

    Raises:
        ValueError: If the timeout is not valid.
        HumeClientException: If the `BatchJob` has not reached a terminal state within
            the specified timeout. Also can be raised if `raise_on_failed` is set and
            the job reaches a `FAILED` terminal state.

    Returns:
        BatchJobDetails: Details for the `BatchJob`.
    """
    if timeout < 1:
        raise ValueError("timeout must be at least 1 second")

    # pylint: disable=unused-argument
    @retry(timeout_message=self.TIMEOUT_MESSAGE.format(timeout, self.id))
    def _await_complete(timeout: int = timeout) -> BatchJobDetails:
        details = self._client.get_job_details(self.id)
        if not BatchJobStatus.is_terminal(details.state.status):
            raise RetryIterError
        if raise_on_failed and details.state.status == BatchJobStatus.FAILED:
            raise HumeClientException(f"BatchJob {self.id} failed.")
        return details

    return _await_complete(timeout=timeout)

download_artifacts(filepath)

Download BatchJob artifacts zip file.

Parameters:

Name Type Description Default
filepath Optional[Union[str, Path]]

Filepath where artifacts will be downloaded.

 required
Source code in hume/_batch/batch_job.py 
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def download_artifacts(self, filepath: Union[str, Path]) -> None:
    """Download `BatchJob` artifacts zip file.

    Args:
        filepath (Optional[Union[str, Path]]): Filepath where artifacts will be downloaded.
    """
    self._client.download_job_artifacts(self.id, filepath)

download_predictions(filepath)

Download BatchJob predictions file.

Parameters:

Name Type Description Default
filepath Union[str, Path]

Filepath where predictions will be downloaded.

 required
Source code in hume/_batch/batch_job.py 
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def download_predictions(self, filepath: Union[str, Path]) -> None:
    """Download `BatchJob` predictions file.

    Args:
        filepath (Union[str, Path]): Filepath where predictions will be downloaded.
    """
    predictions = self.get_predictions()
    with Path(filepath).open("w") as f:
        json.dump(predictions, f)

get_details()

Get details for the BatchJob.

Note that the details for a job may be fetched before the job has completed. You may want to use job.await_complete() which will wait for the job to reach a terminal state before returning.

Returns:

Name Type Description
BatchJobDetails BatchJobDetails

Details for the BatchJob.
Source code in hume/_batch/batch_job.py 
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def get_details(self) -> BatchJobDetails:
    """Get details for the BatchJob.

    Note that the details for a job may be fetched before the job has completed.
    You may want to use `job.await_complete()` which will wait for the job to
    reach a terminal state before returning.

    Returns:
        BatchJobDetails: Details for the `BatchJob`.
    """
    return self._client.get_job_details(self.id)

get_predictions()

Get BatchJob predictions.

Returns:

Name Type Description
Any Any

Predictions for the BatchJob.
Source code in hume/_batch/batch_job.py 
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def get_predictions(self) -> Any:
    """Get `BatchJob` predictions.

    Returns:
        Any: Predictions for the `BatchJob`.
    """
    return self._client.get_job_predictions(self.id)

get_status()

Get the status of the job.

Returns:

Name Type Description
BatchJobStatus BatchJobStatus

The status of the BatchJob.
Source code in hume/_batch/batch_job.py 
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def get_status(self) -> BatchJobStatus:
    """Get the status of the job.

    Returns:
        BatchJobStatus: The status of the `BatchJob`.
    """
    return self.get_details().state.status