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Powertrain Timeseries API Client

Bases: BasePowertrainAPIClient

Powertrain Timeseries API Client.

Swagger Documentation

Source code in reportconnectors/api_client/powertrain/timeseries/__init__.py 
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class PowertrainTimeseriesAPIClient(BasePowertrainAPIClient):
    """
    Powertrain Timeseries API Client.

    [Swagger Documentation](https://motion-pt-dev-we-timeseries-api.azurewebsites.net/swagger/index.html)
    """

    _status_prefix = "/timeseries"

    def get_timeseries_config(self, asset_id: int) -> TimeseriesConfigResponse:
        """
        Gets the list of available timeseries for asset identified by `asset_id`.
        Uses `/timeseries/report/config` endpoint

        Args:
            asset_id: Asset identifier

        Returns:
            Timeseries configuration.
        """
        endpoint = "api/report/Timeseries/Report/Config"
        params = {"assetId": asset_id}
        response = self._make_request(method="GET", endpoint=endpoint, params=params)
        response_model = self._decode_response_to_model(response, TimeseriesConfigResponse)
        return response_model

    def get_timeseries_limits(self, asset_id: int) -> AssetTimeseriesLimitsResponse:
        """
        Gets the collection of timeseries limits for asset identified by `asset_id`.
        Uses `/timeseries/limits` endpoint

        Args:
            asset_id: Asset identifier

        Returns:
            Timeseries limits.
        """
        endpoint = "/timeseries/timeseries/limits"
        params = {"assetId": asset_id}
        response = self._make_request(method="GET", endpoint=endpoint, params=params)
        response_model = self._decode_response_to_model(response, AssetTimeseriesLimitsResponse)
        return response_model

    def get_aggregated_timeseries(
        self, asset_id: int, start_date: DateType, end_date: DateType, symbolic_name: str
    ) -> AggregatedTimeseriesResponse:
        """
        Gets the list of aggregated timeseries for given asset id and time range.
        Uses `/timeseries/report/aggregated` endpoint.

        The aggregation resolution depends on the requested time range.

        Args:
            asset_id: Asset identifier
            start_date: Start date of the requested timeseries data
            end_date: End date of the requested timeseries data
            symbolic_name: Symbolic name identifying the requested timeseries.
                It can be found in the timeseries config response for the asset.

        Returns:
            List of aggregated timeseries.
        """
        endpoint = "/api/report/Timeseries/Report/AggregatedData"
        params = {
            "assetId": asset_id,
            "from": start_date.strftime(self._datetime_format),
            "to": end_date.strftime(self._datetime_format),
            "symbolicName": symbolic_name,
        }

        response = self._make_request(method="GET", endpoint=endpoint, params=params)
        response_model = self._decode_response_to_model(response, AggregatedTimeseriesResponse)
        return response_model

    def get_raw_timeseries(
        self, asset_id: int, start_date: DateType, end_date: DateType, symbolic_name: str
    ) -> RawTimeseriesResponse:
        """
        Gets the list of raw timeseries for given asset id and time range.
        Uses `/timeseries/report/raw` endpoint.

        The aggregation resolution depends on the requested time range.

        Args:
            asset_id: Asset identifier
            start_date: Start date of the requested timeseries data
            end_date: End date of the requested timeseries data
            symbolic_name: Symbolic name identifying the requested timeseries.
                It can be found in the timeseries config response for the asset.

        Returns:
            List of aggregated timeseries.
        """
        endpoint = "/api/report/Timeseries/Report/RawData"
        params = {
            "assetId": asset_id,
            "from": start_date.strftime(self._datetime_format),
            "to": end_date.strftime(self._datetime_format),
            "symbolicName": symbolic_name,
        }
        response = self._make_request(method="GET", endpoint=endpoint, params=params)
        response_model = self._decode_response_to_model(response, RawTimeseriesResponse)
        return response_model

get_aggregated_timeseries(asset_id, start_date, end_date, symbolic_name)

Gets the list of aggregated timeseries for given asset id and time range. Uses /timeseries/report/aggregated endpoint.

The aggregation resolution depends on the requested time range.

Parameters:

Name Type Description Default
asset_id int

Asset identifier

 required
start_date DateType

Start date of the requested timeseries data

 required
end_date DateType

End date of the requested timeseries data

 required
symbolic_name str

Symbolic name identifying the requested timeseries. It can be found in the timeseries config response for the asset.

 required

Returns:

Type Description
AggregatedTimeseriesResponse

List of aggregated timeseries.
Source code in reportconnectors/api_client/powertrain/timeseries/__init__.py 
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def get_aggregated_timeseries(
    self, asset_id: int, start_date: DateType, end_date: DateType, symbolic_name: str
) -> AggregatedTimeseriesResponse:
    """
    Gets the list of aggregated timeseries for given asset id and time range.
    Uses `/timeseries/report/aggregated` endpoint.

    The aggregation resolution depends on the requested time range.

    Args:
        asset_id: Asset identifier
        start_date: Start date of the requested timeseries data
        end_date: End date of the requested timeseries data
        symbolic_name: Symbolic name identifying the requested timeseries.
            It can be found in the timeseries config response for the asset.

    Returns:
        List of aggregated timeseries.
    """
    endpoint = "/api/report/Timeseries/Report/AggregatedData"
    params = {
        "assetId": asset_id,
        "from": start_date.strftime(self._datetime_format),
        "to": end_date.strftime(self._datetime_format),
        "symbolicName": symbolic_name,
    }

    response = self._make_request(method="GET", endpoint=endpoint, params=params)
    response_model = self._decode_response_to_model(response, AggregatedTimeseriesResponse)
    return response_model

get_raw_timeseries(asset_id, start_date, end_date, symbolic_name)

Gets the list of raw timeseries for given asset id and time range. Uses /timeseries/report/raw endpoint.

The aggregation resolution depends on the requested time range.

Parameters:

Name Type Description Default
asset_id int

Asset identifier

 required
start_date DateType

Start date of the requested timeseries data

 required
end_date DateType

End date of the requested timeseries data

 required
symbolic_name str

Symbolic name identifying the requested timeseries. It can be found in the timeseries config response for the asset.

 required

Returns:

Type Description
RawTimeseriesResponse

List of aggregated timeseries.
Source code in reportconnectors/api_client/powertrain/timeseries/__init__.py 
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def get_raw_timeseries(
    self, asset_id: int, start_date: DateType, end_date: DateType, symbolic_name: str
) -> RawTimeseriesResponse:
    """
    Gets the list of raw timeseries for given asset id and time range.
    Uses `/timeseries/report/raw` endpoint.

    The aggregation resolution depends on the requested time range.

    Args:
        asset_id: Asset identifier
        start_date: Start date of the requested timeseries data
        end_date: End date of the requested timeseries data
        symbolic_name: Symbolic name identifying the requested timeseries.
            It can be found in the timeseries config response for the asset.

    Returns:
        List of aggregated timeseries.
    """
    endpoint = "/api/report/Timeseries/Report/RawData"
    params = {
        "assetId": asset_id,
        "from": start_date.strftime(self._datetime_format),
        "to": end_date.strftime(self._datetime_format),
        "symbolicName": symbolic_name,
    }
    response = self._make_request(method="GET", endpoint=endpoint, params=params)
    response_model = self._decode_response_to_model(response, RawTimeseriesResponse)
    return response_model

get_timeseries_config(asset_id)

Gets the list of available timeseries for asset identified by asset_id. Uses /timeseries/report/config endpoint

Parameters:

Name Type Description Default
asset_id int

Asset identifier

 required

Returns:

Type Description
TimeseriesConfigResponse

Timeseries configuration.
Source code in reportconnectors/api_client/powertrain/timeseries/__init__.py 
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def get_timeseries_config(self, asset_id: int) -> TimeseriesConfigResponse:
    """
    Gets the list of available timeseries for asset identified by `asset_id`.
    Uses `/timeseries/report/config` endpoint

    Args:
        asset_id: Asset identifier

    Returns:
        Timeseries configuration.
    """
    endpoint = "api/report/Timeseries/Report/Config"
    params = {"assetId": asset_id}
    response = self._make_request(method="GET", endpoint=endpoint, params=params)
    response_model = self._decode_response_to_model(response, TimeseriesConfigResponse)
    return response_model

get_timeseries_limits(asset_id)

Gets the collection of timeseries limits for asset identified by asset_id. Uses /timeseries/limits endpoint

Parameters:

Name Type Description Default
asset_id int

Asset identifier

 required

Returns:

Type Description
AssetTimeseriesLimitsResponse

Timeseries limits.
Source code in reportconnectors/api_client/powertrain/timeseries/__init__.py 
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def get_timeseries_limits(self, asset_id: int) -> AssetTimeseriesLimitsResponse:
    """
    Gets the collection of timeseries limits for asset identified by `asset_id`.
    Uses `/timeseries/limits` endpoint

    Args:
        asset_id: Asset identifier

    Returns:
        Timeseries limits.
    """
    endpoint = "/timeseries/timeseries/limits"
    params = {"assetId": asset_id}
    response = self._make_request(method="GET", endpoint=endpoint, params=params)
    response_model = self._decode_response_to_model(response, AssetTimeseriesLimitsResponse)
    return response_model