def disabled_test_time_series_api_write():
prediction_storage_provider = TimeSeriesAPIPredictionStorageProvider(
_get_config())
prediction_data = PredictionData(name=name,
time_range=time_range,
data=data)
prediction_storage_provider.put_predictions(prediction_data)
def test_name_lookup_bug1():
config = _get_config()
logger.info("")
logger.info("WRITING Data 1 ---------------")
prediction_storage_provider = TimeSeriesAPIPredictionStorageProvider(
config)
name = "an inconspicuous tag name"
in_meta = {"name": name, "unit": unit, "asset_id": asset}
prediction_data = PredictionDataSet(meta_data=in_meta,
time_range=time_range,
data=data1_wrapped)
out_meta1 = prediction_storage_provider.put_prediction(
prediction_data=prediction_data)
logger.info(pprint.pformat(out_meta1))
logger.info("")
logger.info("WRITING Data 2 ---------------")
name2 = f"{name}_with_apendage"
in_meta2 = {"name": name2, "unit": unit, "asset_id": asset}
prediction_data2 = PredictionDataSet(meta_data=in_meta2,
time_range=time_range,
data=data2_wrapped)
out_meta2 = prediction_storage_provider.put_prediction(
prediction_data=prediction_data2)
logger.info(pprint.pformat(out_meta2))
logger.info("")
logger.info("READING ---------------")
sensor_data_provider = TimeSeriesAPISensorDataProvider(config)
sensor_data = sensor_data_provider.get_data_for_range(
spec=spec, time_range=time_range)
def prediction_storage_provider_factory(prediction_storage_provider_config):
prediction_storage_provider_type = prediction_storage_provider_config.get(
"type", None
)
prediction_storage_provider = None
if "time_series_api" == prediction_storage_provider_type:
from latigo.time_series_api import TimeSeriesAPIPredictionStorageProvider
prediction_storage_provider = TimeSeriesAPIPredictionStorageProvider(
prediction_storage_provider_config
)
elif "influx" == prediction_storage_provider_type:
from latigo.prediction_storage_provider import InfluxPredictionStorageProvider
prediction_storage_provider = InfluxPredictionStorageProvider(
prediction_storage_provider_config
)
elif "mock" == prediction_storage_provider_type:
prediction_storage_provider = MockPredictionStorageProvider(
prediction_storage_provider_config
)
else:
prediction_storage_provider = DevNullPredictionStorageProvider(
prediction_storage_provider_config
)
return prediction_storage_provider
def test_time_series_api_write_read():
config = _get_config()
logger.info("")
logger.info("WRITING ---------------")
prediction_storage_provider = TimeSeriesAPIPredictionStorageProvider(
config)
meta_data = {"unit": unit, "asset_id": asset, "name": name}
prediction_data = PredictionDataSet(time_range=time_range,
data=data1_wrapped,
meta_data=meta_data)
meta = prediction_storage_provider.put_prediction(
prediction_data=prediction_data)
logger.info(pprint.pformat(meta))
logger.info("")
logger.info("READING ---------------")
sensor_data_provider = TimeSeriesAPISensorDataProvider(config)
sensor_data = sensor_data_provider.get_data_for_range(
spec=spec, time_range=time_range)
def prediction_storage(config) -> TimeSeriesAPIPredictionStorageProvider:
prediction_storage = TimeSeriesAPIPredictionStorageProvider(
config["prediction_storage"])
return prediction_storage