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In trying to ingest into our data lake we want to set up a pipeline to pull historical forecasts for backfilling in cases the pipeline has failed and for training purposes. Should it be possible to run something like this?
Running this I get a 500 status (internal server error).
The endpoint works if I set include_metadata to False and specify a forecast_horizon_minutes so I have previously just iterated through forecast_horizons to backfill data for my personal consumption. However this doesn’t work with include_metadata = True (which we would like to keep)
The text was updated successfully, but these errors were encountered:
National: You could try something like https://api.quartz.solar/v0/solar/GB/national/forecast?include_metadata=true&start_datetime_utc=2024-07-01&end_datetime_utc=2024-07-02&creation_limit_utc=2024-07-01, so including a creation_limit_utc, but the does take quite long unfortunately. We have optimized our database to make the recent data very fast to access
For GSP: Similar as above creation_limit_utc. This however might take a long time.
I run things in swagger https://api.quartz.solar/swagger, and sometimes it takes longer there than it does in cmd line, or python
I think in general if you are trying to backfill with forecasts then you should use creation_limit_utc otherwise you will just get the latest forecast, which will be more accurate than real time forecasts
In trying to ingest into our data lake we want to set up a pipeline to pull historical forecasts for backfilling in cases the pipeline has failed and for training purposes. Should it be possible to run something like this?
params = {'include_metadata': True
'historic': True,
'start_datetime_utc': "2024-07-01 00:00:00",
'end_datetime_utc': "2024-07-02 00:00:00"}
url = https://api.quartz.solar/v0/solar/GB/national/forecast
r = requests.get(
url=url,
headers={"Authorization": "Bearer " + access_token}, params=params
)
Running this I get a 500 status (internal server error).
The endpoint works if I set
include_metadata
toFalse
and specify aforecast_horizon_minutes
so I have previously just iterated through forecast_horizons to backfill data for my personal consumption. However this doesn’t work withinclude_metadata = True
(which we would like to keep)The text was updated successfully, but these errors were encountered: