Data Seeding Scripts For Analysis Ready Dataset #53
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alxmrs
reviewed
Sep 14, 2023
| def get_pressure_levels_arg(pressure_levels_group: str): | ||
| return PRESSURE_LEVELS_GROUPS[pressure_levels_group] | ||
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| class LoadTemporalDataForDateDoFn(beam.DoFn): |
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Can we make this a PTransform instead?
| # Make sure we print the date as part of the error for easier debugging | ||
| # if something goes wrong. Note "from e" will also raise the details of the | ||
| # original exception. | ||
| raise Exception(f"Error loading {year}-{month}-{day}") from e |
src/arco_era5/update.py
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| init_date: str | ||
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| def expand(self, pcoll: beam.PCollection) -> beam.PCollection: | ||
| return pcoll | beam.Map(update, target=self.target, init_date=self.init_date) |
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Do you want to make this MapTuple?
src/arco_era5/update.py
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| def update(offset_ds: Tuple[int, xr.Dataset, str], target: str, init_date: str): | ||
| """Generate region slice and update zarr array directly""" | ||
| key, ds = offset_ds |
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If this is called with MapTuple, then you wouldn't have to unpack this.
src/arco_era5/update.py
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| date = datetime.datetime.strptime(init_date, '%Y-%m-%d') + datetime.timedelta(days=offset / HOURS_PER_DAY) | ||
| date_str = date.strftime('%Y-%m-%d') |
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Why do we parse a date string into a datetime, then write it back to a string?
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This is only for logs. So we can see the logs like below.
Started 10m_u_component_of_wind for 2014-06-29
Done 10m_u_component_of_wind for 2014-06-29
DarshanSP19
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Closing this PR as I've raised a separate PR including these changes and for CO data back fill scripts. Here #58 |
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Here are some changes in the current script to initialize the
zarrstore from some specific date and a script to seed the data later on in the dataset.Change Includes
netcdf_to_zarrscript.--init_date,--from_init_dateand--only_initialize_store.--temp_locationfrom arguments as the pipeline is ignoring it while running onDataflowRunner.zarrarray itself without involving thexarraylayer and chunking scheme.source_data.pyfromnetcdf_to_zarr.pyas it's reused in the data seeding script.netcdf_to_zarrscript can now be used in three different ways.start_datetoend_dateand write chunks. (Current flow)init_datetoend_dateand write chunks fromstart_datetoend_date. The other values which are falling beyond the range ofstart_dateandend_datewill remainnans. (Required--from_init_dateand optional--init_date.)update_data.py. (Required--only_initialize_storeand optional--init_date)Some defaults
init_datewill be1900-01-01. Can be changed via--init_datearg.--only_initialize_storewhich will only create stores and not write data.