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update samples from Release-101 as a part of SDK release

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amlrelsa-ms
2021-06-05 02:54:13 +00:00
parent a2d20b0f47
commit ec97207bb1
1 changed files with 3 additions and 3 deletions
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6
how-to-use-azureml/automated-machine-learning/continuous-retraining/upload_weather_data.py
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@@ -54,17 +54,17 @@ try:
end_time_last_slice = ds.data_changed_time.replace(tzinfo=None) end_time_last_slice = ds.data_changed_time.replace(tzinfo=None)
print("Dataset {0} last updated on {1}".format(args.ds_name, print("Dataset {0} last updated on {1}".format(args.ds_name,
end_time_last_slice)) end_time_last_slice))
except Exception as e: except Exception:
print(traceback.format_exc()) print(traceback.format_exc())
print("Dataset with name {0} not found, registering new dataset.".format(args.ds_name)) print("Dataset with name {0} not found, registering new dataset.".format(args.ds_name))
register_dataset = True register_dataset = True
end_time_last_slice = datetime.today() - relativedelta(weeks=2) end_time_last_slice = datetime.today() - relativedelta(weeks=4)
end_time = datetime.utcnow() end_time = datetime.utcnow()
train_df = get_noaa_data(end_time_last_slice, end_time) train_df = get_noaa_data(end_time_last_slice, end_time)
if train_df.size > 0: if train_df.size > 0:
print("Received {0} rows of new data after {0}.".format( print("Received {0} rows of new data after {1}.".format(
train_df.shape[0], end_time_last_slice)) train_df.shape[0], end_time_last_slice))
folder_name = "{}/{:04d}/{:02d}/{:02d}/{:02d}/{:02d}/{:02d}".format(args.ds_name, end_time.year, folder_name = "{}/{:04d}/{:02d}/{:02d}/{:02d}/{:02d}/{:02d}".format(args.ds_name, end_time.year,
end_time.month, end_time.day, end_time.month, end_time.day,