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46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
import json
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import os
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import logging
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from predictions import prediction
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logger = logging.getLogger()
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logger.setLevel(logging.INFO)
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RUNTIME_ENVIRONMENT = os.environ.get("RUNTIME_ENVIRONMENT", "dev")
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def handler(event, context):
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"""
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Take in event and trigger the prediction pipeline
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"""
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logger.info("received event: " + str(event))
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# Assuming a file in a bucket landing for now?
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# Assuming we have a model to use
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body = json.loads(event["body"])
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data_path = body["file_location"]
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property_id = body["property_id"]
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portfolio_id = body["portfolio_id"]
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created_at = body["created_at"]
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try:
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# We could fix the model path but for the moment, we just take the best model path based on the registry
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outputs = prediction(model_path=None, data_path=data_path)
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# Store into s3, with key of {portfolio_id}-{property_id}
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storage_filepath = f"s3://retrofit-sap-predictions-{RUNTIME_ENVIRONMENT}/{portfolio_id}/{property_id}/" \
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f"{created_at}.csv"
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outputs.to_csv(storage_filepath)
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return storage_filepath
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except (Exception, KeyError, ValueError) as e:
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logger.info("Prediction failed")
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logger.info(e)
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if __name__ == "__main__":
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handler()
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