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10
block.py
10
block.py
@ -100,6 +100,7 @@ def __main__(
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ownhome: str,
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payfrequency: str,
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monthsatresidence: str,
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state: str,
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#thxresponse->
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EventType: str,
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DigitalIdConfidence: str,
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@ -127,6 +128,7 @@ def __main__(
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"ownhome" : ownhome,
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"payfrequency" : payfrequency,
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"monthsatresidence" : monthsatresidence,
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"state" : state,
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"EventType" : EventType,
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"DigitalIdConfidence" : DigitalIdConfidence,
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"RiskRating" : RiskRating,
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@ -165,7 +167,13 @@ def __main__(
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df["application_timestamp"] = df["application_timestamp"].astype(str)
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# logger.info("prediction: %.8f", float(df['prediction'].iloc[0]))
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result = post_processing(df)
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# logger.info("Score: %.0f", float(result["hd_score_m1"]))
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logger.info("post_processed_data")
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logger.info(result)
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# State Check
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state_value = combined_df["state"].iloc[0]
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if pd.notnull(state_value) and state_value == "ZZ":
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result["hd_score_m1"] = 1250
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logger.info("post_processed_data after state check")
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logger.info(result)
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return result
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@ -89,6 +89,10 @@
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"monthsatresidence": {
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"type": ["number", "null"],
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"description": "Number of months the applicant has lived at their current residence."
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},
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"state": {
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"type": ["string", "null"],
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"description": "State of the current residence."
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}
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},
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"required": []
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@ -26,7 +26,8 @@ input_json = {
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"payfrequency": None,
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"lengthatbank": None,
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"educationlevel": None,
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"monthsatresidence": None
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"monthsatresidence": None,
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"state": None
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}
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