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54
block.py
54
block.py
@ -1,37 +1,21 @@
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import logging
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@flowx_block
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from score_processing import processing
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def example_function(request: dict) -> dict:
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# Configure logging
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# Processing logic here...
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
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)
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logger = logging.getLogger(__name__)
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def __main__(
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return {
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hd_score_m1: float,
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"meta_info": [
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hd_score_g1: float,
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{
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hd_score_s1: float,
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"name": "created_date",
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hd_score_s2: float,
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"type": "string",
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hd_score_s3: float,
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"value": "2024-11-05"
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hd_score_iso_m2: float,
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}
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hd_score_g2: float
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],
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) -> dict:
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"fields": [
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{
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data = {
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"name": "",
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"hd_score_m1": hd_score_m1,
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"type": "",
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"hd_score_g1": hd_score_g1,
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"value": ""
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"hd_score_s1": hd_score_s1,
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}
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"hd_score_s2": hd_score_s2,
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]
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"hd_score_s3": hd_score_s3,
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}
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"hd_score_iso_m2": hd_score_iso_m2,
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"hd_score_g2": hd_score_g2
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}
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final = processing(data)
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logger.info(f"Scores of application: {final}")
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return final
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# testing :
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# __main__
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@ -1,35 +1 @@
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{
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{}
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"$schema": "http://json-schema.org/draft-07/schema#",
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"type": "object",
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"properties": {
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"hd_score_m1": {
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"type": ["number", "null"],
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"description": "HD Fraud Score M1"
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},
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"hd_score_g1": {
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"type": ["number", "null"],
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"description": "HD Fraud Score G1"
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},
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"hd_score_g2": {
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"type": ["number", "null"],
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"description": "HD Fraud Score G1"
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},
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"hd_score_s1": {
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"type": ["number", "null"],
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"description": "HD Fraud Score S1"
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},
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"hd_score_s2": {
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"type": ["number", "null"],
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"description": "HD Fraud Score S2"
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},
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"hd_score_s3": {
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"type": ["number", "null"],
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"description": "HD Fraud Score S3"
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},
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"hd_score_iso_m2": {
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"type": ["number", "null"],
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"description": "HD Fraud Score M2"
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}
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},
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"required": []
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}
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@ -1 +1 @@
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{}
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@ -1,25 +1 @@
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{
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{}
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"$schema": "http://json-schema.org/draft-07/schema#",
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"type": "object",
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"properties": {
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"hd_score": {
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"type": ["number", "null"],
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"description": "HD fraud Score"
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},
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"recommended_action": {
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"type": ["string", "null"],
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"description": "Recommended Action"
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},
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"description": {
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"type": ["string", "null"],
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"description": "Description of Recommended Action"
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},
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"hd_action_reasoncode": {
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"type": ["string", "null"],
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"description": "HD Action Reasoncode"
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}
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}
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}
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@ -1,102 +0,0 @@
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import logging
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
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)
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logger = logging.getLogger(__name__)
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def processing(data: dict) -> dict:
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score_threshold = 1200
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score_threshold2 = 1225
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# ---- Compute hd_score based on hierarchy ----
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try:
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reason_hierarchy = [
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("hd_score_s1", "S1 Triggered", score_threshold, True),
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("hd_score_s2", "S2 Triggered", score_threshold, True),
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("hd_score_g1", "G1 Triggered", score_threshold, True),
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("hd_score_s3", "S3 Triggered", score_threshold, True),
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("hd_score_m1", "M1 Triggered", score_threshold, True),
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("hd_score_iso_m2", "M2 Triggered", score_threshold2, False),
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("hd_score_g2", "G2 Triggered", score_threshold2, False),
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]
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winning_score = None
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winning_reason = "Pass"
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winning_threshold = None
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for key, reason, threshold, use_gt in reason_hierarchy:
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score = data.get(key)
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if score is None:
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continue
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passes = (score > threshold) if use_gt else (score >= threshold)
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if passes:
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winning_score = score
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winning_reason = reason
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winning_threshold = threshold
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break
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if winning_score is None:
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winning_score = max([
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data.get("hd_score_s1", 0),
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data.get("hd_score_s2", 0),
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data.get("hd_score_g1", 0),
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data.get("hd_score_s3", 0),
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data.get("hd_score_m1", 0),
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data.get("hd_score_iso_m2", 0),
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data.get("hd_score_g2", 0),
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])
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winning_reason = "Pass"
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hd_score = winning_score
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except Exception as e:
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logging.error(f"Error calculating hd_score values: {e}")
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return {}
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# ---- recommended_action ----
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try:
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if winning_reason != "Pass":
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recommended_action = "Decline Application"
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else:
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recommended_action = "Pass Application"
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logging.info(f"recommended_action: {recommended_action}")
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except Exception as e:
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logging.error(f"Error assigning recommended_action: {e}")
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return {}
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# ---- description ----
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try:
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if winning_reason != "Pass":
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threshold_used = winning_threshold if winning_threshold is not None else score_threshold
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description = (
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f"HD Fraud Score is above the risk threshold {threshold_used}, "
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f"Recommended action: Decline Application"
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)
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else:
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description = (
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"HD Fraud Score is below the risk threshold, Recommended action: Pass Application"
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)
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logging.info(f"description: {description}")
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except Exception as e:
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logging.error(f"Error creating description: {e}")
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return {}
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# ---- hd_action_reasoncode ----
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hd_action_reasoncode = winning_reason
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logging.info(f"hd_action_reasoncode: {hd_action_reasoncode}")
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# ---- Return only original 4 fields ----
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return {
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"hd_score": hd_score,
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"recommended_action": recommended_action,
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"description": description,
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"hd_action_reasoncode": hd_action_reasoncode,
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}
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@ -1,17 +0,0 @@
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import unittest
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from block import __main__
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data = {'hd_score_m1': 1173.0, 'hd_score_g1': 1203.0, 'hd_score_s1': 1240.0, 'hd_score_s2': 0, 'hd_score_s3': 0, 'hd_score_iso_m2': 1001.0, 'hd_score_g2': 0.0}
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class TestBlock(unittest.TestCase):
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def test_main_success(self):
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# blockResult = main(data)
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blockResult = __main__(**data)
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# breakpoint()
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self.assertIsInstance(blockResult, dict, "Result should be a dictionary.")
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self.assertIn("hd_score", blockResult, "Result dictionary should contain 'hd_score' if success.")
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if __name__ == "__main__":
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unittest.main()
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