
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import sys
import io
import pandas as pd

class TestTask(unittest.TestCase):
    def setUp(self):
        self.df = pd.DataFrame({
            'principal': [10000, 20000, 15000, 25000, 18000],
            'interest_rate': [0.05, 0.07, 0.09, 0.04, 0.08],
            'risk_score': [0.6, 0.8, 0.75, 0.65, 0.9]
        })

    def test_filter_high_risk_loans(self):
        import user_code
        importlib.reload(user_code)
        df = self.df.copy()
        # Capture output
        f = io.StringIO()
        sys.stdout = f
        user_code.analyze_high_risk_loans(df)
        sys.stdout = sys.__stdout__
        output = f.getvalue().strip().split('\\n')
        # High risk loans are rows with risk_score > 0.7: index 1,2,4
        expected_principal = 20000 + 15000 + 18000
        expected_avg_rate = (0.07 + 0.09 + 0.08)/3
        _dynamic_test(
            self,
            str(expected_principal) in output[0],
            "Correct total principal printed for high-risk loans",
            f"Expected total principal {expected_principal}, got {output[0]}"
        )
        _dynamic_test(
            self,
            abs(float(output[1]) - expected_avg_rate) < 1e-6,
            "Correct average interest rate printed for high-risk loans",
            f"Expected average interest rate {expected_avg_rate}, got {output[1]}"
        )

    def test_no_high_risk_loans(self):
        import user_code
        importlib.reload(user_code)
        # All risk_scores <= 0.7
        df = pd.DataFrame({
            'principal': [5000, 8000],
            'interest_rate': [0.03, 0.04],
            'risk_score': [0.5, 0.7]
        })
        f = io.StringIO()
        sys.stdout = f
        user_code.analyze_high_risk_loans(df)
        sys.stdout = sys.__stdout__
        output = f.getvalue().strip().split('\\n')
        # Should print 0 and nan
        _dynamic_test(
            self,
            output[0] == '0',
            "Prints 0 for total principal when no high-risk loans",
            f"Expected 0 for total principal, got {output[0]}"
        )
        _dynamic_test(
            self,
            output[1].lower() == 'nan',
            "Prints nan for average interest rate when no high-risk loans",
            f"Expected nan for average interest rate, got {output[1]}"
        )

    def test_all_high_risk_loans(self):
        import user_code
        importlib.reload(user_code)
        # All risk_scores > 0.7
        df = pd.DataFrame({
            'principal': [3000, 4000],
            'interest_rate': [0.1, 0.12],
            'risk_score': [0.8, 0.9]
        })
        f = io.StringIO()
        sys.stdout = f
        user_code.analyze_high_risk_loans(df)
        sys.stdout = sys.__stdout__
        output = f.getvalue().strip().split('\\n')
        expected_principal = 3000 + 4000
        expected_avg_rate = (0.1 + 0.12)/2
        _dynamic_test(
            self,
            str(expected_principal) in output[0],
            "Correct total principal when all loans are high-risk",
            f"Expected total principal {expected_principal}, got {output[0]}"
        )
        _dynamic_test(
            self,
            abs(float(output[1]) - expected_avg_rate) < 1e-6,
            "Correct average interest rate when all loans are high-risk",
            f"Expected average interest rate {expected_avg_rate}, got {output[1]}"
        )

def _dynamic_test(test_case, condition, success_message, failure_message):
    if condition:
        test_case._testMethodName = success_message
        test_case.assertTrue(True, success_message)
    else:
        test_case._testMethodName = failure_message
        test_case.fail(failure_message)

def normalize_text(text):
    text = text.lower()
    text = re.sub(r"\\s{2,}", " ", text)
    text = re.sub(r"\\s*([,:?])\\s*", r"\\1 ", text)
    return text.strip()

def change_var(code: str, var_name: str, value: str) -> str:
    tree = ast.parse(code)
    lines = code.splitlines()
    changed = False
    # Collect all assignment nodes to modify
    assign_nodes = [
        (i, node)
        for i, node in enumerate(tree.body)
        if isinstance(node, ast.Assign)
        and any(isinstance(target, ast.Name) and target.id == var_name for target in node.targets)
    ]

    # If nothing to change, return unmodified code
    if not assign_nodes:
        return code

    # Perform replacements for all matching assignments (from last to first to not break line offsets)
    for i, node in reversed(assign_nodes):
        start_line = node.lineno - 1
        line = lines[start_line]
        indent = ' ' * (len(line) - len(line.lstrip()))
        lines[start_line] = f"{indent}{var_name} = {value}"
        next_line = len(lines)
        for next_node in tree.body[i+1:]:
            if hasattr(next_node, 'lineno'):
                next_line = next_node.lineno - 1
                break
        if next_line > start_line + 1:
            lines[start_line+1:next_line] = []
        changed = True

    return '\\n'.join(lines) if changed else code

if __name__ == "__main__":
    unittest.main()


test_main.py

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Challenge: Analyze Loan Portfolio Risk

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Challenge: Analyze Loan Portfolio Risk

Ratkaisu