
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import pandas as pd

class TestTask(unittest.TestCase):
    def setUp(self):
        self.df = pd.DataFrame({
            'loan_id': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
            'risk_score': [45, 60, 55, 70, 62, 49, 80, 73, 58, 66],
            'interest_rate': [5.2, 6.1, 5.8, 7.0, 6.5, 5.4, 7.5, 7.2, 6.0, 6.8]
        })

    def test_histogram_and_boxplot_displayed(self):
        import user_code
        importlib.reload(user_code)
        plt.close('all')
        user_code.visualize_loan_data(self.df)
        figs = [plt.figure(i) for i in plt.get_fignums()]
        _dynamic_test(
            self,
            len(figs) >= 2,
            "Two plots (histogram and boxplot) are displayed.",
            f"Expected at least two plots, found {len(figs)}."
        )

    def test_histogram_title_and_labels(self):
        import user_code
        importlib.reload(user_code)
        plt.close('all')
        user_code.visualize_loan_data(self.df)
        figs = [plt.figure(i) for i in plt.get_fignums()]
        # Histogram is the first figure
        ax = figs[0].axes[0] if figs and figs[0].axes else None
        _dynamic_test(
            self,
            ax is not None,
            "Histogram axis exists.",
            "Histogram axis not found."
        )
        title = ax.get_title()
        xlabel = ax.get_xlabel()
        ylabel = ax.get_ylabel()
        _dynamic_test(
            self,
            "risk" in title.lower() and "score" in title.lower(),
            "Histogram has descriptive title.",
            f"Histogram title is not descriptive: '{title}'"
        )
        _dynamic_test(
            self,
            "risk" in xlabel.lower(),
            "Histogram has descriptive x-axis label.",
            f"Histogram x-axis label is not descriptive: '{xlabel}'"
        )
        _dynamic_test(
            self,
            "loan" in ylabel.lower() or "count" in ylabel.lower() or "number" in ylabel.lower(),
            "Histogram has descriptive y-axis label.",
            f"Histogram y-axis label is not descriptive: '{ylabel}'"
        )

    def test_boxplot_title_and_labels(self):
        import user_code
        importlib.reload(user_code)
        plt.close('all')
        user_code.visualize_loan_data(self.df)
        figs = [plt.figure(i) for i in plt.get_fignums()]
        # Boxplot is the second figure
        ax = figs[1].axes[0] if len(figs) > 1 and figs[1].axes else None
        _dynamic_test(
            self,
            ax is not None,
            "Boxplot axis exists.",
            "Boxplot axis not found."
        )
        title = ax.get_title()
        xlabel = ax.get_xlabel()
        _dynamic_test(
            self,
            "box" in title.lower() and "interest" in title.lower(),
            "Boxplot has descriptive title.",
            f"Boxplot title is not descriptive: '{title}'"
        )
        _dynamic_test(
            self,
            "interest" in xlabel.lower() and "rate" in xlabel.lower(),
            "Boxplot has descriptive x-axis label.",
            f"Boxplot x-axis label is not descriptive: '{xlabel}'"
        )

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

A practical Python course tailored for banking professionals, focusing on real-world financial data analysis, risk assessment, and automation tasks. Learn how Python can streamline banking operations, analyze financial data, and solve common problems faced by bankers.

Learn how to use Python to analyze, manipulate, and visualize financial data relevant to banking operations.

Apply Python to assess credit risk, analyze loan portfolios, and perform key calculations relevant to banking risk management.

Explore how Python can automate banking tasks and help detect fraudulent activities using data analysis techniques.

Challenge: Visualize Loan Data

Ratkaisu

Challenge: Visualize Loan Data

Ratkaisu