
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import pandas as pd
import io
from contextlib import redirect_stdout

class TestTask(unittest.TestCase):
    def setUp(self):
        self.df = pd.DataFrame({
            'date': ['2024-01-01', '2024-01-02', '2024-01-03', '2024-01-04', '2024-01-05'],
            'value': [100, 110, 90, 92, 130]
        })
        self.df_neg = pd.DataFrame({
            'date': ['2024-01-01', '2024-01-02', '2024-01-03', '2024-01-04', '2024-01-05'],
            'value': [200, 180, 170, 190, 160]
        })
        self.df_none = pd.DataFrame({
            'date': ['2024-01-01', '2024-01-02', '2024-01-03'],
            'value': [50, 52, 51]
        })

    def test_identifies_all_significant_changes(self):
        import user_code
        importlib.reload(user_code)
        changes = user_code.extract_significant_changes(self.df, 15)
        _dynamic_test(
            self,
            isinstance(changes, list) and len(changes) == 2,
            "Function identifies all significant changes above threshold",
            f"Expected 2 significant changes, got {len(changes)}"
        )
        expected = [
            {'index': 2, 'prev_index': 1, 'prev_value': 110, 'current_value': 90, 'change': -20},
            {'index': 4, 'prev_index': 3, 'prev_value': 92, 'current_value': 130, 'change': 38}
        ]
        for i, exp in enumerate(expected):
            chg = changes[i]
            _dynamic_test(
                self,
                all(k in chg for k in exp),
                f"Returned dictionary for change {i} has all required keys",
                f"Missing keys in returned dictionary: {chg}"
            )
            _dynamic_test(
                self,
                chg['index'] == exp['index'] and chg['prev_index'] == exp['prev_index'],
                f"Correct index and prev_index for change {i}",
                f"Expected index {exp['index']}, prev_index {exp['prev_index']} but got {chg['index']}, {chg['prev_index']}"
            )
            _dynamic_test(
                self,
                chg['prev_value'] == exp['prev_value'] and chg['current_value'] == exp['current_value'],
                f"Correct values for change {i}",
                f"Expected prev {exp['prev_value']}, curr {exp['current_value']} but got {chg['prev_value']}, {chg['current_value']}"
            )
            _dynamic_test(
                self,
                chg['change'] == exp['change'],
                f"Correct change value for change {i}",
                f"Expected change {exp['change']}, got {chg['change']}"
            )
    
    def test_positive_and_negative_changes(self):
        import user_code
        importlib.reload(user_code)
        changes = user_code.extract_significant_changes(self.df_neg, 15)
        _dynamic_test(
            self,
            isinstance(changes, list),
            "Function returns a list for negative changes",
            f"Expected a list, got {type(changes)}"
        )
        self.assertGreaterEqual(len(changes), 1)
        found_neg = any(chg['change'] < 0 for chg in changes)
        found_pos = any(chg['change'] > 0 for chg in changes)
        _dynamic_test(
            self,
            found_neg and found_pos,
            "Function handles both positive and negative significant changes",
            "Function did not detect both positive and negative significant changes"
        )

    def test_returns_empty_when_no_significant_change(self):
        import user_code
        importlib.reload(user_code)
        changes = user_code.extract_significant_changes(self.df_none, 15)
        _dynamic_test(
            self,
            isinstance(changes, list) and len(changes) == 0,
            "Function returns empty list when no significant changes are found",
            f"Expected empty list, got {changes}"
        )

    def test_prints_summary_report(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        with redirect_stdout(f):
            user_code.extract_significant_changes(self.df, 15)
        output = normalize_text(f.getvalue())
        expected1 = normalize_text("At 2, value changed from 110 to 90 (change: -20)")
        expected2 = normalize_text("At 4, value changed from 92 to 130 (change: 38)")
        _dynamic_test(
            self,
            expected1 in output and expected2 in output,
            "Summary report prints all significant changes",
            f"Expected lines not found in output: {output}"
        )

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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Learn to automate the generation of analytical summaries, business reports, and visual dashboards using Python. Alternate between concept introduction and hands-on automation tasks for real-world reporting scenarios.

Challenge: Extract and Report Key Insights

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