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

class TestTask(unittest.TestCase):
    def setUp(self):
        self.user_code = importlib.import_module("user_code")
        self.data = [
            {'sales': 100, 'timestamp': '2024-05-01'},
            {'sales': 200, 'timestamp': '2024-05-02'},
            {'sales': 150, 'timestamp': '2024-05-08'},
            {'sales': 300, 'timestamp': '2024-05-10'},
            {'sales': 120, 'timestamp': '2024-05-15'},
            {'sales': 180, 'timestamp': '2024-05-16'},
            {'sales': 220, 'timestamp': '2024-05-22'},
            {'sales': 140, 'timestamp': '2024-05-23'},
        ]

    def test_timestamps_converted(self):
        # Check that timestamps are converted to datetime
        result = self.user_code.weekly_sales_summary(self.data)
        df = pd.DataFrame(self.data)
        df['timestamp'] = pd.to_datetime(df['timestamp'])
        _dynamic_test(
            self,
            pd.api.types.is_datetime64_any_dtype(df['timestamp']),
            "Timestamps are converted to pandas datetime objects.",
            "Timestamps are not converted to pandas datetime objects."
        )

    def test_week_column_created(self):
        # Check that week column is created and is present in the result
        result = self.user_code.weekly_sales_summary(self.data)
        _dynamic_test(
            self,
            isinstance(result, pd.DataFrame) and 'week' in result.columns,
            "Week column is present in the summary DataFrame.",
            "Week column is missing from the summary DataFrame."
        )

    def test_grouped_and_summed_by_week(self):
        # Check that sales are summed per week correctly
        result = self.user_code.weekly_sales_summary(self.data)
        # Manually compute expected sums
        # May 1-2: 100+200 = 300 (week starting 2024-04-29)
        # May 8,10: 150+300 = 450 (week starting 2024-05-06)
        # May 15,16: 120+180 = 300 (week starting 2024-05-13)
        # May 22,23: 220+140 = 360 (week starting 2024-05-20)
        expected = pd.DataFrame({
            'week': [pd.Timestamp('2024-04-29'), pd.Timestamp('2024-05-06'), pd.Timestamp('2024-05-13'), pd.Timestamp('2024-05-20')],
            'sales': [300, 450, 300, 360]
        })
        # Merge to compare
        merged = pd.merge(result, expected, on='week', how='outer', suffixes=('', '_expected'))
        correct = all(merged['sales'] == merged['sales_expected'])
        _dynamic_test(
            self,
            correct,
            "Sales values are correctly summed for each week.",
            f"Sales values are incorrect. Got: {result}, Expected: {expected}"
        )

    def test_returns_dataframe(self):
        # Check that the function returns a DataFrame
        result = self.user_code.weekly_sales_summary(self.data)
        _dynamic_test(
            self,
            isinstance(result, pd.DataFrame),
            "The function returns a pandas DataFrame.",
            f"The function does not return a pandas DataFrame. Got: {type(result)}"
        )

    def test_multiple_records_same_week(self):
        # All records in same week
        test_data = [
            {'sales': 10, 'timestamp': '2024-05-01'},
            {'sales': 20, 'timestamp': '2024-05-02'},
            {'sales': 30, 'timestamp': '2024-05-03'},
        ]
        result = self.user_code.weekly_sales_summary(test_data)
        expected_sum = 60
        _dynamic_test(
            self,
            len(result) == 1 and result.iloc[0]['sales'] == expected_sum,
            "Multiple records in the same week are summed correctly.",
            f"Expected sales sum {expected_sum}, got {result.iloc[0]['sales']}"
        )

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: Generate Weekly Summary Table

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