
import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import sys
import io

class TestTask(unittest.TestCase):
    def test_groupby_segment(self):
        import user_code
        importlib.reload(user_code)
        data = {
            "customer_id": [1, 2, 3, 4, 5, 6],
            "segment": ["A", "B", "A", "B", "C", "C"],
            "spend": [120.0, 80.0, 150.0, 60.0, 200.0, 180.0]
        }
        df = user_code.pd.DataFrame(data)
        segment_summary = df.groupby("segment")["spend"].mean().reset_index()
        expected_groups = set(["A", "B", "C"])
        actual_groups = set(segment_summary["segment"])
        _dynamic_test(
            self,
            actual_groups == expected_groups,
            "Data correctly grouped by segment.",
            f"Expected segments {expected_groups}, got {actual_groups}.",
        )

    def test_average_spend_per_segment(self):
        import user_code
        importlib.reload(user_code)
        data = {
            "customer_id": [1, 2, 3, 4, 5, 6],
            "segment": ["A", "B", "A", "B", "C", "C"],
            "spend": [120.0, 80.0, 150.0, 60.0, 200.0, 180.0]
        }
        df = user_code.pd.DataFrame(data)
        segment_summary = df.groupby("segment")["spend"].mean().reset_index()
        expected = {"A": 135.0, "B": 70.0, "C": 190.0}
        actual = dict(zip(segment_summary["segment"], segment_summary["spend"]))
        _dynamic_test(
            self,
            all(abs(actual[k] - v) < 0.001 for k, v in expected.items()),
            "Average spend per segment is calculated correctly.",
            f"Expected averages {expected}, got {actual}.",
        )

    def test_output_contains_summary(self):
        import user_code
        importlib.reload(user_code)
        f = io.StringIO()
        sys_stdout = sys.stdout
        sys.stdout = f
        user_code.summarize_customer_segments()
        sys.stdout = sys_stdout
        output = normalize_text(f.getvalue())
        # Check all segments and their averages appear in output
        checks = [
            "a 135.0" in output,
            "b 70.0" in output,
            "c 190.0" in output,
        ]
        _dynamic_test(
            self,
            all(checks),
            "Output summary contains all segments and correct averages.",
            f"Output summary missing expected segment averages: {output}",
        )

    def test_data_used_is_provided(self):
        import user_code
        importlib.reload(user_code)
        # Check that the function uses the provided data
        data = {
            "customer_id": [1, 2, 3, 4, 5, 6],
            "segment": ["A", "B", "A", "B", "C", "C"],
            "spend": [120.0, 80.0, 150.0, 60.0, 200.0, 180.0]
        }
        df = user_code.pd.DataFrame(data)
        segment_summary = df.groupby("segment")["spend"].mean().reset_index()
        expected = {"A": 135.0, "B": 70.0, "C": 190.0}
        actual = dict(zip(segment_summary["segment"], segment_summary["spend"]))
        _dynamic_test(
            self,
            all(abs(actual[k] - v) < 0.001 for k, v in expected.items()),
            "Provided data is used for processing.",
            f"Expected averages from provided data {expected}, got {actual}.",
        )

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: Segment Customers and Summarize Spend

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