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

class TestTask(unittest.TestCase):
    def setUp(self):
        # Prepare test DataFrame
        self.data = {
            'date': pd.date_range(start='2024-01-01', periods=10, freq='D'),
            'sales': [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
        }
        self.df = pd.DataFrame(self.data)
        # Patch plt.show to avoid blocking
        self._original_show = plt.show
        plt.show = lambda *args, **kwargs: None

    def tearDown(self):
        plt.show = self._original_show

    def test_moving_average_column(self):
        import user_code
        importlib.reload(user_code)
        df = self.df.copy()
        user_code.plot_sales_with_moving_average(df)
        has_col = 'MovingAverage' in df.columns
        correct_values = df['MovingAverage'].iloc[6] == sum(self.data['sales'][:7])/7
        _dynamic_test(
            self,
            has_col and correct_values,
            "Function correctly calculates 7-day moving average and adds 'MovingAverage' column.",
            f"Missing or incorrect 'MovingAverage' column in DataFrame."
        )

    def test_plot_lines_count(self):
        import user_code
        importlib.reload(user_code)
        df = self.df.copy()
        plt.clf()
        user_code.plot_sales_with_moving_average(df)
        lines = plt.gca().get_lines()
        _dynamic_test(
            self,
            len(lines) >= 2,
            "Both sales and moving average lines are plotted.",
            f"Expected at least 2 lines on the plot, found {len(lines)}."
        )

    def test_axis_labels_and_title(self):
        import user_code
        importlib.reload(user_code)
        df = self.df.copy()
        plt.clf()
        user_code.plot_sales_with_moving_average(df)
        ax = plt.gca()
        xlabel = ax.get_xlabel()
        ylabel = ax.get_ylabel()
        title = ax.get_title()
        _dynamic_test(
            self,
            xlabel.lower() == 'date' and ylabel.lower() == 'sales' and 'moving average' in title.lower(),
            "Axis labels and title are correct.",
            f"Expected xlabel 'Date', ylabel 'Sales', and title containing 'Moving Average'. Got xlabel '{xlabel}', ylabel '{ylabel}', title '{title}'."
        )

    def test_legend_present(self):
        import user_code
        importlib.reload(user_code)
        df = self.df.copy()
        plt.clf()
        user_code.plot_sales_with_moving_average(df)
        ax = plt.gca()
        legend = ax.get_legend()
        labels = legend.get_texts() if legend else []
        label_texts = [t.get_text().lower() for t in labels]
        _dynamic_test(
            self,
            'daily sales' in label_texts and '7-day moving average' in label_texts,
            "Legend includes both 'Daily Sales' and '7-Day Moving Average'.",
            f"Legend missing required labels. Found: {label_texts}"
        )

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

Advance your Python automation skills by learning to generate analytical summaries, business reports, and visual dashboards automatically. This course guides you through practical workflows for automating data analysis, reporting, and visualization tasks using Python, pandas, matplotlib, and seaborn.

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: Plot Sales Moving Average

Løsning