import unittest
import user_code
import ast
import re   
import importlib
import csv
import unittest
import importlib
import os
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from PIL import Image

class TestTask(unittest.TestCase):
    def setUp(self):
        self.module_name = "user_code"
        self.df = pd.DataFrame({
            "date": pd.date_range(start="2024-04-01", periods=5, freq="D"),
            "sales": [100, 120, 90, 130, 110]
        })
        self.output_path = "test_sales_trend_chart.png"
        if os.path.exists(self.output_path):
            os.remove(self.output_path)

    def tearDown(self):
        if os.path.exists(self.output_path):
            os.remove(self.output_path)

    def test_chart_is_saved_as_png(self):
        import user_code
        importlib.reload(user_code)
        user_code.plot_sales_trend_chart(self.df, "date", "sales", "Test Sales", self.output_path)
        exists = os.path.exists(self.output_path)
        _dynamic_test(
            self,
            exists,
            "Chart file saved as PNG.",
            "PNG file was not saved at the specified output path."
        )
        if exists:
            img = Image.open(self.output_path)
            _dynamic_test(
                self,
                img.format == "PNG",
                "File is valid PNG image.",
                f"File at {self.output_path} is not a PNG image."
            )

    def test_plot_sales_against_dates(self):
        import user_code
        importlib.reload(user_code)
        plt.close("all")
        user_code.plot_sales_trend_chart(self.df, "date", "sales", "Test Sales", self.output_path)
        img = Image.open(self.output_path)
        arr = np.array(img)
        _dynamic_test(
            self,
            arr.std() > 0,
            "Image contains plotted data (not blank).",
            "Saved PNG appears to be blank."
        )

    def test_title_is_set(self):
        import user_code
        importlib.reload(user_code)
        plt.close("all")
        title_to_test = "My Unique Sales Chart"
        called = {}
        orig_savefig = plt.savefig
        def fake_savefig(*args, **kwargs):
            called['fig'] = plt.gcf()
            return orig_savefig(*args, **kwargs)
        plt.savefig = fake_savefig
        user_code.plot_sales_trend_chart(self.df, "date", "sales", title_to_test, self.output_path)
        plt.savefig = orig_savefig
        fig = called.get('fig')
        actual_title = None
        if fig:
            actual_title = fig.axes[0].get_title()
        _dynamic_test(
            self,
            actual_title == title_to_test,
            f"Title is set to '{title_to_test}'.",
            f"Expected title '{title_to_test}', got '{actual_title}'."
        )

    def test_axis_labels(self):
        import user_code
        importlib.reload(user_code)
        plt.close("all")
        called = {}
        orig_savefig = plt.savefig
        def fake_savefig(*args, **kwargs):
            called['fig'] = plt.gcf()
            return orig_savefig(*args, **kwargs)
        plt.savefig = fake_savefig
        user_code.plot_sales_trend_chart(self.df, "date", "sales", "Test Sales", self.output_path)
        plt.savefig = orig_savefig
        fig = called.get('fig')
        x_label, y_label = None, None
        if fig:
            x_label = fig.axes[0].get_xlabel()
            y_label = fig.axes[0].get_ylabel()
        _dynamic_test(
            self,
            x_label == "Date" and y_label == "Sales",
            "Axis labels are set to 'Date' and 'Sales'.",
            f"Expected x-label 'Date' and y-label 'Sales', got '{x_label}' and '{y_label}'."
        )

    def test_grid_lines_exist(self):
        import user_code
        importlib.reload(user_code)
        plt.close("all")
        called = {}
        orig_savefig = plt.savefig
        def fake_savefig(*args, **kwargs):
            called['fig'] = plt.gcf()
            return orig_savefig(*args, **kwargs)
        plt.savefig = fake_savefig
        user_code.plot_sales_trend_chart(self.df, "date", "sales", "Test Sales", self.output_path)
        plt.savefig = orig_savefig
        fig = called.get('fig')
        grid_on = False
        if fig:
            ax = fig.axes[0]
            # Modern matplotlib: check gridlines visibility via line objects
            x_grid_lines = ax.xaxis.get_gridlines()
            y_grid_lines = ax.yaxis.get_gridlines()
            grid_on = (
                any(line.get_visible() for line in x_grid_lines) and
                any(line.get_visible() for line in y_grid_lines)
            )
        _dynamic_test(
            self,
            grid_on,
            "Grid lines are enabled on the chart.",
            "Grid lines are not enabled on the chart."
        )

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
    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 not assign_nodes:
        return code
    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: Create a Sales Trend Chart

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