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

class TestTask(unittest.TestCase):
    def setUp(self):
        # Prepare the DataFrame
        self.data = {
            "Time": ["2024-06-01", "2024-06-02", "2024-06-03", "2024-06-04", "2024-06-05"],
            "DeviceA": [88, 90, 85, 87, 92],
            "DeviceB": [78, 80, 79, 82, 81],
            "DeviceC": [95, 94, 96, 97, 98]
        }
        self.df = pd.DataFrame(self.data)

    def test_plot_lines_and_labels(self):
        import user_code
        importlib.reload(user_code)
        plt.clf()
        # Call user's function
        user_code.plot_device_performance(self.df)
        # Get current axes
        ax = plt.gca()
        # Check title
        _dynamic_test(
            self,
            ax.get_title() and "performance" in ax.get_title().lower(),
            "Chart has a descriptive title",
            f"Expected a descriptive title, got: '{ax.get_title()}'",
        )
        # Check x/y labels
        _dynamic_test(
            self,
            ax.get_xlabel() and "time" in ax.get_xlabel().lower(),
            "X-axis is labeled appropriately",
            f"Expected x-axis labeled with 'Time', got: '{ax.get_xlabel()}'",
        )
        _dynamic_test(
            self,
            ax.get_ylabel() and ("performance" in ax.get_ylabel().lower()),
            "Y-axis is labeled appropriately",
            f"Expected y-axis labeled with 'Performance Metric', got: '{ax.get_ylabel()}'",
        )
        # Check number of lines
        lines = ax.get_lines()
        _dynamic_test(
            self,
            len(lines) == 3,
            "Three lines plotted for three devices",
            f"Expected 3 lines, got {len(lines)}",
        )

    def test_plot_colors(self):
        import user_code
        importlib.reload(user_code)
        plt.clf()
        user_code.plot_device_performance(self.df)
        ax = plt.gca()
        lines = ax.get_lines()
        # The order of lines is DeviceA, DeviceB, DeviceC
        color_map = ["blue", "green", "red"]
        for idx, expected_color in enumerate(color_map):
            actual_color = lines[idx].get_color()
            _dynamic_test(
                self,
                actual_color == expected_color,
                f"Device {chr(65+idx)} line is {expected_color}",
                f"Expected color '{expected_color}' for Device {chr(65+idx)}, got '{actual_color}'",
            )

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

Master Python as a powerful tool for automation engineering. This course guides you through practical and advanced Python techniques to automate repetitive tasks, analyze data, and interact with systems, all tailored for automation engineers. Each section blends engaging theory with hands-on, real-world challenges.

Learn how Python can automate repetitive and time-consuming tasks commonly faced by automation engineers, from log parsing to report generation.

Dive into data manipulation and analysis using Python and pandas, tailored for automation engineers handling structured data.

Master Python techniques for interacting with systems, automating tests, and analyzing results—core skills for automation engineers.

Challenge: Plot Device Performance

Рішення

Challenge: Plot Device Performance

Рішення