
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 user_code

class TestTask(unittest.TestCase):
    def setUp(self):
        importlib.reload(user_code)
        self.volumes = [24.3, 24.7, 24.5, 24.6, 24.8, 24.4, 24.7, 24.6, 24.9, 24.5, 24.7, 24.8, 24.6]
        plt.close('all')

    def test_histogram_created(self):
        plt.close('all')
        user_code.plot_titration_histogram(self.volumes)
        figs = list(map(plt.figure, plt.get_fignums()))
        _dynamic_test(
            self,
            len(figs) > 0,
            "A figure was created by the function.",
            "No figure was created by the function."
        )
        fig = figs[-1]
        axes = fig.get_axes()
        _dynamic_test(
            self,
            len(axes) > 0,
            "An axis was created in the figure.",
            "No axes found in the figure."
        )
        ax = axes[0]
        # Check if at least one histogram bar exists
        patches = ax.patches
        _dynamic_test(
            self,
            len(patches) > 0,
            "Histogram bars were plotted.",
            "No histogram bars were plotted."
        )

    def test_xlabel(self):
        plt.close('all')
        user_code.plot_titration_histogram(self.volumes)
        fig = plt.gcf()
        ax = fig.get_axes()[0]
        xlabel = ax.get_xlabel()
        _dynamic_test(
            self,
            xlabel == "Titration Volume (mL)",
            "X-axis label is correctly set.",
            f"X-axis label is '{xlabel}', expected 'Titration Volume (mL)'"
        )

    def test_ylabel(self):
        plt.close('all')
        user_code.plot_titration_histogram(self.volumes)
        fig = plt.gcf()
        ax = fig.get_axes()[0]
        ylabel = ax.get_ylabel()
        _dynamic_test(
            self,
            ylabel == "Frequency",
            "Y-axis label is correctly set.",
            f"Y-axis label is '{ylabel}', expected 'Frequency'"
        )

    def test_title(self):
        plt.close('all')
        user_code.plot_titration_histogram(self.volumes)
        fig = plt.gcf()
        ax = fig.get_axes()[0]
        title = ax.get_title()
        _dynamic_test(
            self,
            title == "Distribution of Titration Volumes",
            "Plot title is correctly set.",
            f"Plot title is '{title}', expected 'Distribution of Titration Volumes'"
        )

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

An engaging, hands-on course introducing Python programming through real-world chemistry problems. Learn to clean experimental data, perform molar calculations, visualize spectra, and analyze reaction rates using Python and scientific libraries.

Learn Python basics through chemistry-themed examples, focusing on variables, data types, and simple calculations relevant to laboratory work.

Dive into real-world chemistry data: clean, process, and analyze raw experimental results using Python.

Explore how to visualize and analyze chemical spectra and reaction rates using Python's scientific libraries.

Challenge: Visualize Titration Results

Ratkaisu

Challenge: Visualize Titration Results

Ratkaisu