Converting Multi-Level Excel Test Cases to XMind Mind Maps Using Python

In software testing, managing and executing test cases is crucial, and while Excel is a common tool, large numbers of cases benefit from visual organization using mind maps; this article explains how to convert a multi‑level Excel test case file into an XMind mind‑map using Python.

1. Preparation Before converting, install the required libraries with: pip install openpyxl xmind-sdk 2. Reading Test Cases The example uses test_cases.xlsx containing a sheet named "Multiple Levels". The following Python code loads the workbook, defines a function to calculate indentation based on leading spaces, iterates through rows, extracts fields, and stores each row as a dictionary in a list:

from openpyxl import load_workbook
import re
# Open Excel file
workbook = load_workbook('test_cases.xlsx')
# Get worksheet
sheet = workbook['Multiple Levels']
# Determine indentation level from row data
def get_indentation(row_data):
    result = re.search(r'^(\s*)(\S.*)', row_data, re.IGNORECASE)
    if result:
        return len(result.group(1)) / 4
    else:
        return 0
# List to store data
data = []
# Iterate rows
for row in sheet.iter_rows(min_row=2, max_row=sheet.max_row, values_only=True):
    indentation = get_indentation(row[1])
    step_index = 2
    steps = []
    while sheet.cell(row=row[0]+1, column=step_index).value:
        if get_indentation(sheet.cell(row=row[0]+1, column=step_index).value) > indentation:
            steps[-1] += '
' + sheet.cell(row=row[0]+1, column=step_index).value.strip()
        else:
            steps.append(sheet.cell(row=row[0]+1, column=step_index).value.strip())
        step_index += 1
    row_dict = {
        "繁忙度": row[0],
        "问题描述": row[1].strip(),
        "步骤": steps,
        "预期结果": row[step_index].strip()
    }
    data.append(row_dict)
print(data)

3. Generating the XMind File Create an XMind workbook, sheet, and root topic:

from xmind.core import workbook, sheet, topic
# Create XMind workbook
xmind_workbook = workbook.Workbook()
# Set XMind file name
xmind_file = 'test_cases.xmind'
# Add a sheet to the workbook
xmind_sheet = xmind_workbook.addSheet()
xmind_sheet.setTitle('TestCases')
# Add root topic
root_topic = xmind_sheet.getRootTopic()
root_topic.setTitle('TestCases')

Then loop through each test case, adding it as a topic with its steps and expected result, setting appropriate markers and hierarchy levels:

# Loop through test cases and convert to XMind
for row in data:
    t = topic.TopicElement(ownerWorkbook=xmind_workbook)
    t.setTitle(row['问题描述'])
    t.setMarkerIds([row['繁忙度']])
    root_topic.addSubTopic(t)
    for i, step in enumerate(row['步骤']):
        step_topic = topic.TopicElement(ownerWorkbook=xmind_workbook)
        step_topic.setTitle(step)
        step_topic.setMarkerIds([row['繁忙度']])
        step_level = len(step.split('
')) if '
' in step else 1
        step_topic.setStructureClass(f"level-{step_level}")
        t.addSubTopic(step_topic)
    expected_topic = topic.TopicElement(ownerWorkbook=xmind_workbook)
    expected_topic.setTitle(row['预期结果'])
    expected_topic.setMarkerIds([row['繁忙度']])
    expected_topic.setStructureClass('level-3')
    t.addSubTopic(expected_topic)

The setMarkerIds() method assigns priority markers, and setStructureClass() defines the visual level (from level‑1 to level‑6) for each topic.

4. Saving the XMind File Finally, save the workbook to a file:

# Save XMind workbook to file
xmind_workbook.save(xmind_file)

5. Summary The article shows how to read hierarchical test case data from Excel with openpyxl, transform it into XMind topics using xmind-sdk, and produce a mind‑map that helps organize and visualize test cases effectively.