Auto Insights

Version 1.0.0 — final stable release

Auto Insights is a Python and CustomTkinter desktop application that converts a validated dealership workbook into an executive dashboard, interactive sales analysis, charts, inventory-health indicators, plain-language findings, recommended actions, and a printable HTML report.

Important

AI-assisted development disclosure: I developed the project concept and business scenario, defined the functional and visual requirements, selected the analysis and dashboard features, tested each iteration, reported defects, evaluated workbook compatibility, and directed revisions through the final release. ChatGPT generated the implementation code in response to that direction and feedback. I am publishing this project as an example of requirements development, product direction, data-analysis planning, iterative testing, quality assurance, and responsible AI-assisted software development—not as code I wrote independently from scratch.

My role

• Defined the application as an internal dealership-analysis tool that could accept future editions of the same workbook structure.
• Selected the dashboard, sales-analysis, chart, inventory-health, findings, report-export, and workbook-selection workflows.
• Chose the clean interface direction, vivid blue accents, navigation structure, and responsive-layout priorities.
• Tested successive versions on Ubuntu and provided screenshots, bug reports, edge cases, and usability feedback.
• Required validation to reject incompatible workbooks without replacing the last successfully loaded data.
• Established the final Version 1.0.0 acceptance criteria and approved the completed workflow.

Main features

• Executive dashboard with current-year sales, prior-year growth, forecasts, inventory totals, performance highlights, and urgent alerts.
• Sales analysis filtered by year, dealership, and vehicle model.
• Five chart views: annual trend, monthly trend, sales by dealership, sales by model, and inventory versus demand.
• Inventory-health calculations using months of supply, condition classifications, filters, and recommendations.
• Plain-language findings and prioritized recommended actions.
• Printable HTML report export.
• User-selectable .xlsx or .xlsm workbooks with full structural validation before activation.
• Automatic detection of future years, current cutoff months, dealerships, and vehicle models.
• Remembered last-valid workbook path with safe fallback to the included default workbook.
• Responsive desktop layouts and keyboard shortcuts.

Screenshots

Sales Analysis

Charts

Inventory Health

Key Findings

Responsive Dashboard

Workbook workflow

1. Click Open Workbook or press Ctrl+O.
2. Select a dealership workbook in the documented format.
3. Auto Insights validates the complete workbook before it becomes active.
4. When validation succeeds, all five pages refresh from the selected data.
5. When validation fails, the previously validated workbook remains active.
6. Reload Data refreshes the currently active workbook.
7. The last successful workbook path is remembered for the next launch.
8. Use Included Default Workbook restores the bundled workbook.

The remembered path is stored outside the repository in the operating-system configuration directory. On Linux, the default location is:

~/.config/auto_insights/settings.json

Only the workbook path is stored there; dealership records are not copied into the settings file.

Required workbook format

See WORKBOOK_FORMAT.md for the complete specification.

Monthly_Sales

Year
Month
Location
Model
Units_Sold

YYYY_YTD_Summary

The worksheet year must match the latest sales year, such as 2028_YTD_Summary.

Location
Model
one YTD sales field, such as Jan_Sep_Sales or YTD_Sales
Projected_YYYY_Sales

Current_Inventory

Location
one column for each vehicle model

Dealership and model names are discovered from the workbook. New locations or models are supported when all worksheets remain consistent.

Included workbooks and data provenance

data/Ford_Revised_Dealership_Workbook.xlsx
sample_data/Auto_Insights_2028_Demo_Workbook.xlsx

The 2028 workbook contains synthetic demonstration data and verifies that the program can process a future edition without code changes.

The default 2026 workbook originated as the supplied input for the academic project. Its embedded author metadata has been removed from this portfolio copy. Before publishing or redistributing it, confirm that your course or institution permits public redistribution of supplied assignment data. If redistribution is not permitted, replace it with a fully synthetic workbook in the same documented format before making the repository public.

Installation

Requirements

• Python 3.10 or newer
• Tkinter
• CustomTkinter
• pandas
• openpyxl
• PyTest for the automated test suite

On Ubuntu, Tkinter may need to be installed separately:

sudo apt install python3-tk

Run the application

git clone https://github.com/YOUR-USERNAME/auto-insights.git
cd auto-insights
python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -r requirements.txt
python main.py

Testing

Run the complete automated suite with:

python -m pytest -v

Version 1.0.0 includes 80 automated tests covering workbook validation, dynamic-year handling, dashboard calculations, sales analysis, charts, inventory classifications, findings, HTML export, responsive helpers, settings persistence, safe workbook replacement, and restoration of the included default workbook.

See TEST_RESULTS.txt and ACCEPTANCE_TEST_CHECKLIST.md for additional evidence and manual checks.

Calculation notes

• The current year is the latest year in Monthly_Sales.
• The current cutoff is the latest available month in that year.
• Prior-year growth compares the same month range.
• The seasonal forecast applies historical full-year-to-YTD ratios to current YTD sales.
• The workbook projection comes from Projected_YYYY_Sales.
• Months of supply equals current inventory divided by average monthly current-year sales.
• Recommendations are transparent rule-based business indicators, not guarantees or machine-learning predictions.

Project documentation

• USER_GUIDE.md — application workflow and controls
• WORKBOOK_FORMAT.md — required workbook structure
• CHANGELOG.md — version history
• FINAL_RELEASE_NOTES.md — Version 1.0.0 summary
• ACCEPTANCE_TEST_CHECKLIST.md — final manual checks
• TEST_RESULTS.txt — automated test record
• documentation/Auto_Insights_2026_Sample_Report.html — sample report from the default workbook
• documentation/Auto_Insights_2028_Sample_Report.html — sample report from synthetic future data

Current limitations

• The application accepts the documented dealership workbook format; it is not a universal spreadsheet analyzer.
• HTML is the only report-export format.
• Charts cannot be exported directly as image files.
• Forecasts and recommendations are rule-based rather than machine-learning predictions.
• The responsive interface is intended for desktop-sized windows rather than phones.

Third-party names and trademarks

Vehicle manufacturers, model names, and other third-party names belong to their respective owners. They are used for identification within an educational portfolio project and do not imply endorsement or affiliation.