Demolition Estimating

Desktop tooling for demolition estimating and financial analysis, built with Tkinter, PostgreSQL, pandas, scikit-learn, and Prophet.

What This Repository Includes

This repo currently has two main GUI applications:

• Estimating + proposal workflow (estimate_project/work_scope_bid_proposal.py)

  • Multi-page work scope and bid proposal form
  • Contact and equipment lookup/edit windows
  • Historical + machine-learning estimate support
  • Word document export to your Downloads folder

• Financials workflow (financials/financials_main.py)

  • Daily/monthly/yearly operating-cost calculations
  • Equipment/disposal/sales/QuickBooks-style summaries
  • Forecast charts using Prophet (matplotlib and Plotly)

Current Project Structure

demolition_estimating/
├── data/
│   ├── equipment_sample_data_public.csv
│   ├── contact_sample_data_public.json
│   ├── monthly_numbers_sample_data_public.csv
│   ├── project_sample_data_public.csv
│   └── project_management_public.json
├── estimate_project/
│   ├── building_demo.py
│   ├── contact_book.py
│   ├── equipment_book.py
│   ├── estimate_project.py
│   ├── estimating_main.py
│   ├── house_demo.py
│   ├── interior_demo.py
│   ├── postgresql.py
│   └── work_scope_bid_proposal.py
├── financials/
│   ├── expenses.py
│   ├── financials_main.py
│   ├── postgresql.py
│   └── revenue.py
├── requirements.txt
├── README.md
└── LICENSE.txt

Prerequisites

• Python 3.10+
• PostgreSQL database with required tables
• Tkinter (usually included with standard Python installers)

Setup

1. Create and activate a virtual environment.

Windows PowerShell:

python -m venv .venv
.\.venv\Scripts\Activate.ps1

Windows Command Prompt:

python -m venv .venv
.venv\Scripts\activate.bat

2. Install dependencies.

pip install -r requirements.txt

3. Create a .env file in the repository root.

POSTGRESQL_HOST=host
POSTGRESQL_PORT=port
DATABASE=your_database_name
POSTGRESQL_USER=your_username
POSTGRESQL_PASSWORD=your_password

Both estimate_project/postgresql.py and financials/postgresql.py read these same environment variables.

Database Data Requirements

The application expects these tables:

• project

  • Used by estimating workflows
  • Columns used in code: job_number, awarded_date, project_description, structure_type, sqft, bid_price, job_cost, estimator

• monthly_numbers

  • Used by financials workflows
  • Columns used in code: year_month, disposalcost, expense, sales, payroll

• equipment

  • Used by both financials and estimating workflows
  • Columns used in code: equipment_name, project_type, purchase_price, day_rate, week_rate, month_rate

• company and client

  • Used by the contact book workflow

If PostgreSQL is unavailable, these programs fall back to public sample data in data/:

• estimate_project/contact_book.py → data/contact_sample_data_public.json
• estimate_project/equipment_book.py → data/equipment_sample_data_public.csv
• estimate_project/estimating_main.py and estimate_project/work_scope_bid_proposal.py → data/project_sample_data_public.csv
• financials/financials_main.py → data/monthly_numbers_sample_data_public.csv and data/equipment_sample_data_public.csv
• estimate_project/project_management.py (public mode) → data/project_management_public.json

Running The Apps

From the repository root:

Main estimating/proposal GUI:

python estimate_project/work_scope_bid_proposal.py

Financials GUI:

python financials/financials_main.py

Optional standalone tools:

python estimate_project/contact_book.py
python estimate_project/equipment_book.py
python estimate_project/estimating_main.py

Output

• Proposal documents are exported as .docx files to your user Downloads directory.
• Chart windows open via matplotlib and Plotly from within the desktop apps.

Notes

License

This project is licensed under the MIT License. See LICENSE.txt.