📡 DXCC Need List Tracker

A Flet-based desktop/web application for Amateur Radio operators

The DXCC Need List Tracker is a modern, cross-platform logging companion tool built using Python and Flet. It allows amateur radio operators to manage, track, and analyze their DXCC progress with features normally seen in full-scale logging programs — but in a lightweight, user-friendly interface.

🌟 Features

✔ User Authentication

• Log in using your ham radio callsign
• Each user has their own isolated data file
• Passwords stored securely using SHA-256 hashing

✔ DXCC Tracking

• Full list of 340+ ARRL DXCC entities
• Add QSOs manually
• Edit entries with dialog UI
• Delete entries
• Save & reload to/from Excel

✔ Dashboard Summary

Displays real-time stats including:

• Total QSOs
• Worked DXCC entities
• Needed / Requested / Confirmed
• Remaining DXCC count

✔ ADIF Import

Import QSOs directly from your logging software (.adi / .adif files). Auto-detects:

• Callsign
• Country
• QSO Date
• QSL status (maps LoTW/eQSL/paper flags automatically)

✔ Sorting & Filtering

• Filter by QSL Status (All, Needed, Requested, Confirmed)
• Sort by:
  • Country
  • Callsign
  • QSO Date
  • QSL Status

✔ Multi-Platform

Runs on:

• Windows
• macOS
• Linux
• Web (with limited filesystem access)

🛠 Technology Stack

• Python 3.10+
• Flet 0.28.3 (Flutter UI in Python)
• OpenPyXL for Excel storage
• Regex & custom parser for ADIF import
• SHA-256 for password hashing

📦 Project Structure

dxcc-tracker/
│
├── app/
│   ├── main.py              # Main Flet application
│   ├── auth.py              # Login / registration logic
│   ├── data_manager.py      # Excel saving/loading
│   ├── dxcc_list.py         # Full DXCC entity list
│   ├── adif_import.py       # ADIF (.adi) parser
│   ├── ui_components.py     # Shared UI elements
│   └── users/               # Auto-created Excel files per user
│
├── README.md
├── requirements.txt
└── .gitignore

🚀 Running Locally

1. Clone the repository

git clone https://github.com/YOUR_USERNAME/dxcc-tracker.git
cd dxcc-tracker

2. Create a virtual environment (recommended)

python -m venv venv
source venv/bin/activate    # macOS / Linux
venv\Scripts\activate       # Windows

3. Install dependencies

pip install -r requirements.txt

4. Run the application

python -m app.main

📁 User Data Storage

Each callsign gets its own Excel file stored in:

app/users/<CALLSIGN>.xlsx

📥 ADIF Import

Export from your logging software using ADIF format, then import via the UI.

🧭 Roadmap

• Band/Mode matrix
• Color-coded rows
• Cloud sync
• SQLite database option
• DX Cluster integration
• Mobile builds

📝 License

MIT License.

🤝 Contributions

Pull requests welcome!