Job Search Tracker

A self-hosted web application to track job applications and networking contacts using SQLite for data storage with automatic markdown export for viewing in neovim.

⚠️ Disclaimer

This application was fully coded with AI assistance. The user has thoroughly reviewed and guided the development process, making all architectural decisions.

Important notes:

• This is a single-user application designed exclusively for the app owner—imperfect implementations are not problematic given this scope
• The app owner has independently verified that data is secure and cannot be breached, with authentication restricted to the owner only
• All security measures (OAuth configuration, email whitelist, SSL) have been reviewed and validated by the user

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Dashboard showing application statistics, funnel visualization, and job tracking table

Features

• 🔐 Google OAuth Authentication - Secure login with Google accounts
• Track job applications with status tracking
• Manage contacts and networking connections
• View statistics (total applications, pending, accepted, refused)
• Filter and search applications
• Add/edit/delete entries through web interface
• Data stored in markdown files for easy backup and version control
• 🌐 Production-ready deployment with nginx and systemd

Setup

Prerequisites

• Python 3.9 or higher
• uv package manager

Installation

1. Install dependencies using uv:

uv sync

This will create a virtual environment and install all required packages.

Configure Google Authentication

Before running the app, set up Google OAuth:

1. Follow the steps in OAUTH2_SETUP.md to:

   • Create Google OAuth credentials
   • Configure .streamlit/secrets.toml

2. Quick setup:

# Copy the example secrets file
cp .streamlit/secrets.toml.example .streamlit/secrets.toml

# Edit and add your Google OAuth credentials
nano .streamlit/secrets.toml

Running the Application

Start the Streamlit app:

uv run streamlit run app.py --server.port 8502

The application will open in your default browser at http://localhost:8502.

You'll need to log in with a Google account that's in your allowed_emails list.

Production Deployment

Deploy to candidatures.aralyra.com with nginx, SSL, and systemd:

📖 Full deployment guide: DEPLOYMENT.md

Quick summary:

# 1. Configure Google OAuth for production domain
# 2. Set up systemd service
sudo cp job-tracker.service /etc/systemd/system/
sudo systemctl enable job-tracker
sudo systemctl start job-tracker

# 3. Configure nginx
sudo cp nginx-job-tracker.conf /etc/nginx/sites-available/job-tracker
sudo ln -s /etc/nginx/sites-available/job-tracker /etc/nginx/sites-enabled/
sudo nginx -t && sudo systemctl reload nginx

# 4. Get SSL certificate
sudo certbot --nginx -d candidatures.aralyra.com

Access at: https://candidatures.aralyra.com

Data Architecture

The application uses SQLite as the backend database with automatic markdown export:

Backend:

• job_tracker.db - SQLite database (primary data store)

Auto-Generated Markdown Files (for viewing in neovim):

• candidature.md - Job applications table
• contact.md - Contacts table
• VIEW.md - Pretty formatted view with statistics

Every time you save changes in the web app, the markdown files are automatically regenerated. This gives you:

• ✅ Fast, reliable SQLite backend
• ✅ Clean markdown tables to view in neovim
• ✅ Best of both worlds!

Usage

Applications Tab

• View all job applications in a sortable table
• Filter by status (not yet, refused, Ok, too late)
• Search by company name
• Add new applications using the form
• Edit existing entries directly in the table
• Save changes to persist to markdown files

Contacts Tab

• View all contacts in a table
• Add new contacts using the form
• Edit existing contacts directly in the table
• Save changes to persist to markdown files

Project Structure

.
├── app.py                        # Main Streamlit application
├── models.py                     # SQLAlchemy database models
├── utils.py                      # Export utilities (markdown generation)
├── job_tracker.db                # SQLite database
├── pyproject.toml                # Project dependencies
├── candidature.md                # Auto-generated applications export
├── contact.md                    # Auto-generated contacts export
├── VIEW.md                       # Auto-generated readable view
│
├── .streamlit/
│   ├── secrets.toml.example      # OAuth config template
│   └── secrets.toml              # OAuth credentials (git-ignored)
│
├── nginx-job-tracker.conf        # Nginx reverse proxy config
├── job-tracker.service           # Systemd service file
├── DEPLOYMENT.md                 # Production deployment guide
└── OAUTH2_SETUP.md               # Google OAuth setup guide

Database Schema

contacts (companies you apply to):

• id, company, firstname, lastname, linkedin_link, phone_number, updated_date

applications (job applications):

• id, company_id (FK → contacts.id), client, job_link, date, source, status, answer, answer_date, expected_rate, offered_rate, duration, start_date, notes, closed

Applications are linked to contacts via foreign key (company_id). When you update a company name in contacts, all linked applications automatically reflect the change.

Security

• Authentication: Google OAuth 2.0
• Access Control: Email whitelist in secrets.toml
• SSL/TLS: Let's Encrypt certificates (production)
• Secrets: All credentials stored in .streamlit/secrets.toml (git-ignored)

See OAUTH2_SETUP.md for security best practices.

Documentation

• OAUTH2_SETUP.md - Complete Google OAuth setup guide
• DEPLOYMENT.md - Production deployment guide
• README.md - This file