django-salestrack 1.0.1

A Django app for tracking sales personnel, distributors, and retailers with Google Maps integration

Django SalesTrack

A comprehensive Django app for tracking sales personnel, distributors, and retailers with Google Maps integration and advanced filtering capabilities.

Features

• Multi-tier Tracking: Track employees, distributors, and retailers with hierarchical relationships
• Google Maps Integration: Interactive map visualization with custom markers and clustering
• Advanced Filtering: Dynamic filter controls with individual marker counts
• Performance Optimized: Bulk database queries and efficient data loading for large datasets
• Activity Tracking: Log and visualize sales activities and visits
• GeoJSON Support: Export tracking data in GeoJSON format
• Responsive UI: Mobile-friendly interface with dynamic control states

Installation

1. Install the package

Basic installation:

pip install django-salestrack

With MySQL support:

pip install django-salestrack[mysql]

With REST API support:

pip install django-salestrack[api]

Full installation:

pip install django-salestrack[mysql,api]

2. Add to Django settings

Add 'salestrack' to your INSTALLED_APPS in settings.py:

INSTALLED_APPS = [
    ...
    'salestrack',
    ...
]

3. Configure URLs

Include the salestrack URLs in your main urls.py:

from django.urls import path, include

urlpatterns = [
    ...
    path('salestrack/', include('salestrack.urls')),
    ...
]

4. Database Setup

This app requires specific database models. Make sure you have models similar to:

• SpUsers - User/Employee model
• SpVisits - Visit tracking model
• SpUserVisits - User visit relationships
• SpActivityLogs - Activity logging model

Run migrations:

python manage.py migrate

Configuration

Required Settings

Add these settings to your Django settings.py:

# Google Maps API Key (required)
GOOGLE_MAPS_API_KEY = 'your-google-maps-api-key'

# Database configuration (MySQL recommended)
DATABASES = {
    'default': {
        'ENGINE': 'django.db.backends.mysql',
        'NAME': 'your_database_name',
        'USER': 'your_database_user',
        'PASSWORD': 'your_database_password',
        'HOST': 'localhost',
        'PORT': '3306',
        'OPTIONS': {
            'init_command': "SET sql_mode='STRICT_TRANS_TABLES'"
        }
    }
}

Optional Settings

# Customize marker clustering (optional)
SALESTRACK_CLUSTER_MARKERS = True
SALESTRACK_MAX_MARKERS_PER_REQUEST = 1000

# Performance settings (optional)
SALESTRACK_BATCH_SIZE = 500
SALESTRACK_CACHE_TIMEOUT = 300  # seconds

Usage

Basic Setup

1. Access the tracking interface: Navigate to /salestrack/ in your application

2. API Endpoints:

   • /salestrack/user-markers/ - Get marker data
   • /salestrack/tracks.geo - Get GeoJSON track data

Model Requirements

Your models should follow this structure:

# Example model structure (adapt to your needs)
class SpUsers(models.Model):
    first_name = models.CharField(max_length=100)
    last_name = models.CharField(max_length=100)
    latitude = models.DecimalField(max_digits=10, decimal_places=8)
    longitude = models.DecimalField(max_digits=11, decimal_places=8)
    user_type = models.CharField(max_length=50)
    # ... other fields

class SpVisits(models.Model):
    user = models.ForeignKey(SpUsers, on_delete=models.CASCADE)
    visit_date = models.DateField()
    latitude = models.DecimalField(max_digits=10, decimal_places=8)
    longitude = models.DecimalField(max_digits=11, decimal_places=8)
    # ... other fields

Frontend Integration

The app includes a complete Google Maps interface with:

• Dynamic marker loading and filtering
• Marker type toggles with individual counts
• Performance optimizations for large datasets
• Automatic control state management during API calls

API Reference

GET /user-markers/

Returns marker data for map visualization.

Parameters:

• date (optional): Filter by specific date (YYYY-MM-DD format)

Response:

{
  "employees": [...],
  "distributors": [...],
  "retailers": [...],
  "activities": [...]
}

GET /tracks.geo

Returns GeoJSON formatted tracking data.

Parameters:

• date (optional): Filter by specific date

Response:

{
  "type": "FeatureCollection",
  "features": [...]
}

Performance Considerations

• The app is optimized for datasets with 7,000+ markers
• Uses bulk database queries to minimize N+1 problems
• Implements client-side batching for large marker sets
• Includes control disable/enable during API calls

Dependencies

Core dependencies:

• Django >= 3.2 (compatible with Django 3.2, 4.x, and 5.x)
• requests >= 2.20.0
• python-dateutil >= 2.7.0

Optional dependencies:

• mysqlclient >= 2.0.0 (install with [mysql])
• django-mysql >= 4.5.0 (install with [mysql])
• djangorestframework >= 3.13.0 (install with [api])

Browser Support

• Chrome 60+
• Firefox 60+
• Safari 12+
• Edge 79+

License

MIT License

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Support

For support, please open an issue in the GitHub repository or contact the maintainers.