Examples

The Memories-Dev framework includes several example applications that demonstrate its capabilities and usage patterns.

Property Analyzer

The Property Analyzer example demonstrates how to analyze real estate properties using satellite imagery and local context.

from memories import MemoryStore, Config
from examples.property_analyzer import Property

# Initialize memory store
config = Config(
    storage_path="./property_data",
    hot_memory_size=50,
    warm_memory_size=200,
    cold_memory_size=1000
)
memory_store = MemoryStore(config)

# Create memory
property = Property(memory_store)

# Analyze property
insights = await property.analyze_property(property_data)

Key features: - Property condition analysis using satellite imagery - Location scoring based on amenities and environment - Investment potential calculation - Automated recommendations generation

Location Ambience Analyzer

The Location Ambience Analyzer evaluates the environmental and urban characteristics of locations.

from examples.location_ambience import LocationAnalyzer

analyzer = LocationAnalyzer(memory_store)
insights = await analyzer.analyze_location(location_data)

Features: - Environmental quality assessment - Urban feature analysis - Noise level estimation - Ambience scoring - Location-specific recommendations

Traffic Analyzer

The Traffic Analyzer monitors and analyzes traffic patterns and road conditions.

from examples.traffic_analyzer import TrafficAnalyzer

analyzer = TrafficAnalyzer(memory_store)
insights = await analyzer.analyze_traffic(road_segment)

Features: - Traffic pattern analysis - Road condition monitoring - Congestion prediction - Hazard detection - Traffic-based recommendations

Water Bodies Monitor

The Water Bodies Monitor tracks changes in water bodies using satellite data.

from examples.water_bodies_monitor import WaterBody

water_body = WaterBody(memory_store)
insights = await water_body.analyze_water_body(water_body_data)

Features: - Water body change detection - Water quality analysis - Surface area calculation - Environmental impact assessment

Common Usage Patterns

All examples follow these common patterns:

  1. Memory Store Initialization

    • Configure storage paths and memory tiers

    • Initialize appropriate memory store

  2. Data Processing

    • Collect data from various sources

    • Process and analyze data

    • Generate insights

  3. Memory Management

    • Store insights in appropriate memory tiers

    • Retrieve and update stored information

    • Clean up old or irrelevant data

Requirements

To run the examples, you need:

  1. Python 3.8 or higher

  2. Memories-Dev framework installed

  3. Required environment variables:

    • PLANETARY_COMPUTER_API_KEY

    • GEO_MEMORIES path set

  4. Dependencies from requirements.txt

Installation:

pip install -r examples/requirements.txt

For more detailed information about each example, refer to their respective source files in the examples/ directory.