Examples

This section provides practical examples of how to use the memories-dev framework in various applications. Each example demonstrates different aspects of the framework’s capabilities.

🌍 Environmental Monitoring

Environmental monitoring examples demonstrate how to use the memories-dev framework to track and analyze environmental conditions.

Environmental Examples

Environmental Monitoring

🏙️ Urban Development

Urban development examples show how to analyze urban environments and patterns.

🔍 Advanced Analysis

Advanced analysis examples demonstrate sophisticated analytical capabilities.

🏠 Real Estate & Property Analysis

New in version 2.0.5, our real estate and property analysis tools provide comprehensive insights into properties using Earth memory data.

Real Estate Examples

🤖 AI Integration

New in version 2.0.5, these examples demonstrate advanced AI integration capabilities.

AI Examples

Basic Examples

Memory Formation

The following example demonstrates how to create basic memories:

from memories import MemoryStore

# Initialize memory store
store = MemoryStore()

# Create basic memory
memory = store.create_memory(
    location=(40.7128, -74.0060),  # New York City
    timestamp="2024-02-18T12:00:00",
    data={
        "temperature": 22.5,
        "humidity": 65,
        "air_quality_index": 42
    }
)

Query and Analysis

This example shows how to query memories and analyze patterns:

# Query memories in area
memories = store.query(
    center=(40.7128, -74.0060),
    radius=5000,  # meters
    time_range=("2024-01-01", "2024-02-18")
)

# Analyze patterns
analysis = store.analyze(
    memories=memories,
    metrics=["temperature_trend", "urban_development"]
)

Advanced Usage

Multi-Source Integration

This example demonstrates how to integrate multiple data sources:

from memories.sources import SatelliteSource, SensorSource

# Initialize data sources
satellite = SatelliteSource(provider="sentinel-2")
sensors = SensorSource(network="environmental")

# Create integrated memory
memory = store.create_memory(
    location=(40.7128, -74.0060),
    sources=[satellite, sensors],
    integration_method="temporal_fusion"
)

Custom Analysis

This example shows how to create custom analyzers:

from memories.analysis import MemoryAnalyzer

class UrbanGrowthAnalyzer(MemoryAnalyzer):
    def analyze(self, memories):
        # Custom analysis logic
        return {
            "growth_rate": self._calculate_growth(memories),
            "density_change": self._analyze_density(memories),
            "impact_score": self._assess_impact(memories)
        }

# Use custom analyzer
analyzer = UrbanGrowthAnalyzer()
results = analyzer.analyze(memories)

Performance Tips

Memory Management - Use appropriate batch sizes - Implement memory cleanup - Monitor resource usage
Query Optimization - Use spatial indexing - Implement caching - Optimize time ranges
Data Processing - Use parallel processing - Implement batching - Optimize data formats