# Zenoo RPC - Comprehensive Architecture Analysis

## 📋 Executive Summary

Zenoo RPC is a modern async Python library designed to replace odoorpc with advanced features:

- **Async-first design** with httpx transport
- **Type safety** with Pydantic models
- **Intelligent caching** with TTL/LRU strategies
- **Transaction management** with ACID compliance
- **Batch operations** for high performance
- **Enhanced connection pooling** with HTTP/2
- **Structured exception handling**

## 🏗️ Overall Architecture

### Layered Architecture

Zenoo RPC follows a clear layered architecture:

#### 1. **Presentation Layer (Client Interface)**
- `ZenooClient`: Main entry point
- Public API with zen-like simplicity
- Context managers for resource management

#### 2. **Business Logic Layer**
- **Query System**: QueryBuilder, QuerySet, expressions
- **Model System**: OdooModel, relationships, validation
- **Operations**: BatchManager, TransactionManager

#### 3. **Infrastructure Layer**
- **Caching**: CacheManager, backends, strategies
- **Transport**: AsyncTransport, ConnectionPool
- **Retry & Error**: RetryManager, policies, strategies

#### 4. **Data Layer**
- HTTP/2 client with httpx
- JSON-RPC protocol
- Odoo server integration

## 🎯 Design Patterns

### 1. Factory Pattern
- **ModelRegistry**: Dynamic model creation
- **CacheFactory**: Backend creation
- **TransportFactory**: Transport creation

### 2. Builder Pattern
- **QueryBuilder**: Fluent query interface
- **QuerySet**: Chainable operations

### 3. Strategy Pattern
- **CacheStrategy**: TTL, LRU, LFU
- **RetryStrategy**: Exponential, Linear, Fixed

### 4. Decorator Pattern
- **CacheDecorator**: Function caching
- **RetryDecorator**: Retry logic
- **TransactionDecorator**: Transaction wrapping

### 5. Context Manager Pattern
- **ZenooClient**: Connection management
- **TransactionContext**: Transaction lifecycle
- **BatchContext**: Batch operations

### 6. Facade Pattern
- **ZenooClient**: Simplifies complex subsystems
- Hides implementation complexity

### 7. Adapter Pattern
- **TransportAdapter**: HTTP client adaptation
- **CacheAdapter**: Backend adaptation

### 8. Observer Pattern
- **EventManager**: Event notifications
- **Observers**: Event handlers

### 9. Singleton Pattern
- **Global Registry**: Single model registry
- **Global Managers**: Shared managers

## 🎯 Core Client & Session Management

### ZenooClient Architecture

```python
class ZenooClient:
    """Main async client với comprehensive features"""
    
    # Core components
    transport: AsyncTransport
    session_manager: SessionManager
    cache_manager: Optional[CacheManager]
    transaction_manager: Optional[TransactionManager]
    batch_manager: Optional[BatchManager]
```

### Key Features:

#### **URL Parsing & Configuration**
- Flexible URL parsing (full URL, host+port, host only)
- Protocol detection (HTTP/HTTPS)
- Default port assignment

#### **Authentication Flow**
1. `get_server_version()` - Server info
2. `authenticate()` - User authentication
3. `load_user_context()` - User context loading
4. Session state management

#### **Session Management**
- Session state tracking
- User context management
- API key authentication support
- Session validation & refresh

#### **Context Management**
- Async context managers (`__aenter__`, `__aexit__`)
- Automatic resource cleanup
- Exception handling

## 🚀 Transport Layer & Connection Pooling

### AsyncTransport Features

#### **HTTP/2 Support**
- Multiplexing for better performance
- Connection reuse
- Header compression

#### **Connection Pooling**
```python
class ConnectionPool:
    """Advanced connection pooling with:"""

    # Features
    - HTTP/2 multiplexing
    - Health monitoring
    - Auto recovery
    - Load balancing
    - Performance statistics
```

#### **Health Monitoring**
- Connection health checks
- Automatic unhealthy connection removal
- Background health check loops
- Performance metrics tracking

#### **Error Handling**
- Circuit breaker pattern
- Exponential backoff retry
- Graceful degradation
- Fallback mechanisms

## 🏗️ ORM System & Model Relationships

### OdooModel Architecture

#### **Pydantic Integration**
```python
class OdooModel(BaseModel):
    """Type-safe Odoo models with:"""

    # Features
    - Runtime validation
    - Type hints
    - IDE support
    - Serialization
```

#### **Model Registry**
- Dynamic model creation
- Model registration
- Field introspection
- Model caching

#### **Relationships**
```python
class LazyRelationship:
    """Lazy-loaded relationships with:"""

    # Features
    - On-demand loading
    - Batch loading
    - Prefetch strategies
    - Caching
```

#### **Query System**
```python
# Fluent interface
partners = await client.model(ResPartner).filter(
    is_company=True,
    name__ilike="acme%"
).order_by("name").limit(10).all()
```

## 💾 Caching System & Strategies

### Cache Architecture

#### **CacheManager**
- Backend coordination
- Strategy management
- Configuration management
- Statistics tracking

#### **Cache Backends**
- **MemoryCache**: In-memory with TTL/LRU
- **RedisCache**: Enterprise Redis with resilience
- **Custom Backends**: Extensible architecture

#### **Cache Strategies**
- **TTLCache**: Time-based expiration
- **LRUCache**: Least Recently Used
- **LFUCache**: Least Frequently Used

#### **Key Management**
```python
# Intelligent key generation
model_key = make_model_cache_key("res.partner", 123)
query_key = make_query_cache_key("res.partner", domain)
```

#### **Performance Features**
- Batch operations
- Async operations
- Memory management
- Compression support

## 🔄 Transaction & Batch Processing

### Transaction Management
- ACID compliance
- Nested transactions
- Rollback mechanisms
- Context managers

### Batch Operations
- Bulk operations
- Chunk processing
- Concurrent execution
- Progress tracking

## 🔄 Retry Mechanisms & Error Handling

### Retry Strategies
- **ExponentialBackoff**: Exponential delay
- **LinearBackoff**: Linear delay
- **FixedDelay**: Fixed delay

### Error Handling
- Structured exception hierarchy
- Error mapping from Odoo
- Graceful degradation
- Recovery mechanisms

## 📊 Performance Optimizations

### Connection Level
- HTTP/2 multiplexing
- Connection pooling
- Keep-alive connections
- Load balancing

### Query Level
- Lazy loading
- Batch loading
- Query optimization
- Result caching

### Memory Level
- Memory management
- Resource cleanup
- Garbage collection
- Memory monitoring

## 🛡️ Type Safety & Validation

### Pydantic Integration
- Runtime validation
- Type hints
- IDE support
- MyPy compatibility

### Model Validation
- Field validation
- Business rules
- Data conversion
- Error reporting

## 🔗 Integration Points

### Client Integration
- Transport layer
- Session management
- Cache management
- Transaction management

### Model Integration
- Query builder
- Relationships
- Validation
- Serialization

### Cache Integration
- Query caching
- Model caching
- Transport caching
- Decorator caching

## 📈 Monitoring & Observability

### Performance Metrics
- Request statistics
- Connection statistics
- Cache statistics
- Error statistics

### Health Monitoring
- Connection health
- Service health
- Performance monitoring
- Alert mechanisms

## 🎯 Best Practices Implementation

### Resource Management
- Context managers
- Automatic cleanup
- Memory management
- Connection pooling

### Error Handling
- Structured exceptions
- Graceful degradation
- Recovery mechanisms
- Logging & monitoring

### Performance
- Async operations
- Batch processing
- Intelligent caching
- Connection optimization

## 🚀 Advanced Features

### Intelligent Caching
- Multi-level caching
- Cache hierarchies
- Invalidation strategies
- Performance optimization

### Transaction Management
- ACID compliance
- Nested transactions
- Rollback mechanisms
- Context management

### Batch Operations
- Bulk processing
- Concurrent execution
- Progress tracking
- Error handling

## 📋 Conclusion

Zenoo RPC represents a modern, well-architected solution for Odoo RPC communication with:

- **Clean Architecture**: Layered design with clear separation of concerns
- **Modern Patterns**: Implementation of proven design patterns
- **Performance**: Optimized for high-performance scenarios
- **Reliability**: Robust error handling and recovery mechanisms
- **Developer Experience**: Type safety, IDE support, and intuitive APIs
- **Extensibility**: Plugin architecture for customization
- **Monitoring**: Comprehensive observability and metrics

This architecture ensures scalability, maintainability, and performance for enterprise applications.

## 🔍 Detailed Component Analysis

### 1. ZenooClient Deep Dive

#### Core Responsibilities:
- **Connection Management**: Connection lifecycle management
- **Authentication**: User authentication and session management
- **API Gateway**: Unified interface for all operations
- **Resource Coordination**: Coordination between subsystems

#### Key Methods:
```python
# Authentication
await client.login(database, username, password)
await client.login_with_api_key(database, username, api_key)

# CRUD Operations
record_id = await client.create(model, values)
records = await client.read(model, ids, fields)
success = await client.write(model, ids, values)
success = await client.unlink(model, ids)

# Search Operations
ids = await client.search(model, domain, limit, offset)
count = await client.search_count(model, domain)
records = await client.search_read(model, domain, fields)

# Model Interface
query_builder = client.model(ModelClass)
```

### 2. Transport Layer Deep Dive

#### AsyncTransport Features:
- **JSON-RPC Protocol**: Odoo-compatible JSON-RPC implementation
- **HTTP/2 Support**: Modern HTTP protocol with multiplexing
- **Connection Pooling**: Efficient connection reuse
- **Error Handling**: Comprehensive error mapping

#### Connection Pool Features:
```python
class ConnectionPool:
    # Configuration
    max_connections: int = 20
    max_idle_time: int = 300
    health_check_interval: int = 30

    # Operations
    async def acquire() -> Connection
    async def release(connection: Connection)
    async def health_check() -> bool
```

### 3. ORM System Deep Dive

#### Model Definition:
```python
class ResPartner(OdooModel):
    _name = "res.partner"

    # Fields
    name: str
    email: Optional[str]
    is_company: bool = False

    # Relationships
    company_id: Optional["ResCompany"] = None
    child_ids: List["ResPartner"] = []
```

#### Relationship Types:
- **Many2One**: Single related record
- **One2Many**: List of related records
- **Many2Many**: Many-to-many relationships

#### Lazy Loading:
```python
# Automatic lazy loading
partner = await Partner.get(123)
company = await partner.company_id  # Lazy loaded
children = await partner.child_ids.all()  # Lazy loaded list
```

### 4. Caching System Deep Dive

#### Cache Hierarchy:
```python
# L1 Cache - Memory (hot data)
await cache_manager.setup_memory_cache(
    name="l1", max_size=200, default_ttl=60
)

# L2 Cache - Redis (warm data)
await cache_manager.setup_redis_cache(
    name="l2", redis_url="redis://localhost:6379/0"
)
```

#### Cache Decorators:
```python
@cached(ttl=300, backend="redis")
async def expensive_operation():
    # Cached function
    pass

@cache_result(key_func=lambda x: f"user:{x}")
async def get_user(user_id):
    # Result caching
    pass
```

### 5. Transaction System Deep Dive

#### Transaction Context:
```python
async with client.transaction() as tx:
    # All operations in transaction
    partner_id = await client.create("res.partner", {...})
    await client.write("res.partner", [partner_id], {...})

    # Auto-commit on success, rollback on exception
```

#### Nested Transactions:
```python
async with client.transaction() as tx1:
    # Outer transaction

    async with client.transaction() as tx2:
        # Nested transaction (savepoint)
        pass
```

### 6. Batch Processing Deep Dive

#### Batch Operations:
```python
async with client.batch() as batch:
    # Queue operations
    batch.create("res.partner", {...})
    batch.create("res.partner", {...})
    batch.write("res.partner", [1, 2], {...})

    # Execute all at once
    results = await batch.execute()
```

#### Batch Configuration:
```python
await client.setup_batch_manager(
    max_chunk_size=50,
    max_concurrent_batches=5,
    timeout=30
)
```

## 🎯 Usage Patterns

### 1. Basic Usage
```python
async with ZenooClient("localhost") as client:
    await client.login("demo", "admin", "admin")

    partners = await client.search_read(
        "res.partner",
        [("is_company", "=", True)],
        ["name", "email"]
    )
```

### 2. Advanced Usage with ORM
```python
async with ZenooClient("localhost") as client:
    await client.login("demo", "admin", "admin")

    # Setup caching
    await client.setup_cache_manager()

    # ORM queries
    companies = await client.model(ResPartner).filter(
        is_company=True,
        name__ilike="acme%"
    ).cache(ttl=300).all()
```

### 3. Enterprise Usage
```python
async with ZenooClient("production.odoo.com") as client:
    # Setup all managers
    await client.setup_cache_manager(backend="redis")
    await client.setup_transaction_manager()
    await client.setup_batch_manager()

    # Enterprise operations
    async with client.transaction():
        async with client.batch() as batch:
            # Bulk operations in transaction
            pass
```
