Configuration

def get_behaviors() -> dict:
    """
    Get current behavior settings with symbolic names.
    
    Returns:
    dict: Current behaviors with string keys and appropriate values
    """

def set_behaviors(behaviors: dict):
    """
    Set behavior configuration options.
    
    Parameters:
    - behaviors (dict): Behavior name to value mapping
    
    Raises:
    - ValueError: For unknown behavior names or invalid values
    """

@property
def behaviors() -> BehaviorDict:
    """
    Behavior dictionary property that syncs changes to client.
    Allows both getting and setting behaviors via dict interface.
    
    Returns:
    BehaviorDict: Special dict that updates client on changes
    """

# Hash algorithm constants
hashers: dict = {
    "default": hash_default,
    "md5": hash_md5,
    "crc": hash_crc,
    "fnv1_64": hash_fnv1_64,
    "fnv1a_64": hash_fnv1a_64,
    "fnv1_32": hash_fnv1_32,
    "fnv1a_32": hash_fnv1a_32,
    "murmur": hash_murmur,
    "hsieh": hash_hsieh,
    "jenkins": hash_jenkins
}

hashers_rvs: dict  # Reverse mapping: constant to name

# Distribution algorithm constants
distributions: dict = {
    "modula": distribution_modula,
    "consistent": distribution_consistent,
    "random": distribution_random,
    "consistent ketama": distribution_consistent_ketama,
    "consistent ketama spy": distribution_consistent_ketama_spy,
    "consistent weighted": distribution_consistent_weighted,
    "virtual bucket": distribution_virtual_bucket,
    "consistent max": distribution_consistent_max
}

distributions_rvs: dict  # Reverse mapping: constant to name

all_behaviors: list = [
    "auto_eject",
    "buffer_requests", 
    "cas",
    "connect_timeout",
    "distribution",
    "failure_limit",
    "hash",
    "ketama",
    "ketama_hash",
    "ketama_weighted",
    "no_block",
    "num_replicas",
    "pickle_protocol",
    "receive_timeout",
    "retry_timeout", 
    "send_timeout",
    "tcp_keepalive",
    "tcp_nodelay",
    "verify_keys"
]

all_callbacks: list = [
    "namespace"
]

class BehaviorDict(dict):
    """
    Dictionary that syncs behavior changes to client automatically.
    Inherits from dict with additional client synchronization.
    """
    
    def __init__(client, *args, **kwargs):
        """
        Initialize behavior dictionary.
        
        Parameters:
        - client: Client instance to sync changes to
        - args, kwargs: Standard dict initialization arguments
        """

    def __setitem__(name: str, value):
        """
        Set behavior and sync to client.
        
        Parameters:
        - name (str): Behavior name
        - value: Behavior value
        """

    def update(d: dict):
        """
        Update multiple behaviors and sync to client.
        
        Parameters:
        - d (dict): Behaviors to update
        """

def translate_server_spec(server: str, port: int = 11211, weight: int = 1) -> tuple:
    """
    Parse server specification string into connection tuple.
    
    Parameters:
    - server (str): Server specification (host:port, /path/to/socket, etc.)
    - port (int): Default port if not specified
    - weight (int): Server weight for consistent hashing
    
    Returns:
    tuple: (server_type, address, port, weight)
    """

def translate_server_specs(servers: list) -> list:
    """
    Parse list of server specifications.
    
    Parameters:
    - servers (list): List of server specifications
    
    Returns:
    list: List of parsed server tuples
    """

# Connection timeouts (milliseconds)
client.behaviors.update({
    "connect_timeout": 5000,      # Connection establishment timeout
    "send_timeout": 5000,         # Send operation timeout  
    "receive_timeout": 5000,      # Receive operation timeout
    "retry_timeout": 30,          # Retry failed servers after N seconds
})

# Network optimization
client.behaviors.update({
    "tcp_nodelay": True,          # Disable Nagle's algorithm
    "tcp_keepalive": True,        # Enable TCP keepalive
    "no_block": True,             # Non-blocking I/O operations
    "buffer_requests": True,      # Buffer multiple requests
})

# Hash algorithm selection
client.behaviors.update({
    "hash": "fnv1a_64",          # Use FNV1a 64-bit hash
    "ketama_hash": "md5",        # Hash for ketama distribution
})

# Distribution algorithm
client.behaviors.update({
    "distribution": "consistent ketama",  # Consistent hashing
    "ketama": True,                       # Enable ketama consistent hashing
    "ketama_weighted": True,              # Weight servers by memory
    "num_replicas": 160,                  # Virtual nodes per server
})

# Server failure handling  
client.behaviors.update({
    "auto_eject": True,           # Remove failed servers automatically
    "failure_limit": 3,           # Max failures before server ejection
})

# Protocol options
client.behaviors.update({
    "cas": True,                  # Enable Compare-And-Store support
    "verify_keys": True,          # Validate key format
})

# Serialization
client.behaviors.update({
    "pickle_protocol": 2,         # Python pickle protocol version
})

import pylibmc

# Create client with behaviors
client = pylibmc.Client(["localhost:11211"], binary=True)

# Set behaviors for optimal performance
client.behaviors = {
    "tcp_nodelay": True,
    "ketama": True,
    "no_block": True,
    "connect_timeout": 5000,
    "retry_timeout": 30
}

# Check current configuration
print("Current behaviors:", client.behaviors)

import pylibmc

client = pylibmc.Client(["server1:11211", "server2:11211"], binary=True)

# Optimize for high-throughput scenarios
high_perf_behaviors = {
    # Network optimization
    "tcp_nodelay": True,
    "no_block": True,
    "buffer_requests": True,
    
    # Consistent hashing for even distribution
    "distribution": "consistent ketama",
    "ketama": True,
    "hash": "fnv1a_64",
    "ketama_hash": "md5",
    
    # Fast failover
    "auto_eject": True,
    "failure_limit": 2,
    "retry_timeout": 10,
    
    # Reasonable timeouts
    "connect_timeout": 2000,
    "send_timeout": 2000,
    "receive_timeout": 2000,
}

client.behaviors.update(high_perf_behaviors)

import pylibmc

# Define server cluster with weights
servers = [
    ("server1.cache.local", 11211, 1),  # Standard weight
    ("server2.cache.local", 11211, 2),  # Double weight (more memory)
    ("server3.cache.local", 11211, 1),  
]

client = pylibmc.Client(servers, binary=True)

# Configure for cluster reliability
cluster_behaviors = {
    # Consistent hashing with weights
    "distribution": "consistent ketama",
    "ketama": True,
    "ketama_weighted": True,
    "num_replicas": 160,
    
    # Robust failure handling
    "auto_eject": True,
    "failure_limit": 3,
    "retry_timeout": 60,
    
    # Conservative timeouts for stability
    "connect_timeout": 5000,
    "send_timeout": 10000,
    "receive_timeout": 10000,
}

client.behaviors.update(cluster_behaviors)

import pylibmc
import os

def create_client(servers, environment="development"):
    """Create client with environment-specific configuration."""
    
    client = pylibmc.Client(servers, binary=True)
    
    if environment == "development":
        # Development: Faster timeouts, more verbose errors
        client.behaviors.update({
            "connect_timeout": 1000,
            "send_timeout": 1000, 
            "receive_timeout": 1000,
            "retry_timeout": 5,
            "verify_keys": True,
            "tcp_nodelay": True,
        })
    else:
        # Production: Conservative timeouts, high performance
        client.behaviors.update({
            "connect_timeout": 5000,
            "send_timeout": 5000,
            "receive_timeout": 5000,
            "retry_timeout": 30,
            "tcp_nodelay": True,
            "no_block": True,
            "buffer_requests": True,
            "auto_eject": True,
            "failure_limit": 3,
            "ketama": True,
            "distribution": "consistent ketama",
        })
    
    return client

# Usage
dev_client = create_client(["localhost:11211"], "development")
prod_client = create_client(["cache1:11211", "cache2:11211"], "production")

import pylibmc

client = pylibmc.Client(["localhost:11211"])

# Validate behavior settings
def validate_behaviors(client):
    """Check if client has recommended behaviors."""
    behaviors = client.get_behaviors()
    
    recommendations = {
        "tcp_nodelay": True,
        "ketama": True,
        "connect_timeout": lambda x: 1000 <= x <= 10000,
        "retry_timeout": lambda x: x >= 10,
    }
    
    for behavior, expected in recommendations.items():
        current = behaviors.get(behavior)
        
        if callable(expected):
            valid = expected(current) if current is not None else False
        else:
            valid = current == expected
            
        status = "✓" if valid else "✗"
        print(f"{status} {behavior}: {current}")

validate_behaviors(client)

server_type_tcp: int    # TCP connection (value: 1)
server_type_udp: int    # UDP connection (value: 2)  
server_type_unix: int   # Unix socket connection (value: 4)

support_compression: bool   # Whether zlib compression is available
support_sasl: bool         # Whether SASL authentication is available
libmemcached_version: str  # Version of underlying libmemcached