Cloud Services Integration

from google.cloud.location.locations_pb2 import (
    ListLocationsRequest, ListLocationsResponse, 
    GetLocationRequest, Location
)

class ListLocationsRequest(message.Message):
    """Request to list available service locations."""
    name: str  # Parent resource name (e.g., "projects/my-project")
    filter: str  # Filter expression for locations
    page_size: int  # Maximum number of locations to return
    page_token: str  # Page token for pagination

class ListLocationsResponse(message.Message):
    """Response containing available locations."""
    locations: list[Location]  # List of available locations
    next_page_token: str  # Token for next page (if any)

class GetLocationRequest(message.Message):
    """Request to get details of a specific location."""
    name: str  # Location resource name

class Location(message.Message):
    """Cloud service location information."""
    name: str  # Location resource name
    location_id: str  # Location identifier (e.g., "us-central1")
    display_name: str  # Human-readable location name
    labels: dict[str, str]  # Location labels and metadata
    metadata: Any  # Location-specific metadata

from google.cloud.extended_operations_pb2 import ExtendedOperation

class ExtendedOperation(message.Message):
    """Extended operation with additional cloud-specific fields."""
    # Inherits basic operation fields and adds:
    # Additional cloud-specific operation metadata
    # Enhanced status reporting
    # Region and zone information
    # Resource hierarchy context

from google.gapic.metadata.gapic_metadata_pb2 import (
    GapicMetadata, ServiceForTransport, ServiceAsClient, MethodList
)

class GapicMetadata(message.Message):
    """Metadata for GAPIC (Generated API Client) libraries."""
    schema: str  # Metadata schema version
    comment: str  # Additional comments
    language: str  # Target programming language
    proto_package: str  # Protocol buffer package name
    library_package: str  # Generated library package name
    services: dict[str, ServiceForTransport]  # Service transport mappings

class ServiceForTransport(message.Message):
    """Service configuration for different transports."""
    clients: dict[str, ServiceAsClient]  # Client configurations

class ServiceAsClient(message.Message):
    """Service as client configuration."""
    library_client: str  # Client class name
    rpcs: dict[str, MethodList]  # RPC method mappings

class MethodList(message.Message):
    """List of methods for a service."""
    methods: list[str]  # Method names

from google.cloud.location.locations_pb2 import ListLocationsRequest, ListLocationsResponse

def list_all_locations(parent: str, client) -> list:
    """List all available locations for a service."""
    request = ListLocationsRequest()
    request.name = parent  # e.g., "projects/my-project"
    request.page_size = 100
    
    all_locations = []
    
    while True:
        response: ListLocationsResponse = client.list_locations(request)
        all_locations.extend(response.locations)
        
        # Check if there are more pages
        if not response.next_page_token:
            break
            
        # Set up next page request
        request.page_token = response.next_page_token
    
    return all_locations

# Example usage
locations = list_all_locations("projects/my-project", location_client)
for location in locations:
    print(f"Location: {location.location_id} ({location.display_name})")

from google.cloud.location.locations_pb2 import ListLocationsRequest

def list_locations_by_region(parent: str, client, region_filter: str = None):
    """List locations with optional region filtering."""
    request = ListLocationsRequest()
    request.name = parent
    
    if region_filter:
        # Filter by region (e.g., "us-", "europe-", "asia-")
        request.filter = f'labels.region:"{region_filter}*"'
    
    response = client.list_locations(request)
    return response.locations

# Examples
us_locations = list_locations_by_region("projects/my-project", client, "us")
europe_locations = list_locations_by_region("projects/my-project", client, "europe")

from google.cloud.location.locations_pb2 import GetLocationRequest, Location

def get_location_info(location_name: str, client) -> Location:
    """Get detailed information about a specific location."""
    request = GetLocationRequest()
    request.name = location_name  # e.g., "projects/my-project/locations/us-central1"
    
    location = client.get_location(request)
    return location

def print_location_details(location: Location):
    """Print detailed location information."""
    print(f"Location Name: {location.name}")
    print(f"Location ID: {location.location_id}")
    print(f"Display Name: {location.display_name}")
    
    print("Labels:")
    for key, value in location.labels.items():
        print(f"  {key}: {value}")
    
    if location.metadata:
        print(f"Metadata: {location.metadata}")

# Example usage
location = get_location_info("projects/my-project/locations/us-central1", client)
print_location_details(location)

from google.cloud.location.locations_pb2 import Location

def select_optimal_location(locations: list[Location], preferences: dict) -> Location:
    """Select optimal location based on preferences."""
    scored_locations = []
    
    for location in locations:
        score = 0
        
        # Score based on region preference
        if preferences.get("preferred_region"):
            if location.location_id.startswith(preferences["preferred_region"]):
                score += 10
        
        # Score based on labels
        for label_key, preferred_value in preferences.get("labels", {}).items():
            if location.labels.get(label_key) == preferred_value:
                score += 5
        
        # Score based on availability zones (if in metadata)
        if preferences.get("multi_zone") and "zones" in location.labels:
            zone_count = len(location.labels["zones"].split(","))
            score += zone_count
        
        scored_locations.append((location, score))
    
    # Return location with highest score
    if scored_locations:
        return max(scored_locations, key=lambda x: x[1])[0]
    
    return locations[0] if locations else None

# Example usage
preferences = {
    "preferred_region": "us-central",
    "labels": {
        "tier": "premium"
    },
    "multi_zone": True
}

optimal_location = select_optimal_location(locations, preferences)
print(f"Selected location: {optimal_location.location_id}")

from google.gapic.metadata.gapic_metadata_pb2 import GapicMetadata

def parse_gapic_metadata(metadata: GapicMetadata):
    """Parse and display GAPIC metadata information."""
    print(f"Schema: {metadata.schema}")
    print(f"Language: {metadata.language}")
    print(f"Proto Package: {metadata.proto_package}")
    print(f"Library Package: {metadata.library_package}")
    
    print("\nServices:")
    for service_name, service_transport in metadata.services.items():
        print(f"  Service: {service_name}")
        
        for transport_name, client_config in service_transport.clients.items():
            print(f"    Transport: {transport_name}")
            print(f"    Client: {client_config.library_client}")
            
            for rpc_name, method_list in client_config.rpcs.items():
                print(f"      RPC: {rpc_name}")
                for method in method_list.methods:
                    print(f"        Method: {method}")

from google.cloud.location.locations_pb2 import Location

def plan_multi_region_deployment(locations: list[Location], 
                                service_requirements: dict) -> dict:
    """Plan multi-region deployment based on requirements."""
    deployment_plan = {
        "primary_regions": [],
        "secondary_regions": [],
        "backup_regions": []
    }
    
    # Group locations by region
    regions = {}
    for location in locations:
        region = location.location_id.split('-')[0] + '-' + location.location_id.split('-')[1]
        if region not in regions:
            regions[region] = []
        regions[region].append(location)
    
    # Sort regions by preference
    preferred_regions = service_requirements.get("preferred_regions", [])
    
    # Select primary regions
    for region in preferred_regions:
        if region in regions and len(deployment_plan["primary_regions"]) < 2:
            deployment_plan["primary_regions"].extend(regions[region][:1])
    
    # Select secondary regions
    remaining_regions = [r for r in regions.keys() 
                        if r not in [loc.location_id for loc in deployment_plan["primary_regions"]]]
    
    for region in remaining_regions[:2]:
        deployment_plan["secondary_regions"].extend(regions[region][:1])
    
    # Select backup regions
    for region in remaining_regions[2:4]:
        deployment_plan["backup_regions"].extend(regions[region][:1])
    
    return deployment_plan

# Example usage
requirements = {
    "preferred_regions": ["us-central", "us-east"],
    "min_regions": 3,
    "disaster_recovery": True
}

deployment = plan_multi_region_deployment(locations, requirements)
print("Deployment Plan:")
print(f"Primary: {[loc.location_id for loc in deployment['primary_regions']]}")
print(f"Secondary: {[loc.location_id for loc in deployment['secondary_regions']]}")
print(f"Backup: {[loc.location_id for loc in deployment['backup_regions']]}")

from google.cloud.location.locations_pb2 import Location
from google.protobuf.struct_pb2 import Struct

def extract_location_capabilities(location: Location) -> dict:
    """Extract service capabilities from location metadata."""
    capabilities = {
        "location_id": location.location_id,
        "display_name": location.display_name,
        "services": [],
        "features": {},
        "zones": []
    }
    
    # Extract from labels
    for key, value in location.labels.items():
        if key.startswith("service/"):
            service_name = key.replace("service/", "")
            if value.lower() == "true":
                capabilities["services"].append(service_name)
        elif key.startswith("feature/"):
            feature_name = key.replace("feature/", "")
            capabilities["features"][feature_name] = value
        elif key == "zones":
            capabilities["zones"] = value.split(",")
    
    # Extract from metadata if available
    if location.metadata:
        # Metadata processing would be service-specific
        pass
    
    return capabilities

# Example usage
for location in locations:
    caps = extract_location_capabilities(location)
    print(f"\nLocation: {caps['location_id']}")
    print(f"Services: {', '.join(caps['services'])}")
    print(f"Zones: {', '.join(caps['zones'])}")
    if caps['features']:
        print("Features:")
        for feature, value in caps['features'].items():
            print(f"  {feature}: {value}")

def calculate_deployment_cost(locations: list[Location], 
                            usage_requirements: dict) -> dict:
    """Calculate estimated deployment costs by location."""
    cost_estimates = {}
    
    # Sample cost factors (would come from actual pricing data)
    base_costs = {
        "us-central": 1.0,    # Base cost multiplier
        "us-east": 0.95,      # 5% cheaper
        "us-west": 1.1,       # 10% more expensive
        "europe-west": 1.2,   # 20% more expensive
        "asia-east": 1.15     # 15% more expensive
    }
    
    for location in locations:
        region_prefix = '-'.join(location.location_id.split('-')[:2])
        base_multiplier = base_costs.get(region_prefix, 1.0)
        
        # Calculate costs based on usage
        compute_cost = usage_requirements.get("compute_hours", 0) * base_multiplier * 0.10
        storage_cost = usage_requirements.get("storage_gb", 0) * base_multiplier * 0.02
        network_cost = usage_requirements.get("network_gb", 0) * base_multiplier * 0.08
        
        total_cost = compute_cost + storage_cost + network_cost
        
        cost_estimates[location.location_id] = {
            "compute": compute_cost,
            "storage": storage_cost,
            "network": network_cost,
            "total": total_cost,
            "multiplier": base_multiplier
        }
    
    return cost_estimates

# Example usage
usage = {
    "compute_hours": 720,  # 1 month
    "storage_gb": 1000,    # 1TB
    "network_gb": 500      # 500GB transfer
}

costs = calculate_deployment_cost(locations, usage)
for location_id, cost_info in sorted(costs.items(), key=lambda x: x[1]["total"]):
    print(f"{location_id}: ${cost_info['total']:.2f}/month")