wag-managment-api-service-version-4/Services/MongoDb/how_to.py

"""
MongoDB Operations Examples

This module provides practical examples of using MongoDB operations through our mixins.
Each example demonstrates different aspects of CRUD operations and aggregation.
"""

from typing import Dict, List, Any
from datetime import datetime

from Services.MongoDb.database import mongodb


def insert_examples() -> None:
    """Examples of insert operations."""
    # Single document insert
    user_doc = {
        "username": "john_doe",
        "email": "john@example.com",
        "age": 30,
        "created_at": datetime.utcnow(),
    }
    user_id = mongodb.insert_one(
        database="user_db", collection="users", document=user_doc
    )
    print(f"Inserted user with ID: {user_id}")

    # Multiple documents insert
    products = [
        {"name": "Laptop", "price": 999.99, "stock": 50},
        {"name": "Mouse", "price": 29.99, "stock": 100},
        {"name": "Keyboard", "price": 59.99, "stock": 75},
    ]
    product_ids = mongodb.insert_many(
        database="store_db", collection="products", documents=products
    )
    print(f"Inserted {len(product_ids)} products")


def find_examples() -> None:
    """Examples of find operations."""
    # Find one document
    user = mongodb.find_one(
        database="user_db",
        collection="users",
        filter_query={"email": "john@example.com"},
        projection={"username": 1, "email": 1, "_id": 0},
    )
    print(f"Found user: {user}")

    # Find many with pagination
    page_size = 10
    page_number = 1
    products = mongodb.find_many(
        database="store_db",
        collection="products",
        filter_query={"price": {"$lt": 100}},
        projection={"name": 1, "price": 1},
        sort=[("price", 1)],  # Sort by price ascending
        limit=page_size,
        skip=(page_number - 1) * page_size,
    )
    print(f"Found {len(products)} products under $100")


def update_examples() -> None:
    """Examples of update operations."""
    # Update single document
    result = mongodb.update_one(
        database="store_db",
        collection="products",
        filter_query={"name": "Laptop"},
        update_data={"price": 899.99, "stock": 45},
        upsert=False,
    )
    print(f"Updated {result['modified_count']} laptop(s)")

    # Update multiple documents
    result = mongodb.update_many(
        database="store_db",
        collection="products",
        filter_query={"stock": {"$lt": 10}},
        update_data={"status": "low_stock"},
        upsert=True,
    )
    print(f"Updated {result['modified_count']} low stock products")


def delete_examples() -> None:
    """Examples of delete operations."""
    # Delete single document
    count = mongodb.delete_one(
        database="user_db",
        collection="users",
        filter_query={"email": "john@example.com"},
    )
    print(f"Deleted {count} user")

    # Delete multiple documents
    count = mongodb.delete_many(
        database="store_db", collection="products", filter_query={"stock": 0}
    )
    print(f"Deleted {count} out-of-stock products")


def aggregate_examples() -> None:
    """Examples of aggregation operations."""
    # Calculate average price by category
    pipeline = [
        {
            "$group": {
                "_id": "$category",
                "avg_price": {"$avg": "$price"},
                "total_products": {"$sum": 1},
            }
        },
        {"$sort": {"avg_price": -1}},
    ]
    results = mongodb.aggregate(
        database="store_db", collection="products", pipeline=pipeline
    )
    print("Category statistics:", list(results))


def complex_query_example() -> None:
    """Example of a complex query combining multiple operations."""
    # Find active users who made purchases in last 30 days
    pipeline = [
        {
            "$match": {
                "status": "active",
                "last_purchase": {
                    "$gte": datetime.utcnow().replace(day=datetime.utcnow().day - 30)
                },
            }
        },
        {
            "$lookup": {
                "from": "orders",
                "localField": "_id",
                "foreignField": "user_id",
                "as": "recent_orders",
            }
        },
        {
            "$project": {
                "username": 1,
                "email": 1,
                "total_orders": {"$size": "$recent_orders"},
                "total_spent": {"$sum": "$recent_orders.amount"},
            }
        },
        {"$sort": {"total_spent": -1}},
    ]
    results = mongodb.aggregate(
        database="user_db", collection="users", pipeline=pipeline
    )
    print("Active users with recent purchases:", list(results))


if __name__ == "__main__":
    # Example usage of all operations
    insert_examples()
    find_examples()
    update_examples()
    delete_examples()
    aggregate_examples()
    complex_query_example()