from arcadedb_python import DatabaseDao

# Connect to ArcadeDB
db = DatabaseDao(
    host="localhost",
    port=2480,
    database="mydb",
    username="root",
    password="playwithdata"
)

# Execute SQL queries
result = db.query("sql", "SELECT FROM V LIMIT 10")
print(result)

# Create vertices and edges
db.command("sql", "CREATE VERTEX TYPE Person")
db.command("sql", "INSERT INTO Person SET name = 'John', age = 30")

# Graph traversal
result = db.query("sql", """
    MATCH {type: Person, as: person} 
    RETURN person.name, person.age
""")

from arcadedb_python import ArcadeDBConfig, DatabaseDao

# Using configuration object
config = ArcadeDBConfig(
    host="localhost",
    port=2480,
    username="root",
    password="playwithdata"
)

db = DatabaseDao.from_config(config, "mydb")

import asyncio
from arcadedb_python import DatabaseDao

async def main():
    db = DatabaseDao("localhost", 2480, "mydb", "root", "playwithdata")
    
    # Async query execution
    result = await db.query_async("sql", "SELECT FROM V LIMIT 10")
    print(result)

asyncio.run(main())

# Document operations
db.command("sql", "CREATE DOCUMENT TYPE Product")
db.command("sql", """
    INSERT INTO Product CONTENT {
        "name": "Laptop",
        "price": 999.99,
        "specs": {
            "cpu": "Intel i7",
            "ram": "16GB"
        }
    }
""")

# Graph operations
db.command("sql", "CREATE VERTEX TYPE Customer")
db.command("sql", "CREATE EDGE TYPE Purchased")
db.command("sql", """
    CREATE EDGE Purchased 
    FROM (SELECT FROM Customer WHERE name = 'John')
    TO (SELECT FROM Product WHERE name = 'Laptop')
    SET date = date(), amount = 999.99
""")

# Key-Value operations
db.command("sql", "CREATE DOCUMENT TYPE Settings")
db.command("sql", "INSERT INTO Settings SET key = 'theme', value = 'dark'")

# Time-Series operations
db.command("sql", "CREATE VERTEX TYPE Sensor")
db.command("sql", """
    INSERT INTO Sensor SET 
    sensor_id = 'temp_01', 
    timestamp = sysdate(), 
    temperature = 23.5
""")

# Store embeddings
db.command("sql", """
    CREATE VERTEX TYPE Document SET 
    title = 'AI Research Paper',
    embedding = [0.1, 0.2, 0.3, ...],  # Your vector embeddings
    content = 'Full document text...'
""")

# Vector similarity search
result = db.query("sql", """
    SELECT title, content, 
           cosine_similarity(embedding, [0.1, 0.2, 0.3, ...]) as similarity
    FROM Document 
    ORDER BY similarity DESC 
    LIMIT 10
""")