Data Handling

Database Connections

PostgreSQL

from utils.data import PostgresClient

# Initialize client
db = PostgresClient(
    host="localhost",
    database="mydb",
    username="user",
    password="pass"
)

# Execute query
async with db.transaction():
    result = await db.fetch_all("SELECT * FROM users")

Connection Pooling

from utils.data import ConnectionPool

# Create connection pool
pool = ConnectionPool(
    min_size=5,
    max_size=20,
    timeout=30
)

async with pool.acquire() as conn:
    await conn.execute("INSERT INTO logs (msg) VALUES ($1)", "test")

Data Validation

from utils.data import validate_schema

# Define schema
schema = {
    "type": "object",
    "properties": {
        "name": {"type": "string"},
        "age": {"type": "integer"}
    }
}

# Validate data
is_valid = validate_schema(data, schema)

Hash Generation

from utils.data import HashGenerator

# Create hash
hasher = HashGenerator(algorithm="blake3")
file_hash = hasher.hash_file("path/to/file")
data_hash = hasher.hash_data("my string data")

Data Transformation

from utils.data import Transform

# Convert data formats
transform = Transform()
yaml_data = transform.json_to_yaml(json_data)
xml_data = transform.json_to_xml(json_data)

TODO & Updates Needed

• Add MongoDB support
• Document data migration utilities
• Add data encryption features
• Include data compression utilities
• Document backup procedures
• Add data streaming capabilities