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Basic Logging

Basic Logging

The ByteHide Logs SDK for Python provides six logging levels that cover the full spectrum of application events, from debug information to critical errors.

Logging Levels

The SDK supports the standard logging levels:

Python
from bytehide_logs import Log, LogLevel

# Debug level - detailed information for debugging
Log.debug("Application started in development mode")

# Info level - general informational messages
Log.info("User login successful")

# Warning level - warning messages about potential issues
Log.warning("API rate limit approaching: 95% used")

# Error level - error messages for recoverable errors
Log.error("Failed to connect to database")

# Critical level - critical messages for severe errors
Log.critical("Payment processing service unavailable")

# Trace level - extremely detailed diagnostic information
Log.trace("Processing request in authentication middleware")

Logging with Exception Handling

Capture exception details automatically using the exception parameter:

Python
try:
    result = perform_payment()
except Exception as e:
    Log.error("Payment processing failed", exception=e)

The SDK automatically captures:

  • Exception type and message
  • Full stack trace
  • Exception chain (if applicable)

Logging with Context

Add contextual data to your log entries using the context parameter:

Python
Log.error(
    "Database query failed",
    exception=query_exception,
    context={
        "query": "SELECT * FROM users WHERE id = ?",
        "database": "production",
        "retry_count": 3
    }
)

Context helps with:

  • Debugging specific issues
  • Correlating related logs
  • Understanding the state when an error occurred

Fluent Syntax

Chain multiple configuration methods together for expressive logging:

Python
Log.with_tags("payment", "stripe") \
    .with_context("transaction_id", "txn_123456") \
    .with_context("amount_cents", 9999) \
    .info("Payment processed successfully")

Fluent syntax allows you to:

  • Add multiple tags in a single call
  • Build up context progressively
  • Write readable, self-documenting logs

Fluent vs Direct Methods

Choose the style that fits your workflow:

Python
# Fluent style - method chaining
Log.with_tags("auth").with_context("user_id", 42).info("Login successful")

# Direct style - straightforward
Log.info("Login successful", context={"user_id": 42})

Both approaches are equally supported and produce identical log entries.

Complete Example

Python
from bytehide_logs import Log

def process_order(order_id, user_id):
    """Process a customer order with comprehensive logging."""
    try:
        Log.info(f"Starting order processing for order {order_id}")
        
        # Perform order validation
        validate_order(order_id)
        
        # Process payment
        payment_result = process_payment(order_id)
        
        Log.with_tags("order", "payment") \
            .with_context("order_id", order_id) \
            .with_context("payment_id", payment_result.id) \
            .info("Order processed successfully")
            
    except ValidationError as e:
        Log.warning(
            f"Order validation failed for order {order_id}",
            exception=e,
            context={"order_id": order_id}
        )
        raise
    except PaymentError as e:
        Log.error(
            f"Payment processing failed for order {order_id}",
            exception=e,
            context={
                "order_id": order_id,
                "user_id": user_id,
                "retry_attempt": 1
            }
        )
        raise

Next Steps

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