Python Error Handling Agent Skill

def fetch_page(url: str, page_size: int) -> Page:
    if not url:
        raise ValueError("'url' is required")
    if not 1 <= page_size <= 100:
        raise ValueError(f"'page_size' must be 1-100, got {page_size}")
    # Now safe to proceed...

def process_order(
    order_id: str,
    quantity: int,
    discount_percent: float,
) -> OrderResult:
    """Process an order with validation."""
    # Validate required fields
    if not order_id:
        raise ValueError("'order_id' is required")

    # Validate ranges
    if quantity <= 0:
        raise ValueError(f"'quantity' must be positive, got {quantity}")

    if not 0 <= discount_percent <= 100:
        raise ValueError(
            f"'discount_percent' must be 0-100, got {discount_percent}"
        )

    # Validation passed, proceed with processing
    return _process_validated_order(order_id, quantity, discount_percent)

from enum import Enum

class OutputFormat(Enum):
    JSON = "json"
    CSV = "csv"
    PARQUET = "parquet"

def parse_output_format(value: str) -> OutputFormat:
    """Parse string to OutputFormat enum.

    Args:
        value: Format string from user input.

    Returns:
        Validated OutputFormat enum member.

    Raises:
        ValueError: If format is not recognized.
    """
    try:
        return OutputFormat(value.lower())
    except ValueError:
        valid_formats = [f.value for f in OutputFormat]
        raise ValueError(
            f"Invalid format '{value}'. "
            f"Valid options: {', '.join(valid_formats)}"
        )

# Usage at API boundary
def export_data(data: list[dict], format_str: str) -> bytes:
    output_format = parse_output_format(format_str)  # Fail fast
    # Rest of function uses typed OutputFormat
    ...

from pydantic import BaseModel, Field, field_validator

class CreateUserInput(BaseModel):
    """Input model for user creation."""

    email: str = Field(..., min_length=5, max_length=255)
    name: str = Field(..., min_length=1, max_length=100)
    age: int = Field(ge=0, le=150)

    @field_validator("email")
    @classmethod
    def validate_email_format(cls, v: str) -> str:
        if "@" not in v or "." not in v.split("@")[-1]:
            raise ValueError("Invalid email format")
        return v.lower()

    @field_validator("name")
    @classmethod
    def normalize_name(cls, v: str) -> str:
        return v.strip().title()

# Usage
try:
    user_input = CreateUserInput(
        email="[email protected]",
        name="john doe",
        age=25,
    )
except ValidationError as e:
    # Pydantic provides detailed error information
    print(e.errors())

# Good: Specific exception with context
raise ValueError(f"'page_size' must be 1-100, got {page_size}")

# Avoid: Generic exception, no context
raise Exception("Invalid parameter")