Prompt
Check conditions early to skip unnecessary processing and reuse computed values where possible to optimize performance. This reduces CPU cycles and improves execution speed, especially in performance-critical code paths.
Early condition checking example:
# Less performant approach
def process_value(assigned_value):
# Perform expensive operations regardless of value state
result = complex_calculation(assigned_value)
if assigned_value is PydanticUndefined:
return default_value
return result
# More performant approach
def process_value(assigned_value):
# Early check avoids unnecessary processing
if assigned_value is PydanticUndefined:
return default_value
result = complex_calculation(assigned_value)
return result
Value caching example:
def get_schema(cls: type) -> Schema:
# Check if schema already exists before regenerating
schema = cls.__dict__.get('__schema__')
if (
schema is not None
and not isinstance(schema, MockSchema)
and conditions_for_reuse_met(cls)
):
return schema
# Only build new schema when necessary
return build_new_schema(cls)
Apply these patterns whenever you find yourself performing expensive operations that might be unnecessary based on input conditions or when values can be safely reused across calls.