Dynamic typing determines a variable’s data type during program execution rather than requiring type checks before execution. Python is dynamically typed, so the same variable can receive values of different types as a program runs. section 3.5
Runtime behavior in Python
Python attempts method calls during execution. If an object lacks the requested method, the call raises AttributeError rather than failing during compilation. This supports duck typing: objects can provide compatible behavior without sharing the same class. section 3.5
Dynamic typing affects everyday Python design in several ways:
- Inspect objects with type(), isinstance(), and issubclass() when debugging makes an object’s type unclear. section 8.3.1
- Use type hints as guidance for developers and automated tools; Python does not enforce them during execution. section 8.3.1
- Prefer behavior and shared messages over rigid type-dependent designs when creating loosely coupled code. section 10.1.3
- Recognize that dynamic typing can remove the need for some creational design patterns developed for statically typed languages. section 11.2.1
>>> type(42)
<class 'int'>
>>> type({'dessert': 'cookie', 'flavor': 'chocolate chip'})
<class 'dict'>
Inspecting values such as integers and dictionaries makes runtime type determination concrete. section 8.3.1
