Overview, Historical Timeline, Problems & Solutions
An Overview of Python Object Type
What is an object’s type in Python?
In Python, every object has a type. The type tells Python what kind of object it is and what actions it can support. Types define behavior. They decide what you can do with the object.
The type is fixed when the object is created. You cannot change an object’s type. You can use the type() function to check what type an object has.
Python lets you check and use the type of any object.
thing = [1, 2, 3]
print(type(thing)) # <class 'list'>
This tells Python and the programmer that thing is a list.
Why does type matter?
The type controls what happens when you use +, check the length, or call a method. Python checks the type to know what code to run. If the type does not support an operation, Python will raise an error.
Some types are mutable. Some are not. Some can be iterated. Some cannot. The type decides everything the object can and cannot do.
A Historical Timeline of Python Object Type
Where does Python’s type system come from?
Python’s idea of types comes from earlier languages and type systems. But Python made the type system dynamic — values carry types, but names do not. This lets the language stay flexible.
People made types shape behavior.
1960 — Typed variables, ALGOL and early languages linked types to variables.
1972 — Pointers and structs, C showed how types control layout and function over memory.
1980 — Type as behavior, Smalltalk made the type match what methods are supported.
People gave Python dynamic types.
1991 — type() for all objects, Python 0.9.0 linked types to objects, not names.
2001 — Unified type/class model, Python 2.2 made user classes behave like built-in types.
2007 — Abstract base classes, gave standard interfaces to types like Iterable and Sequence.
People made types clearer, not stricter.
2014 — Type hints added, PEP 484 let you describe types without enforcing them.
2023 — Optional strict typing, Python kept the runtime flexible but supported static checkers.
Problems & Solutions with Python Object Type
How do object types help you understand and guide behavior?
Python uses types to define how each object works. The type says what the object can do and what it supports. These examples show how types help solve problems in real code.
Problem 1: Checking if something is a list
Problem: You write a function that may receive a list or something else. You want to check before calling .append().
Solution: Use type() or isinstance() to confirm the object is a list.
Python lets you test type to guide safe behavior.
thing = [1, 2, 3]
if isinstance(thing, list):
thing.append(4)
print(thing)
Only a list supports .append(). Checking avoids errors.
Problem 2: Grouping behavior under one label
Problem: You want to check if something acts like a sequence, even if it’s not a list.
Solution: Use collections.abc.Sequence to check if it matches sequence behavior.
Python lets you check behavior by abstract type.
from collections.abc import Sequence
for item in ([], (), "abc"):
print(isinstance(item, Sequence)) # True for all
All these types support indexed access and length, even though they are different.
Problem 3: Knowing what methods you can call
Problem: You are handed an object and want to know if it can be sorted.
Solution: Check the type. Some types like list can be sorted in place. Others cannot.
Python uses type to control what methods are valid.
a = [3, 1, 2]
a.sort()
print(a) # [1, 2, 3]
Lists support .sort(). Tuples and strings do not.
Problem 4: Type affects mutability
Problem: You want to create a set of stable values. You choose strings, but accidentally use lists, which change.
Solution: The type decides whether a value can change. Use an immutable type like a string or tuple.
Python uses type to define what can and cannot change.
x = (1, 2, 3)
# x[0] = 9 # Error: 'tuple' object does not support item assignment
Tuples cannot be changed. Lists can.
Problem 5: Two things, same value, different behavior
Problem: You write a = 1 and b = "1". They look the same. You want to add them.
Solution: Their types are different, so Python does not know how to combine them.
Python uses type to control how values combine.
a = 1
b = "1"
# print(a + b) # TypeError
The type of each object decides what actions are allowed.
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Mike Vincent is an American software engineer and writer based in Los Angeles. More about Mike Vincent
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