What is dynamic typing?

What you need to know

Names point at objects

In Python, x = 10 does not create a box called x that only holds integers. It creates an int object with the value 10, and makes the name x point at it. Rebinding the name to something else is always allowed:

1x = 102print(type(x))    # <class 'int'>3x = "ten"4print(type(x))    # <class 'str'>

The object 10 still knows it is an int. Only the name moved.

Two separate questions: static or dynamic, strong or weak

• Static vs dynamic — when are types checked? Static languages (Java, Rust, Go) check before running. Dynamic languages (Python, JavaScript) check while running.
• Strong vs weak — does the language silently convert mismatched types? Python refuses; JavaScript converts, so "5" + 5 is "55" there.

1print("5" * 3)            # 555   -> str * int is defined: repetition2try:3    print("5" + 5)4except TypeError as e:5    print(e)              # can only concatenate str (not "int") to str6print(int("5") + 5)       # 10    -> you convert explicitly

Type hints: documentation that tools can check

1def double(x: int) -> int:2    return x * 234print(double(4))        # 85print(double("ab"))     # abab -> no error: hints are not checked at runtime

Type hints (int, list[float], dict[str, int], str | None) do nothing at runtime — Python happily calls double with a string. Their value is that a type checker such as mypy or pyright reads them before the code runs and reports mismatches, and your editor uses them for autocomplete. Modern syntax: built-in generics like list[str] work from Python 3.9, and X | None from 3.10.

A real-life example

You load a CSV of card transactions and total the amounts. The csv module returns every field as a str, but nothing tells you that until the code runs:

1import csv, io23data = io.StringIO("txn_id,amount\nT1,499.00\nT2,120.50\n")4rows = list(csv.DictReader(data))56total = 07try:8    for row in rows:9        total += row["amount"]        # row["amount"] is the str "499.00"10except TypeError as e:11    print("Bug:", e)   # Bug: unsupported operand type(s) for +=: 'int' and 'str'1213total = sum(float(row["amount"]) for row in rows)14print(total)           # 619.5

In a nightly job this crash would happen at 2 a.m., on the server. With a hint like def total(rows: list[dict[str, str]]) -> float, mypy flags the int + str mix in the pull request instead.

Follow-up questions to expect

• "Do type hints make Python faster or enforce types?" — No. CPython ignores them at runtime. Tools like mypy use them, and libraries like Pydantic and FastAPI read them to validate data.
• "What is duck typing?" — Caring about what an object can do, not what class it is. If it has a .read() method, you can treat it like a file.
• "What are the benefits of dynamic typing?" — Less code, fast prototyping in notebooks, and flexible functions that work on many types.