Python typing.assert_never() Function: Exhaustive Checking

assert_never(value) reports an impossible type to a static checker and raises an AssertionError if executed.

What It Does and Why It Matters

assert_never(value) reports an impossible type to a static checker and raises an AssertionError if executed. It helps keep branches exhaustive as a Literal or enum evolves.

Annotations guide static tools; by default they do not validate external input or change the return value at runtime.

Step-by-Step Example

Start with the complete example below. Read the inputs and predict what the final print statement will show before you run it.

from typing import Literal, assert_never
Status = Literal['ready', 'paused']
def status_message(status: Status) -> str:
    if status == 'ready':
        return 'Run now'
    if status == 'paused':
        return 'Stand by'
    assert_never(status)
print(status_message('ready'))

How the Code Works

The imports make these standard-library tools available: typing.
The definition of status_message creates reusable behavior; its body runs only when called or instantiated as appropriate.
The name Status receives the value of Literal['ready', 'paused']. Changing this input lets you explore a different case.
The print calls display the results. Compare these results with the method’s documented return type and the input used.
The annotations describe intended types for editors and checkers. They are not a replacement for validating input values when the function runs.

Expected output:

Run now

For the demonstrated inputs, Python displays 'Run now'. This result follows from the operation described above; change one input at a time to understand which rule matters.

What to Notice

Pay attention to the accepted input types, the returned value and the boundary behavior. Predict what changes if you replace the example input with an empty, zero, negative or missing value, where that value is meaningful for this operation.

If the task uses a library function, inspect its documented exceptions and return type before reusing it inside a larger function.

Where You Would Use This

This helps maintain larger projects where functions and data shapes cross module boundaries. Check the code with a static analyzer, and still validate data received from files, users or remote APIs. Annotation constructs do not normally enforce types automatically at runtime.

Practice Exercise

Implement exhaustive handling for two Literal states.

Before running your edited example, write down the result you expect. Then test at least one valid boundary or deliberately invalid value, using appropriate exception handling where necessary.

Reference: official Python documentation for the complete API contract and version notes.

Common Beginner Mistakes

Using assert_never() to handle normal invalid user input instead of validating it first.
Overlooking the documented condition: assert_never(value) reports an impossible type to a static checker and raises an AssertionError if executed.

Key Takeaways

assert_never(value) reports an impossible type to a static checker and raises an AssertionError if executed.
Implement exhaustive handling for two Literal states.
Annotations guide static tools; by default they do not validate external input or change the return value at runtime.