@Scout How can I utilize mypy with assets?

The documentation does not provide explicit instructions on how to utilize

mypy

with assets. However, since assets in Dagster are defined using Python functions, and

mypy

is a static type checker for Python, you can use

mypy

with Dagster assets in the same way you would with any other Python code. To utilize

mypy

with assets, you would: 1. Annotate your asset functions with type hints. This includes specifying the types of any input parameters and the return type of the function. 2. Run

mypy

on your codebase where your assets are defined to perform static type checking. Here's a hypothetical example of how you might annotate a simple asset with type hints:

python from dagster import asset  @asset def my_asset(input_data: str) -> int:     # process the input_data in some way     result = len(input_data)     return result

In this example,

input_data

is expected to be a string, and the asset is expected to return an integer. After annotating your assets, you would run

mypy

from the command line to check for type consistency:

shell mypy path_to_your_assets.py

Remember to replace

path_to_your_assets.py

with the actual path to the Python file containing your asset definitions. If

mypy

finds any type inconsistencies, it will report them, and you can then make the necessary adjustments to your code. Please note that while the documentation does not explicitly discuss the use of

mypy

with Dagster assets, the above approach is a general practice for using

mypy

with Python code and should be applicable to Dagster assets as well.

@Scout If I write a test for my asset that asserts the correct length for the input_data I get the following error: Incompatible types in assignment

The error message "Incompatible types in assignment" typically indicates that

mypy

has detected a type mismatch between the expected type and the actual type of a variable at the point of assignment. This can happen if the type of the value being assigned does not match the declared type of the variable. To resolve this issue, you should ensure that the types in your test match the expected types in your asset definition. Here's a step-by-step approach to troubleshoot and fix the issue: 1. Review the Asset Function: Check the type hints in your asset function to confirm the expected types for inputs and outputs. 2. Check the Test Code: Look at the test code where the assignment is happening. Ensure that the value being assigned to a variable matches the type expected by the asset function. 3. Correct the Types: If there is a mismatch, you will need to correct the types in your test. This might involve changing the type of the test input to match the expected type or casting the input to the correct type. 4. Run mypy Again: After making the necessary changes, run

mypy

again to see if the error has been resolved. Here's an example of how you might write a test for the asset function provided earlier, ensuring that the types match:

python from dagster import execute_pipeline, pipeline  # Assuming this is your asset function @asset def my_asset(input_data: str) -> int:     return len(input_data)  # A pipeline that includes your asset @pipeline def my_pipeline():     my_asset()  # A test function for the asset def test_my_asset():     result = execute_pipeline(my_pipeline, run_config={         "solids": {             "my_asset": {                 "inputs": {                     "input_data": "test string"                 }             }         }     })     assert result.success     assert result.result_for_solid("my_asset").output_value() == len("test string")

In this test, we're passing a string

"test string"

to the

input_data

parameter, which matches the expected type

str

in the asset function. We then assert that the output is an integer equal to the length of the input string, which matches the expected return type

int

. If you continue to encounter issues, please provide the specific code snippet that is causing the error, and I can help you troubleshoot further.