<｜begin▁of▁sentence｜>### Instruction:
In the dynamic world of fashion design, envision a scenario where a digital tool has been developed to assist with fabric calculations, critical for creating flawless garments. This tool is pivotal for preparing accurate material estimates, and it must operate on precise numerical input, in this case, positive integers representing measurements such as lengths and widths.

As a fashion designer, you understand the importance of precision. Thus, before the tool commences its fabric computations, you want to guarantee that the input values for measurements adhere strictly to the standard of being positive integers, safeguarding the integrity of your design process.

To ensure your digital fabric calculator functions with the necessary precision, how can one employ graspologic's check_argument API to establish this stringent precondition, ensuring that any value failing to meet the criterion of being a positive integer triggers a ValueError, complete with an informative message to alert the user?
### Response:
from graspologic.preconditions import check_argument

# Suppose you have a function that requires a positive integer as an argument
def process_data(value):
    # Use check_argument to assert that the condition is met
    check_argument(value > 0, 'Value must be a positive integer')
    # Rest of the function logic goes here
    print(f'Processing data: {value}')

try:
    process_data(-10)
except ValueError as e:
    print(e)
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