[REQ] Add More Information To `expect_near()` Output When Comparison Fails

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Request Overview

The current implementation of expect_near() in our testing framework provides limited information when a comparison fails, resulting in cryptic error messages. This request aims to enhance the output of expect_near() to provide more detailed information about the comparison failure, including the actual difference between the expected and actual values. This improvement will facilitate better debugging and troubleshooting of issues.

Current Limitations

When a comparison fails using expect_near(), the error message is often unclear, making it challenging to identify the root cause of the issue. The current output typically includes the tolerance value and the expected and actual values, but it does not provide any information about the actual difference between the two values. This lack of detail can lead to confusion and make it more difficult to resolve the problem.

Desired Output

To improve the debugging experience, we should aim to provide an output that is similar to what is obtained from using the np.testing functions, such as assert_almost_equal(). This would involve including the actual difference between the expected and actual values in the error message. For example:

Error, expect_near() failed with tolerance 1e-08
	 Expected: 2
	 Actual: 2.5
	 Difference: 0.5

Proposed Changes

To achieve the desired output, we can modify the expect_near() function to calculate the actual difference between the expected and actual values when a comparison fails. This can be done by subtracting the expected value from the actual value and including the result in the error message.

Here is an example of how the modified expect_near() function could be implemented:

def expect_near(expected, actual, tolerance):
    # Calculate the actual difference between the expected and actual values
    difference = abs(expected - actual)
    
    # Check if the difference is within the tolerance
    if difference > tolerance:
        # If the difference is not within the tolerance, raise an error
        raise ValueError(f"Error, expect_near() failed with tolerance {tolerance}")
        
        # Include the actual difference in the error message
        print(f"	 Expected: {expected}")
        print(f"	 Actual: {actual}")
        print(f"	 Difference: {difference}")
    else:
        # If the difference is within the tolerance, return True
        return True

Benefits of the Proposed Changes

The proposed changes to the expect_near() function will provide several benefits, including:

  • Improved debugging: By including the actual difference between the expected and actual values in the error message, developers will be able to quickly identify the root cause of the issue and resolve the problem more efficiently.
  • Enhanced testing: The modified expect_near() function will provide more detailed information about the comparison failure, making it easier to write and maintain tests.
  • Better error handling: The proposed changes will enable developers to handle errors more effectively, reducing the likelihood of errors and improving the overall quality of the code.

Conclusion

Q: What is the current issue with expect_near() output?

A: The current implementation of expect_near() in our testing framework provides limited information when a comparison fails, resulting in cryptic error messages. The output typically includes the tolerance value and the expected and actual values, but it does not provide any information about the actual difference between the two values.

Q: Why is it important to include the actual difference in the error message?

A: Including the actual difference in the error message will facilitate better debugging and troubleshooting of issues. By providing more detailed information about the comparison failure, developers will be able to quickly identify the root cause of the issue and resolve the problem more efficiently.

Q: How will the proposed changes to expect_near() function improve testing?

A: The modified expect_near() function will provide more detailed information about the comparison failure, making it easier to write and maintain tests. This will lead to improved testing and reduced errors.

Q: What are the benefits of using np.testing functions like assert_almost_equal()?

A: Using np.testing functions like assert_almost_equal() provides more detailed information about the comparison failure, including the actual difference between the expected and actual values. This makes it easier to debug and troubleshoot issues.

Q: How will the proposed changes to expect_near() function improve error handling?

A: The modified expect_near() function will enable developers to handle errors more effectively, reducing the likelihood of errors and improving the overall quality of the code.

Q: What is the proposed solution to enhance expect_near() output?

A: The proposed solution involves modifying the expect_near() function to calculate the actual difference between the expected and actual values when a comparison fails. This will include the actual difference in the error message, providing more detailed information about the comparison failure.

Q: How will the proposed changes to expect_near() function be implemented?

A: The proposed changes to expect_near() function will be implemented by modifying the function to calculate the actual difference between the expected and actual values when a comparison fails. This will involve adding code to calculate the difference and including it in the error message.

Q: What are the potential challenges in implementing the proposed changes to expect_near() function?

A: The potential challenges in implementing the proposed changes to expect_near() function include:

  • Code modifications: Modifying the expect_near() function to calculate the actual difference between the expected and actual values will require code modifications.
  • Testing: Thorough testing will be required to ensure that the modified expect_near() function works as expected.
  • Integration: The modified expect_near() function will need to be integrated with the existing testing framework.

Q: How will the proposed changes to expect_near() function be tested?

A: The proposed changes to expect_near() function will be tested using a combination of unit and integration tests. This will ensure that the modified function works as expected and provides the desired output.

Q: What is the expected outcome of the proposed changes to expect_near() function?

A: The expected outcome of the proposed changes to expect_near() function is to provide more detailed information about the comparison failure, making it easier to debug and troubleshoot issues. This will lead to improved testing, reduced errors, and better error handling.