How to Add Custom Xml Attributes At Collection Time In Pytest?

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To add custom XML attributes at collection time in pytest, you can use the pytest_collection_modifyitems hook provided by pytest. This hook allows you to modify the collected items before they are run.


You can define a function that uses this hook to add custom XML attributes to the collected items. Inside this function, you can iterate through the collected items and add the desired attributes using the extra_args attribute.


For example, you can add custom attributes like test_id, description, or any other metadata that you want to include in the generated XML report. These attributes will be included in the XML report and can be used for additional analysis or reporting purposes.


Overall, using the pytest_collection_modifyitems hook allows you to add custom XML attributes at collection time in pytest, providing you with more flexibility and customization options for your test suite.


What is the reason for assigning custom data to pytest test cases?

Assigning custom data to pytest test cases allows for more specific and targeted testing. By providing custom data, test cases can be tailored to different scenarios or edge cases, ensuring thorough coverage of the code being tested. Custom data can also help with debugging and troubleshooting, as it provides more context for any failures or errors that may occur during testing. Additionally, custom data can be used to parameterize test cases, allowing for more efficient and reusable testing.


What is the benefit of including custom metadata in pytest XML reports?

Including custom metadata in pytest XML reports allows users to add additional information or context to their test results, making it easier to analyze and interpret the test reports. Custom metadata can be used to provide details such as environment configurations, test setup information, or any other relevant data that can help in troubleshooting or debugging test failures. This additional information can help in identifying the root causes of test failures quickly and accurately, and makes it easier to track and manage test results across different test runs.


How to categorize pytest tests based on user-defined attributes?

To categorize pytest tests based on user-defined attributes, you can use marker annotations provided by pytest. Here's a step-by-step guide on how to do this:

  1. Define custom markers: You can define custom markers using the pytest.mark decorator. For example, you can define a custom marker sanity like this:
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import pytest

@pytest.mark.sanity
def test_sanity_check():
    assert True


  1. Add markers to tests: You can then add the custom markers to your tests by using the pytest.mark decorator. In the above example, the test_sanity_check test has been marked with the sanity marker.
  2. Run tests with markers: To run tests based on markers, you can use the -m option with pytest. For example, to run only tests marked with the sanity marker, you can use the following command:
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pytest -m sanity


This command will only run tests that have been marked with the sanity marker.

  1. Group tests with custom attributes: You can also define custom attributes for your tests and group them based on these attributes. For example, you can define a custom attribute group and categorize tests based on this attribute like this:
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import pytest

@pytest.mark.parametrize("input,expected", [
    ("", True),
    ("hello", False),
])
@pytest.mark.group("empty_strings")
def test_empty_string_check(input, expected):
    assert input == "" == expected


  1. Run tests based on custom attributes: You can run tests based on custom attributes by using the -k option with pytest. For example, to run only tests that belong to the empty_strings group, you can use the following command:
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pytest -k "empty_strings"


By following these steps, you can categorize pytest tests based on user-defined attributes and group them accordingly for better organization and control over test execution.

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