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You need to enhance the test suite by creating a mechanism that allows selective execution of tests marked with xfail conditions depending on dynamic criteria derived from the test environment or runtime information. Specifically, the solution should integrate the usage of the pytest xfail marker as demonstrated in the xfail_demo.py file with the test collection capabilities shown in pythoncollection.py, so that tests marked with xfail can be programmatically collected and filtered before execution. This involves programmatically extracting tests that utilize xfail markers and then dynamically deciding to skip, execute, or rerun them based on criteria such as test name patterns, presence of certain attributes, or runtime checks (similar to those used in xfail conditions). The system should provide a way for users to specify these filters through command line arguments or configuration files so that the pytest test runner executes tests accordingly. This enhancement helps in managing flaky or conditionally failing tests efficiently within a larger test suite, ensuring relevant tests are executed or reported based on up-to-date context rather than static markers alone.
Ensure the solution can discover all tests decorated with xfail markers during test collection phase using pytest's collection hooks.
Implement filtering logic that inspects xfail conditions and other test metadata, allowing dynamic decision making on test execution or skipping.
Allow users to define filtering criteria via pytest command-line options or pytest.ini configuration entries to drive which xfail-marked tests to run or skip.
Maintain compatibility with the existing pytest xfail functionality, preserving the original semantics when no filters are applied.
Test the implementation against test functions and classes similar to those in pythoncollection.py to ensure correct integration with pytest's collection and execution model.
Verify that runtime conditions (such as environment variables or version checks) can influence the filtering behavior dynamically at test run time.
Document the added command-line options and behavior in a way pytest users can easily understand and utilize the new selective xfail execution features.
Ensure that test reports clearly indicate which xfail-marked tests were skipped or executed based on the dynamic filter criteria applied.
The current release process for the pytest project involves two main scripts: `prepare-release-pr.py` and `release.py`. The first script, `prepare-release-pr.py`, is responsible for preparing a release pull request by creating a new release branch from a specified base branch, determining the next version number according to semantic versioning rules (major, minor/feature, patch), running the release tox environment with the appropriate template, pushing the branch to the remote repository, and opening a pull request on GitHub. The `release.py` script handles generating the release announcement documentation, regenerating the project's documentation examples and outputs, fixing formatting using pre-commit hooks, checking links in the docs, and creating the changelog with towncrier before committing all changes locally.
A notable problem arises due to the disjointed nature of these scripts: after the `prepare-release-pr.py` script creates the release branch and runs the release tox environment, the associated documentation generation, changelog updates, announcements, and formatting fixes done in `release.py` are not automatically integrated into the release pull request branch before pushing or pull request creation. This causes an incomplete release PR that lacks the updated documentation artifacts, changelog, and possibly proper commit formatting, forcing developers to manually re-run the second script or perform these steps later.
The task is to improve and integrate the release process such that upon preparing a release pull request with `prepare-release-pr.py`, the script will also invoke, at the appropriate point, the relevant functionality from `release.py` (or equivalent logic) to generate the release announcement, update docs, update the changelog, fix formatting, and optionally check links, so that the release PR branch is fully prepared with all necessary release artifacts before pushing and creating the PR. This must be accomplished without requiring the user to manually run the secondary script or perform additional steps after the PR creation.
The solution should carefully handle environment contexts (e.g., tox environments, git branch states), correctly pass the dynamically determined version, template names, and doc versions consistently between the scripts, and handle any errors gracefully. It should also maintain the current process flow such that if this integration is skipped/disabled, the scripts still work independently as before. This facilitates a smoother, more reliable, and more automated release preparation workflow requiring fewer manual interventions.
Analyze the `prepare-release-pr.py` script to identify the point after the version is determined and the release branch is created and checked out where additional processing should be invoked.
Examine the `release.py` script to understand how the release announcement, docs regeneration, changelog update, formatting fixes, and link checks are performed and the parameters needed (version, template_name, doc_version).
Design an integrated approach in `prepare-release-pr.py` to call the necessary functions or subprocess commands to perform all the release preparation steps currently done by `release.py` after the release branch has been created and checked out, but before pushing and creating the PR.
Ensure environment variables and contexts used in the secondary script (`release.py`) are appropriately set in the integrated calls, especially for tox environments and git state.
Maintain the ability to pass command-line flags such as `--skip-check-links` from the initial release preparation invocation or make it configurable in the integrated process.
Test that the newly integrated release PR branch created includes all updated docs, changelog, and formatting fixes as expected before push.
Validate the error handling so if any sub-steps fail (e.g., docs regeneration or changelog creation), the process exits with an understandable error and does not push an incomplete release PR.
Ensure the commit author and email configurations remain correct when committing changes from the integrated steps within the release branch.
Preserve the existing command-line interface and usage patterns for `prepare-release-pr.py` with minimal additions, such that existing workflows are minimally disrupted.
Verify that authentication tokens and GitHub API usage remain correct and secure after integration, and that pull requests continue to be created with accurate descriptions and metadata.
Enhance the terminal output functionality to provide safe, truncated, and well-formatted string representations when writing potentially large or unrepresentable objects to the terminal. Currently, the TerminalWriter class handles output with support for unicode and markup, but it does not integrate automated safeguarding for large or faulty object representations, which can lead to terminal performance issues or crashes due to unhandled exceptions in __repr__ methods. The objective is to implement a robust mechanism in the TerminalWriter such that whenever it writes an object representation, it uses a safe representation function to truncate output to a maximum size, handle exceptions raised by __repr__, and represent non-unicode safely. This requires modifying the TerminalWriter's write or line methods to utilize the saferepr and saferepr_unlimited functions to generate controlled textual representations of objects before outputting. The solution should ensure that terminal output respects the terminal width constraints, applies markup correctly when enabled, and prevents the propagation of exceptions from faulty __repr__ implementations within written objects. Additionally, the solution must add test coverage validating that large objects, objects with broken __repr__, and unicode content are handled gracefully and their output lines do not exceed terminal width limits or cause crashes.
Verify TerminalWriter's write and line methods accept arbitrary objects and get their string representation using saferepr or saferepr_unlimited appropriately.
Ensure that any exception raised from __repr__ of objects is caught and handled by saferepr mechanisms to output a descriptive fallback string without breaking the TerminalWriter usage.
Test that large object representations are truncated to a controlled max size to avoid flooding the terminal with oversized output.
Confirm that unicode characters in object representations are encoded or escaped safely and do not cause encoding errors in terminal output streams.
Check that the implemented wrappers correctly integrate with TerminalWriter's markup and width computation functionalities, preserving formatting and line widths.
Validate that existing tests for TerminalWriter can be extended or new tests added to verify the robust handling of broken or oversized repr outputs without crashes or unexpected behavior.
Confirm environment variables affecting output formats (e.g., PY_COLORS, NO_COLOR, FORCE_COLOR) still operate correctly with the enhanced safe representation integration.
Problem Statement:
In the given pytest testing codebase, there is comprehensive handling and testing of fixture resolution, parametrization, and dependencies, as well as test collection and module handling. However, there is an opportunity to improve error reporting quality and traceability when a fixture dependency lookup fails due to indirect parametrization or multiple layers of fixture overrides, especially in scenarios involving parametrized fixtures overridden at different levels (e.g., module level vs. conftest vs. class level).
Your task is to enhance the pytest framework's error reporting mechanism so that when a fixture dependency is not found or cannot be resolved (particularly in the presence of indirect parametrization and fixture overrides), the error messages provide richer contextual information. Specifically, the error should include:
1. The precise location (source file and line number) of the test function or fixture that caused the lookup failure.
2. The call chain of fixtures leading to the unresolved fixture dependency, including which fixtures were overridden and where.
3. The parametrization states of the relevant fixtures and how indirect parametrization contributed to the failure.
This enhancement should integrate with pytest's fixture resolution, request, and test collection mechanisms to gather the necessary context. It should also consider cases of overridden fixtures at various scopes (module, class, conftest, plugin) and dynamic fixture parametrization.
Requirements:
- Modify the fixture lookup and resolution error handling to include detailed context (call chain, source locations, parametrization states).
- Ensure the error messages are displayed cleanly as part of test collection or setup failure output.
- Integrate with the existing test reporting infrastructure to display the additional info without disrupting existing formatting.
- Maintain backward compatibility so tests without errors behave unchanged.
- Write new tests to cover scenarios where complex fixture dependency failures occur, confirming the enhanced error messages.
This problem requires modifying error handling and message generation in the fixture management system together with adjusting test collection and reporting, making use of APIs related to fixtures, requests, test items, and collection nodes.
The current setup generates a standalone executable for running pytest tests by embedding pytest using PyInstaller. However, the 'create_executable.py' script builds the executable without explicitly handling or verifying inclusion of all necessary test dependencies and entry points which may cause the produced executable to fail when executed in environments missing those dependencies. The problem is to enhance the process by implementing a more robust and automated dependency inclusion in 'create_executable.py' and ensure that when the generated executable (using 'runtests_script.py' as an entry script) is run, it can correctly locate and execute pytest with all required plugins and dependencies without errors. This improvement should consider dynamically detecting required hidden imports beyond the current manual list, properly passing them to PyInstaller, and verifying the executable runs successfully with a range of testing scenarios. The solution should automate this so the user does not need to manually add hidden imports or dependencies for the pytest executable to work on any target environment.
Analyze how hidden imports are currently collected via 'pytest.freeze_includes()' and identify if it covers all necessary dependencies for the pytest runner.
Enhance 'create_executable.py' to dynamically detect and include all runtime dependencies required by pytest (including plugins and auxiliary modules).
Ensure that '--hidden-import' flags passed to PyInstaller cover these dependencies to avoid import errors at execution.
Maintain inclusion of 'distutils' or any other necessary standard libraries explicitly if needed.
Test the generated executable against a variety of pytest test collections to validate it runs correctly and exits with appropriate status codes.
Handle any potential edge cases where particular pytest plugins or hooks might not be detected automatically and provide a fallback or warning system.
Avoid breaking the current command-line interface and usage of the 'create_executable.py' script.
Document the enhanced process clearly to allow maintainers and users to understand how dependencies are gathered and included.