Exam Bundle

Unit tests and two separate notebooks import the same function successfully pertains to a different control (Move transformation functions into an importable Python package in the repository) and a different need (Shared transformations are duplicated across five notebooks and need one maintained implementation). It cannot establish that Read validated parameters from job parameters or environment configuration met the stated goal.

This signal belongs to the adjacent case “A library release must be reproducible rather than resolving an arbitrary latest release,” whose remedy is Pin an appropriate tested dependency version in the project or environment manifest. The observed result for the present requirement is The same packaged code runs with two allowed configuration sets.

This signal belongs to the adjacent case “A Python module import fails only when running a deployed Databricks job,” whose remedy is Package the module and install or declare the dependency in the job environment. The observed result for the present requirement is The same packaged code runs with two allowed configuration sets.

This action solves a different issue: “A task reports conflicting transitive package requirements after adding a dependency.” Its normal signal is The dependency resolver installs a consistent environment without conflicts. Here the requested behavior is “A required PyPI library is missing when the Python task starts,” so that signal is not sufficient.

Build or choose a wheel compatible with the target Python/runtime environment is appropriate when “A local wheel works on one runtime but fails because its Python ABI is incompatible on another”; it would be verified by The wheel installs and import tests pass on that target compute. It does not directly satisfy “A required PyPI library is missing when the Python task starts,” whose relevant acceptance evidence is The task imports the required package and the package version is visible.

Pin the dependency to a validated version and redeploy is appropriate when “An external dependency silently changes behavior after an unpinned upgrade”; it would be verified by The job resolves the tested version and regression tests pass. It does not directly satisfy “A required PyPI library is missing when the Python task starts,” whose relevant acceptance evidence is The task imports the required package and the package version is visible.

That observation is a valid indicator for “A package import works in an interactive notebook but not in the production job” when using Install the dependency for the actual job task environment rather than relying on the notebook session. The scenario instead tests “A required PyPI library is missing when the Python task starts”; the relevant result is The task imports the required package and the package version is visible.

The dependency resolver installs a consistent environment without conflicts would demonstrate the separate action Resolve the package constraint conflict and lock compatible versions, which addresses “A task reports conflicting transitive package requirements after adding a dependency.” It does not verify the requirement “A required PyPI library is missing when the Python task starts” following Declare or install the supported package in the task environment.

That observation is a valid indicator for “A local wheel works on one runtime but fails because its Python ABI is incompatible on another” when using Build or choose a wheel compatible with the target Python/runtime environment. The scenario instead tests “A required PyPI library is missing when the Python task starts”; the relevant result is The task imports the required package and the package version is visible.

This action solves a different issue: “A task reports conflicting transitive package requirements after adding a dependency.” Its normal signal is The dependency resolver installs a consistent environment without conflicts. Here the requested behavior is “A local wheel works on one runtime but fails because its Python ABI is incompatible on another,” so that signal is not sufficient.

This action solves a different issue: “A package import works in an interactive notebook but not in the production job.” Its normal signal is The same import succeeds in a fresh scheduled job run. Here the requested behavior is “A local wheel works on one runtime but fails because its Python ABI is incompatible on another,” so that signal is not sufficient.

The alternative Pin the dependency to a validated version and redeploy has a distinct purpose—An external dependency silently changes behavior after an unpinned upgrade. It would not establish the required outcome (A local wheel works on one runtime but fails because its Python ABI is incompatible on another); the necessary verification concerns The wheel installs and import tests pass on that target compute.

The same import succeeds in a fresh scheduled job run pertains to a different control (Install the dependency for the actual job task environment rather than relying on the notebook session) and a different need (A package import works in an interactive notebook but not in the production job). It cannot establish that Build or choose a wheel compatible with the target Python/runtime environment met the stated goal.

The job resolves the tested version and regression tests pass pertains to a different control (Pin the dependency to a validated version and redeploy) and a different need (An external dependency silently changes behavior after an unpinned upgrade). It cannot establish that Build or choose a wheel compatible with the target Python/runtime environment met the stated goal.

The task imports the required package and the package version is visible pertains to a different control (Declare or install the supported package in the task environment) and a different need (A required PyPI library is missing when the Python task starts). It cannot establish that Build or choose a wheel compatible with the target Python/runtime environment met the stated goal.

The alternative Declare or install the supported package in the task environment has a distinct purpose—A required PyPI library is missing when the Python task starts. It would not establish the required outcome (An external dependency silently changes behavior after an unpinned upgrade); the necessary verification concerns The job resolves the tested version and regression tests pass.

Build or choose a wheel compatible with the target Python/runtime environment is appropriate when “A local wheel works on one runtime but fails because its Python ABI is incompatible on another”; it would be verified by The wheel installs and import tests pass on that target compute. It does not directly satisfy “An external dependency silently changes behavior after an unpinned upgrade,” whose relevant acceptance evidence is The job resolves the tested version and regression tests pass.

Resolve the package constraint conflict and lock compatible versions is appropriate when “A task reports conflicting transitive package requirements after adding a dependency”; it would be verified by The dependency resolver installs a consistent environment without conflicts. It does not directly satisfy “An external dependency silently changes behavior after an unpinned upgrade,” whose relevant acceptance evidence is The job resolves the tested version and regression tests pass.

This signal belongs to the adjacent case “A package import works in an interactive notebook but not in the production job,” whose remedy is Install the dependency for the actual job task environment rather than relying on the notebook session. The observed result for the present requirement is The job resolves the tested version and regression tests pass.

The task imports the required package and the package version is visible pertains to a different control (Declare or install the supported package in the task environment) and a different need (A required PyPI library is missing when the Python task starts). It cannot establish that Pin the dependency to a validated version and redeploy met the stated goal.

The dependency resolver installs a consistent environment without conflicts pertains to a different control (Resolve the package constraint conflict and lock compatible versions) and a different need (A task reports conflicting transitive package requirements after adding a dependency). It cannot establish that Pin the dependency to a validated version and redeploy met the stated goal.

The alternative Declare or install the supported package in the task environment has a distinct purpose—A required PyPI library is missing when the Python task starts. It would not establish the required outcome (A task reports conflicting transitive package requirements after adding a dependency); the necessary verification concerns The dependency resolver installs a consistent environment without conflicts.

Install the dependency for the actual job task environment rather than relying on the notebook session belongs to the separate case “A package import works in an interactive notebook but not in the production job,” where The same import succeeds in a fresh scheduled job run would be expected. That differs from the condition in this stem: “A task reports conflicting transitive package requirements after adding a dependency.”

The alternative Build or choose a wheel compatible with the target Python/runtime environment has a distinct purpose—A local wheel works on one runtime but fails because its Python ABI is incompatible on another. It would not establish the required outcome (A task reports conflicting transitive package requirements after adding a dependency); the necessary verification concerns The dependency resolver installs a consistent environment without conflicts.

This signal belongs to the adjacent case “A required PyPI library is missing when the Python task starts,” whose remedy is Declare or install the supported package in the task environment. The observed result for the present requirement is The dependency resolver installs a consistent environment without conflicts.

This signal belongs to the adjacent case “A package import works in an interactive notebook but not in the production job,” whose remedy is Install the dependency for the actual job task environment rather than relying on the notebook session. The observed result for the present requirement is The dependency resolver installs a consistent environment without conflicts.

This signal belongs to the adjacent case “An external dependency silently changes behavior after an unpinned upgrade,” whose remedy is Pin the dependency to a validated version and redeploy. The observed result for the present requirement is The dependency resolver installs a consistent environment without conflicts.

Pin the dependency to a validated version and redeploy is appropriate when “An external dependency silently changes behavior after an unpinned upgrade”; it would be verified by The job resolves the tested version and regression tests pass. It does not directly satisfy “A package import works in an interactive notebook but not in the production job,” whose relevant acceptance evidence is The same import succeeds in a fresh scheduled job run.

Resolve the package constraint conflict and lock compatible versions belongs to the separate case “A task reports conflicting transitive package requirements after adding a dependency,” where The dependency resolver installs a consistent environment without conflicts would be expected. That differs from the condition in this stem: “A package import works in an interactive notebook but not in the production job.”

This action solves a different issue: “A local wheel works on one runtime but fails because its Python ABI is incompatible on another.” Its normal signal is The wheel installs and import tests pass on that target compute. Here the requested behavior is “A package import works in an interactive notebook but not in the production job,” so that signal is not sufficient.

The dependency resolver installs a consistent environment without conflicts pertains to a different control (Resolve the package constraint conflict and lock compatible versions) and a different need (A task reports conflicting transitive package requirements after adding a dependency). It cannot establish that Install the dependency for the actual job task environment rather than relying on the notebook session met the stated goal.

The task imports the required package and the package version is visible would demonstrate the separate action Declare or install the supported package in the task environment, which addresses “A required PyPI library is missing when the Python task starts.” It does not verify the requirement “A package import works in an interactive notebook but not in the production job” following Install the dependency for the actual job task environment rather than relying on the notebook session.

This signal belongs to the adjacent case “An external dependency silently changes behavior after an unpinned upgrade,” whose remedy is Pin the dependency to a validated version and redeploy. The observed result for the present requirement is The same import succeeds in a fresh scheduled job run.