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make_query()
parameter name (#61). Themake_query()
fixture's documentation has been updated to correct the name of thequery
parameter tosql_query
. Thesql_query
parameter is used to specify the SQL query stored in the fixture, with the default value being "SELECT * FROM ". This change aims to enhance clarity and consistency in the naming of the argument, making it easier for users of themake_query()
fixture to comprehend its purpose and usage. By correcting the parameter name, the documentation provides a clearer and more consistent user experience.create
function incatalog.py
now appends a random string to "dummy_t", "dummy_s", ordummy_c
for table, schema, and catalog names, respectively, instead of using "ucx_t", "ucx_S", and "ucx_C". Thetest_catalog_fixture
function has also been updated to replacedummy
withdummy_c
anddummy_s
for catalogs and schemas. Additionally, the description of a test query inredash.py
has been updated to remove the reference to UCX. Lastly, fixture names in the unit tests for a catalog have been updated to usedummy
instead of "ucx". These changes improve the independence of the testing process by removing technology-specific references, without affecting functionality.watchdog_remove_after
fixture has been added to the README file for documentation. Themake_storage_credential
fixture has been updated to include a new parameter,watchdog_remove_after
, which specifies the time at which the storage credential should be removed by the watchdog. Thecreate
function has been updated to accept this parameter and adds it as a comment to the storage credential. Theremove
function remains unmodified. The related fixtures section has been updated to include the newwatchdog_remove_after
fixture. This change was co-authored by Eric Vergnaud, but please note that it has not been tested yet.make_job
to runSparkPythonTask
(#60). Themake_job
fixture has been extended to support runningSparkPythonTask
in addition to notebook tasks. A newmake_workspace_file
fixture has been added to create and manage Python files in the workspace. Themake_job
fixture now supports SQL notebooks and files and includes atask_type
parameter to specify the type of task to run and aninstance_pool_id
parameter to reuse an instance pool for faster job execution during integration tests. Additionally, unit and integration tests have been added to ensure the proper functioning of the new and modified fixtures. These changes allow for more flexible and efficient testing of Databricks jobs with different task types and configurations. Themake_notebook
fixture has also been updated to accept acontent
parameter for creating notebooks with custom content. TheLanguage
enum from thedatabricks.sdk.service.workspace
module is used to specify the language of a notebook or workspace file.