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Update conftest.py #4306

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5 changes: 4 additions & 1 deletion libs/template/templates/default/template/{{.project_name}}/tests/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -59,7 +59,8 @@ def _loader(filename: str):
def _enable_fallback_compute():
"""Enable serverless compute if no compute is specified."""
conf = WorkspaceClient().config
if conf.serverless_compute_id or conf.cluster_id or os.environ.get("SPARK_REMOTE"):
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@lennartkats-db lennartkats-db Jan 19, 2026

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I worry this line is pretty surprising to maintainers, since most users will run with the SDK referenced in pyproject.toml. Can you add a comment that this is for older Databricks SDK versions?

has_serverles_compute_id = hasattr(conf, "serverless_compute_id") and conf.serverless_compute_id
if has_serverles_compute_id or conf.cluster_id or os.environ.get("SPARK_REMOTE"):
Comment on lines +62 to +63
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@lennartkats-db lennartkats-db Jan 19, 2026

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Suggested change
has_serverles_compute_id = hasattr(conf, "serverless_compute_id") and conf.serverless_compute_id
if has_serverles_compute_id or conf.cluster_id or os.environ.get("SPARK_REMOTE"):
has_serverless_compute_id = hasattr(conf, "serverless_compute_id") and conf.serverless_compute_id
if has_serverless_compute_id or conf.cluster_id or os.environ.get("SPARK_REMOTE"):

return

url = "https://docs.databricks.com/dev-tools/databricks-connect/cluster-config"
Expand All @@ -83,6 +84,8 @@ def _allow_stderr_output(config: pytest.Config):
def pytest_configure(config: pytest.Config):
"""Configure pytest session."""
with _allow_stderr_output(config):
src_path = pathlib.Path(__file__).parent.parent / "src"
sys.path.insert(0, str(src_path))
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@lennartkats-db lennartkats-db Jan 19, 2026

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This line doesn't seem right to me, could you look at alternative options for your test runner instead? Normally imports in tests just work out of the box, as seen at https://github.com/databricks/bundle-examples/blob/333bab00d7dc17aa3d2491f3a9d1883590984793/default_python/tests/sample_taxis_test.py#L3. There must be something wrong with your environment, maybe that can be fixed in some other way?

_enable_fallback_compute()

# Initialize Spark session eagerly, so it is available even when
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