4141import bigframes .dataframe
4242import bigframes .pandas as bpd
4343import bigframes .series
44- import tests . system .utils
44+ import bigframes . testing .utils
4545
4646# Use this to control the number of cloud functions being deleted in a single
4747# test session. This should help soften the spike of the number of mutations per
@@ -615,7 +615,7 @@ def scalars_pandas_df_default_index() -> pd.DataFrame:
615615 DATA_DIR / "scalars.jsonl" ,
616616 lines = True ,
617617 )
618- tests . system .utils .convert_pandas_dtypes (df , bytes_col = True )
618+ bigframes . testing .utils .convert_pandas_dtypes (df , bytes_col = True )
619619
620620 df = df .set_index ("rowindex" , drop = False )
621621 df .index .name = None
@@ -1422,12 +1422,12 @@ def use_fast_query_path():
14221422@pytest .fixture (scope = "session" , autouse = True )
14231423def cleanup_cloud_functions (session , cloudfunctions_client , dataset_id_permanent ):
14241424 """Clean up stale cloud functions."""
1425- permanent_endpoints = tests . system .utils .get_remote_function_endpoints (
1425+ permanent_endpoints = bigframes . testing .utils .get_remote_function_endpoints (
14261426 session .bqclient , dataset_id_permanent
14271427 )
14281428 delete_count = 0
14291429 try :
1430- for cloud_function in tests . system .utils .get_cloud_functions (
1430+ for cloud_function in bigframes . testing .utils .get_cloud_functions (
14311431 cloudfunctions_client ,
14321432 session .bqclient .project ,
14331433 session .bqclient .location ,
@@ -1447,7 +1447,7 @@ def cleanup_cloud_functions(session, cloudfunctions_client, dataset_id_permanent
14471447
14481448 # Go ahead and delete
14491449 try :
1450- tests . system .utils .delete_cloud_function (
1450+ bigframes . testing .utils .delete_cloud_function (
14511451 cloudfunctions_client , cloud_function .name
14521452 )
14531453 delete_count += 1
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