feat: bigframes.options and bigframes.option_context now uses thread-local variables to prevent context managers in separate threads from affecting each other

bigframes/_config/__init__.py

@@ -17,6 +17,9 @@
 DataFrames from this package.
 """
 
+import copy
+import threading
+
 import bigframes_vendored.pandas._config.config as pandas_config
 
 import bigframes._config.bigquery_options as bigquery_options
@@ -29,44 +32,91 @@ class Options:
     """Global options affecting BigQuery DataFrames behavior."""
 
     def __init__(self):
+        self._local = threading.local()
+
+        # Initialize these in the property getters to make sure we do have a
+        # separate instance per thread.
+        self._local.bigquery_options = None
+        self._local.display_options = None
+        self._local.sampling_options = None
+        self._local.compute_options = None
+
+        # BigQuery options are special because they can only be set once per
+        # session, so we need an indicator as to whether we are using the
+        # thread-local session or the global session.
         self._bigquery_options = bigquery_options.BigQueryOptions()
-        self._display_options = display_options.DisplayOptions()
-        self._sampling_options = sampling_options.SamplingOptions()
-        self._compute_options = compute_options.ComputeOptions()
+
+    def _init_bigquery_thread_local(self):
+        """Initialize thread-local options, based on current global options."""
+
+        # Already thread-local, so don't reset any options that have been set
+        # already. No locks needed since this only modifies thread-local
+        # variables.
+        if self._local.bigquery_options is not None:
+            return
+
+        self._local.bigquery_options = copy.deepcopy(self._bigquery_options)
+        self._local.bigquery_options._session_started = False
 
     @property
     def bigquery(self) -> bigquery_options.BigQueryOptions:
         """Options to use with the BigQuery engine."""
+        if self._local.bigquery_options is not None:
+            # The only way we can get here is if someone called
+            # _init_bigquery_thread_local.
+            return self._local.bigquery_options
+
         return self._bigquery_options
 
     @property
     def display(self) -> display_options.DisplayOptions:
         """Options controlling object representation."""
-        return self._display_options
+        if self._local.display_options is None:
+            self._local.display_options = display_options.DisplayOptions()
+
+        return self._local.display_options
 
     @property
     def sampling(self) -> sampling_options.SamplingOptions:
         """Options controlling downsampling when downloading data
-        to memory. The data will be downloaded into memory explicitly
+        to memory.
+
+        The data can be downloaded into memory explicitly
         (e.g., to_pandas, to_numpy, values) or implicitly (e.g.,
         matplotlib plotting). This option can be overriden by
-        parameters in specific functions."""
-        return self._sampling_options
+        parameters in specific functions.
+        """
+        if self._local.sampling_options is None:
+            self._local.sampling_options = sampling_options.SamplingOptions()
+
+        return self._local.sampling_options
 
     @property
     def compute(self) -> compute_options.ComputeOptions:
-        """Options controlling object computation."""
-        return self._compute_options
+        """Thread-local options controlling object computation."""
+        if self._local.compute_options is None:
+            self._local.compute_options = compute_options.ComputeOptions()
+
+        return self._local.compute_options
+
+    @property
+    def is_bigquery_thread_local(self) -> bool:
+        """Indicator that we're using a thread-local session.
+
+        A thread-local session can be started by using
+        `with bigframes.option_context("bigquery.some_option", "some-value"):`.
+        """
+        return self._local.bigquery_options is not None
 
 
 options = Options()
 """Global options for default session."""
 
+option_context = pandas_config.option_context
+
 
 __all__ = (
     "Options",
     "options",
+    "option_context",
 )
-
-
-option_context = pandas_config.option_context

bigframes/core/global_session.py

@@ -26,6 +26,24 @@
 
 _global_session: Optional[bigframes.session.Session] = None
 _global_session_lock = threading.Lock()
+_global_session_state = threading.local()
+_global_session_state.thread_local_session = None
+
+
+def _try_close_session(session):
+    """Try to close the session and warn if couldn't."""
+    try:
+        session.close()
+    except google.auth.exceptions.RefreshError as e:
+        session_id = session.session_id
+        location = session._location
+        project_id = session._project
+        warnings.warn(
+            f"Session cleanup failed for session with id: {session_id}, "
+            f"location: {location}, project: {project_id}",
+            category=bigframes.exceptions.CleanupFailedWarning,
+        )
+        traceback.print_tb(e.__traceback__)
 
 
 def close_session() -> None:
@@ -37,24 +55,30 @@ def close_session() -> None:
     Returns:
         None
     """
-    global _global_session
+    global _global_session, _global_session_lock, _global_session_state
+
+    if bigframes._config.options.is_bigquery_thread_local:
+        if _global_session_state.thread_local_session is not None:
+            _try_close_session(_global_session_state.thread_local_session)
+            _global_session_state.thread_local_session = None
+
+        # Currently using thread-local options, so no global lock needed.
+        # Don't reset options.bigquery, as that's the responsibility
+        # of the context manager that started it in the first place. The user
+        # might have explicitly closed the session in the context manager and
+        # the thread-locality property needs to be retained.
+        bigframes._config.options.bigquery._session_started = False
+
+        # Don't close the non-thread-local session.
+        return
 
     with _global_session_lock:
         if _global_session is not None:
-            try:
-                _global_session.close()
-            except google.auth.exceptions.RefreshError as e:
-                session_id = _global_session.session_id
-                location = _global_session._location
-                project_id = _global_session._project
-                warnings.warn(
-                    f"Session cleanup failed for session with id: {session_id}, "
-                    f"location: {location}, project: {project_id}",
-                    category=bigframes.exceptions.CleanupFailedWarning,
-                )
-                traceback.print_tb(e.__traceback__)
+            _try_close_session(_global_session)
             _global_session = None
 
+        # This should be global, not thread-local because of the if clause
+        # above.
         bigframes._config.options.bigquery._session_started = False
 
 
@@ -63,7 +87,15 @@ def get_global_session():
 
     Creates the global session if it does not exist.
     """
-    global _global_session, _global_session_lock
+    global _global_session, _global_session_lock, _global_session_state
+
+    if bigframes._config.options.is_bigquery_thread_local:
+        if _global_session_state.thread_local_session is None:
+            _global_session_state.thread_local_session = bigframes.session.connect(
+                bigframes._config.options.bigquery
+            )
+
+        return _global_session_state.thread_local_session
 
     with _global_session_lock:
         if _global_session is None:

bigframes/core/indexes/base.py

@@ -239,7 +239,7 @@ def __repr__(self) -> str:
         opts = bigframes.options.display
         max_results = opts.max_rows
         if opts.repr_mode == "deferred":
-            return formatter.repr_query_job(self.query_job)
+            return formatter.repr_query_job(self._block._compute_dry_run())
 
         pandas_df, _, query_job = self._block.retrieve_repr_request_results(max_results)
         self._query_job = query_job

bigframes/dataframe.py

@@ -595,7 +595,7 @@ def __repr__(self) -> str:
         opts = bigframes.options.display
         max_results = opts.max_rows
         if opts.repr_mode == "deferred":
-            return formatter.repr_query_job(self.query_job)
+            return formatter.repr_query_job(self._compute_dry_run())
 
         self._cached()
         # TODO(swast): pass max_columns and get the true column count back. Maybe
@@ -632,9 +632,9 @@ def _repr_html_(self) -> str:
         many notebooks are not configured for large tables.
         """
         opts = bigframes.options.display
-        max_results = bigframes.options.display.max_rows
+        max_results = opts.max_rows
         if opts.repr_mode == "deferred":
-            return formatter.repr_query_job_html(self.query_job)
+            return formatter.repr_query_job(self._compute_dry_run())
 
         self._cached()
         # TODO(swast): pass max_columns and get the true column count back. Maybe

bigframes/series.py

@@ -282,7 +282,7 @@ def __repr__(self) -> str:
         opts = bigframes.options.display
         max_results = opts.max_rows
         if opts.repr_mode == "deferred":
-            return formatter.repr_query_job(self.query_job)
+            return formatter.repr_query_job(self._compute_dry_run())
 
         self._cached()
         pandas_df, _, query_job = self._block.retrieve_repr_request_results(max_results)

tests/system/small/ml/test_llm.py

@@ -55,25 +55,28 @@ def test_create_text_generator_model_default_session(
 ):
     import bigframes.pandas as bpd
 
-    bpd.close_session()
-    bpd.options.bigquery.bq_connection = bq_connection
-    bpd.options.bigquery.location = "us"
-
-    model = llm.PaLM2TextGenerator()
-    assert model is not None
-    assert model._bqml_model is not None
-    assert (
-        model.connection_name.casefold()
-        == f"{bigquery_client.project}.us.bigframes-rf-conn"
-    )
-
-    llm_text_df = bpd.read_pandas(llm_text_pandas_df)
-
-    df = model.predict(llm_text_df).to_pandas()
-    assert df.shape == (3, 4)
-    assert "ml_generate_text_llm_result" in df.columns
-    series = df["ml_generate_text_llm_result"]
-    assert all(series.str.len() > 20)
+    # Note: This starts a thread-local session.
+    with bpd.option_context(
+        "bigquery.bq_connection",
+        bq_connection,
+        "bigquery.location",
+        "US",
+    ):
+        model = llm.PaLM2TextGenerator()
+        assert model is not None
+        assert model._bqml_model is not None
+        assert (
+            model.connection_name.casefold()
+            == f"{bigquery_client.project}.us.bigframes-rf-conn"
+        )
+
+        llm_text_df = bpd.read_pandas(llm_text_pandas_df)
+
+        df = model.predict(llm_text_df).to_pandas()
+        assert df.shape == (3, 4)
+        assert "ml_generate_text_llm_result" in df.columns
+        series = df["ml_generate_text_llm_result"]
+        assert all(series.str.len() > 20)
 
 
 @pytest.mark.flaky(retries=2)
@@ -82,25 +85,28 @@ def test_create_text_generator_32k_model_default_session(
 ):
     import bigframes.pandas as bpd
 
-    bpd.close_session()
-    bpd.options.bigquery.bq_connection = bq_connection
-    bpd.options.bigquery.location = "us"
-
-    model = llm.PaLM2TextGenerator(model_name="text-bison-32k")
-    assert model is not None
-    assert model._bqml_model is not None
-    assert (
-        model.connection_name.casefold()
-        == f"{bigquery_client.project}.us.bigframes-rf-conn"
-    )
-
-    llm_text_df = bpd.read_pandas(llm_text_pandas_df)
-
-    df = model.predict(llm_text_df).to_pandas()
-    assert df.shape == (3, 4)
-    assert "ml_generate_text_llm_result" in df.columns
-    series = df["ml_generate_text_llm_result"]
-    assert all(series.str.len() > 20)
+    # Note: This starts a thread-local session.
+    with bpd.option_context(
+        "bigquery.bq_connection",
+        bq_connection,
+        "bigquery.location",
+        "US",
+    ):
+        model = llm.PaLM2TextGenerator(model_name="text-bison-32k")
+        assert model is not None
+        assert model._bqml_model is not None
+        assert (
+            model.connection_name.casefold()
+            == f"{bigquery_client.project}.us.bigframes-rf-conn"
+        )
+
+        llm_text_df = bpd.read_pandas(llm_text_pandas_df)
+
+        df = model.predict(llm_text_df).to_pandas()
+        assert df.shape == (3, 4)
+        assert "ml_generate_text_llm_result" in df.columns
+        series = df["ml_generate_text_llm_result"]
+        assert all(series.str.len() > 20)
 
 
 @pytest.mark.flaky(retries=2)
@@ -232,27 +238,33 @@ def test_create_embedding_generator_multilingual_model(
 def test_create_text_embedding_generator_model_defaults(bq_connection):
     import bigframes.pandas as bpd
 
-    bpd.close_session()
-    bpd.options.bigquery.bq_connection = bq_connection
-    bpd.options.bigquery.location = "us"
-
-    model = llm.PaLM2TextEmbeddingGenerator()
-    assert model is not None
-    assert model._bqml_model is not None
+    # Note: This starts a thread-local session.
+    with bpd.option_context(
+        "bigquery.bq_connection",
+        bq_connection,
+        "bigquery.location",
+        "US",
+    ):
+        model = llm.PaLM2TextEmbeddingGenerator()
+        assert model is not None
+        assert model._bqml_model is not None
 
 
 def test_create_text_embedding_generator_multilingual_model_defaults(bq_connection):
     import bigframes.pandas as bpd
 
-    bpd.close_session()
-    bpd.options.bigquery.bq_connection = bq_connection
-    bpd.options.bigquery.location = "us"
-
-    model = llm.PaLM2TextEmbeddingGenerator(
-        model_name="textembedding-gecko-multilingual"
-    )
-    assert model is not None
-    assert model._bqml_model is not None
+    # Note: This starts a thread-local session.
+    with bpd.option_context(
+        "bigquery.bq_connection",
+        bq_connection,
+        "bigquery.location",
+        "US",
+    ):
+        model = llm.PaLM2TextEmbeddingGenerator(
+            model_name="textembedding-gecko-multilingual"
+        )
+        assert model is not None
+        assert model._bqml_model is not None
 
 
 @pytest.mark.flaky(retries=2)