From 2f597f51fa9626b1c901bfb3b9c03058acd0b7b3 Mon Sep 17 00:00:00 2001
From: Shenyang Cai <sycai@google.com>
Date: Mon, 21 Jul 2025 18:29:36 +0000
Subject: [PATCH] docs: add snippets for performance optimization doc

---
 .../performance_optimizations_test.py         | 52 +++++++++++++++++++
 1 file changed, 52 insertions(+)
 create mode 100644 samples/snippets/performance_optimizations_test.py

diff --git a/samples/snippets/performance_optimizations_test.py b/samples/snippets/performance_optimizations_test.py
new file mode 100644
index 0000000000..43e14e31cc
--- /dev/null
+++ b/samples/snippets/performance_optimizations_test.py
@@ -0,0 +1,52 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+def test_performance_optimizations() -> None:
+    # [START bigquery_bigframes_use_peek_to_preview_data]
+    import bigframes.pandas as bpd
+
+    # Read the "Penguins" table into a dataframe
+    df = bpd.read_gbq("bigquery-public-data.ml_datasets.penguins")
+
+    # Preview 3 random rows
+    df.peek(3)
+    # [END bigquery_bigframes_use_peek_to_preview_data]
+    assert df.peek(3) is not None
+
+    import bigframes.pandas as bpd
+
+    users = bpd.DataFrame({"user_name": ["John"]})
+    groups = bpd.DataFrame({"group_id": ["group_1"]})
+    transactions = bpd.DataFrame({"amount": [3], "completed": [True]})
+
+    # [START bigquery_bigframes_use_cache_after_expensive_operations]
+    # Assume you have 3 large dataframes "users", "group" and "transactions"
+
+    # Expensive join operations
+    final_df = users.join(groups).join(transactions)
+    final_df.cache()
+    # Subsequent derived results will reuse the cached join
+    print(final_df.peek())
+    print(len(final_df[final_df["completed"]]))
+    print(final_df.groupby("group_id")["amount"].mean().peek(30))
+    # [END bigquery_bigframes_use_cache_after_expensive_operations]
+    assert final_df is not None
+
+    # [START bigquery_bigframes_enable_deferred_repr_for_debugging]
+    import bigframes.pandas as bpd
+
+    bpd.options.display.repr_mode = "deferred"
+    # [END bigquery_bigframes_enable_deferred_repr_for_debugging]
+    assert bpd.options.display.repr_mode == "deferred"