From ab8e6d5cb1c2328d551405477a2623998e735886 Mon Sep 17 00:00:00 2001
From: Kevin Liu <kevin.jq.liu@gmail.com>
Date: Mon, 29 Dec 2025 14:56:00 -0800
Subject: [PATCH 1/7] add `make notebook`

---
 Makefile       |  12 +
 pyproject.toml |   4 +
 uv.lock        | 928 ++++++++++++++++++++++++++++++++++++++++++++++++-
 3 files changed, 943 insertions(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 85d7743897..095c8b3b12 100644
--- a/Makefile
+++ b/Makefile
@@ -153,6 +153,16 @@ docs-serve: ## Serve local docs preview (hot reload)
 docs-build: ## Build the static documentation site
 	uv run $(PYTHON_ARG) mkdocs build -f mkdocs/mkdocs.yml --strict
 
+# ========================
+# Experimentation
+# ========================
+
+##@ Experimentation
+
+notebook: ## Launch notebook for experimentation
+	uv sync $(PYTHON_ARG) --group notebook
+	uv run jupyter lab
+
 # ===================
 # Project Maintenance
 # ===================
@@ -167,4 +177,6 @@ clean: ## Remove build artifacts and caches
 	@find . -name "__pycache__" -exec echo Deleting {} \; -exec rm -rf {} +
 	@find . -name "*.pyd" -exec echo Deleting {} \; -delete
 	@find . -name "*.pyo" -exec echo Deleting {} \; -delete
+	@echo "Cleaning up Jupyter notebook checkpoints..."
+	@find . -name ".ipynb_checkpoints" -exec echo Deleting {} \; -exec rm -rf {} +
 	@echo "Cleanup complete."
diff --git a/pyproject.toml b/pyproject.toml
index 9bca14c53f..2899e46577 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -132,6 +132,10 @@ docs = [
     "mkdocs-material-extensions==1.3.1",
     "mkdocs-section-index==0.3.10",
 ]
+# for experimentation
+notebook = [
+    "jupyterlab>=4.0.0",
+]
 
 [tool.uv]
 default-groups = [
diff --git a/uv.lock b/uv.lock
index 64a759d19d..7324507223 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 3
+revision = 2
 requires-python = ">=3.10.0, <4.0.0"
 resolution-markers = [
     "python_full_version >= '3.14'",
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 ]
 
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+[[package]]
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+version = "1.3.0"
+source = { registry = "https://pypi.org/simple" }
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From a1422745ce2c39f9bc5ed7aae5b38ba00a440641 Mon Sep 17 00:00:00 2001
From: Kevin Liu <kevin.jq.liu@gmail.com>
Date: Mon, 29 Dec 2025 15:25:11 -0800
Subject: [PATCH 2/7] ignore notebook checkpoint

---
 .gitignore | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.gitignore b/.gitignore
index ba659e586f..ef8c522482 100644
--- a/.gitignore
+++ b/.gitignore
@@ -41,6 +41,9 @@ bin/
 .mypy_cache/
 htmlcov
 
+# Jupyter notebook checkpoints
+.ipynb_checkpoints/
+
 pyiceberg/avro/decoder_fast.c
 pyiceberg/avro/*.html
 pyiceberg/avro/*.so

From 375085bd2b0e9b4070d3df54952c05ad7b2f92d6 Mon Sep 17 00:00:00 2001
From: Kevin Liu <kevin.jq.liu@gmail.com>
Date: Mon, 29 Dec 2025 15:25:27 -0800
Subject: [PATCH 3/7] add make commands

---
 Makefile | 13 +++++++++----
 1 file changed, 9 insertions(+), 4 deletions(-)

diff --git a/Makefile b/Makefile
index 095c8b3b12..62310e3121 100644
--- a/Makefile
+++ b/Makefile
@@ -97,7 +97,7 @@ test: ## Run all unit tests (excluding integration)
 
 test-integration: test-integration-setup test-integration-exec test-integration-cleanup ## Run integration tests
 
-test-integration-setup: ## Start Docker services for integration tests
+test-integration-setup: install ## Start Docker services for integration tests
 	docker compose -f dev/docker-compose-integration.yml kill
 	docker compose -f dev/docker-compose-integration.yml rm -f
 	docker compose -f dev/docker-compose-integration.yml up -d --wait
@@ -159,9 +159,14 @@ docs-build: ## Build the static documentation site
 
 ##@ Experimentation
 
-notebook: ## Launch notebook for experimentation
-	uv sync $(PYTHON_ARG) --group notebook
-	uv run jupyter lab
+notebook-install: ## Install notebook dependencies
+	uv sync $(PYTHON_ARG) --all-extras --group notebook
+
+notebook: notebook-install ## Launch notebook for experimentation
+	uv run jupyter lab --notebook-dir=notebooks
+
+notebook-infra: notebook-install test-integration-setup ## Launch notebook with integration test infra (Spark, Iceberg Rest Catalog, object storage, etc.)
+	uv run jupyter lab --notebook-dir=notebooks
 
 # ===================
 # Project Maintenance

From d69f3596c38f9a27b5deb0f45020c59a013d919f Mon Sep 17 00:00:00 2001
From: Kevin Liu <kevin.jq.liu@gmail.com>
Date: Mon, 29 Dec 2025 15:33:32 -0800
Subject: [PATCH 4/7] add example notebooks

---
 notebooks/pyiceberg_example.ipynb         | 364 ++++++++++++++++++++++
 notebooks/spark_integration_example.ipynb | 124 ++++++++
 2 files changed, 488 insertions(+)
 create mode 100644 notebooks/pyiceberg_example.ipynb
 create mode 100644 notebooks/spark_integration_example.ipynb

diff --git a/notebooks/pyiceberg_example.ipynb b/notebooks/pyiceberg_example.ipynb
new file mode 100644
index 0000000000..db290eb78f
--- /dev/null
+++ b/notebooks/pyiceberg_example.ipynb
@@ -0,0 +1,364 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c6cc20c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Import required libraries\n",
+    "import pyiceberg\n",
+    "from pyiceberg.catalog import load_catalog\n",
+    "from pyiceberg.table import Table\n",
+    "import pandas as pd\n",
+    "import pyarrow as pa\n",
+    "print(f\"PyIceberg version: {pyiceberg.__version__}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "33dcfca9",
+   "metadata": {},
+   "source": [
+    "## Setup: Connecting to a Catalog\n",
+    "\n",
+    "Iceberg uses a catalog to organize tables. For this example, we'll use a `SqlCatalog` with SQLite for local testing."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "649053ed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Import required libraries\n",
+    "from pyiceberg.catalog import load_catalog\n",
+    "import pyarrow.parquet as pq\n",
+    "import pyarrow.compute as pc\n",
+    "import tempfile\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "72d5da19",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a temporary warehouse location\n",
+    "warehouse_path = tempfile.mkdtemp(prefix=\"iceberg_warehouse_\")\n",
+    "print(f\"Warehouse location: {warehouse_path}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "14e9429c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Configure and load the catalog\n",
+    "catalog = load_catalog(\n",
+    "    \"default\",\n",
+    "    **{\n",
+    "        'type': 'sql',\n",
+    "        \"uri\": f\"sqlite:///{warehouse_path}/pyiceberg_catalog.db\",\n",
+    "        \"warehouse\": f\"file://{warehouse_path}\",\n",
+    "    },\n",
+    ")\n",
+    "\n",
+    "print(\"Catalog loaded successfully!\")\n",
+    "print(f\"Namespaces: {list(catalog.list_namespaces())}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e330d377",
+   "metadata": {},
+   "source": [
+    "## Create a Namespace and Table\n",
+    "\n",
+    "Let's create a namespace and a simple Iceberg table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "90312e03",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create a namespace\n",
+    "catalog.create_namespace(\"default\")\n",
+    "print(f\"Available namespaces: {list(catalog.list_namespaces())}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f96438ef",
+   "metadata": {},
+   "source": [
+    "## Write Data to an Iceberg Table\n",
+    "\n",
+    "We'll create a sample dataset and write it to an Iceberg table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2ef11eb9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create sample data using PyArrow\n",
+    "import pyarrow as pa\n",
+    "\n",
+    "# Sample taxi-like data\n",
+    "data = {\n",
+    "    'vendor_id': [1, 2, 1, 2, 1],\n",
+    "    'trip_distance': [1.5, 2.3, 0.8, 5.2, 3.1],\n",
+    "    'fare_amount': [10.0, 15.5, 6.0, 22.0, 18.0],\n",
+    "    'tip_amount': [2.0, 3.0, 1.0, 4.5, 3.5],\n",
+    "    'passenger_count': [1, 2, 1, 3, 2]\n",
+    "}\n",
+    "\n",
+    "df = pa.table(data)\n",
+    "print(\"Sample data:\")\n",
+    "print(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "678d122a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create an Iceberg table with the schema from our dataframe\n",
+    "table = catalog.create_table(\n",
+    "    \"default.sample_trips\",\n",
+    "    schema=df.schema,\n",
+    ")\n",
+    "\n",
+    "print(f\"Created table: {table}\")\n",
+    "print(f\"Table schema: {table.schema()}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8e135b2a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Append data to the table\n",
+    "table.append(df)\n",
+    "print(f\"Rows written: {len(table.scan().to_arrow())}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0ef43fbf",
+   "metadata": {},
+   "source": [
+    "## Read Data from the Table\n",
+    "\n",
+    "Let's read back the data we just wrote."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d1ef0396",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Scan and read the entire table\n",
+    "result = table.scan().to_arrow()\n",
+    "print(\"Table contents:\")\n",
+    "print(result)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a8a3c906",
+   "metadata": {},
+   "source": [
+    "## Schema Evolution\n",
+    "\n",
+    "One of Iceberg's powerful features is schema evolution. Let's add a new computed column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8725f3ce",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Add a new computed column: tip per mile\n",
+    "df = df.append_column(\"tip_per_mile\", pc.divide(df[\"tip_amount\"], df[\"trip_distance\"]))\n",
+    "print(\"Updated dataframe with new column:\")\n",
+    "print(df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e0c4550b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Evolve the table schema to include the new column\n",
+    "with table.update_schema() as update_schema:\n",
+    "    update_schema.union_by_name(df.schema)\n",
+    "\n",
+    "print(\"Schema evolved!\")\n",
+    "print(f\"Updated table schema: {table.schema()}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2a65eee4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Overwrite the table with the new data\n",
+    "table.overwrite(df)\n",
+    "print(\"Data overwritten with new schema\")\n",
+    "\n",
+    "# Verify the new column exists\n",
+    "result = table.scan().to_arrow()\n",
+    "print(result)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7140ba0c",
+   "metadata": {},
+   "source": [
+    "## Filtering Data\n",
+    "\n",
+    "PyIceberg supports predicate pushdown for efficient data filtering."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3af0f0b1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Filter rows where tip_per_mile > 1.0\n",
+    "filtered_df = table.scan(row_filter=\"tip_per_mile > 1.0\").to_arrow()\n",
+    "print(f\"Rows with tip_per_mile > 1.0: {len(filtered_df)}\")\n",
+    "print(filtered_df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ff173f80",
+   "metadata": {},
+   "source": [
+    "## Inspect Table Metadata\n",
+    "\n",
+    "Iceberg tables maintain rich metadata about their structure and history."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e3763e27",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# View table properties\n",
+    "print(f\"Table location: {table.location()}\")\n",
+    "print(f\"Table properties: {table.properties}\")\n",
+    "print(f\"Current snapshot ID: {table.current_snapshot()}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "49154477",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# View table history (snapshots)\n",
+    "print(\"Table history:\")\n",
+    "for snapshot in table.history():\n",
+    "    print(f\"  Snapshot: {snapshot}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "448a1962",
+   "metadata": {},
+   "source": [
+    "## Explore Data Files\n",
+    "\n",
+    "Let's see what files Iceberg created in the warehouse."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3c8948e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# List all files in the warehouse\n",
+    "import os\n",
+    "for root, dirs, files in os.walk(warehouse_path):\n",
+    "    level = root.replace(warehouse_path, '').count(os.sep)\n",
+    "    indent = ' ' * 2 * level\n",
+    "    print(f'{indent}{os.path.basename(root)}/')\n",
+    "    subindent = ' ' * 2 * (level + 1)\n",
+    "    for file in files:\n",
+    "        print(f'{subindent}{file}')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e9db29ad",
+   "metadata": {},
+   "source": [
+    "## Additional Operations\n",
+    "\n",
+    "PyIceberg supports many more operations including:\n",
+    "- Time travel queries\n",
+    "- Partition evolution\n",
+    "- Table maintenance (expire snapshots, rewrite data files)\n",
+    "- Integration with pandas, DuckDB, Ray, and more\n",
+    "\n",
+    "Check the [PyIceberg documentation](https://py.iceberg.apache.org/) for more details!"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/spark_integration_example.ipynb b/notebooks/spark_integration_example.ipynb
new file mode 100644
index 0000000000..c416c2b8df
--- /dev/null
+++ b/notebooks/spark_integration_example.ipynb
@@ -0,0 +1,124 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "191f31b2",
+   "metadata": {},
+   "source": [
+    "# Spark Integration Example\n",
+    "\n",
+    "This notebook demonstrates how to connect to Spark and interact with Iceberg tables using Spark Connect.\n",
+    "\n",
+    "## Prerequisites\n",
+    "\n",
+    "**⚠️ This notebook requires the integration test infrastructure to be running.**\n",
+    "\n",
+    "To start the infrastructure, use one of these commands:\n",
+    "- `make test-integration-setup` - Start just the infrastructure\n",
+    "- `make notebook-infra` - Start infrastructure and launch JupyterLab\n",
+    "\n",
+    "The infrastructure includes:\n",
+    "- Spark Connect server (port 15002)\n",
+    "- Iceberg REST catalog\n",
+    "- S3-compatible storage (MinIO)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c6cc20c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Import required libraries\n",
+    "from pyspark.sql import SparkSession"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8c1a3fad",
+   "metadata": {},
+   "source": [
+    "## Connecting to Spark\n",
+    "\n",
+    "Connect to the Spark server using Spark Connect."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "28bf42fc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create SparkSession against the remote Spark Connect server\n",
+    "spark = SparkSession.builder.remote(\"sc://localhost:15002\").getOrCreate()\n",
+    "spark.sql(\"SHOW CATALOGS\").show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "550f2a5c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Show available namespaces/databases\n",
+    "spark.sql(\"SHOW NAMESPACES\").show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9971fd4a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Show tables in the default namespace\n",
+    "spark.sql(\"SHOW TABLES FROM default\").show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2a8d3463",
+   "metadata": {},
+   "source": [
+    "## Exploring Iceberg Tables\n",
+    "\n",
+    "Use Spark SQL commands to explore Iceberg table structure and metadata."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1b9d7dba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Describe a table\n",
+    "spark.sql(\"DESCRIBE TABLE default.test_all_types\").show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From 451a58c3e1cb07aa0ad97e9cf869e47ef41a91ef Mon Sep 17 00:00:00 2001
From: Kevin Liu <kevin.jq.liu@gmail.com>
Date: Mon, 29 Dec 2025 15:41:05 -0800
Subject: [PATCH 5/7] make lint

---
 notebooks/pyiceberg_example.ipynb | 45 ++++++++++++++-----------------
 1 file changed, 20 insertions(+), 25 deletions(-)

diff --git a/notebooks/pyiceberg_example.ipynb b/notebooks/pyiceberg_example.ipynb
index db290eb78f..2db4853ad0 100644
--- a/notebooks/pyiceberg_example.ipynb
+++ b/notebooks/pyiceberg_example.ipynb
@@ -8,11 +8,11 @@
    "outputs": [],
    "source": [
     "# Import required libraries\n",
+    "import pyarrow as pa\n",
+    "\n",
     "import pyiceberg\n",
     "from pyiceberg.catalog import load_catalog\n",
-    "from pyiceberg.table import Table\n",
-    "import pandas as pd\n",
-    "import pyarrow as pa\n",
+    "\n",
     "print(f\"PyIceberg version: {pyiceberg.__version__}\")"
    ]
   },
@@ -34,11 +34,10 @@
    "outputs": [],
    "source": [
     "# Import required libraries\n",
-    "from pyiceberg.catalog import load_catalog\n",
-    "import pyarrow.parquet as pq\n",
-    "import pyarrow.compute as pc\n",
+    "import os\n",
     "import tempfile\n",
-    "import os"
+    "\n",
+    "import pyarrow.compute as pc"
    ]
   },
   {
@@ -63,11 +62,9 @@
     "# Configure and load the catalog\n",
     "catalog = load_catalog(\n",
     "    \"default\",\n",
-    "    **{\n",
-    "        'type': 'sql',\n",
-    "        \"uri\": f\"sqlite:///{warehouse_path}/pyiceberg_catalog.db\",\n",
-    "        \"warehouse\": f\"file://{warehouse_path}\",\n",
-    "    },\n",
+    "    type=\"sql\",\n",
+    "    uri=f\"sqlite:///{warehouse_path}/pyiceberg_catalog.db\",\n",
+    "    warehouse=f\"file://{warehouse_path}\",\n",
     ")\n",
     "\n",
     "print(\"Catalog loaded successfully!\")\n",
@@ -114,15 +111,14 @@
    "outputs": [],
    "source": [
     "# Create sample data using PyArrow\n",
-    "import pyarrow as pa\n",
     "\n",
     "# Sample taxi-like data\n",
     "data = {\n",
-    "    'vendor_id': [1, 2, 1, 2, 1],\n",
-    "    'trip_distance': [1.5, 2.3, 0.8, 5.2, 3.1],\n",
-    "    'fare_amount': [10.0, 15.5, 6.0, 22.0, 18.0],\n",
-    "    'tip_amount': [2.0, 3.0, 1.0, 4.5, 3.5],\n",
-    "    'passenger_count': [1, 2, 1, 3, 2]\n",
+    "    \"vendor_id\": [1, 2, 1, 2, 1],\n",
+    "    \"trip_distance\": [1.5, 2.3, 0.8, 5.2, 3.1],\n",
+    "    \"fare_amount\": [10.0, 15.5, 6.0, 22.0, 18.0],\n",
+    "    \"tip_amount\": [2.0, 3.0, 1.0, 4.5, 3.5],\n",
+    "    \"passenger_count\": [1, 2, 1, 3, 2],\n",
     "}\n",
     "\n",
     "df = pa.table(data)\n",
@@ -313,14 +309,13 @@
    "outputs": [],
    "source": [
     "# List all files in the warehouse\n",
-    "import os\n",
-    "for root, dirs, files in os.walk(warehouse_path):\n",
-    "    level = root.replace(warehouse_path, '').count(os.sep)\n",
-    "    indent = ' ' * 2 * level\n",
-    "    print(f'{indent}{os.path.basename(root)}/')\n",
-    "    subindent = ' ' * 2 * (level + 1)\n",
+    "for root, _dirs, files in os.walk(warehouse_path):\n",
+    "    level = root.replace(warehouse_path, \"\").count(os.sep)\n",
+    "    indent = \" \" * 2 * level\n",
+    "    print(f\"{indent}{os.path.basename(root)}/\")\n",
+    "    subindent = \" \" * 2 * (level + 1)\n",
     "    for file in files:\n",
-    "        print(f'{subindent}{file}')"
+    "        print(f\"{subindent}{file}\")"
    ]
   },
   {

From c4ad0a30a0b2f74f9ffad9b1a9621fbdab16856d Mon Sep 17 00:00:00 2001
From: Kevin Liu <kevin.jq.liu@gmail.com>
Date: Mon, 29 Dec 2025 15:47:05 -0800
Subject: [PATCH 6/7] exclude notebooks from rat check

---
 dev/.rat-excludes | 1 +
 1 file changed, 1 insertion(+)

diff --git a/dev/.rat-excludes b/dev/.rat-excludes
index 16e996dba8..8ae4680cb2 100644
--- a/dev/.rat-excludes
+++ b/dev/.rat-excludes
@@ -5,3 +5,4 @@ build
 .gitignore
 uv.lock
 mkdocs/*
+notebooks/*
\ No newline at end of file

From b55d7bd2588f966def84e5d9fe067d38e8f1448d Mon Sep 17 00:00:00 2001
From: Kevin Liu <kevin.jq.liu@gmail.com>
Date: Mon, 29 Dec 2025 15:47:45 -0800
Subject: [PATCH 7/7] newline

---
 dev/.rat-excludes | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/dev/.rat-excludes b/dev/.rat-excludes
index 8ae4680cb2..282326edd8 100644
--- a/dev/.rat-excludes
+++ b/dev/.rat-excludes
@@ -5,4 +5,4 @@ build
 .gitignore
 uv.lock
 mkdocs/*
-notebooks/*
\ No newline at end of file
+notebooks/*