robertwb commented on code in PR #31701:
URL: https://github.com/apache/beam/pull/31701#discussion_r1672782726


##########
examples/notebooks/blogposts/unittests_in_beam.ipynb:
##########
@@ -0,0 +1,259 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyP+whTO0l5Xd2TU4xa2Z7KC",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a 
href=\"https://colab.research.google.com/github/svetakvsundhar/beam/blob/testing_blog_post/examples/notebooks/blogposts/unittests_in_beam.ipynb\";
 target=\"_parent\"><img 
src=\"https://colab.research.google.com/assets/colab-badge.svg\"; alt=\"Open In 
Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 36,
+      "metadata": {
+        "id": "7DSE6TgWy7PP"
+      },
+      "outputs": [],
+      "source": [
+        "# @title ###### Licensed to the Apache Software Foundation (ASF), 
Version 2.0 (the \"License\")\n",
+        "\n",
+        "# Licensed to the Apache Software Foundation (ASF) under one\n",
+        "# or more contributor license agreements. See the NOTICE file\n",
+        "# distributed with this work for additional information\n",
+        "# regarding copyright ownership. The ASF licenses this file\n",
+        "# to you under the Apache License, Version 2.0 (the\n",
+        "# \"License\"); you may not use this file except in compliance\n",
+        "# with the License. You may obtain a copy of the License at\n",
+        "#\n",
+        "#   http://www.apache.org/licenses/LICENSE-2.0\n";,
+        "#\n",
+        "# Unless required by applicable law or agreed to in writing,\n",
+        "# software distributed under the License is distributed on an\n",
+        "# \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n",
+        "# KIND, either express or implied. See the License for the\n",
+        "# specific language governing permissions and limitations\n",
+        "# under the License"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Install the Apache Beam library\n",
+        "\n",
+        "!pip install apache_beam[gcp] --quiet"
+      ],
+      "metadata": {
+        "id": "5W2nuV7uzlPg"
+      },
+      "execution_count": 37,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#The following packages are used to run the example pipelines\n",
+        "\n",
+        "import apache_beam as beam\n",
+        "from apache_beam.io import ReadFromText, WriteToText\n",
+        "from apache_beam.options.pipeline_options import PipelineOptions\n",
+        "\n",
+        "class CustomClass(beam.DoFn):\n",
+        "  def custom_function(x):\n",
+        "          ...\n",
+        "          # returned_record = 
requests.get(\"http://my-api-call.com\";)\n",
+        "          ...\n",
+        "          # if len(returned_record)!=10:\n",
+        "          # raise ValueError(\"Length of record does not match 
expected length\")\n",
+        "          return x\n",
+        "\n",
+        "  with beam.Pipeline() as p:\n",
+        "    result = (\n",
+        "            p\n",
+        "            | ReadFromText(\"/content/sample_data/anscombe.json\")\n",
+        "            | beam.ParDo(lambda x: CustomClass.custom_function(x))\n",
+        "            | WriteToText(\"/content/\")\n",
+        "    )"
+      ],
+      "metadata": {
+        "id": "Ktk9EVIFzGfP"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "**Example Pipeline 1**\n"
+      ],
+      "metadata": {
+        "id": "IVjBkewt1sLA"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# This function is going to return the square the integer at the 
first index of our record.\n",
+        "def compute_square(element):\n",
+        "  return int(element[1])**2\n",
+        "\n",
+        "with beam.Pipeline() as p1:\n",
+        "    result = (\n",
+        "        p1\n",
+        "        | 
ReadFromText(\"/content/sample_data/california_housing_test.csv\",skip_header_lines=1)\n",
+        "        | beam.Map(compute_square)\n",
+        "        | WriteToText(\"/content/\")\n",
+        "    )"
+      ],
+      "metadata": {
+        "id": "oHbSvOUI1pOe"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "**Example Pipeline 2**"
+      ],
+      "metadata": {
+        "id": "Mh3nZZ1_12sX"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "with beam.Pipeline() as p2:\n",
+        "    result = (\n",
+        "        p2\n",
+        "        | ReadFromText(\"/content/sample_data/anscombe.json\")\n",
+        "        | beam.Map(str.strip)\n",

Review Comment:
   Seeing `output = manipulate_strings(inputs)` makes me wonder how we could 
make composite PTransforms even easier/more natural. 



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