damccorm commented on code in PR #31701:
URL: https://github.com/apache/beam/pull/31701#discussion_r1672046384
##########
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>"
Review Comment:
```suggestion
"<a
href=\"https://colab.research.google.com/github/apache/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>"
```
##########
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:
I wonder if a better way to do this would be to split `beam.Map(str.strip)`
out into a separate function which can be called from the test. As it is, the
test isn't actually invoking any of the code we've written.
A more interesting example might be:
```
def manipulate_strings(incoming_pcoll):
return incoming_pcoll | beam.Map(str.strip) | beam.Map(str.upper)
```
The functions themselves don't need tested, but the beam transforms do. That
would let you test the actual code you've written below with:
```
with TestPipeline() as p:
inputs = p | beam.Create(strings)
output = manipulate_strings(inputs)
assert_that(output, equal_to(expected))
```
##########
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:
Basically, I don't like that you could totally change the user code (which
you're supposed to be testing) without a test failing.
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