davidcavazos commented on a change in pull request #14045:
URL: https://github.com/apache/beam/pull/14045#discussion_r585064007
##########
File path: examples/notebooks/tour-of-beam/reading-and-writing-data.ipynb
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@@ -0,0 +1,939 @@
+{
+ "nbformat": 4,
+ "nbformat_minor": 0,
+ "metadata": {
+ "colab": {
+ "name": "Reading and writing data -- Tour of Beam",
+ "provenance": [],
+ "collapsed_sections": [],
+ "toc_visible": true
+ },
+ "kernelspec": {
+ "name": "python3",
+ "display_name": "Python 3"
+ }
+ },
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "view-in-github",
+ "colab_type": "text"
+ },
+ "source": [
+ "<a
href=\"https://colab.research.google.com/github/apache/beam/blob/master/examples/notebooks/tour-of-beam/reading-and-writing-data.ipynb\";
target=\"_parent\"><img
src=\"https://colab.research.google.com/assets/colab-badge.svg\"; alt=\"Open In
Colab\"/></a>"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "metadata": {
+ "cellView": "form",
+ "id": "upmJn_DjcThx"
+ },
+ "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."
+ ],
+ "execution_count": 95,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "5UC_aGanx6oE"
+ },
+ "source": [
+ "# Reading and writing data -- _Tour of Beam_\n",
+ "\n",
+ "So far we've learned some of the basic transforms like\n",
+
"[`Map`](https://beam.apache.org/documentation/transforms/python/elementwise/map)
_(one-to-one)_,\n",
+
"[`FlatMap`](https://beam.apache.org/documentation/transforms/python/elementwise/flatmap)
_(one-to-many)_,\n",
+
"[`Filter`](https://beam.apache.org/documentation/transforms/python/elementwise/filter)
_(one-to-zero)_,\n",
+
"[`Combine`](https://beam.apache.org/documentation/transforms/python/aggregation/combineglobally)
_(many-to-one)_, and\n",
+
"[`GroupByKey`](https://beam.apache.org/documentation/transforms/python/aggregation/groupbykey).\n",
+ "These allow us to transform data in any way, but so far we've created
data from an in-memory\n",
+ "[`iterable`](https://docs.python.org/3/glossary.html#term-iterable),
like a `List`, using\n",
+
"[`Create`](https://beam.apache.org/documentation/transforms/python/other/create).\n",
+ "\n",
+ "This works well for experimenting with small datasets. For larger
datasets we use a **`Source`** transform to read data and a **`Sink`**
transform to write data.\n",
+ "\n",
+ "Let's create some data files and see how we can read them in Beam."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "metadata": {
+ "id": "R_Yhoc6N_Flg"
+ },
+ "source": [
+ "# Install apache-beam with pip.\n",
+ "!pip install --quiet apache-beam\n",
+ "\n",
+ "# Create a directory for our data files.\n",
+ "!mkdir -p data"
+ ],
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "metadata": {
+ "id": "sQUUi4H9s-g2"
+ },
+ "source": [
+ "%%writefile data/my-text-file-1.txt\n",
+ "This is just a plain text file, UTF-8 strings are allowed 🎉.\n",
+ "Each line in the file is one element in the PCollection."
+ ],
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "metadata": {
+ "id": "BWVVeTSOlKug"
+ },
+ "source": [
+ "%%writefile data/my-text-file-2.txt\n",
+ "There are no guarantees on the order of the elements.\n",
+ "ฅ^•ﻌ•^ฅ"
+ ],
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "metadata": {
+ "id": "NhCws6ncbDJG"
+ },
+ "source": [
+ "%%writefile data/penguins.csv\n",
+
"species,culmen_length_mm,culmen_depth_mm,flipper_length_mm,body_mass_g\n",
+
"0,0.2545454545454545,0.6666666666666666,0.15254237288135594,0.2916666666666667\n",
+
"0,0.26909090909090905,0.5119047619047618,0.23728813559322035,0.3055555555555556\n",
+
"1,0.5236363636363636,0.5714285714285713,0.3389830508474576,0.2222222222222222\n",
+
"1,0.6509090909090909,0.7619047619047619,0.4067796610169492,0.3333333333333333\n",
+ "2,0.509090909090909,0.011904761904761862,0.6610169491525424,0.5\n",
+
"2,0.6509090909090909,0.38095238095238104,0.9830508474576272,0.8333333333333334"
+ ],
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "_OkWHiAvpWDZ"
+ },
+ "source": [
+ "# Reading from text files\n",
+ "\n",
+ "We can use the\n",
+
"[`ReadFromText`](https://beam.apache.org/releases/pydoc/current/apache_beam.io.textio.html#apache_beam.io.textio.ReadFromText)\n",
+ "transform to read text files into `str` elements.\n",
+ "\n",
+ "It takes a\n",
+ "[_glob
pattern_](https://en.wikipedia.org/wiki/Glob_%28programming%29)\n",
+ "as an input, and reads all the files that match that pattern.\n",
+ "It returns one element for each line in the file.\n",
+ "\n",
+ "For example, in the pattern `data/*.txt`, the `*` is a wildcard that
matches anything. This pattern matches all the files in the `data/` directory
with a `.txt` extension."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/";
+ },
+ "id": "xDXdE9uysriw",
+ "outputId": "f5d58b5d-892a-4a42-89c5-b78f1d329cf3"
+ },
+ "source": [
+ "import apache_beam as beam\n",
+ "\n",
+ "file_name = 'data/*.txt'\n",
Review comment:
That's a great suggestion, I'll be changing that. Thanks!
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