From 7620de2d911877b888122b36f7314ff80ab037e2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Shan=C3=A9=20Winner?=
 <43390034+swinner95@users.noreply.github.com>
Date: Wed, 21 Aug 2019 10:16:42 -0700
Subject: [PATCH] Delete secrets.ipynb

---
 .../dataprep/how-to-guides/secrets.ipynb      | 140 ------------------
 1 file changed, 140 deletions(-)
 delete mode 100644 work-with-data/dataprep/how-to-guides/secrets.ipynb

diff --git a/work-with-data/dataprep/how-to-guides/secrets.ipynb b/work-with-data/dataprep/how-to-guides/secrets.ipynb
deleted file mode 100644
index c77169c9..00000000
--- a/work-with-data/dataprep/how-to-guides/secrets.ipynb
+++ /dev/null
@@ -1,140 +0,0 @@
-{
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "![Impressions](https://PixelServer20190423114238.azurewebsites.net/api/impressions/MachineLearningNotebooks/work-with-data/dataprep/how-to-guides/secrets.png)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "# Providing Secrets\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "Currently, secrets are only persisted for the lifetime of the engine process. Even if the dataflow is saved to a file, the secrets are not persisted in the dprep file. If you started a new session (i.e. start a new engine process), loaded a dataflow and wanted to run it, you will need to call `use_secrets` to register the required secrets to use during execution, otherwise the execution will fail as the required secrets are not available.\n",
-        "\n",
-        "In this notebook, we will:\n",
-        "1. Loading a previously saved dataflow\n",
-        "2. Call `get_missing_secrets` to determine the missing secrets\n",
-        "3. Call `use_secrets` and pass in the missing secrets to register it with the engine for this session\n",
-        "4. Call `head` to see the a preview of the data"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "import azureml.dataprep as dprep\n",
-        "\n",
-        "import os"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "Let's load the previously saved dataflow."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "dflow = dprep.Dataflow.open(file_path='../data/secrets.dprep')\n",
-        "dflow"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "You can call `get_missing_secrets` to see which required secrets are missing in the engine."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "dflow.get_missing_secrets()"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "You can now read the secrets from an environment variable, put it in a secret dictionary, and call `use_secrets` with the secrets. This will register the secrets in the engine so you don't need to provide them again in this session.\n",
-        "\n",
-        "_Note: It is a bad practice to have secrets in files that will be checked into source control._"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "sas = os.environ['SCENARIOS_SECRETS']\n",
-        "secrets = {\n",
-        "    'https://dpreptestfiles.blob.core.windows.net/testfiles/read_csv_duplicate_headers.csv': sas\n",
-        "}\n",
-        "dflow.use_secrets(secrets=secrets)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "You can now call `head` without passing in `secrets` and the engine will successfully execute. Here is a preview of the data."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "dflow.head(5)"
-      ]
-    }
-  ],
-  "metadata": {
-    "authors": [
-      {
-        "name": "sihhu"
-      }
-    ],
-    "kernelspec": {
-      "display_name": "Python 3.6",
-      "language": "python",
-      "name": "python36"
-    },
-    "language_info": {
-      "codemirror_mode": {
-        "name": "ipython",
-        "version": 3
-      },
-      "file_extension": ".py",
-      "mimetype": "text/x-python",
-      "name": "python",
-      "nbconvert_exporter": "python",
-      "pygments_lexer": "ipython3",
-      "version": "3.6.4"
-    },
-    "notice": "Copyright (c) Microsoft Corporation. All rights reserved. Licensed under the MIT License."
-  },
-  "nbformat": 4,
-  "nbformat_minor": 2
-}
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