{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Content Management: Check for broken URLs\n",
    "\n",
    "> * ✏️ Needs Configuration\n",
    "* 🗄️ Administration\n",
    "* 🔔 Notifications\n",
    "\n",
    "A WebMap is a collection of layers, basemaps, and other services. These services are hosted on either ArcGIS Online or an external ArcGIS Server, separate from the WebMap itself. If the external service gets deleted, the WebMap will still exist, but it will not function properly.\n",
    "\n",
    "This notebook will search through all WebMaps in specified groups, and will attempt to connect to each layer URL, basemap URL, etc. If the connection fails for any URL, the owner of the WebMap and other specified users will be notified. This notebook can be used to automatically identify broken WebMaps, and alert the necessary users so they can take the appropriate action."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get started, import the necessary libraries and connect to our GIS:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "import smtplib\n",
    "import requests\n",
    "import logging\n",
    "log = logging.getLogger()\n",
    "\n",
    "from arcgis.gis import GIS\n",
    "from arcgis.mapping import WebMap\n",
    "\n",
    "gis = GIS(\"home\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will create our function that sends out notifications."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Notifications\n",
    "\n",
    "An important part of this process is notifying the right people when we come across a broken URL. We will achieve this by connecting to an external SMTP server and sending out emails, but you can write _any_ code that connects to _any_ external service to send out notifications. __View the 'Notifications' notebook in the examples gallery for more information__.\n",
    "\n",
    "__<span style=\"color:red;\">You MUST modify the below cell</span>__ to update `secret_csv_item_id`, `smtp_server_url`, `username`, and any other information needed to connect to your external smtp server. This includes making sure your _secrets.csv_ file item contains the `smtp_email_password` entry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Helper function for using your private secrets.csv file\n",
    "def get_secrets(gis=gis,\n",
    "                secret_csv_item_id = '<YOUR_ITEM_ID_HERE>'):\n",
    "    \"\"\"Returns a dict of { secret_key : secret_value } from the \n",
    "    secrets.csv item. See the 'Notifications' notebook in the \n",
    "    examples gallery for more information.\n",
    "    \"\"\"\n",
    "    try:\n",
    "        item = gis.content.get(secret_csv_item_id)\n",
    "        with open(item.download(), 'r') as local_item_file:\n",
    "            reader = csv.DictReader(local_item_file)\n",
    "            return { rows['secret_key'] : rows['secret_value'] \\\n",
    "                     for rows in reader }\n",
    "    except Exception:\n",
    "        return {}\n",
    "\n",
    "SECRETS = get_secrets()\n",
    "\n",
    "# Helper function to send out emails through an SMTP server\n",
    "def send_email_smtp(recipients, message,\n",
    "                    subject=\"Message from your Notebook\"):\n",
    "    \"\"\"Sends the `message` string to all of the emails in the \n",
    "    `recipients` list using the configured SMTP email server. \n",
    "    See the 'Notifications' notebook in the examples gallery\n",
    "    for more information.\n",
    "    \"\"\"\n",
    "    try:\n",
    "        # Set up server and credential variables\n",
    "        smtp_server_url = \"smtp.example.com\"\n",
    "        smtp_server_port = 587\n",
    "        sender = \"your_sender@example.com\"\n",
    "        username = \"your_username\"\n",
    "        password = SECRETS[\"smtp_email_password\"]\n",
    "\n",
    "        # Instantiate our server, configure the necessary security\n",
    "        server = smtplib.SMTP(smtp_server_url, smtp_server_port)\n",
    "        server.ehlo()\n",
    "        server.starttls() # Needed if TLS is required w/ SMTP server\n",
    "        server.login(username, password)\n",
    "    except Exception as e:\n",
    "        log.warning(\"Error setting up SMTP server, couldn't send \" +\n",
    "                    f\"message to {recipients}\")\n",
    "        raise e\n",
    "\n",
    "    # For each recipient, construct the message and attempt to send\n",
    "    did_succeed = True\n",
    "    for recipient in recipients:\n",
    "        try:\n",
    "            message_body = '\\r\\n'.join(['To: {}'.format(recipient),\n",
    "                                        'From: {}'.format(sender),\n",
    "                                        'Subject: {}'.format(subject),\n",
    "                                        '{}'.format(message)])\n",
    "            message_body = message_body.encode(\"utf-8\")\n",
    "            server.sendmail(sender, [recipient], message_body)\n",
    "            print(f\"SMTP server returned success for sending email \"\\\n",
    "                  f\"to {recipient}\")\n",
    "        except Exception as e:\n",
    "            log.warning(f\"Failed sending message to {recipient}\")\n",
    "            log.warning(e)\n",
    "            did_succeed = False\n",
    "    \n",
    "    # Cleanup and return\n",
    "    server.quit()\n",
    "    return did_succeed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make sure to independently test that your notifications function works before proceeding forward with this notebook."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Configure Behavior\n",
    "\n",
    "Now that we have a function that sends out notifications, let's configure some variables specific to our Organization that will tell our notebook how we want it to run. With the default `CHECK_ALL_ITEMS` set to `False`, this notebook will check all items in the groups specified in the `CHECK_THESE_GROUPS` list of strings. If you would instead prefer to check all items in your Organization, set `CHECK_ALL_ITEMS` to `True`.\n",
    "\n",
    "__<span style=\"color:red;\">You MUST modify the below cell</span>__ to add your group names to `CHECK_THESE_GROUPS`, __<span style=\"color:red;\">OR</span>__ you must set `CHECK_ALL_ITEMS` to `True`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set to `True` you would like to check ALL items in an Org\n",
    "CHECK_ALL_ITEMS = False\n",
    "# If `CHECK_ALL_ITEMS` is `False`, will check all items in these groups\n",
    "CHECK_THESE_GROUPS = ['group_name_1', 'group_name_2']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's specify who we want to email when we find broken URLs. If `TRY_EMAIL_WEBMAP_AUTHOR` is set to `True`, the owner of the WebMap will attempt to be notified via email. All the email address strings in the `EMAIL_THESE_ADDITIONAL_PEOPLE` list will also be emailed in the event of any broken URL in any WebMap. Example:\n",
    " \n",
    "```python\n",
    "EMAIL_THESE_ADDITIONAL_PEOPLE = ['somebody@example.com', 'somebodyelse@example.com']\n",
    "```\n",
    "\n",
    "The default behavior is to only email the webmap owner. Modify the below cell to change that default behavior."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# If you try to email the author of the WebMap of the Broken URLs\n",
    "TRY_EMAIL_WEBMAP_OWNER = True\n",
    "# Email these additional people about any broken URLs\n",
    "EMAIL_THESE_ADDITIONAL_PEOPLE = []"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## WebMap Parsing Logic\n",
    "\n",
    "A core component of this notebook will be testing if different URLs are 'reachable'. We will do this by creating a helper function that uses the `requests` library to make an HTTP GET request to the specified url and assert that is returns a good HTTP status code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def is_url_reachable(url):\n",
    "    \"\"\"Returns a bool representing if the URL is reachable\"\"\"\n",
    "    try:\n",
    "        response = requests.get(url)\n",
    "        return response.ok\n",
    "    except Exception as e:\n",
    "        return False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test out this helper function by passing in strings such as `\"https://arcgis.com\"` or `\"https://arcgis.com/nonexistantpage.html\"`.\n",
    "\n",
    "Now, we can create a function that will test the URLs of all operational layers and basemap layers of a WebMap. This function will return a tuple of reachable and unreachable layers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def test_urls_in_webmap(webmap_item):\n",
    "    \"\"\"Takes in an `Item` class instance of a Web Map Item.\n",
    "    Tests if all operational layers and basemap layers are\n",
    "    reachable. Returns a tuple of (reachable, unreachable), \n",
    "    with each tuple entry being a list of layers/basemaps JSON.\n",
    "    \"\"\"\n",
    "    reachable = []\n",
    "    unreachable = []\n",
    "    wm = WebMap(webmap_item)\n",
    "\n",
    "    # Concatanate all operational layers and basemap layers to 1 list\n",
    "    all_layers = list(wm.layers)\n",
    "    if hasattr(wm.basemap, 'baseMapLayers'):\n",
    "        all_layers += wm.basemap.baseMapLayers\n",
    "\n",
    "    # Test all of the layers, return the results\n",
    "    for layer in [layer for layer in all_layers \\\n",
    "                  if hasattr(layer, 'url')]:\n",
    "        if is_url_reachable(layer.url):\n",
    "            log.debug(f\"    [✓] url {layer.url} reachable\")\n",
    "            reachable.append(layer)\n",
    "        else:\n",
    "            log.debug(f\"    [X] url {layer.url} NOT reachable\")\n",
    "            unreachable.append(layer)\n",
    "    return (reachable, unreachable)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test out this function by passing in an `Item` class instance of a Web Map Item.\n",
    "\n",
    "Now, let's create a helper function that assembles a human readable string with information about the WebMap, what URLs aren't reachable, etc. We will use this when sending out emails."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def assemble_message(webmap_item, reachable, unreachable):\n",
    "    \"\"\"Makes a human readable message with the args passed in\"\"\"\n",
    "    def _assemble_bullet_point(layer, is_reachable):\n",
    "        \"\"\"Internal function to assemble one bullet point from a layer\"\"\"\n",
    "        icon = '✅' if is_reachable else '❌'\n",
    "        return f\"* {icon} {layer.id}\"\n",
    "\n",
    "    # Assemble a string representation of both lists\n",
    "    reachable_str = \"\\n\".join(_assemble_bullet_point(layer, True) \\\n",
    "                               for layer in reachable)\n",
    "    unreachable_str = \"\\n\".join(_assemble_bullet_point(layer, False) \\\n",
    "                               for layer in unreachable)\n",
    "\n",
    "    # Asemble the message and return it\n",
    "    return f\"Webmap ID '{webmap_item.id}' contains unreachable URLs. \"\\\n",
    "           f\"You can view the webmap here: {webmap_item.homepage}\\n\"\\\n",
    "           f\"\\n\"\\\n",
    "           f\"Reachable Layers\\n\"\\\n",
    "           f\"-----------------\\n\"\\\n",
    "           f\"{reachable_str}\\n\"\\\n",
    "           f\"\\n\"\\\n",
    "           f\"Unreachable Layers\\n\"\\\n",
    "           f\"-------------------\\n\"\\\n",
    "           f\"{unreachable_str}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's create the function that will be called whenever we encounter a WebMap with broken URLs. This function will assemble the appropriate people to email, assemble the message/subject to send, then send the message to the recipients."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def handle_unreachable(webmap_item, reachable, unreachable,\n",
    "                        gis=gis):\n",
    "    \"\"\"Called whenever we encounter a WebMap with broken URLs. Will \n",
    "    assemble an appropriate message, and send it out to the previously\n",
    "    configured emails.\n",
    "    \"\"\"\n",
    "    # Get the people we need to email\n",
    "    recipients = list(EMAIL_THESE_ADDITIONAL_PEOPLE)\n",
    "    if TRY_EMAIL_WEBMAP_OWNER:\n",
    "        owner = gis.users.get(webmap_item.owner)\n",
    "        recipients.append(owner.email)\n",
    "\n",
    "    # Assemble the message and send it\n",
    "    message = assemble_message(webmap_item, reachable, unreachable)\n",
    "    subject = f\"WebMap '{webmap_item.id}' contains broken URLs\"\n",
    "    if send_email_smtp(recipients, message, subject):\n",
    "        return True\n",
    "    else:\n",
    "        log.warning(f\"Error emailing users about WebMap {webmap_item.id}.\")\n",
    "        return False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> __Note__: If you have an alternative notification function you want to use, make sure you modify the above cell to include that function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's create a generator function that will `yield` `Item`(s). This notebook can run against all items in an Organization, or all items from certain groups, depending on how you configured the notebook above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_items_to_check():\n",
    "    \"\"\"Generator function that will yield Items depending on how you\n",
    "    configured your notebook. Will either yield every item in an \n",
    "    organization, or will yield items in specific groups.\n",
    "    \"\"\"\n",
    "    if CHECK_ALL_ITEMS:\n",
    "        for user in gis.users.search():\n",
    "            for item in user.items(max_items=999999999):\n",
    "                # For the user's root folder\n",
    "                yield item\n",
    "            for folder in user.folders:\n",
    "                # For all the user's other folders\n",
    "                for item in user.items(folder, max_items=999999999):\n",
    "                    yield item\n",
    "    else:\n",
    "        for group_name in CHECK_THESE_GROUPS:\n",
    "            group = gis.groups.search(f\"title: {group_name}\")[0]\n",
    "            for item in group.content():\n",
    "                yield item"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## main()\n",
    "\n",
    "Finally, let's create our `main()` function that links together all our previously defined functions to search through groups, test all webmaps for broken URLs, and alert the correct people when we find unreachable URLs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def main():\n",
    "    print(\"Notebook is now running, please wait...\\n-----\")\n",
    "    for item in get_items_to_check():\n",
    "        print(f\"\\rChecking item {item.id}\", end=\"\")\n",
    "        if item.type == \"Web Map\":\n",
    "            reachable, unreachable = test_urls_in_webmap(item)\n",
    "            if unreachable:\n",
    "                print(f\"\\nWebmap {item.id} unreachable. Notifying...\")\n",
    "                handle_unreachable(item, reachable, unreachable)\n",
    "    print(\"-----\\nNotebook completed running.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have just defined a `main()` function, but we haven't called it yet. Set up some test WebMaps with broken URLs in the specified groups, call `main()` manually, and assert that the correct people are emailed. Once you are sure that this function is working properly, do the following:\n",
    "\n",
    "1. __Double check the notebook content__, make sure no secrets are visible in the notebook, delete unused code, refactor, etc.\n",
    "2. Place a single call to `main()` in the below cell\n",
    "3. Save the notebook\n",
    "4. In the 'Kernel' menu, press 'Restart and Run All'\n",
    "5. Assert that the whole notebook runs without error, and assert that you are seeing the same correct behavior as before"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Notebook is now running, please wait...\n",
      "-----\n",
      "Webmap ee28fe0d5b8b46aba7c4b746f7bb180a unreacheable. Notifying...\n",
      "SMTP server returned success for sending email to somebody@example.com\n",
      "SMTP server returned success for sending email to somebodyelse@example.com\n",
      "-----\n",
      "Notebook completed running.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "main()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Congratulations! If all is setup correctly, emails should be sent out for any WebMaps with broken URLs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\" data:image/png;base64,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\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion\n",
    "\n",
    "This notebook provided you the workflow for checking WebMaps for broken URLs and notifying users via an external service. When configured properly, this notebook can be a powerful administrative tool to help you anticipate problems stemming from broken WebMaps. As the saying goes, \"An ounce of prevention is worth a pound of cure\".\n",
    "\n",
    "### Related Notebooks\n",
    "For related notebooks, search for the following in your samples notebook gallery:\n",
    "\n",
    "- Notifications\n",
    "- Identify Items That Use Insecure URLs"
   ]
  }
 ],
 "metadata": {
  "esriNotebookRuntime": {
   "notebookRuntimeName": "ArcGIS Notebook Python 3 Standard",
   "notebookRuntimeVersion": "10.7.1"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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