Get User Reports.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get User Reports"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook will walk you through the process of querying the ArcGIS REST API to find out what Users have been created in the last 24 hours as well as what Users have logged in the last 24 hours."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import what we need from Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from datetime import datetime, timedelta\n",
    "from arcgis import GIS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Log in"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "username = input('Username: ')\n",
    "gis = GIS('https://www.arcgis.com', username)\n",
    "print ('logged in')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Access to the UserManager and get a list of the users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "users = gis.users.search()\n",
    "users"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filter the Users"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Find users that have **logged in** the past 24 hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = datetime.utcnow() - timedelta(days=1)\n",
    "end = datetime.utcnow()\n",
    "\n",
    "print (start, end)\n",
    "\n",
    "filtered_users = []\n",
    "for user in users:\n",
    "    ts = user.lastLogin\n",
    "    new_lastlogin = datetime.utcfromtimestamp(ts/1000)\n",
    "    \n",
    "    if new_lastlogin >= start and new_lastlogin <= end:\n",
    "        filtered_users.append(user)\n",
    "\n",
    "filtered_users"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### OR -- Find users that have been **created** in the past 24 hours"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = datetime.utcnow() - timedelta(days=1)\n",
    "end = datetime.utcnow()\n",
    "\n",
    "print (start, end)\n",
    "\n",
    "filtered_users = []\n",
    "for user in users:\n",
    "    ts = user.created\n",
    "    new_created = datetime.utcfromtimestamp(ts/1000)\n",
    "    \n",
    "    if new_created >= start and new_created <= end:\n",
    "        filtered_users.append(user)\n",
    "\n",
    "filtered_users"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Export the User information"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Export user list to CSV string to copy/paste in email"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_list = []\n",
    "for user in filtered_users:\n",
    "    user_list.append(user.email)\n",
    "\n",
    "','.join(user_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Export user list to CSV file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Setup Pandas DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = ['username', 'firstName', 'lastName', 'created', 'lastLogin', 'email']\n",
    "df = pd.DataFrame(filtered_users, columns=columns)\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Export DataFrame to CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('user_list.csv')"
   ]
  }
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