{
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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c02da3c-5d89-40f7-bced-2d8e73d4b92b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cell 1: Install saspy (if not already present)\n",
    "!pip install --quiet saspy\n",
    "\n",
    "# Cell 2: Import all our libraries\n",
    "import saspy\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import time\n",
    "from IPython.display import display, clear_output\n",
    "\n",
    "# Connect to our SAS session\n",
    "sas = saspy.SASsession()\n",
    "print(\"SAS Session is ready!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f337e392-e404-4d0d-8ea9-2d077ba5c6b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cell 3: Create the \"baseline\" data using SAS code\n",
    "sas.submitLST(f\"\"\"\n",
    "    DATA WORK.BASELINE;\n",
    "        /* Create 50 normal transactions */\n",
    "        DO time = 1 TO 50;\n",
    "            /* Mean = $50, Std Dev = $15 */\n",
    "            amount = RAND('NORMAL', 50, 15); \n",
    "            OUTPUT;\n",
    "        END;\n",
    "    RUN;\n",
    "\"\"\", print_log=False)\n",
    "\n",
    "print(\"Baseline 'normal' data created in SAS.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f7b0ded-1d8c-4daf-af68-8328860a418f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cell 4: Calculate and save the control limits\n",
    "sas.submitLST(f\"\"\"\n",
    "    /* Run the Shewhart procedure on our baseline data */\n",
    "    PROC SHEWHART DATA=WORK.BASELINE;\n",
    "    \n",
    "        /* Create an Individual & Moving Range chart */\n",
    "        IRCHART amount * time / \n",
    "            NOCHART         /* Don't show the chart yet */\n",
    "            OUTLIMITS=WORK.CONTROL_LIMITS; /* Save the limits to a new dataset */\n",
    "    RUN;\n",
    "\"\"\", print_log=False)\n",
    "\n",
    "print(\"Control limits (our 'model') have been calculated and saved.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "209e1029-7a24-49ee-807a-8e5967a1d5df",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cell 5: The Live Simulation\n",
    "sas.submitLST(\"DATA WORK.LIVE_STREAM; SET WORK.BASELINE;\", print_log=False)\n",
    "\n",
    "# Simulate 20 new transactions\n",
    "for i in range(1, 21):\n",
    "    # 1. GENERATE new data point in Python\n",
    "    time_id = 50 + i\n",
    "    if i == 15:\n",
    "        # --- THE ANOMALY ---\n",
    "        new_amount = 300\n",
    "        print(f\"Time={time_id}: FRAUDULENT transaction injected: ${new_amount:.2f}\")\n",
    "    else:\n",
    "        # --- NORMAL ---\n",
    "        new_amount = np.random.normal(50, 15)\n",
    "        print(f\"Time={time_id}: New 'normal' transaction: ${new_amount:.2f}\")\n",
    "\n",
    "    # 2. SEND the single new row to SAS\n",
    "    new_row_df = pd.DataFrame({'time': [time_id], 'amount': [new_amount]})\n",
    "    sas.df2sd(new_row_df, 'WORK.LIVE_STREAM', append=True) # Append the new row\n",
    "\n",
    "    # 3. RE-RUN the chart\n",
    "    # Tell SAS to use the 'WORK.LIVE_STREAM' data\n",
    "    # but apply the 'WORK.CONTROL_LIMITS' we already built\n",
    "    chart_html = sas.submitLST(f\"\"\"\n",
    "        ODS GRAPHICS ON;\n",
    "        PROC SHEWHART DATA=WORK.LIVE_STREAM LIMITS=WORK.CONTROL_LIMITS;\n",
    "            IRCHART amount * time /\n",
    "                TURNHLABELS  /* Makes X-axis labels vertical */\n",
    "                NOLIMITLEGEND; /* Hides the legend */\n",
    "        RUN;\n",
    "        ODS GRAPHICS OFF;\n",
    "    \"\"\")\n",
    "    \n",
    "    # 4. \"ANIMATE\" the chart in Jupyter\n",
    "    clear_output(wait=True) # Clear the previous chart\n",
    "    display(chart_html)    # Display the new chart\n",
    "    time.sleep(1)          # Pause for 1 second\n",
    "\n",
    "print(\"Streaming demo complete!\")"
   ]
  }
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