{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ⌚ Herbie Latest\n",
    "\n",
    "A little helper to get the most recent model data. (Not super efficient, but it works)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from herbie import Herbie, Herbie_latest, FastHerbie\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[48;2;255;255;255m\u001b[38;2;136;33;27m▌\u001b[0m\u001b[38;2;12;53;118m\u001b[48;2;240;234;210m▌\u001b[38;2;0;0;0m\u001b[1mHerbie\u001b[0m HRRR model \u001b[3msfc\u001b[0m product initialized \u001b[38;2;41;130;13m2022-Dec-10 21:00 UTC\u001b[92m F00\u001b[0m ┊ \u001b[38;2;255;153;0m\u001b[3msource=aws\u001b[0m"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "H = Herbie_latest()\n",
    "H"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[48;2;255;255;255m\u001b[38;2;136;33;27m▌\u001b[0m\u001b[38;2;12;53;118m\u001b[48;2;240;234;210m▌\u001b[38;2;0;0;0m\u001b[1mHerbie\u001b[0m GFS model \u001b[3mpgrb2.0p25\u001b[0m product initialized \u001b[38;2;41;130;13m2022-Dec-10 18:00 UTC\u001b[92m F06\u001b[0m ┊ \u001b[38;2;255;153;0m\u001b[3msource=aws\u001b[0m"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "H = Herbie_latest(model=\"gfs\", n=6, freq=\"6H\", fxx=[6])\n",
    "H"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "herbie-dev",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8 | packaged by conda-forge | (main, Nov 22 2022, 08:16:33) [MSC v.1929 64 bit (AMD64)]"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "ac511961bc6976a3d289cde8fc247e6b0e9298cf513cb762aa0a7df646d192ed"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}