{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run workfow with subset chain\n",
    "\n",
    "**Rooki** calls climate data operations on the **rook** processing service."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## workflow with subset chain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.environ['ROOK_URL'] = 'http://rook.dkrz.de/wps'\n",
    "\n",
    "from rooki import operators as ops"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "wf = ops.Subset(\n",
    "        ops.Subset(\n",
    "            ops.Input(\n",
    "                'tas', ['c3s-cmip6.ScenarioMIP.INM.INM-CM5-0.ssp245.r1i1p1f1.day.tas.gr1.v20190619']\n",
    "            ),\n",
    "            time=\"2016-01-01/2020-12-30\",\n",
    "        ),\n",
    "        time=\"2017-01-01/2017-12-30\",\n",
    ")\n",
    "   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp = wf.orchestrate()\n",
    "resp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**metalink output**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(resp.xml)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Size in MBytes**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp.size_in_mb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**URLs in metalink document ...**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "resp.download_urls()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**... and open with xarray**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = resp.datasets()[0]\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**provenance**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Image\n",
    "Image(resp.provenance_image())\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.9.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}