zonca/read_zarr_jetstream.ipynb

## read_zarr_jetstream.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dask import distributed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a local cluster of workers all running on the same machine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table style=\"border: 2px solid white;\">\n",
       "<tr>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3>Client</h3>\n",
       "<ul>\n",
       "  <li><b>Scheduler: </b>tcp://127.0.0.1:34052\n",
       "  <li><b>Dashboard: </b><a href='http://127.0.0.1:34695/status' target='_blank'>http://127.0.0.1:34695/status</a>\n",
       "</ul>\n",
       "</td>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3>Cluster</h3>\n",
       "<ul>\n",
       "  <li><b>Workers: </b>6</li>\n",
       "  <li><b>Cores: </b>6</li>\n",
       "  <li><b>Memory: </b>16.83 GB</li>\n",
       "</ul>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Client: scheduler='tcp://127.0.0.1:34052' processes=6 cores=6>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client = distributed.Client()\n",
    "client"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Connect to object store and check the content of a folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import s3fs\n",
    "fs = s3fs.S3FileSystem(anon=True, client_kwargs=dict(endpoint_url=\"JETSTREAM_SWIFT_ENDPOINT\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sandy_zarr/.zattrs', 'sandy_zarr/.zgroup', 'sandy_zarr/AKv']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fs.ls(\"sandy_zarr\")[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a data store compatible with xarray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = s3fs.S3Map(\"sandy_zarr\", s3=fs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a distributed array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "ds = xr.open_zarr(d)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load data into memory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "278e05a527e64a51878472d9fd1bc8a5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>VBox</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "VBox()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds = ds.persist()\n",
    "distributed.progress(ds)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Make a plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(97, 64, 84)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.rain.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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u1iLpUkfizqykX/2m8h2VuNB2JNFq+/Ytyml0176u+iqbnnlFm449SeTZxB23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\nEsYYY+piIWGMMaYu/x+e3OtP45sV8QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa59ae249b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.rain[45,:,:].plot();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [default]",
   "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}