{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "## GRIB: indexing "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import earthkit.data as ekd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we prepare the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "ekd.download_example_file([\"test.grib\", \"tuv_pl.grib\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "!test -d _grib_dir_with_sql || mkdir -p _grib_dir_with_sql\n",
    "!cp test.grib tuv_pl.grib _grib_dir_with_sql/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "### Indexing"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "editable": true,
    "raw_mimetype": "text/restructuredtext",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "We can perform indexing on the input GRIB data by using the **indexing** option in :ref:`from_source() <data-sources-file>`. The indexing is performed on first data access using the MARS ecCodes keys. The index-data is stored in a sqlite database, which is located in the earthkit-data cache. Subsequent loading of the same data is very fast because it will use the cached index-data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|                                                                                                                                                                    | 0/1 [00:00<?, ?it/s]\n",
      "Parsing tuv_pl.grib:   0%|                                                                                                                                         | 0.00/4.22k [00:00<?, ?B/s]\u001b[A\n",
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 12.27it/s]\u001b[A\n"
     ]
    }
   ],
   "source": [
    "fs = ekd.from_source(\"file\", \"tuv_pl.grib\", indexing=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Indexing also works for a list of files or directories (here \"\\_grib_dir_with_sql\") is a directory:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|                                                                                                                                                                    | 0/2 [00:00<?, ?it/s]\n",
      "Parsing ./_grib_dir_with_sql/tuv_pl.grib:   0%|                                                                                                                    | 0.00/4.22k [00:00<?, ?B/s]\u001b[A\n",
      "                                                                                                                                                                                               \u001b[A\n",
      "Parsing ./_grib_dir_with_sql/test.grib:   0%|                                                                                                                      | 0.00/1.03k [00:00<?, ?B/s]\u001b[A\n",
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 92.85it/s]\u001b[A\n"
     ]
    }
   ],
   "source": [
    "fs = ekd.from_source(\"file\", \"./_grib_dir_with_sql\", indexing=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(fs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "earthkit.data.readers.grib.index.sql.FieldListInFilesWithSqlIndex"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(fs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "### Methods using the SQL database"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "editable": true,
    "raw_mimetype": "text/restructuredtext",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "When calling :py:meth:`~data.readers.grib.index.GribFieldList.sel`, :py:meth:`~data.readers.grib.index.GribFieldList.isel` or :py:meth:`~data.readers.grib.index.GribFieldList.order_by` the metadata is directly read from the index database, so there is no need to load/open any of the GRIB messages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = fs.sel(level=500)\n",
    "len(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = fs.order_by(\"param\")\n",
    "len(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = fs.isel(level=2)\n",
    "len(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For keys not present in the index db the functions above do not work:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "error: 'i_gridType'\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    a = fs.sel(gridType=\"regular_ll\")\n",
    "    print(len(a))\n",
    "except KeyError as e:\n",
    "    print(f\"error: {e}\")   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "### Methods not using the SQL database"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "editable": true,
    "raw_mimetype": "text/restructuredtext",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Most of the other methods still need to load/open the GRIB messages to extract the required :py:meth:`~data.readers.grib.index.GribFieldList.metadata`. Ideally they should all use the index database. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "GribField(u,1000,20180801,1200,0,0)\n"
     ]
    }
   ],
   "source": [
    "print(fs[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['v', 't']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fs[2:4].metadata(\"param\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### from_source() arguments"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "editable": true,
    "raw_mimetype": "text/restructuredtext",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "source": [
    "Selection and sorting arguments can be directly passed to :ref:`from_source() <data-sources-file>`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [
    {
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      "text/plain": [
       "  centre shortName    typeOfLevel  level  dataDate  dataTime stepRange  \\\n",
       "0   ecmf         t  isobaricInhPa    500  20180801      1200         0   \n",
       "1   ecmf         u  isobaricInhPa    500  20180801      1200         0   \n",
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       "0       an       0  regular_ll  \n",
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       "2       an       0  regular_ll  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fs = ekd.from_source(\"file\", \"./_grib_dir_with_sql\", indexing=True, level=500)\n",
    "fs.ls()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
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       "  centre shortName    typeOfLevel  level  dataDate  dataTime stepRange  \\\n",
       "0   ecmf         t  isobaricInhPa    850  20180801      1200         0   \n",
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       "2   ecmf         u  isobaricInhPa    850  20180801      1200         0   \n",
       "3   ecmf         u  isobaricInhPa    500  20180801      1200         0   \n",
       "4   ecmf         v  isobaricInhPa    850  20180801      1200         0   \n",
       "5   ecmf         v  isobaricInhPa    500  20180801      1200         0   \n",
       "\n",
       "  dataType  number    gridType  \n",
       "0       an       0  regular_ll  \n",
       "1       an       0  regular_ll  \n",
       "2       an       0  regular_ll  \n",
       "3       an       0  regular_ll  \n",
       "4       an       0  regular_ll  \n",
       "5       an       0  regular_ll  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fs = ekd.from_source(\"file\", \"./_grib_dir_with_sql\", indexing=True, level=[500, 850], \n",
    "                               order_by=\"variable\")\n",
    "fs.ls()"
   ]
  }
 ],
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