{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mdf_toolbox"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Globus Search Utilities\n",
    "The MDF Toolbox provides a few utilities to make integrating with Globus Search easier."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# format_gmeta\n",
    "`format_gmeta()` takes a dictionary of data you want to change into the Globus Search GMeta format and returns the `GMetaEntry` of that dictionary. It is required to provide the `acl` (Access Control List, or `[\"public\"]` for public data) and `identifier` (unique ID for this entry, or an existing ID to overwrite).\n",
    "\n",
    "To make a `GIngest` (the final form of Globus Search ingests), provide a list of `GMetaEntry` objects."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_data = {\n",
    "    \"foo\": \"bar\",\n",
    "    \"baz\": [1, 2, 3, 4]\n",
    "}\n",
    "gmeta_entry = mdf_toolbox.format_gmeta(my_data,\n",
    "                                       acl=[\"public\"],\n",
    "                                       identifier=\"abc123\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'@datatype': 'GMetaEntry',\n",
       " '@version': '2016-11-09',\n",
       " 'content': {'baz': [1, 2, 3, 4], 'foo': 'bar'},\n",
       " 'subject': 'abc123',\n",
       " 'visible_to': ['public']}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gmeta_entry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_of_gmeta_entry = [gmeta_entry]\n",
    "g_ingest = mdf_toolbox.format_gmeta(list_of_gmeta_entry)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'@datatype': 'GIngest',\n",
       " '@version': '2016-11-09',\n",
       " 'ingest_data': {'@datatype': 'GMetaList',\n",
       "  '@version': '2016-11-09',\n",
       "  'gmeta': [{'@datatype': 'GMetaEntry',\n",
       "    '@version': '2016-11-09',\n",
       "    'content': {'baz': [1, 2, 3, 4], 'foo': 'bar'},\n",
       "    'subject': 'abc123',\n",
       "    'visible_to': ['public']}]},\n",
       " 'ingest_type': 'GMetaList'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g_ingest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# globus_sdk.SearchClient.ingest(index, g_ingest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## gmeta_pop\n",
    "`gmeta_pop()` takes the results from a Globus Search query and unwraps them from the GMeta format. You can pass in a `GlobusHTTPResponse` from the `SearchClient`, a JSON-dumped string, or a dictionary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_search_result = { \n",
    "    '@datatype': 'GSearchResult',\n",
    "    '@version': '2016-11-09',\n",
    "    'count': 11, \n",
    "    'gmeta': [{\n",
    "        '@datatype': 'GMetaResult',\n",
    "        '@version': '2016-11-09',\n",
    "        'content': [{\n",
    "            \"foo\": \"bar\",\n",
    "            \"baz\": [1, 2, 3, 4, 5]\n",
    "        }, {\n",
    "            \"food\": \"bard\",\n",
    "            \"bazd\": [\"d\"]\n",
    "        }],\n",
    "        'subject': \"http://example.com/abc123\",\n",
    "    }],\n",
    "    'offset': 0,\n",
    "    'total': 22\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'baz': [1, 2, 3, 4, 5], 'foo': 'bar'}, {'bazd': ['d'], 'food': 'bard'}]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mdf_toolbox.gmeta_pop(sample_search_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you want the metadata associated with your query (total number of query matches), you can use `info=True` to get a tuple of (results, metadata)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([{'baz': [1, 2, 3, 4, 5], 'foo': 'bar'}, {'bazd': ['d'], 'food': 'bard'}],\n",
       " {'total_query_matches': 22})"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mdf_toolbox.gmeta_pop(sample_search_result, info=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## translate_index\n",
    "Globus Search requires or strongly encourages users to query using an index's UUID instead of the index's name. `translate_index()` takes the index name and returns the UUID (if found, otherwise it returns the input back)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1a57bbe5-5272-477f-9d31-343b8258b7a5'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mdf_toolbox.translate_index(\"mdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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