{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7edbd867",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['french lavender', 'french lavender', 'french lavender', 'french lavender', 'french lavender', 'italian lavender', 'italian lavender']\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "def get_common_names_gbif(scientific_name: str) -> list[str]:\n",
    "    \"\"\"Get all common names for a scientific name via GBIF.\"\"\"\n",
    "    # Step 1: get GBIF taxon key\n",
    "    r = requests.get(\n",
    "        \"https://api.gbif.org/v1/species/match\",\n",
    "        params={\"name\": scientific_name, \"strict\": False}\n",
    "    )\n",
    "    key = r.json().get(\"usageKey\")\n",
    "    if not key:\n",
    "        return []\n",
    "\n",
    "    # Step 2: get vernacular names\n",
    "    r2 = requests.get(f\"https://api.gbif.org/v1/species/{key}/vernacularNames\")\n",
    "    names = r2.json().get(\"results\", [])\n",
    "    return [n[\"vernacularName\"].lower() for n in names if n.get(\"language\") == \"eng\"]\n",
    "\n",
    "# Example:\n",
    "print(get_common_names_gbif(\"Circium vulgare\")) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "67faa7dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lavender\n"
     ]
    }
   ],
   "source": [
    "# import growth database \n",
    "import pandas as pd\n",
    "growth_df = pd.read_csv(\"../data/growth_csv/growth.csv\")\n",
    "\n",
    "from rapidfuzz import process\n",
    "\n",
    "# identify scientific name with the common name in the growth database\n",
    "def find_common_name(scientific_name: str) -> str:\n",
    "    \"\"\"Find the common name for a scientific name in the growth database.\"\"\"\n",
    "    common_names = get_common_names_gbif(scientific_name)\n",
    "    for name in common_names:\n",
    "        \n",
    "        # check if it matches even partially with the common name in the growth database using fuzzy matching\n",
    "        match = process.extractOne(name, growth_df[\"Plant Name\"], score_cutoff=80)\n",
    "        if match:\n",
    "            return match[0]  # return the matched common name from the growth database\n",
    "        else:\n",
    "            for word in name.split():\n",
    "                print(f\"  Checking if '{word}' is in growth database common names...\")\n",
    "                match = process.extractOne(word, growth_df[\"Plant Name\"], score_cutoff=80)\n",
    "                if match:\n",
    "                    print(f\"    Found a match for '{word}': '{match[0]}' with score {match[1]}\")\n",
    "                    return match[0]  # return the matched common name from the growth database\n",
    "        \n",
    "    return None\n",
    "\n",
    "print(find_common_name(\"Circium vulgare\"))  # should return \"Spear Thistle\"\n",
    "\n",
    "def get_growth_info(scientific_name: str) -> dict:\n",
    "    common_name = find_common_name(scientific_name)\n",
    "    if not common_name:\n",
    "        return {}\n",
    "    return growth_df[growth_df[\"Plant Name\"] == common_name].iloc[0].to_dict()\n",
    "\n",
    "# print(get_growth_info(\"Lavandula stoechas\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e41ad2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from geo import city_to_coordinates"
   ]
  }
 ],
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