{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5726d887",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Temperature: 22.7 °C\n",
      "Humidity: 54 %\n",
      "Wind speed: 3.6 km/h\n",
      "{'time': '2026-06-08T21:45', 'interval': 900, 'temperature_2m': 22.7, 'relative_humidity_2m': 54, 'wind_speed_10m': 3.6}\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "\n",
    "# Coordinates for Marseille\n",
    "lat = 43.2965\n",
    "lon = 5.3698\n",
    "\n",
    "url = (\n",
    "    \"https://api.open-meteo.com/v1/forecast\"\n",
    "    f\"?latitude={lat}&longitude={lon}\"\n",
    "    \"&current=temperature_2m,relative_humidity_2m,wind_speed_10m\"\n",
    ")\n",
    "\n",
    "data = requests.get(url).json()\n",
    "\n",
    "current = data[\"current\"]\n",
    "\n",
    "print(\"Temperature:\", current[\"temperature_2m\"], \"°C\")\n",
    "print(\"Humidity:\", current[\"relative_humidity_2m\"], \"%\")\n",
    "print(\"Wind speed:\", current[\"wind_speed_10m\"], \"km/h\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "eda4c3a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chance of rain tomorrow: 35%\n",
      "☀️ Rain unlikely tomorrow\n"
     ]
    }
   ],
   "source": [
    "# check if it rains tommorrow\n",
    "from datetime import datetime, timedelta\n",
    "\n",
    "LATITUDE = 43.2965\n",
    "LONGITUDE = 5.3698\n",
    "\n",
    "url = (\n",
    "    \"https://api.open-meteo.com/v1/forecast\"\n",
    "    f\"?latitude={LATITUDE}\"\n",
    "    f\"&longitude={LONGITUDE}\"\n",
    "    \"&daily=precipitation_probability_max\"\n",
    "    \"&timezone=auto\"\n",
    ")\n",
    "\n",
    "data = requests.get(url, timeout=10).json()\n",
    "\n",
    "tomorrow = (datetime.now() + timedelta(days=1)).strftime(\"%Y-%m-%d\")\n",
    "\n",
    "dates = data[\"daily\"][\"time\"]\n",
    "probs = data[\"daily\"][\"precipitation_probability_max\"]\n",
    "\n",
    "idx = dates.index(tomorrow)\n",
    "prob = probs[idx]\n",
    "\n",
    "print(f\"Chance of rain tomorrow: {prob}%\")\n",
    "\n",
    "if prob >= 50:\n",
    "    print(\"🌧️ Likely to rain tomorrow\")\n",
    "else:\n",
    "    print(\"☀️ Rain unlikely tomorrow\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c806be1c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n",
      "True\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "from datetime import date, datetime\n",
    "def did_or_will_rain(\n",
    "    target_date,\n",
    "    latitude,\n",
    "    longitude,\n",
    "    forecast_threshold=50,\n",
    "):\n",
    "    \"\"\"\n",
    "    Returns True if:\n",
    "      - it rained on a past date\n",
    "      - rain is forecast on a future date above the threshold\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    target_date : str | date | datetime\n",
    "        Date to check (\"YYYY-MM-DD\" or date object)\n",
    "    latitude : float\n",
    "    longitude : float\n",
    "    forecast_threshold : int\n",
    "        Minimum rain probability (%) for future dates\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    bool\n",
    "    \"\"\"\n",
    "\n",
    "    # Normalize date\n",
    "    if isinstance(target_date, str):\n",
    "        target_date = datetime.strptime(target_date, \"%Y-%m-%d\").date()\n",
    "    elif isinstance(target_date, datetime):\n",
    "        target_date = target_date.date()\n",
    "\n",
    "    today = date.today()\n",
    "\n",
    "    # Historical date\n",
    "    if target_date < today:\n",
    "        url = (\n",
    "            \"https://archive-api.open-meteo.com/v1/archive\"\n",
    "            f\"?latitude={latitude}\"\n",
    "            f\"&longitude={longitude}\"\n",
    "            f\"&start_date={target_date}\"\n",
    "            f\"&end_date={target_date}\"\n",
    "            \"&daily=precipitation_sum\"\n",
    "            \"&timezone=auto\"\n",
    "        )\n",
    "\n",
    "        data = requests.get(url, timeout=10).json()\n",
    "\n",
    "        rain_mm = data[\"daily\"][\"precipitation_sum\"][0]\n",
    "        return rain_mm > 0\n",
    "\n",
    "    # Today / future date\n",
    "    else:\n",
    "        url = (\n",
    "            \"https://api.open-meteo.com/v1/forecast\"\n",
    "            f\"?latitude={latitude}\"\n",
    "            f\"&longitude={longitude}\"\n",
    "            \"&daily=precipitation_probability_max,precipitation_sum\"\n",
    "            \"&forecast_days=16\"\n",
    "            \"&timezone=auto\"\n",
    "        )\n",
    "\n",
    "        data = requests.get(url, timeout=10).json()\n",
    "\n",
    "        dates = data[\"daily\"][\"time\"]\n",
    "\n",
    "        target_date_str = target_date.isoformat()\n",
    "\n",
    "        if target_date_str not in dates:\n",
    "            raise ValueError(\"Date outside forecast range\")\n",
    "\n",
    "        idx = dates.index(target_date_str)\n",
    "\n",
    "        probability = data[\"daily\"][\"precipitation_probability_max\"][idx]\n",
    "        precipitation = data[\"daily\"][\"precipitation_sum\"][idx]\n",
    "\n",
    "        return (\n",
    "            probability >= forecast_threshold\n",
    "            or precipitation > 0\n",
    "        )\n",
    "    \n",
    "# Marseille\n",
    "LAT = 43.2965\n",
    "LON = 5.3698\n",
    "\n",
    "# Did it rain yesterday?\n",
    "print(did_or_will_rain(\"2026-06-03\", LAT, LON))\n",
    "\n",
    "# Will it rain tomorrow?\n",
    "print(did_or_will_rain(\"2026-06-04\", LAT, LON))\n",
    "\n",
    "# Require at least 70% confidence\n",
    "print(\n",
    "    did_or_will_rain(\n",
    "        \"2026-06-05\",\n",
    "        LAT,\n",
    "        LON,\n",
    "        forecast_threshold=70,\n",
    "    ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "34b8844f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from plant import Plant\n",
    "p = Plant(\"Ficus\")\n",
    "print(p)"
   ]
  }
 ],
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