Recap.ipynb

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   "source": [
    "# Reboot - Data Collection\n",
    "\n",
    "Let's practise calling an API and navigating a JSON response!\n",
    "\n",
    "---\n",
    "\n",
    "## 1. Simple API call\n",
    "\n",
    "There's an API for pretty much everything. Let's start with a super simple one: the [Breaking Bad quotes API](https://github.com/shevabam/breaking-bad-quotes).\n",
    "\n",
    "For your convenience, we've included the simple syntax to do an HTTP request in Python and convert the response to a Python object as boilerplate code.\n",
    "\n",
    "The goal here is to get a single, random Breaking Bad quote and print it out to the terminal. \n",
    "\n",
    "Go the [doc](https://github.com/shevabam/breaking-bad-quotes) to find out which URL you need to use. Make sure to carefully check out the data types you're getting back from the API and extract the string you need."
   ]
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests"
   ]
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  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Jesse Pinkman said Seriously? \"Hello Kitty\"?'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
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   "source": [
    "url = \"https://breaking-bad-quotes.herokuapp.com/v1/quotes\"\n",
    "response = requests.get(url).json()[0]\n",
    "f\"{response['author']} said {response['quote']}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## 2. Looping over API results\n",
    "\n",
    "Often APIs will serve a list of results that we need to loop over and manipulate. For this next example, we will use the [Star Wars API](https://swapi.dev).\n",
    "\n",
    "First, go to the [documentation](https://swapi.dev/documentation) to find out which URL you're going to need to retrieve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_url = \"https://swapi.dev/api/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use `requests` to retrieve the people from the API. Store this in a `response` variable. What's the type of `response`?"
   ]
  },
  {
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   "execution_count": 11,
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       "dict"
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     "execution_count": 11,
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   "source": [
    "url = base_url + \"people\"\n",
    "response = requests.get(url).json()\n",
    "type(response)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "Loop over the **5 first people** and print a sentence for each following this template:\n",
    "\n",
    "- `Luke Skywalker has blue eyes`\n",
    "- `C-3PO has yellow eyes`\n",
    "- etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
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     "text": [
      "Luke Skywalker has blue eyes\n",
      "C-3PO has yellow eyes\n",
      "R2-D2 has red eyes\n",
      "Darth Vader has yellow eyes\n",
      "Leia Organa has brown eyes\n"
     ]
    }
   ],
   "source": [
    "characters = response['results'][:5]\n",
    "for character in characters:\n",
    "    name = character['name']\n",
    "    eye_color = character[\"eye_color\"]\n",
    "    print(f\"{name} has {eye_color} eyes\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## 3. Geocoding\n",
    "\n",
    "A geocoding service is a tool to convert addresses to geo-coordinates and vice versa. We use them every time we fire up our GPS apps and look for a destination.\n",
    "\n",
    "For this exercise, we will use the [Nominatim API](https://nominatim.openstreetmap.org/)\n",
    "\n",
    "First, get familiar with the documentation, [which you will find here](https://nominatim.org/release-docs/latest/api/Overview/). Take a couple of minutes to read through and become familiar with it. In this exercise, we will need to find a set of geo-coordinates for a given address, and find an address from a set of geo-coordinates."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use the API to find the latitude and longitude for this address: `10 Downing St, Westminster, London SW1A 2AA, United Kingdom`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "51.50344025 -0.12770820958562096\n"
     ]
    }
   ],
   "source": [
    "address = \"10 Downing St, Westminster, London SW1A 2AA, United Kingdom\"\n",
    "url = \"https://nominatim.openstreetmap.org/search\"\n",
    "params = {\n",
    "    \"q\": address,\n",
    "    'format': 'json'\n",
    "}\n",
    "response = requests.get(url, params=params).json()[0]\n",
    "print(response['lat'], response['lon'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Try with another address of your choice!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def coordinates(address):\n",
    "    url = \"https://nominatim.openstreetmap.org/search\"\n",
    "    params = {\n",
    "        \"q\": address,\n",
    "        'format': 'json'\n",
    "    }\n",
    "    response = requests.get(url, params=params).json()[0]\n",
    "    lat = response['lat']\n",
    "    lon = response['lon']\n",
    "    return (lat, lon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('51.531662', '-0.0770283')\n"
     ]
    }
   ],
   "source": [
    "print(coordinates(\"138 kingsland road, e2 8dy, london\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "## 4. Reverse Geocoding\n",
    "\n",
    "Find the address belonging to this set of geo-coordinates: `{'lat': 38.8976633, 'lng': -77.036650 }`.\n",
    "Print the sentence `I would like to visit X`, replacing X with the address you found."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'White House, 1600, Pennsylvania Avenue Northwest, Washington, District of Columbia, 20500, United States'"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coordinates = {'lat': 38.8976633, 'lng': -77.036650 }\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def reverse_coordinates(coordinates):\n",
    "    url = \"https://nominatim.openstreetmap.org/reverse\"\n",
    "    params = {\n",
    "        \"lat\": coordinates['lat'],\n",
    "        \"lon\": coordinates['lng'],\n",
    "        'format': 'json'\n",
    "    }\n",
    "    response = requests.get(url, params=params).json()\n",
    "    return response['display_name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Museum of the Home, 136, Kingsland Road, Shoreditch, London Borough of Hackney, London, Greater London, England, E2 8EA, United Kingdom\n"
     ]
    }
   ],
   "source": [
    "print(reverse_coordinates({'lat': 51.531662, 'lng': -0.0770283}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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