{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "# Get started\n",
    "\n",
    "## Overview\n",
    "\n",
    "The `pywdpa` Python package is an interface to the World Database on Protected Areas (WDPA)\n",
    "hosted on the Protected planet website: <https://www.protectedplanet.net>.\n",
    "It allows users to download spatial shapefiles of protected areas (PA) for world countries using the Protected Planet API (<https://api.protectedplanet.net>).\n",
    "\n",
    "This package contains two main functions:\n",
    "\n",
    "- `.get_token()`: check if your WDPA token is correctly stored (see [usage](https://ecology.ghislainv.fr/pywdpa/reference.html#module-pywdpa.get_token));\n",
    "- `.get_wdpa()`: download the shapefile of protected areas for one specific country (see [usage](https://ecology.ghislainv.fr/pywdpa/reference.html#module-pywdpa.get_wdpa)).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Installation\n",
    "\n",
    "You will need several dependencies to run the `pywdpa` Python package (`numpy`, `gdal`, and `requests`). The best way to install the package is to create a Python virtual environment, either through `virtualenv` or `conda`. A virtual environment is a self-contained directory tree that contains a Python installation for a particular version of Python, plus a number of additional packages.\n",
    "\n",
    "### Using `virtualenv`\n",
    "\n",
    "You first need to have the `virtualenv` package installed (see [here](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/)).\n",
    "\n",
    "Then, create a virtual environment and install the `pywdpa` package with the following commands:\n",
    "\n",
    "```shell\n",
    "# In a shell\n",
    "cd ~\n",
    "mkdir venvs # Directory for virtual environments\n",
    "cd venvs\n",
    "virtualenv --python=/usr/bin/python3 venv-pywppa\n",
    "source ~/venvs/venv-far/bin/activate\n",
    "pip install pywdpa # For PyPI version, this will install all other dependencies\n",
    "# pip install https://github.com/ghislainv/pywdpa/archive/master.zip # For GitHub dev version\n",
    "# pip install geopandas descartes folium python-dotenv # Optional additional packages\n",
    "```\n",
    "\n",
    "To deactivate and delete the virtual environment:\n",
    "\n",
    "```shell\n",
    "deactivate\n",
    "rm -R ~/venvs/venv-pywdpa # Just remove the repository\n",
    "```\n",
    "\n",
    "### Using `conda`\n",
    "\n",
    "You first need to have `miniconda3` installed (see [here](https://docs.conda.io/en/latest/miniconda.html)).\n",
    "\n",
    "Then, create a conda environment (details [here](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html)) and install the `pywdpa` package with the following commands:\n",
    "\n",
    "```shell\n",
    "# In a shell\n",
    "conda create --name conda-pywdpa python pip numpy gdal requests --yes\n",
    "conda activate conda-far\n",
    "# conda install geopandas --yes  # Optional additional packages available in conda\n",
    "# conda install -c conda-forge descartes folium python-dotenv --yes  # Optional additional packages available in conda\n",
    "pip install pywdpa # Install PyPI version\n",
    "# pip install https://github.com/ghislainv/pywdpa/archive/master.zip # For GitHub dev version\n",
    "```\n",
    "\n",
    "To deactivate and delete the conda environment:\n",
    "\n",
    "```shell\n",
    "conda deactivate\n",
    "conda env remove --name conda-pywdpa\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Managing the WDPA API token\n",
    "\n",
    "This package uses the Protected Planet API to access data on world protected areas. You must first have obtained a Personal API Token by\n",
    "filling in the form available at <https://api.protectedplanet.net/request>. Then you need to set an\n",
    "environment variable (we recommend using the name `WDPA_KEY`) using either the command `os.environ[\"WDPA_KEY\"]=\"your_token\"` or\n",
    "[python-dotenv](https://github.com/theskumar/python-dotenv).    \n",
    "\n",
    "The validity of your token can be checked with function `.get_token()`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "raw_mimetype": "text/markdown"
   },
   "source": [
    "```python\n",
    "# In Python\n",
    "import os\n",
    "import pywdpa\n",
    "\n",
    "# Set WDPA_KEY\n",
    "# (assuming that your token is \"ca4703ffba6b9a26b2db73f78e56e088\")\n",
    "os.environ[\"WDPA_KEY\"]=\"ca4703ffba6b9a26b2db73f78e56e088\"\n",
    "\n",
    "# Check your token validity\n",
    "pywdpa.get_token()\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If your token is valid, the function will return its value. Otherwise it will print an error message."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Downloading protected areas\n",
    "\n",
    "The function `.get_wdpa()` can be used to download the shapefile of protected areas for the Reunion Island which has the iso code \"REU\". The output file name in the working directory will be \"pa_REU.shp\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pywdpa\n",
    "\n",
    "pywdpa.get_wdpa(\"REU\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The shapefile can be imported in the Python environment, for example using the Python package `geopandas`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>wdpa_id</th>\n",
       "      <th>pa_name</th>\n",
       "      <th>orig_name</th>\n",
       "      <th>ctry_iso3</th>\n",
       "      <th>owner_type</th>\n",
       "      <th>is_marine</th>\n",
       "      <th>type</th>\n",
       "      <th>iucn_cat</th>\n",
       "      <th>status</th>\n",
       "      <th>date</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>62780</td>\n",
       "      <td>Bois De Nèfles-Saint-Paul</td>\n",
       "      <td>Bois De Nèfles-Saint-Paul</td>\n",
       "      <td>REU</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>Forest Integral Biological Reserve</td>\n",
       "      <td>Ia</td>\n",
       "      <td>Designated</td>\n",
       "      <td>01/01/1985</td>\n",
       "      <td>POLYGON ((55.38600 -21.03200, 55.37700 -21.027...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>62786</td>\n",
       "      <td>Hauts De Saint-Philippe</td>\n",
       "      <td>Hauts De Saint-Philippe</td>\n",
       "      <td>REU</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>Forest Integral Biological Reserve</td>\n",
       "      <td>Ia</td>\n",
       "      <td>Designated</td>\n",
       "      <td>01/01/1987</td>\n",
       "      <td>POLYGON ((55.72300 -21.33500, 55.71100 -21.337...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>62787</td>\n",
       "      <td>Les Mares</td>\n",
       "      <td>Les Mares</td>\n",
       "      <td>REU</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>Forest Integral Biological Reserve</td>\n",
       "      <td>Ia</td>\n",
       "      <td>Designated</td>\n",
       "      <td>01/01/1987</td>\n",
       "      <td>POLYGON ((55.72300 -21.18300, 55.73900 -21.179...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>83081</td>\n",
       "      <td>Bois Blanc</td>\n",
       "      <td>Bois Blanc</td>\n",
       "      <td>REU</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>False</td>\n",
       "      <td>Land Acquired By Conservatoire Du Littoral (Na...</td>\n",
       "      <td>IV</td>\n",
       "      <td>Designated</td>\n",
       "      <td>01/01/1980</td>\n",
       "      <td>MULTIPOLYGON (((55.80000 -21.19700, 55.81900 -...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>83112</td>\n",
       "      <td>Grande Anse</td>\n",
       "      <td>Grande Anse</td>\n",
       "      <td>REU</td>\n",
       "      <td>Not Reported</td>\n",
       "      <td>True</td>\n",
       "      <td>Land Acquired By Conservatoire Du Littoral (Na...</td>\n",
       "      <td>IV</td>\n",
       "      <td>Designated</td>\n",
       "      <td>01/01/1982</td>\n",
       "      <td>MULTIPOLYGON (((55.54900 -21.36800, 55.54800 -...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   wdpa_id                    pa_name                  orig_name ctry_iso3  \\\n",
       "0    62780  Bois De Nèfles-Saint-Paul  Bois De Nèfles-Saint-Paul       REU   \n",
       "1    62786    Hauts De Saint-Philippe    Hauts De Saint-Philippe       REU   \n",
       "2    62787                  Les Mares                  Les Mares       REU   \n",
       "3    83081                 Bois Blanc                 Bois Blanc       REU   \n",
       "4    83112                Grande Anse                Grande Anse       REU   \n",
       "\n",
       "     owner_type is_marine                                               type  \\\n",
       "0  Not Reported     False                 Forest Integral Biological Reserve   \n",
       "1  Not Reported     False                 Forest Integral Biological Reserve   \n",
       "2  Not Reported     False                 Forest Integral Biological Reserve   \n",
       "3  Not Reported     False  Land Acquired By Conservatoire Du Littoral (Na...   \n",
       "4  Not Reported      True  Land Acquired By Conservatoire Du Littoral (Na...   \n",
       "\n",
       "  iucn_cat      status        date  \\\n",
       "0       Ia  Designated  01/01/1985   \n",
       "1       Ia  Designated  01/01/1987   \n",
       "2       Ia  Designated  01/01/1987   \n",
       "3       IV  Designated  01/01/1980   \n",
       "4       IV  Designated  01/01/1982   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((55.38600 -21.03200, 55.37700 -21.027...  \n",
       "1  POLYGON ((55.72300 -21.33500, 55.71100 -21.337...  \n",
       "2  POLYGON ((55.72300 -21.18300, 55.73900 -21.179...  \n",
       "3  MULTIPOLYGON (((55.80000 -21.19700, 55.81900 -...  \n",
       "4  MULTIPOLYGON (((55.54900 -21.36800, 55.54800 -...  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import geopandas as gpd\n",
    "\n",
    "pa_REU = gpd.read_file(\"pa_REU.shp\")\n",
    "pa_REU.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Protected areas can be plotted using either the `.plot` function from the geopandas object or using the Python package `folium` which makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f534817dee0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.colors import ListedColormap\n",
    "cm = ListedColormap([\"green\", \"blue\"])\n",
    "pa_REU.plot(column=\"is_marine\", cmap=cm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" 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onload=\"this.contentDocument.open();this.contentDocument.write(    decodeURIComponent(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f5348d49a90>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import folium\n",
    "latitude = -21.1\n",
    "longitude = 55.5\n",
    "fcol = lambda x: {\n",
    "    'fillColor': \"blue\" if x[\"properties\"][\"is_marine\"] == \"True\" else \"green\",\n",
    "    'color': \"blue\" if x[\"properties\"][\"is_marine\"] == \"True\" else \"green\"\n",
    "}\n",
    "m = folium.Map(location = [latitude, longitude],\n",
    "               zoom_start = 10)\n",
    "folium.GeoJson(pa_REU.to_json(), style_function=fcol).add_to(m)\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Command line \n",
    "\n",
    "The function `.get_wdpa()` can be directly executed in a shell using the `pywdpa` command followed by the country iso code as argument. This will download the shapefile of the protected areas for the Reunion Island in the current working directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Executing pywdpa version 0.1.5.\n",
      "For country with isocode: REU.\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "# In a shell\n",
    "pywdpa REU"
   ]
  }
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