diff --git a/examples/osrmareas.ipynb b/examples/osrmareas.ipynb
new file mode 100644
index 0000000..2eda845
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@@ -0,0 +1,591 @@
+{
+  "cells": [
+    {
+      "cell_type": "raw",
+      "metadata": {},
+      "source": [
+        "---\n",
+        "title: osrm areas\n",
+        "format: gfm\n",
+        "---"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# OSRM areas\n",
+        "\n",
+        "## Download file\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Convert the country names to lowercase and replace spaces with dashes (-).\n",
+            "source: https://download.geofabrik.de/\n"
+          ]
+        }
+      ],
+      "source": [
+        "from osrmareas.downloader import GetPBF\n",
+        "download = GetPBF()"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "Canada, Alberta"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<osrmareas.downloader.GetPBF at 0x17f482505e0>"
+            ]
+          },
+          "execution_count": 7,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "download.sub_region(['alberta']).get(save_dir='sub_region_pbf')\n",
+        "# download.sub_region(['alberta'], country=[\"canada\"], continent=[\"north-america\"])"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## OSRM Connection"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [],
+      "source": [
+        "from osrmareas.osrm import Server\n",
+        "cnd_alb = Server(\"alberta-latest.osm\", \"sub_region_pbf\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Please run the following function only once for each .pbf file. (It takes some time to execute, and consume all the CPU)\n",
+            "Found sub_region_pbf\\alberta-latest.osrm file\n",
+            "Done, generate a osrm file\n",
+            "Please run the following function only once for each .pbf file. (It takes some time to execute, and consume all the CPU)\n",
+            "Done, I have generated the local OSRM server with `{server}.run_server()`.\n"
+          ]
+        },
+        {
+          "data": {
+            "text/plain": [
+              "<osrmareas.osrm.Server at 0x17f4824a2e0>"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "cnd_alb.gen_osrm_1()\n",
+        "cnd_alb.prepare_server_2()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "The server is running in the background, you can start making queries.\n"
+          ]
+        },
+        {
+          "data": {
+            "text/plain": [
+              "<osrmareas.osrm.Server at 0x17f4824a2e0>"
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "cnd_alb.run_server()"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## OSRM Routes"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "c:\\Users\\Jhon\\AppData\\Local\\Programs\\Python\\Python38\\lib\\site-packages\\geopandas\\_compat.py:124: UserWarning: The Shapely GEOS version (3.11.1-CAPI-1.17.1) is incompatible with the GEOS version PyGEOS was compiled with (3.10.4-CAPI-1.16.2). Conversions between both will be slow.\n",
+            "  warnings.warn(\n"
+          ]
+        },
+        {
+          "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>geometry</th>\n",
+              "      <th>dist_driving_km</th>\n",
+              "      <th>dest_lon</th>\n",
+              "      <th>dest_lat</th>\n",
+              "      <th>origin_lon</th>\n",
+              "      <th>origin_lat</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.26895 53...</td>\n",
+              "      <td>1.2714</td>\n",
+              "      <td>53.548449</td>\n",
+              "      <td>-113.258648</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                            geometry  dist_driving_km  \\\n",
+              "0  LINESTRING (-113.26850 53.55087, -113.26895 53...           1.2714   \n",
+              "\n",
+              "    dest_lon    dest_lat  origin_lon  origin_lat  \n",
+              "0  53.548449 -113.258648   53.550905 -113.268436  "
+            ]
+          },
+          "execution_count": 11,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "from osrmareas import areas\n",
+        "from_ = [53.550905, -113.268436]\n",
+        "to_ = [53.548449, -113.258648]\n",
+        "rt = areas.get_osrm_route(from_, to_)\n",
+        "rt"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<Axes: >"
+            ]
+          },
+          "execution_count": 12,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "rt.plot()"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "the [Google Maps route](https://www.google.com/maps/dir/53.550905,+-113.268436/53.548449,+-113.258648/@53.5489972,-113.2648387,17z/data=!4m10!4m9!1m3!2m2!1d-113.268436!2d53.550905!1m3!2m2!1d-113.258648!2d53.548449!3e0?entry=ttu)\n",
+        "\n",
+        "\n",
+        "## OSRM Areas"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "100%|██████████| 100/100 [00:01<00:00, 97.17it/s]\n"
+          ]
+        },
+        {
+          "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>geometry</th>\n",
+              "      <th>dist_driving_km</th>\n",
+              "      <th>dest_lon</th>\n",
+              "      <th>dest_lat</th>\n",
+              "      <th>origin_lon</th>\n",
+              "      <th>origin_lat</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.26895 53...</td>\n",
+              "      <td>5.0417</td>\n",
+              "      <td>53.526882</td>\n",
+              "      <td>-113.308860</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.26895 53...</td>\n",
+              "      <td>5.0352</td>\n",
+              "      <td>53.532221</td>\n",
+              "      <td>-113.308860</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.26895 53...</td>\n",
+              "      <td>4.5280</td>\n",
+              "      <td>53.537560</td>\n",
+              "      <td>-113.308860</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.26895 53...</td>\n",
+              "      <td>3.9101</td>\n",
+              "      <td>53.542899</td>\n",
+              "      <td>-113.308860</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.27509 53...</td>\n",
+              "      <td>4.1813</td>\n",
+              "      <td>53.548236</td>\n",
+              "      <td>-113.308860</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.26910 53...</td>\n",
+              "      <td>5.4344</td>\n",
+              "      <td>53.553573</td>\n",
+              "      <td>-113.228012</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.27509 53...</td>\n",
+              "      <td>6.7640</td>\n",
+              "      <td>53.558910</td>\n",
+              "      <td>-113.228012</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.27509 53...</td>\n",
+              "      <td>6.1856</td>\n",
+              "      <td>53.564245</td>\n",
+              "      <td>-113.228012</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.27509 53...</td>\n",
+              "      <td>6.0089</td>\n",
+              "      <td>53.569580</td>\n",
+              "      <td>-113.228012</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>LINESTRING (-113.26850 53.55087, -113.27509 53...</td>\n",
+              "      <td>6.0849</td>\n",
+              "      <td>53.574915</td>\n",
+              "      <td>-113.228012</td>\n",
+              "      <td>53.550905</td>\n",
+              "      <td>-113.268436</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>100 rows × 6 columns</p>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "                                             geometry  dist_driving_km  \\\n",
+              "0   LINESTRING (-113.26850 53.55087, -113.26895 53...           5.0417   \n",
+              "0   LINESTRING (-113.26850 53.55087, -113.26895 53...           5.0352   \n",
+              "0   LINESTRING (-113.26850 53.55087, -113.26895 53...           4.5280   \n",
+              "0   LINESTRING (-113.26850 53.55087, -113.26895 53...           3.9101   \n",
+              "0   LINESTRING (-113.26850 53.55087, -113.27509 53...           4.1813   \n",
+              "..                                                ...              ...   \n",
+              "0   LINESTRING (-113.26850 53.55087, -113.26910 53...           5.4344   \n",
+              "0   LINESTRING (-113.26850 53.55087, -113.27509 53...           6.7640   \n",
+              "0   LINESTRING (-113.26850 53.55087, -113.27509 53...           6.1856   \n",
+              "0   LINESTRING (-113.26850 53.55087, -113.27509 53...           6.0089   \n",
+              "0   LINESTRING (-113.26850 53.55087, -113.27509 53...           6.0849   \n",
+              "\n",
+              "     dest_lon    dest_lat  origin_lon  origin_lat  \n",
+              "0   53.526882 -113.308860   53.550905 -113.268436  \n",
+              "0   53.532221 -113.308860   53.550905 -113.268436  \n",
+              "0   53.537560 -113.308860   53.550905 -113.268436  \n",
+              "0   53.542899 -113.308860   53.550905 -113.268436  \n",
+              "0   53.548236 -113.308860   53.550905 -113.268436  \n",
+              "..        ...         ...         ...         ...  \n",
+              "0   53.553573 -113.228012   53.550905 -113.268436  \n",
+              "0   53.558910 -113.228012   53.550905 -113.268436  \n",
+              "0   53.564245 -113.228012   53.550905 -113.268436  \n",
+              "0   53.569580 -113.228012   53.550905 -113.268436  \n",
+              "0   53.574915 -113.228012   53.550905 -113.268436  \n",
+              "\n",
+              "[100 rows x 6 columns]"
+            ]
+          },
+          "execution_count": 13,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "all_rt=areas.get_routes(from_, 5)\n",
+        "all_rt"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<Axes: >"
+            ]
+          },
+          "execution_count": 14,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "all_rt.plot()"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Ameba Shapefile"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [],
+      "source": [
+        "ameba = areas.get_ameba(all_rt, max_km = 5, alpha = 80)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {
+        "vscode": {
+          "languageId": "python"
+        }
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "<Axes: >"
+            ]
+          },
+          "execution_count": 16,
+          "metadata": {},
+          "output_type": "execute_result"
+        },
+        {
+          "data": {
+            "image/png": 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",
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "ameba.plot()"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 4
+}
diff --git a/readme.md b/readme.md
index 9abee9f..1d1d504 100644
--- a/readme.md
+++ b/readme.md
@@ -1,6 +1,8 @@
-# Pre requirements
+# OSRM - AREAS
 
-## Windows
+## Pre requirements
+
+### Windows
 
 - Please download the [release archive](https://github.com/christophrust/osrmtime/releases/download/v1.3.3/osrmtime_release1.3.3.zip) and unpack it at a location of your choice.
   - Recommended:
@@ -65,49 +67,111 @@
     ![](figs/01-path.png)
     ![](figs/02-path.png)
 
-# Work with `osrm` localy:
-
-- Download a `pbf` file: [Link](https://download.geofabrik.de/)
-- Move the file to your working environment.
-  - Recomend -> Make a data directory `osrmdata`
-- Open the terminal and change the directory to your working environment.
-
-Done!
+## Features
 
-# Python library
+- Allows downloading PBF files from `geofabrik.de`.
+- Prepares all necessary files for route generation.
+- Initializes the OSRM server in the background.
+- Generates a route between 2 coordinate points.
+- Generates all routes from a coordinate within a radius.
+- Creates a shapefile with the endpoint coordinates of the destinations.
 
 ## Installation
 
-github
+From Github
 
 ```
 pip install git+https://github.com/alexanderquispe/osrm_python
 ```
 
+Specific branch
+
+```
+pip install git+https://github.com/alexanderquispe/osrm_python@{branch}
+```
+
 ## Usage
 
-Chile Example, [dbf]()
+### Download a file
 
 ```py
-from osrmareas.osrm import  Server
-from osrmareas import  areas
-all = areas.get_routes([-20.2015383, -70.1575468], radius_km=20)
+from osrmareas.downloader import GetPBF
+download = GetPBF()
 ```
 
-Connection
+Methods, `GetPBF().continent()`, `GetPBF().country()` and `GetPBF().su_region()`, the methods
+receive an array of continents, countries, and subregions,
+which can be downloaded to a custom folder using the `.get('save\in\this\path')`
+method. The path can be relative or absolute.
+If not specified, it will create a `data_pbf` folder by default in the current execution folder.
+You can force the download with the `get(force_download=True)` parameter.
+
+```py
+download.country(['peru', 'pakistan']).get(save_dir='country_pbf')
+download.sub_region(['alberta']).get(save_dir='country_pbf')
+```
+
+The database can be called as follows:
+
+```py
+import osrmareas.downloader as dwnl
+dwnl.cnt # continent
+dnwl.cntry # continent, countries
+dnwl.region # continent, countries, regions
+```
+
+### OSRM Connection
+
+We define the file name and the directory path where the .pbf file is located.
 
 ```python
-pbf_file = 'chile-latest.osm'
-pbf_file_path = 'D:\Workflow\work\osrm-backend\data'
-client = Server(pbf_file, pbf_file_path)
-client.prepare_server()
-client.run_server()
+pbf_file = 'alberta-latest.osm' #{country, subregion}-latest.osm
+pbf_file_path = 'path/to/dir/with/pbf/file'
 ```
 
-Areas
+- We use `Server` to generate routes for the execution files.
 
 ```python
-all = areas.get_routes([-20.2015383, -70.1575468], radius_km=10)
-all.plot()
-areas.get_ameba(all, 5, alpha = 80).plot()
+from osrmareas.osrm import Server
+cnd_alb = Server(pbf_file, pbf_file_path)
+```
+
+- We generate the necessary files with the following command lines.
+  - If these files already exist, it will prompt for confirmation to execute them again.
+  - These processes may consume 100% of the CPU.
+
+```python
+cnd_alb.gen_osrm_1()
+cnd_alb.prepare_server_2()
+```
+
+- And we initialize the server in the background.
+
+```python
+cnd_alb.run_server()
+```
+
+### OSRM ROUTES
+
+We can make route queries using `areas.get_osrm_routes(from, to)`.
+
+```py
+from osrmareas import areas
+from_ = [53.550905, -113.268436]
+to_ = [53.548449, -113.258648]
+rt = areas.get_osrm_route(from_, to_)
+rt.plot()
+```
+
+We can also obtain all routes within a default radius (in kilometers).
+
+```python
+all_rt=areas.get_routes(from_, 5)
+all_rt
+```
+
+Finally, we can see a difference between the radius we defined in the area radius parameter.
+
+```py
+ameba = areas.get_ameba(all_rt, max_km = 5, alpha = 80, km_col='dist_driving_km')
 ```
diff --git a/requirements.txt b/requirements.txt
index 75b3756..9ed88f4 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -3,4 +3,5 @@ pandas
 geopandas
 alphashape
 shapely
-tqdm
\ No newline at end of file
+tqdm
+twine
\ No newline at end of file
diff --git a/test/osrm_route.ipynb b/test/osrm_route.ipynb
deleted file mode 100644
index a08520d..0000000
--- a/test/osrm_route.ipynb
+++ /dev/null
@@ -1,499 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\Users\\Jhon\\AppData\\Local\\Programs\\Python\\Python38\\lib\\site-packages\\geopandas\\_compat.py:124: UserWarning: The Shapely GEOS version (3.11.1-CAPI-1.17.1) is incompatible with the GEOS version PyGEOS was compiled with (3.10.4-CAPI-1.16.2). Conversions between both will be slow.\n",
-      "  warnings.warn(\n",
-      "C:\\Users\\Jhon\\AppData\\Local\\Temp\\ipykernel_14052\\1076762380.py:2: DeprecationWarning: Shapely 2.0 is installed, but because PyGEOS is also installed, GeoPandas still uses PyGEOS by default. However, starting with version 0.14, the default will switch to Shapely. To force to use Shapely 2.0 now, you can either uninstall PyGEOS or set the environment variable USE_PYGEOS=0. You can do this before starting the Python process, or in your code before importing geopandas:\n",
-      "\n",
-      "import os\n",
-      "os.environ['USE_PYGEOS'] = '0'\n",
-      "import geopandas\n",
-      "\n",
-      "In the next release, GeoPandas will switch to using Shapely by default, even if PyGEOS is installed. If you only have PyGEOS installed to get speed-ups, this switch should be smooth. However, if you are using PyGEOS directly (calling PyGEOS functions on geometries from GeoPandas), this will then stop working and you are encouraged to migrate from PyGEOS to Shapely 2.0 (https://shapely.readthedocs.io/en/latest/migration_pygeos.html).\n",
-      "  import geopandas as gpd\n"
-     ]
-    }
-   ],
-   "source": [
-    "import requests\n",
-    "import geopandas as gpd\n",
-    "from shapely.geometry import LineString\n",
-    "# chile\n",
-    "\n",
-    "pa = [-33.437415, -70.651278] #plaza de armas\n",
-    "pm = [-33.442821, -70.654212] #palacio de la moneda\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<list_reverseiterator at 0x25459341d30>"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "reversed(pa)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'http://127.0.0.1:5000/route/v1/driving/-70.651278,-33.437415;-70.654212,-33.442821?steps=true&geometries=geojson&annotations=duration&alternatives=false'"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "url = 'http://127.0.0.1:5000/route/v1/driving/'\n",
-    "url += f'{pa[1]},{pa[0]};{pm[1]},{pm[0]}?steps=true&geometries=geojson&annotations=duration&alternatives=false'\n",
-    "url"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "r = requests.get(url)\n",
-    "rjson = r.json()\n",
-    "crs_lat='EPSG:4326'\n",
-    "crs_moll='EPSG:3857'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'distance': 966.3,\n",
-       " 'duration': 82.5,\n",
-       " 'weight': 82.5,\n",
-       " 'weight_name': 'routability',\n",
-       " 'geometry': {'type': 'LineString',\n",
-       "  'coordinates': [[-70.651289, -33.437346],\n",
-       "   [-70.655525, -33.437813],\n",
-       "   [-70.6552, -33.440059],\n",
-       "   [-70.654618, -33.442303],\n",
-       "   [-70.654515, -33.44286]]},\n",
-       " 'legs': [{'distance': 966.3,\n",
-       "   'duration': 82.5,\n",
-       "   'weight': 82.5,\n",
-       "   'summary': 'Catedral, Teatinos',\n",
-       "   'steps': [{'mode': 'driving',\n",
-       "     'distance': 396.6,\n",
-       "     'duration': 37.2,\n",
-       "     'intersections': [{'location': [-70.651289, -33.437346],\n",
-       "       'bearings': [262],\n",
-       "       'entry': [True],\n",
-       "       'out': 0},\n",
-       "      {'location': [-70.652651, -33.437503],\n",
-       "       'in': 0,\n",
-       "       'bearings': [75, 180, 255],\n",
-       "       'entry': [False, False, True],\n",
-       "       'out': 2},\n",
-       "      {'location': [-70.654023, -33.437657],\n",
-       "       'in': 1,\n",
-       "       'bearings': [0, 75, 180, 270],\n",
-       "       'entry': [True, False, False, True],\n",
-       "       'out': 3},\n",
-       "      {'location': [-70.654779, -33.437736],\n",
-       "       'in': 0,\n",
-       "       'bearings': [90, 165, 270],\n",
-       "       'entry': [False, True, True],\n",
-       "       'out': 2}],\n",
-       "     'geometry': {'type': 'LineString',\n",
-       "      'coordinates': [[-70.651289, -33.437346],\n",
-       "       [-70.651341, -33.437352],\n",
-       "       [-70.652342, -33.437469],\n",
-       "       [-70.652651, -33.437503],\n",
-       "       [-70.653119, -33.437556],\n",
-       "       [-70.653431, -33.437591],\n",
-       "       [-70.65353, -33.437602],\n",
-       "       [-70.654023, -33.437657],\n",
-       "       [-70.654779, -33.437736],\n",
-       "       [-70.655525, -33.437813]]},\n",
-       "     'weight': 37.2,\n",
-       "     'driving_side': 'right',\n",
-       "     'maneuver': {'type': 'depart',\n",
-       "      'modifier': 'left',\n",
-       "      'location': [-70.651289, -33.437346],\n",
-       "      'bearing_before': 0,\n",
-       "      'bearing_after': 262},\n",
-       "     'name': 'Catedral'},\n",
-       "    {'mode': 'driving',\n",
-       "     'distance': 569.7,\n",
-       "     'duration': 45.3,\n",
-       "     'intersections': [{'location': [-70.655525, -33.437813],\n",
-       "       'in': 1,\n",
-       "       'bearings': [0, 90, 180, 270],\n",
-       "       'entry': [False, False, True, True],\n",
-       "       'out': 2},\n",
-       "      {'location': [-70.655376, -33.438908],\n",
-       "       'in': 0,\n",
-       "       'bearings': [0, 90, 180, 270],\n",
-       "       'entry': [False, True, True, False],\n",
-       "       'out': 2},\n",
-       "      {'location': [-70.6552, -33.440059],\n",
-       "       'in': 0,\n",
-       "       'bearings': [0, 165, 270],\n",
-       "       'entry': [False, True, True],\n",
-       "       'out': 1},\n",
-       "      {'location': [-70.654916, -33.441171],\n",
-       "       'in': 3,\n",
-       "       'bearings': [90, 165, 270, 345],\n",
-       "       'entry': [True, True, False, False],\n",
-       "       'out': 1},\n",
-       "      {'location': [-70.654618, -33.442303],\n",
-       "       'in': 3,\n",
-       "       'bearings': [90, 165, 270, 345],\n",
-       "       'entry': [False, True, True, False],\n",
-       "       'out': 1}],\n",
-       "     'geometry': {'type': 'LineString',\n",
-       "      'coordinates': [[-70.655525, -33.437813],\n",
-       "       [-70.655376, -33.438908],\n",
-       "       [-70.655293, -33.43945],\n",
-       "       [-70.655251, -33.439727],\n",
-       "       [-70.655217, -33.439951],\n",
-       "       [-70.6552, -33.440059],\n",
-       "       [-70.655189, -33.4401],\n",
-       "       [-70.655176, -33.440154],\n",
-       "       [-70.654916, -33.441171],\n",
-       "       [-70.654895, -33.441267],\n",
-       "       [-70.654784, -33.441694],\n",
-       "       [-70.65464, -33.442214],\n",
-       "       [-70.654628, -33.442265],\n",
-       "       [-70.654618, -33.442303],\n",
-       "       [-70.654515, -33.44286]]},\n",
-       "     'weight': 45.3,\n",
-       "     'driving_side': 'right',\n",
-       "     'maneuver': {'type': 'turn',\n",
-       "      'modifier': 'left',\n",
-       "      'location': [-70.655525, -33.437813],\n",
-       "      'bearing_before': 261,\n",
-       "      'bearing_after': 172},\n",
-       "     'name': 'Teatinos'},\n",
-       "    {'mode': 'driving',\n",
-       "     'distance': 0,\n",
-       "     'duration': 0,\n",
-       "     'intersections': [{'location': [-70.654515, -33.44286],\n",
-       "       'in': 0,\n",
-       "       'bearings': [351],\n",
-       "       'entry': [True]}],\n",
-       "     'geometry': {'type': 'LineString',\n",
-       "      'coordinates': [[-70.654515, -33.44286], [-70.654515, -33.44286]]},\n",
-       "     'weight': 0,\n",
-       "     'driving_side': 'right',\n",
-       "     'maneuver': {'type': 'arrive',\n",
-       "      'modifier': 'left',\n",
-       "      'location': [-70.654515, -33.44286],\n",
-       "      'bearing_before': 171,\n",
-       "      'bearing_after': 0},\n",
-       "     'name': 'Teatinos'}],\n",
-       "   'annotation': {'duration': [0.3,\n",
-       "     6.1,\n",
-       "     1.9,\n",
-       "     2.9,\n",
-       "     1.9,\n",
-       "     0.6,\n",
-       "     3,\n",
-       "     4.6,\n",
-       "     4.6,\n",
-       "     8,\n",
-       "     4,\n",
-       "     2,\n",
-       "     1.6,\n",
-       "     0.8,\n",
-       "     0.3,\n",
-       "     0.4,\n",
-       "     7.6,\n",
-       "     0.7,\n",
-       "     3.2,\n",
-       "     3.9,\n",
-       "     0.4,\n",
-       "     0.3,\n",
-       "     4.1]}}]}"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "rjson['routes'][0]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: >"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "route = rjson['routes'][0]['geometry']['coordinates']\n",
-    "# route.append([-66.744416, -54.975603])dd\n",
-    "line = gpd.GeoDataFrame(geometry=[LineString(route)]).set_crs(crs_lat)\n",
-    "line.plot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from shapely.geometry import Point, LineString\n",
-    "from shapely import  Polygon\n",
-    "import numpy as np\n",
-    "#params\n",
-    "\n",
-    "radius_km = 10\n",
-    "\n",
-    "n_grid = radius_km * 2\n",
-    "radius_km = radius_km * 1000\n",
-    "initial_center = Point(pa)\n",
-    "crs_moll='EPSG:3857'\n",
-    "crs_lat='EPSG:4326'\n",
-    "\n",
-    "point_center = gpd.GeoSeries(initial_center, crs=crs_lat)\\\n",
-    "\t.to_crs(crs_moll)\\\n",
-    "\t\t.buffer(radius_km, cap_style=3)\n",
-    "minX, minY, maxX, maxY = point_center.total_bounds\n",
-    "size_grid_km = (maxY - minY) / n_grid\n",
-    "cols_grid=list(np.arange(minX, maxX, size_grid_km))\n",
-    "rows_grid=list(np.arange(minY, maxY, size_grid_km))\n",
-    "\n",
-    "\n",
-    "def make_grid(x, y, size_grid):\n",
-    "\tcoords_pol = [\n",
-    "\t\t(x, y), (x + size_grid, y), \n",
-    "\t\t(x + size_grid, y + size_grid), \n",
-    "\t\t(x, y + size_grid)]\n",
-    "\tcenter = size_grid / 2\n",
-    "\tcoords_center = [x + center, y + center] \n",
-    "\tcoords_center = Point(coords_center)\n",
-    "\tpc = gpd.GeoSeries(coords_center, crs=crs_moll)\\\n",
-    "\t\t.to_crs(crs_lat)\n",
-    "\tlat, lon = pc.x, pc.y\n",
-    "\tdestiny = list(np.array([lat, lon]).flatten())\n",
-    "\tpc_list = pc.tolist()\n",
-    "\tpol = Polygon(coords_pol)\n",
-    "\tgdf = gpd.GeoDataFrame({'geometry': pol}, index=[0])\\\n",
-    "\t\t.set_crs(crs_moll)\\\n",
-    "\t\t.to_crs(crs_lat)\n",
-    "\treturn destiny#pc#gdf, pc_list, \t\n",
-    "final = make_grid(cols_grid[0], rows_grid[1], size_grid_km)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# pa, final\n",
-    "begin_ = pa.copy()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def get_route(from_, to_, how='driving'):\n",
-    "\t\n",
-    "\turl = f'http://127.0.0.1:5000/route/v1/{how}/'\n",
-    "\turl += f'{from_[1]},{from_[0]};{to_[1]},{to_[0]}?steps=true&geometries=geojson&annotations=duration&alternatives=false'\n",
-    "\n",
-    "\tr = requests.get(url)\n",
-    "\trjson = r.json()\n",
-    "\tcrs_lat='EPSG:4326'\n",
-    "\tcrs_moll='EPSG:3857'\n",
-    "\tinfo = rjson['routes'][0]\n",
-    "\tdist = info['distance']\n",
-    "\troute = info['geometry']['coordinates']\n",
-    "\t# route.append([-66.744416, -54.975603])dd\n",
-    "\tline = gpd.GeoDataFrame(geometry=[LineString(route)]).set_crs(crs_lat)\n",
-    "\tline = line.assign(\n",
-    "\t\tdist_km=dist/1000, x = to_[0], y = to_[1],\n",
-    "\t\tx_begin = from_[0], y_begin = from_[1]\n",
-    "\t)\n",
-    "\treturn line"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "final_routes = []\n",
-    "for x in cols_grid:\n",
-    "\tfor y in rows_grid:\n",
-    "\t\tfinal = make_grid(x, y, size_grid_km)\n",
-    "\t\tfinal_routes.append(final)\n",
-    "# final_routes\n",
-    "# get_route(pa, final)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 52,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "all_routes_df = gpd.GeoDataFrame()\n",
-    "for final in final_routes:\n",
-    "\tall_routes_df = \\\n",
-    "\t\tpd.concat([all_routes_df, get_route(begin_, final)])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 55,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: >"
-      ]
-     },
-     "execution_count": 55,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 75,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "border = []\n",
-    "import alphashape\n",
-    "a = all_routes_df.query('dist_km < 10')\n",
-    "for _, row in a.iterrows():\n",
-    "\tborder.append((row['x'], row['y']))\n",
-    "bd = alphashape.alphashape(border, 60)\n",
-    "gdf = gpd.GeoDataFrame(geometry=[bd]).\\\n",
-    "\tset_crs(crs_lat, allow_override=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 76,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: >"
-      ]
-     },
-     "execution_count": 76,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "gdf.plot()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/test/test.ipynb b/test/test.ipynb
deleted file mode 100644
index e867ac0..0000000
--- a/test/test.ipynb
+++ /dev/null
@@ -1,350 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from osrmareas.osrm import Server"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "pbf_file = 'chile-latest.osm'\n",
-    "pbf_file_path = 'D:\\Workflow\\work\\osrm-backend\\data'\n",
-    "tmp_file = ''\n",
-    "a=Server(pbf_file, pbf_file_path)\n",
-    "# a.gen_osrm_file"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Done'"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a.prepare_server()\n",
-    "# a.run_server()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<osrmareas.osrm.Server at 0x22838e15490>"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a.run_server()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'C:\\\\Users\\\\Jhon\\\\AppData\\\\Local\\\\Temp\\\\tmpt0lejroj.bat'"
-      ]
-     },
-     "execution_count": 19,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import tempfile\n",
-    "file = tempfile.NamedTemporaryFile(delete=False, suffix='.bat')\n",
-    "file_name = file.name\n",
-    "# os.path\n",
-    "with open(file_name, 'w') as bt:\n",
-    "\tbt.write(\"algo\")\n",
-    "file_name"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'D:\\\\Workflow\\\\work\\\\osrm-backend\\\\data\\\\chile-latest.osrm'"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pbf_file = 'chile-latest.osm'\n",
-    "pbf_file_path = 'D:\\Workflow\\work\\osrm-backend\\data'\n",
-    "\n",
-    "osrm_path = 'C:\\osrm'\n",
-    "\n",
-    "pbf = f'{pbf_file_path}\\{pbf_file}.pbf'\n",
-    "osm = pbf_file.replace(\".osm\", \"\")\n",
-    "osrm = f'{pbf_file_path}\\{osm}.osrm'\n",
-    "method_lua = 'car'\n",
-    "method = f'{osrm_path}\\{method_lua}.lua'\n",
-    "\n",
-    "osrm_extract = f'{osrm_path}\\osrm-extract.exe'\n",
-    "osrm_contract = f'{osrm_path}\\osrm-contract.exe'\n",
-    "osrm_routed = f'{osrm_path}\\osrm-routed.exe'\n",
-    "\n",
-    "gen_osrm_file = f'{osrm_extract} -p {method} {pbf}'\n",
-    "gen_routes = f'{osrm_extract} {osrm}'\n",
-    "gen_backend = f'{osrm_routed} {osrm}'\n",
-    "osrm"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Substring found in the text.\n"
-     ]
-    }
-   ],
-   "source": [
-    "text = \"yes\"\n",
-    "substring = \"y\"\n",
-    "\n",
-    "if substring in text:\n",
-    "    print(\"Substring found in the text.\")\n",
-    "else:\n",
-    "    print(\"Substring not found in the text.\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "texto = f'''\n",
-    "{gen_osrm_file}\n",
-    "{gen_routes}\n",
-    "{gen_backend}\n",
-    "'''\n",
-    "\n",
-    "\n",
-    "file = 'echo.bat'\n",
-    "with open(file, 'w') as a:\n",
-    "\ta.write(texto)\n",
-    "\n",
-    "# if os.path.exists(osrm):\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'no'"
-      ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "input(f\"Run osrm-routed.exe \")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\Users\\Jhon\\AppData\\Local\\Programs\\Python\\Python38\\lib\\site-packages\\geopandas\\_compat.py:124: UserWarning: The Shapely GEOS version (3.11.1-CAPI-1.17.1) is incompatible with the GEOS version PyGEOS was compiled with (3.10.4-CAPI-1.16.2). Conversions between both will be slow.\n",
-      "  warnings.warn(\n"
-     ]
-    }
-   ],
-   "source": [
-    "from osrmareas import areas\n",
-    "pa = [-33.437415, -70.651278] #plaza de armas\n",
-    "pm = [-33.442821, -70.654212] #palacio de la moneda"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "all = areas.get_routes([-20.2015383, -70.1575468], radius_km=20)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: >"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "all.plot()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot  as plt"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x205bd12c760>"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "all = all.query('dist_km < 20')\n",
-    "x = all.x\n",
-    "y = all.y\n",
-    "plt.scatter(x, y)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: >"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# a=all.query('dist_km < 15')\n",
-    "# a.plot()\n",
-    "areas.get_ameba(all, 100, 20).plot()"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.10"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}