This repo purpose is about getting Tesla stores data and prepare data to create a Maproulette challenge. The final purpose is to add this data in OpenStreetMap.

It contains 👨‍💻 recursive scraping and 🌍 geospatial data analysis. All in Nodejs.

Summary:

1. Init
2. Scrap data
3. Format data
4. Analysis data

Init

Install dependencies with:

npm install

Scrap data

Start the data script with:

npm run scrap

The data will be written in stream in the output/tesla_stores.json file.

Here a sample of output data:

{
  "name": "Cannes-Mandelieu",
  "commonName": "Cannes-Mandelieu",
  "address": "Avenue du Marechal de Lattre de Tassigny",
  "extendedAddress": "Tesla Mandelieu",
  "city": "06210 Mandelieu-la-NapouleFrance",
  "phone": "+33423110178",
  "email": "[email protected]",
  "coordinates": {
    "latitude": "43.5495466",
    "longitude": "6.9446249"
  },
  "storeType": "Stores and Galleries",
  "hasRepearCenter": "yes",
  "services": {
    "type-store": "Stores and Galleries",
    "type-service": "Service Center"
  },
  "storeHours": {
    "tuesday": "10:00am - 6:00pm",
    "wednesday": "10:00am - 6:00pm",
    "thursday": "10:00am - 6:00pm",
    "friday": "10:00am - 6:00pm",
    "saturday": "10:00am - 6:00pm",
    "sunday": "closed"
  },
  "serviceHours": {
    "tuesday": "8:30am - 6:30pm",
    "wednesday": "8:30am - 6:30pm",
    "thursday": "8:30am - 6:30pm",
    "friday": "8:30am - 6:30pm",
    "saturday": "closed",
    "sunday": "closed"
  }
},

Known issues

At the moment, output JSON is not well formated because it ends by },] instead of }]. In the same way, if you stop the script during processing, the final ] will not be added.

I know it's not ideal, but hey! the time it takes to solve it with code is much longer than the time it takes to fix it by hand a hundred times.

Format data

Convert data to geojson with:

npm run format

The opening hours will be converted to OSM specification.
The data will be written in the output/tesla_stores.geojson file.

Here a sample of output data:

{
  "type": "Feature",
  "properties": {
    "name": "Cannes-Mandelieu",
    "commonName": "Cannes-Mandelieu",
    "address": "Avenue du Marechal de Lattre de Tassigny",
    "extendedAddress": "Tesla Mandelieu",
    "city": "06210 Mandelieu-la-NapouleFrance",
    "phone": "+33423110178",
    "email": "[email protected]",
    "storeType": "Stores and Galleries",
    "hasRepearCenter": "yes",
    "services": {
      "type-store": "Stores and Galleries",
      "type-service": "Service Center"
    },
    "storeHours": "Tu-Sa 10:00-18:00; Su off",
    "serviceHours": "Tu-Fr 08:30-18:30; Sa-Su off"
  },
  "geometry": {
    "type": "Point",
    "coordinates": [
      6.9446249,
      43.5495466
    ]
  }
},

Analysis data

The best part. ✨ Datas will be compared with existing OpenStreetMap data (see OSM extract). The script will separate stores already in OSM from those that are not.

npm run analyse

The data will be written in the output/tesla_stores_in_osm.json and output/tesla_stores_not_in_osm.json files.

OSM extract

• Extract data from OpenStreetMap with this request (you can use Overpass Turbo)

  [out:json];
  (
    node["shop"="car"]["name"~"Tesla"];
    node["shop"="car"]["brand"="Tesla"];
    way["shop"="car"]["name"~"Tesla"];
    way["shop"="car"]["brand"="Tesla"];
  );
  out geom;

• Export the data in GeoJSON to a file named overpass-export.geojson, place it in this project's root
• Then you can run the analyse command

Everything is ready to create the Maproulette challenge 😀

---

🇫🇷 Error messages are in french.