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https://github.com/GIScience/openpoiservice

:round_pushpin: Openpoiservice is a flask application which hosts a highly customizable points of interest database derived from OpenStreetMap data.
https://github.com/GIScience/openpoiservice

giscience openstreetmap openstreetmap-data openstreetmap-protobuffer-format

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:round_pushpin: Openpoiservice is a flask application which hosts a highly customizable points of interest database derived from OpenStreetMap data.

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README 

        
# Openpoiservice 



[![Tests](https://github.com/GIScience/openpoiservice/workflows/run%20tests/badge.svg)](https://github.com/GIScience/openpoiservice/actions?query=workflow%3A%22run+tests%22)



Openpoiservice (ops) is a flask application which hosts a highly customizable points of interest database derived from 

OpenStreetMap.org data and thereby **exploits** its notion of tags...



> OpenStreetMap [tags](https://wiki.openstreetmap.org/wiki/Tags) consisting of a key and value describe specific features of 

> map elements (nodes, ways, or relations) or changesets.  Both items are free format text fields, but often represent numeric 

> or other structured items. 



This service consumes OSM tags on nodes, ways and relations by grouping them into predefined categories. 

If it picks up an OSM object tagged with one of the osm keys defined in `categories.yml` it will import this 

point of interest with specific additional tags which may be defined in `ops_settings.yml`. Any additional tag, 

for instance `wheelchair` or `smoking` may then be used to query the service via the API after import.



For instance, if you want to request all pois accessible by wheelchair within a geometry, you could add then add 

`wheelchair: ['yes', 'dedicated]` in `filters` within the body of your HTTP POST request. 



You may pass 3 different types of geometry within the request to the database. Currently, "Point" and "LineString" with

a corresponding and buffer are supported as well as a polygon. Points of interest will be returned within the given geometry.



You can control the maximum size of geometries and further restrictions in the settings file of this service.



#### Import Process 



The osm file(s) to be imported are parsed several times to extract points of interest from relations (osm_type 3), 

ways (osm_type 2) and nodes (osm_type 1) in order. Which type the specific point of interest originated from will be 

returned within the response - this will help you find the object directly on [OpenStreetMap.org](https://www.openstreetmap.org). 



## Installation



You can either run **openpoiservice** on your host machine in a virtual environment or simply with Docker. The Dockerfile 

provided installs a WSGI server (gunicorn) which starts the flask service on port 5000.



### Technical specs for storing and importing OSM files



##### Python version



As this service makes use of the python collections library, in particular the notion of deque's and its functions

it only supports python 3.5 and greater.



##### Database

This application uses a psql/postgis setup for storing the points of interest. We highly recommend [using this](https://github.com/kartoza/docker-postgis) 

docker container.



##### Importer

Please consider the following technical requirements for parsing & importing osm files.



| Region        | Memory        | 

| ------------- |:-------------:|

| Germany       | 8 GB         |

| Europe        | 32 GB         | 

| Planet        | 128 GB        | 



**Note:** Openpoiservice will import any osm pbf file located in the osm folder or subdirectory within. 

This way you can split the planet file into smaller regions (e.g. download from Geofabrik, scraper script for the download

links to be found in the osm folder) and use a *smaller* instance to import the global data set (as long as

the OSM files don't exceed 5 GB of disk space, 16 GB of memory will suffice to import the entire planet).



### Run as Docker Container (Flask + Gunicorn)



Make your necessary changes to the settings in the file `ops_settings_docker.yml` and to categories if you need inside `categories_docker.yml`. These files are mounted as volumes to the docker container.

If you are planning to import a different osm file, please download it to the `osm folder` (any folder within will be scanned

for osm files) as this will be a shared volume. 



### Docker Compose



#### All-in-one docker image



This docker-compose will allow you to run openpoiservice with `psql/postgis` image. This will allow you to deploy this project fast.



**Important :** The database is not exposed, you won't be able to access it from outside the container. If you want to acces it simply adds those lines to the database definition inside the `docker-compose-with-postgis.yml`:



```sh

ports:

   - :5432

```



Don't forget to change the host name and port inside `ops_settings_docker.yml` by the one given to docker container for database.



* Hostname default value : `psql_postgis_db`

* Port default value : `5432`



**Notes :** If openpoiservice can't connect to the database, it's probably because you don't have the same settings inside `ops_settings_docker.yml` and `docker-compose-with-postgis.yml`.



Command to use to run all-in-one docker container



```sh

docker-compose -f /path/to/docker-compose.yml up api -d

```



#### Only deploy openpoiservice



This will only run openpoiservice inside a container, meaning that you will need to handle the database yourself and connect it to this container.



```sh

docker-compose -f /path/to/docker-compose-standalone.yml up api -d

```



#### After deploy



Once the container is built you can either, create the empty database:



```sh

$ docker exec -it container_name /ops_venv/bin/python manage.py create-db

```



Delete the database:



```sh

$ docker exec -it container_name /ops_venv/bin/python manage.py drop-db

```



Or import the OSM data:



```sh

$ docker exec -it container_name /ops_venv/bin/python manage.py import-data

```



### Init and Update DB with docker

You can initialize POI database with docker service init



```sh

docker-compose -f /path/to/docker-compose.yml up init

```



Or updating POI database

```sh

docker-compose -f /path/to/docker-compose.yml up update

```



### Protocol Buffers (protobuf) for imposm.parser 



This repository uses [imposm.parser](https://imposm.org/docs/imposm.parser/latest/index.html) to parse the 

OpenStreetMap pbf files which uses `google's protobuf library` under its hood.



**The imposm.parser requirement will not build with pip unless you are running [protobuf 3.0.0](https://github.com/protocolbuffers/protobuf/releases/tag/v3.0.0).** 



To this end, please make sure that you are running the aforementioned version of protobuf if `pip install -r requirements.txt` fails (install protobuf [from source](https://github.com/google/protobuf/blob/master/src/README.md)) 



### Prepare settings.yml



Update `openpoiservice/server/ops_settings.yml` with your necessary settings and then run one of the following

commands.



[

```sh

$ export APP_SETTINGS="openpoiservice.server.config.ProductionConfig|DevelopmentConfig"

```

]



### Create the POI DB



```sh

$ python manage.py create-db

```

### Drop the POI DB



```sh

$ python manage.py drop-db

```



### Parse and import OSM data



```sh

$ python manage.py import-data

```



### Run the Application with Flask-Werkzeug



```sh

$ python manage.py run

```



Per default you can access the application at the address [http://localhost:5000/](http://localhost:5000/)



> Want to specify a different port?



> ```sh

> $ python manage.py run -h 0.0.0.0 -p 8080

> ```



### Tests



```sh

$ export TESTING="True" && python manage.py test

```



### Category IDs and their configuration



`openpoiservice/server/categories/categories.yml` is a list of (**note:** not all!) OpenStreetMap tags with arbitrary category IDs. 

If you keep the structure as follows, you can manipulate this list as you wish.

 

 ```yaml

 transport:

    id: 580

    children:

        aeroway:

            aerodrome: 581        

            aeroport: 582 

            helipad: 598         

            heliport: 599 

        amenity:

            bicycle_parking: 583  

            

 sustenance:

    id: 560             

    children:

        amenity:

            bar: 561             

            bbq: 562   

 ...

 ```

 

 Openpoiservice uses this mapping while it imports pois from the OpenStreetMap data and assigns the custom category IDs

 accordingly.



`column_mappings` in `openpoiservice/server/ops_settings.yml` controls which OSM information will be considered in the database and also if 

these may be queried by the user via the API , e.g.



```yaml

wheelchair:



smoking:



fees:

```



For instance means that the OpenStreetMap tag [wheelchair](https://wiki.openstreetmap.org/wiki/Key:wheelchair) will be considered

during import and save to the database. A user may then add a list of common values in the filters object `wheelchair: ['yes', 'dedicated', ...]` 

which correspond to the OSM common values of the tag itself, e.g. 

[https://wiki.openstreetmap.org/wiki/Key:wheelchair](https://wiki.openstreetmap.org/wiki/Key:wheelchair).



### API Documentation



The documentation for this flask service is provided via [flasgger](https://github.com/rochacbruno/flasgger) and can be

accessed via `http://localhost:5000/apidocs/`.



Generally you have three different request types `pois`, `stats` and

`list`.



Using `request=pois` in the POST body will return a GeoJSON FeatureCollection

in your specified bounding box or geometry. 



Using `request=stats` will do the same but group by the categories, ultimately

returning a JSON object with the absolute numbers of pois of a certain group. 



Finally, `request=list` will return a JSON object generated from 

`openpoiservice/server/categories/categories.yml`.



### Endpoints



The default base url is `http://localhost:5000/`.



The openpoiservice holds the endpoint `/pois`:



| Method allowed | Parameter | Values \[optional\]                            			     |

|----------------|:----------|:----------------------------------------------------------------------|

| POST           | request   | pois, stats, list                 				     |

|                | geometry  | bbox, geojson, buffer             				     |

|                | filter    | category_group_ids, category_ids, \[name, wheelchair, smoking, fee\]  | 

|                | limit     | integer                           				     |

|                | sortby    | category, distance                				     |



### Examples



##### POIS around a buffered point



```sh

curl -X POST \

  http://localhost:5000/pois \

  -H 'Content-Type: application/json' \

  -d '{

  "request": "pois",

  "geometry": {

    "bbox": [

      [8.8034, 53.0756],

      [8.7834, 53.0456]

    ],

    "geojson": {

      "type": "Point",

      "coordinates": [8.8034, 53.0756]

    },

    "buffer": 250  

  }

}'

```



##### POIs of given categories

```sh

curl -X POST \

  http://localhost:5000/pois \

  -H 'Content-Type: application/json' \

  -d '{

  "request": "pois",

  "geometry": {

    "bbox": [

      [8.8034, 53.0756],

      [8.7834, 53.0456]

    ],

    "geojson": {

      "type": "Point",

      "coordinates": [8.8034, 53.0756]

    },

    "buffer": 100  

  },

  "limit": 200,

  "filters": {

    "category_ids": [180, 245]

  } 

}'

```



##### POIs of given category groups



```sh

curl -X POST \

  http://localhost:5000/pois \

  -H 'Content-Type: application/json' \

  -d '{

  "request": "pois",

  "geometry": {

    "bbox": [

      [8.8034, 53.0756],

      [8.7834, 53.0456]

    ],

    "geojson": {

      "type": "Point",

      "coordinates": [8.8034, 53.0756]

    },

    "buffer": 100  

  },

  "limit": 200,

  "filters": {

    "category_group_ids": [160]

  } 

}'

```



##### POI Statistics

```sh

curl -X POST \

  http://129.206.7.157:5005/pois \

  -H 'Content-Type: application/json' \

  -d '{

  "request": "stats",

  "geometry": {

    "bbox": [

      [8.8034, 53.0756],

      [8.7834, 53.0456]

    ],

    "geojson": {

      "type": "Point",

      "coordinates": [8.8034, 53.0756]

    },

    "buffer": 100  

  }

}'

```



##### POI Categories as a list



```sh

curl -X POST \

  http://127.0.0.1:5000/pois \

  -H 'content-type: application/json' \

  -d '{

	"request": "list"

}'

```