Examples

Raw Data API Basic Usage in Python¶

In [1]:

import requests
import json
import time
import geopandas as gpd

import requests import json import time import geopandas as gpd

Define your API Endpoint¶

Create your payload with your geometry and learn more about payload in API docs , API_URL/docs¶

In [2]:

# defining the api-endpoint
BASE_API_URL = 'https://api-prod.raw-data.hotosm.org/v1'

payload = {
  "outputType": "geojson",
  "fileName": "My_Export",
  "geometry": {
    "type": "Polygon",
    "coordinates": [
      [
        [
          83.96919250488281,
          28.194446860487773
        ],
        [
          83.99751663208006,
          28.194446860487773
        ],
        [
          83.99751663208006,
          28.214869548073377
        ],
        [
          83.96919250488281,
          28.214869548073377
        ],
        [
          83.96919250488281,
          28.194446860487773
        ]
      ]
    ]
  },
  "filters": {
    "tags": {
      "all_geometry": {
        "join_or": {
          "building": ["yes"]
        }
      }
    },
  },
  "geometryType": [
    "point",
    "polygon"
  ]
}

# defining the api-endpoint BASE_API_URL = 'https://api-prod.raw-data.hotosm.org/v1' payload = { "outputType": "geojson", "fileName": "My_Export", "geometry": { "type": "Polygon", "coordinates": [ [ [ 83.96919250488281, 28.194446860487773 ], [ 83.99751663208006, 28.194446860487773 ], [ 83.99751663208006, 28.214869548073377 ], [ 83.96919250488281, 28.214869548073377 ], [ 83.96919250488281, 28.194446860487773 ] ] ] }, "filters": { "tags": { "all_geometry": { "join_or": { "building": ["yes"] } } }, }, "geometryType": [ "point", "polygon" ] }

Call API¶

Make API call , Wait for api to finish its work poll its status¶

In [4]:

headers = {'accept': "application/json","Content-Type": "application/json"}

# making call to the api to get boundary
task_response = requests.post(url = f"{BASE_API_URL}/snapshot/", data = json.dumps(payload),headers=headers)

task_response.raise_for_status()
result = task_response.json() # I will be on queue and it gives my unique task_id and link to track it
print(result)
task_track_url = result['track_link']
stop_loop = False
while not stop_loop:
  check_result = requests.get(url=f"{BASE_API_URL}{task_track_url}")
  check_result.raise_for_status()
  res=check_result.json() # status will tell current status of your task after it turns to success it will give result
  if res['status'] == 'SUCCESS'or res['status'] == 'FAILED':
    stop_loop= True
  time.sleep(2) # check every two second
print(res)

headers = {'accept': "application/json","Content-Type": "application/json"} # making call to the api to get boundary task_response = requests.post(url = f"{BASE_API_URL}/snapshot/", data = json.dumps(payload),headers=headers) task_response.raise_for_status() result = task_response.json() # I will be on queue and it gives my unique task_id and link to track it print(result) task_track_url = result['track_link'] stop_loop = False while not stop_loop: check_result = requests.get(url=f"{BASE_API_URL}{task_track_url}") check_result.raise_for_status() res=check_result.json() # status will tell current status of your task after it turns to success it will give result if res['status'] == 'SUCCESS'or res['status'] == 'FAILED': stop_loop= True time.sleep(2) # check every two second print(res)

{'task_id': 'fcbb860e-221f-45f4-bc00-6d16a3e6039c', 'track_link': '/tasks/status/fcbb860e-221f-45f4-bc00-6d16a3e6039c/', 'queue': 0}
{'id': 'fcbb860e-221f-45f4-bc00-6d16a3e6039c', 'status': 'SUCCESS', 'result': {'download_url': 'https://s3.dualstack.us-east-1.amazonaws.com/production-raw-data-api/default/My_Export_geojson_uid_fcbb860e-221f-45f4-bc00-6d16a3e6039c.zip', 'file_name': 'My_Export', 'process_time': 'a moment', 'query_area': '6.32 Sq Km', 'binded_file_size': '4.21 MB', 'zip_file_size_bytes': 542746}}

Process API¶

Open file , read , do rest of your stuff¶

In [5]:

import io
import urllib.request
import zipfile

# Download the zip file from the URL
url = res['result']['download_url']
response = urllib.request.urlopen(url)

# Open the zip file from the response data
with zipfile.ZipFile(io.BytesIO(response.read()), 'r') as zip_ref:
    with zip_ref.open('My_Export.geojson') as file:
        my_export_geojson=json.loads(file.read())

df = gpd.GeoDataFrame.from_features(my_export_geojson['features'])
print(df.head(2))
df.plot()

import io import urllib.request import zipfile # Download the zip file from the URL url = res['result']['download_url'] response = urllib.request.urlopen(url) # Open the zip file from the response data with zipfile.ZipFile(io.BytesIO(response.read()), 'r') as zip_ref: with zip_ref.open('My_Export.geojson') as file: my_export_geojson=json.loads(file.read()) df = gpd.GeoDataFrame.from_features(my_export_geojson['features']) print(df.head(2)) df.plot()

                    geometry      osm_id osm_type  version  \
0  POINT (83.98476 28.21112)  5578045433    nodes        2   
1  POINT (83.98488 28.21129)  5578045429    nodes        1   

                                                tags  changeset  \
0  {'name': 'Giri Complex', 'building': 'yes', 'b...   59871828   
1  {'name': 'Dipendra City Hall', 'building': 'yes'}   58402131   

             timestamp  
0  2018-06-15T11:25:56  
1  2018-04-25T09:26:56  

Out[5]:

<Axes: >