Replace the old v1 url with v2 url and add logic to get the file

backend/aiproject/settings.py

@@ -33,7 +33,7 @@
 HOSTNAME = env("HOSTNAME", default="127.0.0.1")
 EXPORT_TOOL_API_URL = env(
     "EXPORT_TOOL_API_URL",
-    default="https://galaxy-api.hotosm.org/v1/raw-data/current-snapshot/",
+    default="	https://api-prod.raw-data.hotosm.org/v1",
 )
 
 ALLOWED_HOSTS = ["localhost", "127.0.0.1", HOSTNAME]

backend/core/utils.py

@@ -1,8 +1,11 @@
 import concurrent.futures
+import io
 import json
 import math
 import os
 import re
+import time
+import zipfile
 from datetime import datetime
 from uuid import uuid4
 from xml.dom import ValidationErr
@@ -55,35 +58,65 @@ def is_dir_empty(directory_path):
     return not any(os.scandir(directory_path))
 
 
+class RawDataAPI:
+    def __init__(self, BASE_API_URL):
+        self.BASE_API_URL = BASE_API_URL
+
+    def request_snapshot(self, geometry):
+        headers = {"accept": "application/json", "Content-Type": "application/json"}
+        # Lets start with buildings for now
+        payload = {
+            "geometry": json.loads(geometry),
+            "filters": {"tags": {"all_geometry": {"join_or": {"building": []}}}},
+            "geometryType": ["polygon"],
+        }
+        response = requests.post(
+            f"{self.BASE_API_URL}/snapshot/", data=json.dumps(payload), headers=headers
+        )
+        response.raise_for_status()
+        return response.json()
+
+    def poll_task_status(self, task_link):
+        stop_loop = False
+        while not stop_loop:
+            check_result = requests.get(url=f"{self.BASE_API_URL}{task_link}")
+            check_result.raise_for_status()
+            res = check_result.json()
+            if res["status"] == "SUCCESS" or res["status"] == "FAILED":
+                stop_loop = True
+            time.sleep(1)
+        return res
+
+
+import logging
 
-def request_rawdata(request_params):
-    """will make call to galaxy API & provides response as json
+
+def request_rawdata(geometry):
+    """will make call to Raw Data API & provides response as json
 
     Args:
-        request_params (dict): Galaxy API Request Body
+        geometry (dict): geometry to request
 
     Raises:
-        ImportError: If galaxy url is not exists
+        ImportError: If raw data api url is not exists
 
     Returns:
         Response(json): API Response
     """
 
     export_tool_api_url = settings.EXPORT_TOOL_API_URL
-
-    # following block should be a background task
-    headers = {
-        "accept": "application/json",
-        "Content-Type": "application/json",
-    }
-    print(request_params)
-    with requests.post(
-        url=export_tool_api_url, data=json.dumps(request_params), headers=headers
-    ) as r:  # curl can also be option
-        r.raise_for_status()
-        response_back = r.json()
-        print(response_back)
-        return response_back
+    api = RawDataAPI(export_tool_api_url)
+    snapshot_data = api.request_snapshot(geometry)
+    task_link = snapshot_data["track_link"]
+    logging.info("Fetching latest OSM snapshot")
+    task_result = api.poll_task_status(task_link)
+    logging.info(f"Fetch Task result: {task_result['status']}")
+    if task_result["status"] != "SUCCESS":
+        raise RuntimeError(
+            "Raw Data API did not respond correctly. Please try again later."
+        )
+    snapshot_url = task_result["result"]["download_url"]
+    return snapshot_url
 
 
 def process_rawdata(file_download_url, aoi_id, feedback=False):
@@ -99,7 +132,6 @@ def process_rawdata(file_download_url, aoi_id, feedback=False):
         os.makedirs(path)
     file_temp_path = os.path.join(path, f"{str(uuid4())}.zip")  # unique
     open(file_temp_path, "wb").write(r.content)
-    print("Zip File from API wrote to disk")
     with ZipFile(file_temp_path, "r") as zipObj:
         # Get a list of all archived file names from the zip
         listOfFileNames = zipObj.namelist()

backend/core/views.py

@@ -1,6 +1,7 @@
 from __future__ import absolute_import
 
 import json
+import logging
 import os
 import pathlib
 import shutil
@@ -29,15 +30,14 @@
 from login.permissions import IsOsmAuthenticated
 from orthogonalizer import othogonalize_poly
 from osmconflator import conflate_geojson
+from predictor import predict
 from rest_framework import decorators, serializers, status, viewsets
 from rest_framework.decorators import api_view
 from rest_framework.exceptions import ValidationError
 from rest_framework.response import Response
 from rest_framework.views import APIView
 from rest_framework_gis.filters import InBBoxFilter, TMSTileFilter
 
-from predictor import predict
-
 from .models import (
     AOI,
     Dataset,
@@ -61,12 +61,7 @@
     PredictionParamSerializer,
 )
 from .tasks import train_model
-from .utils import (
-    get_dir_size,
-    gpx_generator,
-    process_rawdata,
-    request_rawdata,
-)
+from .utils import get_dir_size, gpx_generator, process_rawdata, request_rawdata
 
 
 def home(request):
@@ -280,13 +275,7 @@ def post(self, request, feedbackaoi_id, *args, **kwargs):
         try:
             obj.label_status = 0
             obj.save()
-            raw_data_params = {
-                "geometry": json.loads(obj.geom.geojson),
-                "filters": {"tags": {"polygon": {"building": []}}},
-                "geometryType": ["polygon"],
-            }
-            result = request_rawdata(raw_data_params)
-            file_download_url = result["download_url"]
+            file_download_url = request_rawdata(obj.geom.geojson)
             process_rawdata(file_download_url, feedbackaoi_id, feedback=True)
             obj.label_status = 1
             obj.label_fetched = datetime.utcnow()
@@ -296,6 +285,7 @@ def post(self, request, feedbackaoi_id, *args, **kwargs):
             obj.label_status = -1
             obj.save()
             # raise ex
+            logging.error(ex)
             return Response("OSM Fetch Failed", status=500)
 
 
@@ -317,13 +307,7 @@ def post(self, request, aoi_id, *args, **kwargs):
         try:
             obj.label_status = 0
             obj.save()
-            raw_data_params = {
-                "geometry": json.loads(obj.geom.geojson),
-                "filters": {"tags": {"polygon": {"building": []}}},
-                "geometryType": ["polygon"],
-            }
-            result = request_rawdata(raw_data_params)
-            file_download_url = result["download_url"]
+            file_download_url = request_rawdata(obj.geom.geojson)
             process_rawdata(file_download_url, aoi_id)
             obj.label_status = 1
             obj.label_fetched = datetime.utcnow()
@@ -560,7 +544,19 @@ def post(self, request, *args, **kwargs):
                             f"training_{training_instance.id}",
                             "checkpoint.tf",
                         )
-                geojson_data = predict(bbox=bbox,model_path=model_path,zoom_level=zoom_level,tms_url=source, tile_size=DEFAULT_TILE_SIZE,confidence=deserialized_data["confidence"] / 100 if "confidence" in deserialized_data else 0.5,tile_overlap_distance=deserialized_data["tile_overlap_distance"] if "tile_overlap_distance" in deserialized_data else 0.15)
+                geojson_data = predict(
+                    bbox=bbox,
+                    model_path=model_path,
+                    zoom_level=zoom_level,
+                    tms_url=source,
+                    tile_size=DEFAULT_TILE_SIZE,
+                    confidence=deserialized_data["confidence"] / 100
+                    if "confidence" in deserialized_data
+                    else 0.5,
+                    tile_overlap_distance=deserialized_data["tile_overlap_distance"]
+                    if "tile_overlap_distance" in deserialized_data
+                    else 0.15,
+                )
                 print(
                     f"It took {round(time.time()-start_time)}sec for generating predictions"
                 )
@@ -578,7 +574,9 @@ def post(self, request, *args, **kwargs):
                             else 15,
                         )
 
-                print(f"Prediction API took ({round(time.time()-start_time)} sec) in total")
+                print(
+                    f"Prediction API took ({round(time.time()-start_time)} sec) in total"
+                )
 
                 ## TODO : can send osm xml format from here as well using geojson2osm
                 return Response(geojson_data, status=status.HTTP_201_CREATED)

backend/docker_sample_env

@@ -1,7 +1,7 @@
 DEBUG=True
 SECRET_KEY=yl2w)c0boi_ma-1v5)935^2#&m*r!1s9z9^*9e5co^08_ixzo6
 DATABASE_URL=postgis://postgres:admin@pgsql:5432/ai
-EXPORT_TOOL_API_URL=https://galaxy-api.hotosm.org/v1/raw-data/current-snapshot/
+EXPORT_TOOL_API_URL=https://raw api url.hotosm.org/v1
 CORS_ALLOWED_ORIGINS=http://127.0.0.1:3000
 OSM_CLIENT_ID=
 OSM_CLIENT_SECRET=

backend/sample_env

@@ -1,6 +1,6 @@
 SECRET_KEY=yl2w)c0boi_ma-1v5)935^2#&m*r!1s9z9^*9e5co^08_ixzo6
 DATABASE_URL=postgis://admin:password@localhost:5432/ai
-EXPORT_TOOL_API_URL=http://44.203.33.53:8000/raw-data/current-snapshot/
+EXPORT_TOOL_API_URL=MY_RAW_DATA_URL
 CORS_ALLOWED_ORIGINS=http://localhost:3000
 HOSTNAME=
 GDAL_LIBRARY_PATH=''