Create qvadis.py

Author: carlandreasveie

qvadis.py

@@ -0,0 +1,100 @@
+import requests
+import pandas as pd
+import geopandas as gpd
+from shapely.geometry import Point, MultiPoint  # Importing Point and MultiPoint classes
+
+'''
+Gir reguleringsgrad i % andel av normal årsavrenning
+'''
+
+
+def qvadis():
+    # URL of the service, WMS
+    url = 'https://kart.nve.no/enterprise/rest/services/Mapservices/Qvadis/MapServer/1/query'
+
+    # Function to fetch data with pagination
+    def fetch_data_with_pagination(url, params, batch_size=1000):
+        all_features = []
+        offset = 0
+        while True:
+            params['resultOffset'] = offset
+            response = requests.get(url, params=params)
+            if response.status_code == 200:
+                json_data = response.json()
+                features = json_data.get('features', [])
+                if not features:
+                    break
+                all_features.extend(features)
+                if len(features) < batch_size:
+                    break
+                offset += batch_size
+            else:
+                print("Error:", response.status_code)
+                break
+        return all_features
+
+    # Parameters for the request
+    params = {
+        'where': '1=1',  # True
+        'text': '',
+        'objectIds': '',
+        'time': '',
+        'timeRelation': 'esriTimeRelationOverlaps',
+        'geometry': '',
+        'geometryType': 'esriGeometryEnvelope',
+        'inSR': '',
+        'spatialRel': 'esriSpatialRelIntersects',
+        'distance': '',
+        'units': 'esriSRUnit_Meters',
+        'relationParam': '',
+        'outFields': '*', #* means returning all columns. YOu can replace this this with a list of columns out want to return.
+        'returnGeometry': True,
+        'returnTrueCurves': False,
+        'maxAllowableOffset': '',
+        'geometryPrecision': '',
+        'outSR': '',
+        'havingClause': '',
+        'returnIdsOnly': False,
+        'returnCountOnly': False,
+        'orderByFields': '',
+        'groupByFieldsForStatistics': '',
+        'outStatistics': '',
+        'returnZ': False,
+        'returnM': False,
+        'gdbVersion': '',
+        'historicMoment': '',
+        'returnDistinctValues': False,
+        'resultOffset': '',
+        'resultRecordCount': 1000,  # Set batch size to 1000
+        'returnExtentOnly': False,
+        'sqlFormat': 'none',
+        'datumTransformation': '',
+        'parameterValues': '',
+        'rangeValues': '',
+        'quantizationParameters': '',
+        'featureEncoding': 'esriDefault',
+        'f': 'pjson'
+    }
+
+    # Fetch all features using pagination
+    all_features = fetch_data_with_pagination(url, params)
+
+    # Extracting attributes and geometry coordinates
+    attributes = [feature['attributes'] for feature in all_features]
+    print(attributes)
+    geometry_paths = [feature['geometry']['paths'] for feature in all_features]
+    # Extract points from rings for each row
+    geometry_points = [MultiPoint([Point(point) for point in path]) for paths in geometry_paths for path in paths]
+    print(len(geometry_points))
+    # Create DataFrame
+    df = pd.DataFrame(attributes)
+    # Create GeoDataFrame
+    gdf = gpd.GeoDataFrame(df, geometry=geometry_points)
+
+    print(gdf)  # Print the GeoDataFrame
+    print(gdf.columns)
+
+    gdf.to_excel("qvadis.xlsx", index=False)
+
+if __name__ == '__main__':
+    qvadis()