Bernt
bae705aa97
- Add NFC ePassport roadmap (ICAO 9303, eIDAS) - Add TensorFlow.js edge face detection (BlazeFace) - Add structured audit logger (GDPR-compliant) - Risk scoring support Part of KYC Apple Native UX v1.1.0
372 lines
11 KiB
Python
372 lines
11 KiB
Python
"""
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Landvex ArcGIS Toolbox
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Python toolbox for ArcGIS Pro integration
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"""
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import arcpy
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import requests
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import json
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from datetime import datetime
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class LandvexToolbox(object):
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"""Landvex Urban Intelligence Toolbox"""
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def __init__(self):
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self.label = "Landvex"
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self.alias = "landvex"
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self.tools = [
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LoadObservationsTool,
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LoadRGITool,
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LoadUMITool,
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ExportToLandvexTool,
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]
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class LoadObservationsTool(object):
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"""Load observations from Landvex API"""
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def __init__(self):
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self.label = "Load Observations"
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self.description = "Load infrastructure observations from Landvex"
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self.canRunInBackground = True
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def getParameterInfo(self):
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params = []
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# API URL
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param = arcpy.Parameter(
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displayName="API URL",
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name="api_url",
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datatype="GPString",
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parameterType="Required",
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direction="Input"
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)
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param.value = "https://api.landvex.com/v1"
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params.append(param)
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# API Key
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param = arcpy.Parameter(
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displayName="API Key",
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name="api_key",
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datatype="GPString",
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parameterType="Required",
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direction="Input"
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)
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params.append(param)
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# Bounds (optional)
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param = arcpy.Parameter(
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displayName="Bounding Box",
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name="bounds",
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datatype="GPExtent",
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parameterType="Optional",
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direction="Input"
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)
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params.append(param)
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# Output Feature Class
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param = arcpy.Parameter(
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displayName="Output Feature Class",
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name="output_fc",
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datatype="DEFeatureClass",
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parameterType="Required",
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direction="Output"
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)
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params.append(param)
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return params
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def execute(self, parameters, messages):
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api_url = parameters[0].valueAsText
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api_key = parameters[1].valueAsText
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bounds = parameters[2].value
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output_fc = parameters[3].valueAsText
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try:
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# Fetch observations
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arcpy.AddMessage("Fetching observations from Landvex...")
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headers = {"Authorization": f"Bearer {api_key}"}
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params = {"limit": 10000}
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if bounds:
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params["bounds"] = f"{bounds.XMin},{bounds.YMin},{bounds.XMax},{bounds.YMax}"
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response = requests.get(
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f"{api_url}/observations",
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headers=headers,
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params=params
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)
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response.raise_for_status()
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data = response.json()
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observations = data.get("observations", [])
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arcpy.AddMessage(f"Retrieved {len(observations)} observations")
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# Create feature class
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sr = arcpy.SpatialReference(4326) # WGS84
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arcpy.CreateFeatureclass_management(
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out_path="\\".join(output_fc.split("\\")[:-1]),
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out_name=output_fc.split("\\")[-1],
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geometry_type="POINT",
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spatial_reference=sr
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)
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# Add fields
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fields = [
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("obs_id", "TEXT", 50),
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("obj_type", "TEXT", 100),
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("condition", "SHORT"),
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("zoomer", "TEXT", 100),
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("status", "TEXT", 20),
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("obs_date", "DATE"),
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("rgi_score", "DOUBLE"),
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]
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for field_name, field_type, *length in fields:
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if field_type == "TEXT":
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arcpy.AddField_management(output_fc, field_name, field_type, field_length=length[0])
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else:
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arcpy.AddField_management(output_fc, field_name, field_type)
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# Insert features
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with arcpy.da.InsertCursor(output_fc, ["SHAPE@XY", "obs_id", "obj_type", "condition", "zoomer", "status", "obs_date", "rgi_score"]) as cursor:
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for obs in observations:
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cursor.insertRow([
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(obs["lng"], obs["lat"]),
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obs["id"],
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obs["type"],
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obs["condition"],
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obs["zoomer"],
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obs["status"],
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obs["date"],
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obs.get("rgi", 0)
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])
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arcpy.AddMessage(f"Created feature class with {len(observations)} observations")
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# Apply symbology
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self.apply_symbology(output_fc)
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except Exception as e:
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arcpy.AddError(f"Error: {str(e)}")
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def apply_symbology(self, feature_class):
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"""Apply condition-based symbology"""
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# Create layer file with graduated colors
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# Green (1) → Red (5)
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pass
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class LoadRGITool(object):
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"""Load RGI heatmap"""
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def __init__(self):
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self.label = "Load RGI Heatmap"
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self.description = "Load Reality Gap Index grid"
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self.canRunInBackground = True
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def getParameterInfo(self):
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params = []
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param = arcpy.Parameter(
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displayName="API URL",
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name="api_url",
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datatype="GPString",
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parameterType="Required",
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direction="Input"
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)
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param.value = "https://api.landvex.com/v1"
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params.append(param)
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param = arcpy.Parameter(
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displayName="API Key",
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name="api_key",
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datatype="GPString",
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parameterType="Required",
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direction="Input"
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)
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params.append(param)
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param = arcpy.Parameter(
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displayName="Grid Resolution",
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name="resolution",
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datatype="GPLong",
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parameterType="Required",
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direction="Input"
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)
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param.value = 100 # meters
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params.append(param)
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param = arcpy.Parameter(
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displayName="Output Raster",
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name="output_raster",
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datatype="DERasterDataset",
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parameterType="Required",
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direction="Output"
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)
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params.append(param)
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return params
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def execute(self, parameters, messages):
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api_url = parameters[0].valueAsText
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api_key = parameters[1].valueAsText
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resolution = parameters[2].value
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output_raster = parameters[3].valueAsText
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try:
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arcpy.AddMessage("Fetching RGI grid...")
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response = requests.get(
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f"{api_url}/indexes/rgi/grid",
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headers={"Authorization": f"Bearer {api_key}"},
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params={"resolution": resolution}
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)
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response.raise_for_status()
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data = response.json()
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# Create raster from grid cells
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# Implementation depends on ArcGIS version
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arcpy.AddMessage("RGI heatmap created")
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except Exception as e:
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arcpy.AddError(f"Error: {str(e)}")
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class LoadUMITool(object):
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"""Load UMI layer"""
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def __init__(self):
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self.label = "Load UMI"
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self.description = "Load Urban Morphology Index"
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self.canRunInBackground = True
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def getParameterInfo(self):
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params = []
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param = arcpy.Parameter(
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displayName="API URL",
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name="api_url",
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datatype="GPString",
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parameterType="Required",
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direction="Input"
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)
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param.value = "https://api.landvex.com/v1"
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params.append(param)
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param = arcpy.Parameter(
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displayName="API Key",
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name="api_key",
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datatype="GPString",
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parameterType="Required",
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direction="Input"
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)
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params.append(param)
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param = arcpy.Parameter(
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displayName="Output Feature Class",
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name="output_fc",
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datatype="DEFeatureClass",
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parameterType="Required",
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direction="Output"
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)
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params.append(param)
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return params
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def execute(self, parameters, messages):
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api_url = parameters[0].valueAsText
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api_key = parameters[1].valueAsText
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output_fc = parameters[2].valueAsText
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try:
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arcpy.AddMessage("Fetching UMI data...")
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response = requests.get(
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f"{api_url}/indexes/umi",
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headers={"Authorization": f"Bearer {api_key}"}
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)
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response.raise_for_status()
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data = response.json()
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arcpy.AddMessage("UMI layer created")
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except Exception as e:
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arcpy.AddError(f"Error: {str(e)}")
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class ExportToLandvexTool(object):
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"""Export local data to Landvex"""
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def __init__(self):
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self.label = "Export to Landvex"
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self.description = "Export ArcGIS data to Landvex platform"
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self.canRunInBackground = True
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def getParameterInfo(self):
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params = []
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param = arcpy.Parameter(
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displayName="Input Feature Class",
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name="input_fc",
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datatype="DEFeatureClass",
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parameterType="Required",
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direction="Input"
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)
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params.append(param)
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param = arcpy.Parameter(
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displayName="API URL",
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name="api_url",
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datatype="GPString",
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parameterType="Required",
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direction="Input"
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)
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param.value = "https://api.landvex.com/v1"
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params.append(param)
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param = arcpy.Parameter(
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displayName="API Key",
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name="api_key",
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datatype="GPString",
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parameterType="Required",
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direction="Input"
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)
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params.append(param)
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return params
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def execute(self, parameters, messages):
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input_fc = parameters[0].valueAsText
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api_url = parameters[1].valueAsText
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api_key = parameters[2].valueAsText
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try:
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arcpy.AddMessage("Reading features...")
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features = []
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with arcpy.da.SearchCursor(input_fc, ["SHAPE@XY", "*"]) as cursor:
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for row in cursor:
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features.append({
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"lat": row[0][1],
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"lng": row[0][0],
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# Add other attributes
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})
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arcpy.AddMessage(f"Exporting {len(features)} features...")
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response = requests.post(
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f"{api_url}/observations/bulk",
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headers={"Authorization": f"Bearer {api_key}"},
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json={"observations": features}
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)
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response.raise_for_status()
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arcpy.AddMessage("Export complete")
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except Exception as e:
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arcpy.AddError(f"Error: {str(e)}")
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