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Python client for requests to heligeo API services

Project description

Project Description

Quickstart

About HELIWARE

Heliware is a Web-GL Powered Geo-Spatial Analytics Platform for developer ,analytics & data Scientist that provides GIS, Web Mapping, and spatial data science tools which help companies to get InSite in just few click using AI, Data Science & Advance Geo-Processing

Contact

For any query please contact rajan@heliware.co.in

Access Free Api-Key

Get free Api-key by sign-up on Heliware Visit Website

Description About heligeo module

heligeo module provides you high level Geoprocessing,Routing,Isochrone and Visualization services.


Routing and Isochrone

  • routes
  • isochrone

Geoprocessing

  • polygon_union
  • polygon_intersection
  • alias_multistring
  • point_buffer
  • line_buffer
  • point_within_polygon
  • crop_geometry_data
  • Polygon_Grid_Creation
  • Find_Polygon_Center_Point

Visualization without filteration

  • hex_map_from_geojson
  • hex_map_from_csv
  • scatter_map_from_geojson
  • scatter_map_from_csv
  • line_map_from_geojson
  • fill_geo_map_from_geojson
  • density_map_from_geojson
  • density_map_from_csv

Visualization with filteration

  • visualization_from_geojson
  • visualization_from_csv

Requirements

heligeo-py is tested over Python>=3.0

Installation

To install from PyPI, simply use pip: pip install heligeo

How to use

Most of the cases heligeo module accept Polygon,Point,Lisestring data that format must be geojson.

Usage

Basic Example Of Routing Service

By default heligeo support four type of transport mode

  • drive
  • walk
  • bike
  • cycling

Output format

Output always Geojson response

Isochrone Service

image


from heligeo import heliRouteService
apikey = ''
longtitude = [88.3639]
latitude = [22.5726]
transport_mode = "drive" 
isochrone_data = heliRouteService.isochrone(apikey,latitude,longtitude,transport_mode)

Routing Service

image

apikey = ''
transport_mode = "drive" 
direction_coordinates = [[88.3639,22.5726],[72.8777,19.0760]] ### user can use multiple points
route_data = heliRouteService.route(apikey,direction_coordinates,transport_mode)

Basic Example Of Geoprocessing Service

  • heliGeoprocessingService.Union(),heliGeoprocessingService.Intersection() function accept multiple polygon data inside a list.
  • In this example we shown only 2 polygon data

Polygon Union Example

from heligeo import heliGeoprocessingService
apikey = ''
polygon1 = {"type": "FeatureCollection","features":[{
  "type": "Feature",
  "geometry": {
    "type": "Polygon",
    "coordinates": [[[77.4029103817493, 28.36918941103731, 0.0], [77.40184896262588, 28.3722403721131, 0.0][77.39922678901301, 28.37081966588294, 0.0], [77.40030856003351, 28.36816909494472, 0.0], [74029103817493, 28.36918941103731, 0.0]]]
  }}]}
polygon2 = {"type": "FeatureCollection","features":[{
      "type": "Feature",
      "geometry": {
        "type": "Polygon",
        "coordinates": [[[77.40486731638147, 28.36831967535351, 0.0], [77.40416140548453, 28.37080235923333, 0], [77.40218550684746, 28.    3699755298779, 0.0], [77.40187364471585, 28.36769815943599, 0.0], [740486731638147, 28.36831967535351, 0.0]]]
      }}]}
polygon_list = [polygon1,polygon2]
union_data = heliGeoprocessingService.Union(apikey,polygon_list)


Polygon Intersection Example

from heligeo import heliGeoprocessingService
apikey = ''
polygon1 = {"type": "FeatureCollection","features":[{
  "type": "Feature",
  "geometry": {
    "type": "Polygon",
    "coordinates": [[[77.4029103817493, 28.36918941103731, 0.0], [77.40184896262588, 28.3722403721131, 0.0][77.39922678901301, 28.37081966588294, 0.0], [77.40030856003351, 28.36816909494472, 0.0], [74029103817493, 28.36918941103731, 0.0]]]
  }}]}
polygon2 = {"type": "FeatureCollection","features":[{
      "type": "Feature",
      "geometry": {
        "type": "Polygon",
        "coordinates": [[[77.40486731638147, 28.36831967535351, 0.0], [77.40416140548453, 28.37080235923333, 0], [77.40218550684746, 28.    3699755298779, 0.0], [77.40187364471585, 28.36769815943599, 0.0], [740486731638147, 28.36831967535351, 0.0]]]
      }}]}
polygon_list = [polygon1,polygon2]
intersection_data = heliGeoprocessingService.Intersection(apikey,polygon_list)

PointBuffer Example

image

  • point_list accept multiple points data
apikey = ''
point_list = [[88.3639,22.5726]] ### user can user multiple Point inside a list 
area = 100  ### how area user want to conver from this point by default its meter
point_buffer_polygon=heliGeoprocessingService.PointBuffer(apikey,point_list,area)


LineBuffer Example

image

  • linestring_point_list accept multiple linestring.
apikey = ''
linestring_point_list = [[[88.3639,22.5726],[88.4143,22.5797]],[[88.2636,22.5958],[88.4789,22.7248]]] ### usecan  user multiple Point inside a list 
area = 100  ### how area user want to conver from this point by default its meter
linestring_buffer_polygon=heliGeoprocessingService.LineBuffer(apikey,linestring_point_list,area)

PointWithinPoly Example

image

apikey = ''
point_geojson_object = {"type":"FeatureCollection","features":[{"type":"Feature","geometry":                {"type":"Point","coordinates":[76.95513342,28.46301607]}}]}
polygon_list = [polygon1,polygon2]
point_inside_poly = heliGeoprocessingService.PointWithinPoly(apikey,point_geojson_object,polygon_list)


AliasLinestring Example

image

apikey = ''
linestring_geojson_object = {"type": "FeatureCollection","features":[{"type": "Feature","geometry{"type":"LineString",
    "coordinates": [
      [88.3639,22.5726],[88.4143,22.5797]
    ]}}]}
gap = 100 #gap between multiple linestring(meter)
quantity = 100 ## how many line string u need 
alias_linestring_data = heliGeoprocessingService.AliasLinestring(apikey,linestring_geojson_object,gap,quantity)

CropGeometryData

  • CropGeo fuction accept a Polygon GeoJson data and crop other geometry data based on the Polygon Size.
  • CropGeo accept bb={} contain Polygon Geojson data in which size u want to crop other geometry and gd={[]} contain all the getometry data which u want to crop gd list contain Polygon,Linestring and point data. Data must be GeoJson format.
  • CropGeo supported only Polygon,Linestring and point data in Geojson format
apikey = ''
bb = {"type":"FeatureCollection","features":[{"type":"Feature","geometry":{"type":"Polygon","coordinates":[[[76.76781345955712,30.524042786522788],[76.76658493660516,30.521411933136562],[76.76638374787312,30.520437335225605],[76.76812128413364,30.519991051100444],[76.76935817172217,30.5235212331106],[76.76781345955712,30.524042786522788]]]},"properties":{"PERIMETER":"1.166km","ENCLOSED_AREA":"0.0727sqkm"}}]}

gd = [{"type":"FeatureCollection","features":[{"type":"Feature","geometry":{"type":"LineString","coordinates":[[76.76605941690902,30.521077391710715],[76.76854013805993,30.52031431912859],[76.76854013805993,30.52031431912859]]},"properties":{"LENGTH":"252.68m","BEARING":"1093333.9"}},{"type":"Feature","geometry":{"type":"LineString","coordinates":[[76.76629027392768,30.521865657532633],[76.76849050129871,30.521044858531493],[76.768764809871,30.520962819202154],[76.768764809871,30.520962819202154]]},"properties":{"LENGTH":"257.8m","BEARING":"112514.9"}},{"type":"Feature","geometry":{"type":"LineString","coordinates":[[76.76897591153649,30.52205540468611],[76.76691180534269,30.522839498623096],[76.76691197785424,30.522849031168167]]},"properties":{"LENGTH":"217.4m","BEARING":"2935656.9"}},{"type":"Feature","geometry":{"type":"LineString","coordinates":[[76.76727709618594,30.523549659635112],[76.76936689485044,30.52278710560935],[76.76936689485044,30.52278710560935]]},"properties":{"LENGTH":"217.66m","BEARING":"1125115.1"}}]}]

crop_data = heliGeoprocessingService.CropGeo(apikey,bb,gd)

Polygon Grid Creation Example

  • PolyGrid function accept three parameter apikey, polygon_geo_json_data and grid-size.
  • Based on the grid size PolyGrid function break down the parent poly into small grids.
  • PolyGrid accept only polygon geojson data.
apikey = ''

polygon_geo_json_data = {"type":"FeatureCollection","features":[{"type":"Feature","properties":{},"geometry":{"type":"Polygon","coordinates":[[[76.9720448,28.4914468],[76.9734664,28.490094],[76.9745038,28.4891069],[76.9777595,28.4865896],[76.9832406,28.4847617],[76.9877826,28.4817885],[76.9994099,28.4931639],[76.9958932,28.49571],[76.9958867,28.4995722],[76.993081,28.5026631],[76.9897562,28.5047863],[76.9854207,28.5071706],[76.979788,28.501845],[76.9762078,28.4984432],[76.9720448,28.4914468]]]}}]}

gridsize = 3 # in meter user change value as per user choice
poly_grid_data = heliGeoprocessingService.PolyGrid(apikey,polygon_geo_json_data,gridsize)

Find Polygon Center Point Example

  • PolyCenter accept two parameter apikey and list_of_polygon_data=[polygeojson1,polygeojson1...n].

  • PolyCenter function accept only multiple polygon data in geojson format.

  • list_of_polygon_data its a list of multiple polygon data that must be geojson format

apikey = ''

list_of_polygon_data = [{"type":"FeatureCollection","features":[{"type":"Feature","properties":{},"geometry":{"type":"Polygon","coordinates":[[[76.9720448,28.4914468],[76.9734664,28.490094],[76.9745038,28.4891069],[76.9777595,28.4865896],[76.9832406,28.4847617],[76.9877826,28.4817885],[76.9994099,28.4931639],[76.9958932,28.49571],[76.9958867,28.4995722],[76.993081,28.5026631],[76.9897562,28.5047863],[76.9854207,28.5071706],[76.979788,28.501845],[76.9762078,28.4984432],[76.9720448,28.4914468]]]}}]},{"type":"FeatureCollection","features":[{"type":"Feature","properties":{},"geometry":{"type":"Polygon","coordinates":[[[76.9720448,28.4914468],[76.9734664,28.490094],[76.9745038,28.4891069],[76.9777595,28.4865896],[76.9832406,28.4847617],[76.9877826,28.4817885],[76.9994099,28.4931639],[76.9958932,28.49571],[76.9958867,28.4995722],[76.993081,28.5026631],[76.9897562,28.5047863],[76.9854207,28.5071706],[76.979788,28.501845],[76.9762078,28.4984432],[76.9720448,28.4914468]]]}}]},{"type":"FeatureCollection","features":[{"type":"Feature","properties":{},"geometry":{"type":"Polygon","coordinates":[[[76.9720448,28.4914468],[76.9734664,28.490094],[76.9745038,28.4891069],[76.9777595,28.4865896],[76.9832406,28.4847617],[76.9877826,28.4817885],[76.9994099,28.4931639],[76.9958932,28.49571],[76.9958867,28.4995722],[76.993081,28.5026631],[76.9897562,28.5047863],[76.9854207,28.5071706],[76.979788,28.501845],[76.9762078,28.4984432],[76.9720448,28.4914468]]]}}]}]

poly_center_point = heliGeoprocessingService.PolyCenter(apikey,list_of_polygon_data)

Basic Example Of Visualization Service

Hexagon Map

image

  • User Can Select Different type of BaseMap Like basic, streets,outdoors, light, dark, satellite, or satellite-streets
  • User can Create hex_map from .geojon and .csv file
  • File Must be contain geometry data
  • hex_map_from_geojson funtion accepty .geojson file with other parameter and hex_map_from_csv accept .csv file with other parameter.
  • hex_map_from_geojson accept apikey,file_path,hover_properties,basemap_style,hexagon_quantity,zoom_level
  • hex_map_from_csv accept apikey,file_path,column name from csv file that contain latitude value,column name from csv file that contain longtitude value,hover_properties,basemap_style,hexagon_quantity,zoom_level
  • As of Now heligeo module able to visualize only one propertie with their corrosponding Lat,Long value
  • Base_map=''
  • Use res.show() to visualize the data into web.
  • for hex_map_from_geojson user dont need to pass this two parameter column name that contain latitude value,column name that contain longtitude value we create these two value as our own.

Example

from heligeo import heliVisualizationService
apikey=''
file_path = '' 
latitude_value_col_name = ''
longtitude_value_col_name = ''
hover_properties = ''
base_map = ''
hexagan_quantity = 20  
zoom_level = 16
h = heliVisualizationService.hex_map_from_csv(apikey,file_path,latitude_value_col_name,longtitude_value_col_name,hover_properties,base_map,hexagan_quantity,zoom_level)
h.show()

h = heliVisualizationService.hex_map_from_geojson(apikey,file_path,hover_properties,base_map,hexagan_quantity,zoom_level)
h.show()

Scatter Map

image

  • User Can Select Different type of BaseMap Like basic, streets, outdoors, light, dark, satellite, or satellite-streets

  • User can Create scatter_map from .geojson and .csv file

  • File Must be contain geometry data

  • scatter_map_from_geojson funtion accept .geojson file with other parameter and scatter_map_from_csv accept .csv file with other parameter.

  • scatter_map_from_geojson accept apikey,file_path,hover_properties,basemap_style,zoom_level

  • scatter_map_from_csv accept apikey,file_path,column name from csv file that contain latitude value,column name from csv file that contain longtitude value,hover_properties,basemap_style,zoom_level

  • As of Now heligeo Visualization module able to visualize only one propertie with their corrosponding Lat,Long value

  • Use res.show() to visualize the data into web.

  • for scatter_map_from_geojson user dont need to pass this two parameter column name that contain latitude value,column name that contain longtitude value we create these two value as our own.

Example

from heligeo import heliVisualizationService
apikey=''
file_path = '' 
latitude_value_col_name = ''
longtitude_value_col_name = ''
hover_properties = ''
base_map = ''  
zoom_level = 16
h = heliVisualizationService.scatter_map_from_csv(apikey,file_path,latitude_value_col_name,longtitude_value_col_name,hover_properties,base_map,zoom_level)
h.show()

h = heliVisualizationService.scatter_map_from_geojson(apikey,file_path,hover_properties,base_map,zoom_level)
h.show()


Density Map

image

  • User Can Select Different type of BaseMap Like basic, streets, outdoors, light, dark, satellite, or satellite-streets

  • User can Create density_map from .geojson and .csv file

  • File Must be contain geometry data

  • density_map_from_geojson funtion accept .geojson file with other parameter and density_map_from_csv accept .csv file with other parameter.

  • density_map_from_geojson accept apikey,file_path,hover_properties,basemap_style,zoom_level

  • density_map_from_csvacceptapikey,file_path,column name from csv file that contain latitude value,column name from csv file that contain longtitude value,hover_properties,basemap_style,zoom_level`

  • As of Now heligeo Visualization module able to visualize only one propertie with their corrosponding Lat,Long value

  • Use res.show() to visualize the data into web.

  • for density_map_from_geojson user dont need to pass this two parameter column name that contain latitude value,column name that contain longtitude value we create these two value as our own.

Example

from heligeo import heliVisualizationService
apikey=''
file_path = '' 
latitude_value_col_name = ''
longtitude_value_col_name = ''
hover_properties = ''
base_map = ''  
zoom_level = 16
h = heliVisualizationService.density_map_from_csv(apikey,file_path,latitude_value_col_name,longtitude_value_col_name,hover_properties,base_map,zoom_level)
h.show()

h = heliVisualizationService.density_map_from_geojson(apikey,file_path,hover_properties,base_map,zoom_level)
h.show()

Line Map

image

  • User Can Select Different type of BaseMap Like basic, streets, outdoors, light, dark, satellite, or satellite-streets
  • User can Create line_map from .geojson.
  • line_map_from_geojson funtion accept .geojson file with other parameter.
  • density_map_from_geojson accept apikey,file_path,hover_properties,basemap_style,zoom_level
  • As of Now heligeo Visualization module able to visualize only one propertie with their corrosponding Lat,Long value
  • Use res.show() to visualize the data into web.

Example

from heligeo import heliVisualizationService
apikey=''
file_path = '' 
hover_properties = ''
base_map = ''  
zoom_level = 15
h = heliVisualizationService.line_map_from_geojson(apikey,file_path,hover_properties,base_map,zoom_level)
h.show()

Fill Geometry With Color

image

  • User Can Select Different type of BaseMap Like open-street-map, carto-positron, carto-darkmatter, stamen-terrain, stamen-toner or stamen-watercolor
  • User can fill a Geometry with different color and Visualize on map.
  • fill_geo_map_from_geojson funtion accept .geojson file with other parameter.
  • fill_geo_map_from_geojson accept apikey,file_path,color,basemap_style,zoom_level
  • As of Now heligeo Visualization module able to visualize only one propertie with their corrosponding Lat,Long value
  • Use res.show() to visualize the data into web.

Example

from heligeo import heliVisualizationService
apikey=''
file_path = '' 
color = ''
base_map = ''  
zoom_level = 15
h = heliVisualizationService.fill_geo_map_from_geojson(apikey,file_path,color,base_map,zoom_level)
h.show()

Visualization with filteration

image

  • As of now our module accept 10 features``filteration functionality
  • once you call the module its automatically create localserver localhost:8085
  • Paste the local host address on browser
  • Select a Map type

visualization from geojson

  • User Can Select Different type of BaseMap Like basic, streets, outdoors, light, dark, satellite, or satellite-streets
  • User can filter the data in real time
  • visualization_from_geojson function accept file_path,hover_properties,BaseMap(optional)

Example

from heligeo import heliVisualizationWithFilteration
file_path = '' ## local csv file path
hover_properties = '' ## based on this property our module will create map
heliVisualizationWithFilteration.visualization_from_geojson(file_path,hover_properties)

visualization from csv

  • User Can Select Different type of BaseMap Like basic, streets, outdoors, light, dark, satellite, or satellite-streets
  • once you call the module its automatically create localserver localhost:8085
  • User can filter the data in real time
  • visualization_from_geojson function accept file_path,lat_column_name,long_column_name,hover_properties,BaseMap(optional)

Example

from heligeo import heliVisualizationWithFilteration
file_path = '' ## local csv file path
lat_column_name = ''
long_column_name = ''
hover_properties = '' ## based on this property map will create

heliVisualizationWithFilteration.visualization_from_csv(file_path,lat_column_name,long_column_name,hover_properties)

License

© 2021 HELIWARE

This repository is licensed under the MIT license. See LICENSE for details.

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