geoserver-rest 0.3.0

Package for GeoServer rest API

Documentation

Installation

pip install wheel
pip install pipwin
pipwin install gdal

pip install geoserver-rest

How to use

This library is used for creating workspace, coveragestore, featurestore, styles. Some of the examples are shown below.

Initialize the library

This step is used to initialize the library. It takes parameters as geoserver url, username, password.

from geo.Geoserver import Geoserver
geo = Geoserver('http://localhost:8080/geoserver', username='admin', password='geoserver')

Create workspace

geo.create_workspace('demo')

Create coveragestore

It is helpful for publishing the raster data to the geoserver. Here if you forgot to pass the lyr_name parameter, it will take the raster file name as the layer name.

geo.create_coveragestore(lyr_name='layer' path=r'path\to\raster\file.tif', workspace='demo')

Create featurestore and publish layer

It is use for connecting the PostGIS with geoserver and publish this as a layer. It is only use for vector data.

geo.create_featurestore(store_name='geo_data', workspace='demo', db='postgres', host='localhost', pg_user='postgres', pg_password='admin')
geo.publish_featurestore(workspace='demo', store_name='geo_data', pg_table='geodata_table_name')

Upload style and publish it

It is use for uploading SLD files and publish style

geo.upload_style(path=r'path\to\sld\file.sld', workspace='demo')
geo.publish_style(layer_name='geoserver_layer_name', style_name='sld_file_name', workspace='demo')

Create Coverage Style based on the raster (Dynamic) and apply style

It is use to create the style file for raster data. You can get the color_ramp name from matplotlib colormaps.

#Style name will be the same as the raster_file_name
geo.create_coveragestyle(raster_path=r'path\to\raster\file.tiff', style_name='style_1', workspace='demo', color_ramp='RdYiGn')
geo.publish_style(layer_name='geoserver_layer_name', style_name='raster_file_name', workspace='demo')

Create featur style

It is use for creating the style for point, line, polygon dynamically. Currently it supports three different type of feature styles,

1. Outline featurestyle: For only outline color
2. Catagorized featurestyle: For creating catagorized dataset
3. Classified featurestyle: Classify the input data and style it

Note:

• The geom_type must be point or line or polygon
• The color_ramp name can be get from matplotlib colormaps.

geo.create_outline_featurestyle(style_name='new_style' color="#3579b1" geom_type='polygon', workspace='demo')
geo.create_catagorized_featurestyle(column_name='name_of_column', column_distinct_values=[1,2,3,4,5,6,7], workspace='demo', color_ramp='tab20', geom_type='polygon', outline_color='#000000')