The geoserver-rest
package is useful for the management for geospatial data in GeoServer. The package is useful for the creating, updating and deleting geoserver workspaces, stores, layers, and style files. For installation of this package, following packages should be installed first:
The geoserver-rest
package can be installed with pip, if all the dependencies are installed already.
pip install geoserver-rest
This library is used for creating workspace, coveragestore, featurestore, styles. Some of the examples are shown below.
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')
geo.create_workspace(workspace='demo')
It is helpful for publishing the raster data to the geoserver. Here if you don't pass the lyr_name
parameter, it will take the raster file name as the layer name.
geo.create_coveragestore(lyr_name='layer1' path=r'path\to\raster\file.tif', workspace='demo')
If the layername already exists in geoserver, you can pass another parameter overwrite=True
,
geo.create_coveragestore(lyr_name='layer1' path=r'path\to\raster\file.tif', workspace='demo' overwrite=True)
It is used for connecting the PostGIS with geoserver and publish this as a layer. It is only useful for vector data. The postgres connection parameters should be passed as the parameters. For publishing the PostGIS tables, the pg_table parameter represent the table name in postgres
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')
It is used for uploading SLD files and publish style. If the style name already exists, you can pass the parameter overwrite=True
to overwrite it. The name of the style will be name of the uploaded file name.
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')
It is used to create the style file for raster data. You can get the color_ramp
name from matplotlib colormaps. By default color_ramp='RdYlGn'
(red to green color ramp).
#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')
For generating the style for classified raster, you can pass the another parameter called cmap_type='values'
as,
geo.create_coveragestyle(raster_path=r'path\to\raster\file.tiff', style_name='style_1', workspace='demo', color_ramp='RdYiGn', cmap_type='values')
Option | Type | Default | Description |
---|---|---|---|
style_name | string | file_name | This is optional field. If you don't pass the style_name parameter, then it will take the raster file name as the default name of style in geoserver |
raster_path | path | None | path to the raster file |
workspace | string | None | The name of the workspace |
color_ramp | string | RdYlGn | The color ramp name. The name of the color ramp can be found here in matplotlib colormaps |
cmap_type | string | ramp | By default the continuous style will be generated, If you want to generate the style for classified raster then pass the parameter color_ramp='values' |
overwrite | boolean | False | For overwriting the previous style file in geoserver |
It is used for creating the style for point, line and polygon dynamically. Currently, it supports three different types of feature styles,
- Outline featurestyle: For creating the style which have only boundary color but not the fill style
- Catagorized featurestyle: For creating catagorized dataset
- Classified featurestyle: Classify the input data and style it: (For now, it only supports polygon geometry)
geo.create_outline_featurestyle(style_name='new_style' color="#3579b1" geom_type='polygon', workspace='demo')
geo.create_catagorized_featurestyle(style_name='name_of_style', column_name='name_of_column', column_distinct_values=[1,2,3,4,5,6,7], workspace='demo')
geo.create_classified_featurestyle(style_name='name_of_style' column_name='name_of_column', column_distinct_values=[1,2,3,4,5,6,7], workspace='demo')
Note:
- The geom_type must be either
point
,line
orpolygon
. - The
color_ramp
name can be obtained from matplotlib colormaps.
Option | Type | Default | Description |
---|---|---|---|
style_name | string | None | The name of the style file in geoserver |
column_name | string | None | The name of the column, based on which the style will be generated |
column_distinct_values | list/array | None | The column distinct values based on which the style will be applied/classified |
workspace | string | None | The name of the workspace |
color_ramp | string | RdYlGn | The color ramp name. The name of the color ramp can be found here in matplotlib colormaps |
geom_type | string | polygon | The geometry type, available options are point , line or polygon |
outline_color | color hex value | '#3579b1' | The outline color of the polygon/line |
overwrite | boolean | False | For overwriting the previous style file in geoserver |
# delete workspace
geo.delete_workspace(workspace='demo')
# delete layer
geo.delete_layer(layer_name='agri_final_proj', workspace='demo')
# delete feature store, i.e. remove postgresql connection
geo.delete_featurestore(featurestore_name='ftry', workspace='demo')
# delete coveragestore, i.e. delete raster store
geo.delete_coveragestore(coveragestore_name='agri_final_proj', workspace='demo')
# delete style file
geo.delete_style(style_name='kamal2', workspace='demo')
The following code will first convert all the .rst
data format inside C:\Users\gic\Desktop\etlIa\
folder, into tiff
format and then upload all the tiff
files to the GeoServer.
from geo.Geoserver import Geoserver
from osgeo import gdal
import glob
import os
geo = Geoserver('http://localhost:8080/geoserver', username='admin', password='geoserver')
rst_files = glob.glob(r'C:\Users\gic\Desktop\etlIa\*.rst')
# geo.create_workspace('geonode')
for rst in rst_files:
file_name = os.path.basename(file_name)
src = gdal.Open(rst)
tiff = r'C:\Users\tek\Desktop\try\{}'.format(file_name)
gdal.Translate(tiff, src)
geo.create_coveragestore(lyr_name=file_name, path=tiff, workspace='geonode') #, overwrite=True
Created and managed by Tek Bahadur Kshetri for the activites of Geoinformatics Center of Asian Institute of Technology, Thailand.
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