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mapnik/tests/python_tests/python_plugin_test.py

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python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import math
import mapnik
import sys
from utilities import execution_path
from nose.tools import *
def setup():
# All of the paths used are relative, if we run the tests
# from another directory we need to chdir()
os.chdir(execution_path('.'))
class PointDatasource(mapnik.PythonDatasource):
def __init__(self):
super(PointDatasource, self).__init__(
envelope = mapnik.Box2d(0,-10,100,110)
)
def features(self, query):
python plugin: remove Shapely dependency from tests Remove the Shapely dependency by generating the output features directly in WKT format. Update the expected output image because the circles are now generated directly as 72-sided polygons rather than by buffering a point.
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return mapnik.PythonDatasource.wkt_features(
+ code: avoid exposing unsafe static methods in datasource_cache ( #1451) + python: remove redundent 'instance' method (mapnik.DatasourceCache) + python: reflect plugin_directories method + tests: update python usage TODO: consider using similar approach in FontEngine etc.. TODO: consider returning reference from singleton::instance() to safeguard from accidental deleting a 'singleton' pointer
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keys = ('label',),
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
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features = (
+ code: avoid exposing unsafe static methods in datasource_cache ( #1451) + python: remove redundent 'instance' method (mapnik.DatasourceCache) + python: reflect plugin_directories method + tests: update python usage TODO: consider using similar approach in FontEngine etc.. TODO: consider returning reference from singleton::instance() to safeguard from accidental deleting a 'singleton' pointer
2012-09-05 11:53:37 +00:00
( 'POINT (5 6)', { 'label': 'foo-bar'} ),
( 'POINT (60 50)', { 'label': 'buzz-quux'} ),
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
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)
)
class ConcentricCircles(object):
def __init__(self, centre, bounds, step=1):
self.centre = centre
self.bounds = bounds
self.step = step
class Iterator(object):
def __init__(self, container):
self.container = container
centre = self.container.centre
bounds = self.container.bounds
step = self.container.step
python plugin: remove Shapely dependency from tests Remove the Shapely dependency by generating the output features directly in WKT format. Update the expected output image because the circles are now generated directly as 72-sided polygons rather than by buffering a point.
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self.radius = step
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
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def next(self):
python plugin: remove Shapely dependency from tests Remove the Shapely dependency by generating the output features directly in WKT format. Update the expected output image because the circles are now generated directly as 72-sided polygons rather than by buffering a point.
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points = []
for alpha in xrange(0, 361, 5):
x = math.sin(math.radians(alpha)) * self.radius + self.container.centre[0]
y = math.cos(math.radians(alpha)) * self.radius + self.container.centre[1]
points.append('%s %s' % (x,y))
circle = 'POLYGON ((' + ','.join(points) + '))'
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
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# has the circle grown so large that the boundary is entirely within it?
python plugin: remove Shapely dependency from tests Remove the Shapely dependency by generating the output features directly in WKT format. Update the expected output image because the circles are now generated directly as 72-sided polygons rather than by buffering a point.
2012-08-18 16:17:14 +00:00
tl = (self.container.bounds.maxx, self.container.bounds.maxy)
tr = (self.container.bounds.maxx, self.container.bounds.maxy)
bl = (self.container.bounds.minx, self.container.bounds.miny)
br = (self.container.bounds.minx, self.container.bounds.miny)
def within_circle(p):
delta_x = p[0] - self.container.centre[0]
delta_y = p[0] - self.container.centre[0]
return delta_x*delta_x + delta_y*delta_y < self.radius*self.radius
if all(within_circle(p) for p in (tl,tr,bl,br)):
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
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raise StopIteration()
python plugin: remove Shapely dependency from tests Remove the Shapely dependency by generating the output features directly in WKT format. Update the expected output image because the circles are now generated directly as 72-sided polygons rather than by buffering a point.
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self.radius += self.container.step
return ( circle, { } )
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
2012-07-19 18:06:44 +00:00
def __iter__(self):
return ConcentricCircles.Iterator(self)
class CirclesDatasource(mapnik.PythonDatasource):
def __init__(self, centre_x=-20, centre_y=0, step=10):
super(CirclesDatasource, self).__init__(
geometry_type=mapnik.DataGeometryType.Polygon
)
# note that the plugin loader will set all arguments to strings and will not try to parse them
centre_x = int(centre_x)
centre_y = int(centre_y)
step = int(step)
self.centre_x = centre_x
self.centre_y = centre_y
self.step = step
def features(self, query):
python plugin: remove Shapely dependency from tests Remove the Shapely dependency by generating the output features directly in WKT format. Update the expected output image because the circles are now generated directly as 72-sided polygons rather than by buffering a point.
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centre = (self.centre_x, self.centre_y)
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
2012-07-19 18:06:44 +00:00
python plugin: remove Shapely dependency from tests Remove the Shapely dependency by generating the output features directly in WKT format. Update the expected output image because the circles are now generated directly as 72-sided polygons rather than by buffering a point.
2012-08-18 16:17:14 +00:00
return mapnik.PythonDatasource.wkt_features(
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
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keys = (),
python plugin: remove Shapely dependency from tests Remove the Shapely dependency by generating the output features directly in WKT format. Update the expected output image because the circles are now generated directly as 72-sided polygons rather than by buffering a point.
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features = ConcentricCircles(centre, query.bbox, self.step)
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
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)
+ code: avoid exposing unsafe static methods in datasource_cache ( #1451) + python: remove redundent 'instance' method (mapnik.DatasourceCache) + python: reflect plugin_directories method + tests: update python usage TODO: consider using similar approach in FontEngine etc.. TODO: consider returning reference from singleton::instance() to safeguard from accidental deleting a 'singleton' pointer
2012-09-05 11:53:37 +00:00
if 'python' in mapnik.DatasourceCache.plugin_names():
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
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# make sure we can load from ourself as a module
sys.path.append(execution_path('.'))
def test_python_point_init():
ds = mapnik.Python(factory='python_plugin_test:PointDatasource')
e = ds.envelope()
assert_almost_equal(e.minx, 0, places=7)
assert_almost_equal(e.miny, -10, places=7)
assert_almost_equal(e.maxx, 100, places=7)
assert_almost_equal(e.maxy, 110, places=7)
def test_python_circle_init():
ds = mapnik.Python(factory='python_plugin_test:CirclesDatasource')
e = ds.envelope()
assert_almost_equal(e.minx, -180, places=7)
assert_almost_equal(e.miny, -90, places=7)
assert_almost_equal(e.maxx, 180, places=7)
assert_almost_equal(e.maxy, 90, places=7)
def test_python_circle_init_with_args():
ds = mapnik.Python(factory='python_plugin_test:CirclesDatasource', centre_x=40, centre_y=7)
e = ds.envelope()
assert_almost_equal(e.minx, -180, places=7)
assert_almost_equal(e.miny, -90, places=7)
assert_almost_equal(e.maxx, 180, places=7)
assert_almost_equal(e.maxy, 90, places=7)
def test_python_point_rendering():
m = mapnik.Map(512,512)
Move python test maps from 'good_maps' directory If the CirclesDatasource class was not available from the python_plugin_tests module then the 'load_good_maps' test would fail. The class would not be available if, for example, the python plugin had not been built or if shapely was not available on the test system. (Pull request #1414 removes the dependency on Shapely.) The error reporting should be tidied up for this case but for the moment, move the Python plugin's test maps into their own directory since they're not guaranteed to be 'good maps' in all cases at the moment. Hopefully addresses issue #1407
2012-08-18 16:34:58 +00:00
mapnik.load_map(m,'../data/python_plugin/python_point_datasource.xml')
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
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m.zoom_all()
im = mapnik.Image(512,512)
mapnik.render(m,im)
actual = '/tmp/mapnik-python-point-render1.png'
expected = 'images/support/mapnik-python-point-render1.png'
im.save(actual)
expected_im = mapnik.Image.open(expected)
eq_(im.tostring(),expected_im.tostring(),
'failed comparing actual (%s) and expected (%s)' % (actual,'tests/python_tests/'+ expected))
def test_python_circle_rendering():
m = mapnik.Map(512,512)
Move python test maps from 'good_maps' directory If the CirclesDatasource class was not available from the python_plugin_tests module then the 'load_good_maps' test would fail. The class would not be available if, for example, the python plugin had not been built or if shapely was not available on the test system. (Pull request #1414 removes the dependency on Shapely.) The error reporting should be tidied up for this case but for the moment, move the Python plugin's test maps into their own directory since they're not guaranteed to be 'good maps' in all cases at the moment. Hopefully addresses issue #1407
2012-08-18 16:34:58 +00:00
mapnik.load_map(m,'../data/python_plugin/python_circle_datasource.xml')
python: a new plugin to use arbitrary Python as a data source This plugin allows you to write data sources in the Python programming language. This is useful if you want to rapidly prototype a plugin, perform some custom manipulation on data or if you want to bind mapnik to a datasource which is most conveniently accessed through Python. The plugin may be used from the existing mapnik Python bindings or it can embed the Python interpreter directly allowing it to be used from C++, XML or even JavaScript. Mapnik already has excellent Python bindings but they only directly support calling *into* mapnik *from* Python. This forces mapnik and its input plugins to be the lowest layer of the stack. The role of this plugin is to allow mapnik to call *into* Python itself. This allows mapnik to sit as rendering middleware between a custom Python frontend and a custom Python datasource. This increases the utility of mapnik as a component in a larger system. There already exists MemoryDatasource which can be used to dynamically create geometry in Python. It suffers from the problem that it does not allow generating only the geometry which is seen by a particular query. Similarly the entire geometry must exist in memory before rendering can progress. By using a custom iterator object or by using generator expressions this plugin allows geometry to be created on demand and to be destroyed after use. This can have a great impact on memory efficiency. Since geometry is generated on-demand as rendering progresses there can be arbitrarily complex 'cleverness' optimising the geometry generated for a particular query. Obvious examples of this would be generating only geometry within the query bounding box and generating geometry with an appropriate level of detail for the output resolution.
2012-07-19 18:06:44 +00:00
m.zoom_all()
im = mapnik.Image(512,512)
mapnik.render(m,im)
actual = '/tmp/mapnik-python-circle-render1.png'
expected = 'images/support/mapnik-python-circle-render1.png'
im.save(actual)
expected_im = mapnik.Image.open(expected)
eq_(im.tostring(),expected_im.tostring(),
'failed comparing actual (%s) and expected (%s)' % (actual,'tests/python_tests/'+ expected))
if __name__ == "__main__":
setup()
[eval(run)() for run in dir() if 'test_' in run]
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