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Fixed #25072 -- Prevented GDALRaster memory to be uncollectable

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Setting GDALRaster.bands as a cached property was creating a circular
reference with objects having __del__ methods, which means the memory
could never be freed.
Thanks Daniel Wiesmann for the report and test, and Tim Graham for the review.
This commit is contained in:
Claude Paroz 2015-07-09 10:52:11 +02:00
parent 0b02ce54cf
commit d72f8862cb
3 changed files with 32 additions and 12 deletions
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18
django/contrib/gis/gdal/raster/source.py
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@ -6,7 +6,7 @@ from django.contrib.gis.gdal.base import GDALBase
from django.contrib.gis.gdal.driver import Driver
from django.contrib.gis.gdal.error import GDALException
from django.contrib.gis.gdal.prototypes import raster as capi
from django.contrib.gis.gdal.raster.band import GDALBand
from django.contrib.gis.gdal.raster.band import BandList
from django.contrib.gis.gdal.raster.const import GDAL_RESAMPLE_ALGORITHMS
from django.contrib.gis.gdal.srs import SpatialReference, SRSException
from django.contrib.gis.geometry.regex import json_regex
@ -15,7 +15,6 @@ from django.utils.encoding import (
force_bytes, force_text, python_2_unicode_compatible,
)
from django.utils.functional import cached_property
from django.utils.six.moves import range
class TransformPoint(list):
@ -108,9 +107,10 @@ class GDALRaster(GDALBase):
# Set band data if provided
for i, band_input in enumerate(ds_input.get('bands', [])):
self.bands[i].data(band_input['data'])
band = self.bands[i]
band.data(band_input['data'])
if 'nodata_value' in band_input:
self.bands[i].nodata_value = band_input['nodata_value']
band.nodata_value = band_input['nodata_value']
# Set SRID
self.srs = ds_input.get('srid')
@ -273,15 +273,9 @@ class GDALRaster(GDALBase):
return xmin, ymin, xmax, ymax
@cached_property
@property
def bands(self):
"""
Returns the bands of this raster as a list of GDALBand instances.
"""
bands = []
for idx in range(1, capi.get_ds_raster_count(self._ptr) + 1):
bands.append(GDALBand(self, idx))
return bands
return BandList(self)
def warp(self, ds_input, resampling='NearestNeighbour', max_error=0.0):
"""