I sorted it out subclassing LayerMapping and adding a method get_values() that instead of saving the retrieved data, returns them for any use or manipulation.The get_values method is a copy of the LayerMapping::save() method that returns the values instead of saving them. I am using django 1.5
import os
from django.contrib.gis.utils import LayerMapping
import sys
class MyMapping(LayerMapping):
def get_values(self, verbose=False, fid_range=False, step=False,
progress=False, silent=False, stream=sys.stdout, strict=False):
"""
Returns the contents from the OGR DataSource Layer
according to the mapping dictionary given at initialization.
Keyword Parameters:
verbose:
If set, information will be printed subsequent to each model save
executed on the database.
fid_range:
May be set with a slice or tuple of (begin, end) feature ID's to map
from the data source. In other words, this keyword enables the user
to selectively import a subset range of features in the geographic
data source.
step:
If set with an integer, transactions will occur at every step
interval. For example, if step=1000, a commit would occur after
the 1,000th feature, the 2,000th feature etc.
progress:
When this keyword is set, status information will be printed giving
the number of features processed and sucessfully saved. By default,
progress information will pe printed every 1000 features processed,
however, this default may be overridden by setting this keyword with an
integer for the desired interval.
stream:
Status information will be written to this file handle. Defaults to
using `sys.stdout`, but any object with a `write` method is supported.
silent:
By default, non-fatal error notifications are printed to stdout, but
this keyword may be set to disable these notifications.
strict:
Execution of the model mapping will cease upon the first error
encountered. The default behavior is to attempt to continue.
"""
# Getting the default Feature ID range.
default_range = self.check_fid_range(fid_range)
# Setting the progress interval, if requested.
if progress:
if progress is True or not isinstance(progress, int):
progress_interval = 1000
else:
progress_interval = progress
# Defining the 'real' save method, utilizing the transaction
# decorator created during initialization.
@self.transaction_decorator
def _get_values(feat_range=default_range, num_feat=0, num_saved=0):
if feat_range:
layer_iter = self.layer[feat_range]
else:
layer_iter = self.layer
for feat in layer_iter:
num_feat += 1
# Getting the keyword arguments
try:
kwargs = self.feature_kwargs(feat)
except LayerMapError, msg:
# Something borked the validation
if strict: raise
elif not silent:
stream.write('Ignoring Feature ID %s because: %s\n' % (feat.fid, msg))
else:
# Constructing the model using the keyword args
is_update = False
if self.unique:
# If we want unique models on a particular field, handle the
# geometry appropriately.
try:
# Getting the keyword arguments and retrieving
# the unique model.
u_kwargs = self.unique_kwargs(kwargs)
m = self.model.objects.using(self.using).get(**u_kwargs)
is_update = True
# Getting the geometry (in OGR form), creating
# one from the kwargs WKT, adding in additional
# geometries, and update the attribute with the
# just-updated geometry WKT.
geom = getattr(m, self.geom_field).ogr
new = OGRGeometry(kwargs[self.geom_field])
for g in new: geom.add(g)
setattr(m, self.geom_field, geom.wkt)
except ObjectDoesNotExist:
# No unique model exists yet, create.
m = self.model(**kwargs)
else:
m = self.model(**kwargs)
try:
# Attempting to save.
pippo = kwargs
num_saved += 1
if verbose: stream.write('%s: %s\n' % (is_update and 'Updated' or 'Saved', m))
except SystemExit:
raise
except Exception, msg:
if self.transaction_mode == 'autocommit':
# Rolling back the transaction so that other model saves
# will work.
transaction.rollback_unless_managed()
if strict:
# Bailing out if the `strict` keyword is set.
if not silent:
stream.write('Failed to save the feature (id: %s) into the model with the keyword arguments:\n' % feat.fid)
stream.write('%s\n' % kwargs)
raise
elif not silent:
stream.write('Failed to save %s:\n %s\nContinuing\n' % (kwargs, msg))
# Printing progress information, if requested.
if progress and num_feat % progress_interval == 0:
stream.write('Processed %d features, saved %d ...\n' % (num_feat, num_saved))
# Only used for status output purposes -- incremental saving uses the
# values returned here.
return pippo
nfeat = self.layer.num_feat
if step and isinstance(step, int) and step < nfeat:
# Incremental saving is requested at the given interval (step)
if default_range:
raise LayerMapError('The `step` keyword may not be used in conjunction with the `fid_range` keyword.')
beg, num_feat, num_saved = (0, 0, 0)
indices = range(step, nfeat, step)
n_i = len(indices)
for i, end in enumerate(indices):
# Constructing the slice to use for this step; the last slice is
# special (e.g, [100:] instead of [90:100]).
if i + 1 == n_i: step_slice = slice(beg, None)
else: step_slice = slice(beg, end)
try:
pippo = _get_values(step_slice, num_feat, num_saved)
beg = end
except:
stream.write('%s\nFailed to save slice: %s\n' % ('=-' * 20, step_slice))
raise
else:
# Otherwise, just calling the previously defined _save() function.
return _get_values()
In a custom save or save_model method you can then use:
track_mapping = {'nome': 'name',
'track' : 'MULTILINESTRING'}
targetPath = "/my/gpx/file/path.gpx"
gpx_file = DataSource(targetPath)
mytrack = MyMapping(GPXTrack, gpx_file, track_mapping, layer='tracks')
pippo = mytrack.get_values()
obj.track = pippo['track']