Set new Melange version number to 0-5-20090825 in app.yaml.template.
# LayerMapping -- A Django Model/OGR Layer Mapping Utility
"""
The LayerMapping class provides a way to map the contents of OGR
vector files (e.g. SHP files) to Geographic-enabled Django models.
This grew out of my personal needs, specifically the code repetition
that went into pulling geometries and fields out of an OGR layer,
converting to another coordinate system (e.g. WGS84), and then inserting
into a GeoDjango model.
Please report any bugs encountered using this utility.
Requirements: OGR C Library (from GDAL) required.
Usage:
lm = LayerMapping(model, source_file, mapping) where,
model:
GeoDjango model (not an instance)
data:
OGR-supported data source file (e.g. a shapefile) or
gdal.DataSource instance
mapping:
A python dictionary, keys are strings corresponding
to the GeoDjango model field, and values correspond to
string field names for the OGR feature, or if the model field
is a geographic then it should correspond to the OGR
geometry type, e.g. 'POINT', 'LINESTRING', 'POLYGON'.
Keyword Args:
layer:
The index of the layer to use from the Data Source (defaults to 0)
source_srs:
Use this to specify the source SRS manually (for example,
some shapefiles don't come with a '.prj' file). An integer SRID,
a string WKT, and SpatialReference objects are valid parameters.
encoding:
Specifies the encoding of the string in the OGR data source.
For example, 'latin-1', 'utf-8', and 'cp437' are all valid
encoding parameters.
transaction_mode:
May be 'commit_on_success' (default) or 'autocommit'.
transform:
Setting this to False will disable all coordinate transformations.
unique:
Setting this to the name, or a tuple of names, from the given
model will create models unique only to the given name(s).
Geometries will from each feature will be added into the collection
associated with the unique model. Forces transaction mode to
be 'autocommit'.
Example:
1. You need a GDAL-supported data source, like a shapefile.
Assume we're using the test_poly SHP file:
>>> from django.contrib.gis.gdal import DataSource
>>> ds = DataSource('test_poly.shp')
>>> layer = ds[0]
>>> print layer.fields # Exploring the fields in the layer, we only want the 'str' field.
['float', 'int', 'str']
>>> print len(layer) # getting the number of features in the layer (should be 3)
3
>>> print layer.geom_type # Should be 3 (a Polygon)
3
>>> print layer.srs # WGS84
GEOGCS["GCS_WGS_1984",
DATUM["WGS_1984",
SPHEROID["WGS_1984",6378137,298.257223563]],
PRIMEM["Greenwich",0],
UNIT["Degree",0.017453292519943295]]
2. Now we define our corresponding Django model (make sure to use syncdb):
from django.contrib.gis.db import models
class TestGeo(models.Model, models.GeoMixin):
name = models.CharField(maxlength=25) # corresponds to the 'str' field
poly = models.PolygonField(srid=4269) # we want our model in a different SRID
objects = models.GeoManager()
def __str__(self):
return 'Name: %s' % self.name
3. Use LayerMapping to extract all the features and place them in the database:
>>> from django.contrib.gis.utils import LayerMapping
>>> from geoapp.models import TestGeo
>>> mapping = {'name' : 'str', # The 'name' model field maps to the 'str' layer field.
'poly' : 'POLYGON', # For geometry fields use OGC name.
} # The mapping is a dictionary
>>> lm = LayerMapping(TestGeo, 'test_poly.shp', mapping)
>>> lm.save(verbose=True) # Save the layermap, imports the data.
Saved: Name: 1
Saved: Name: 2
Saved: Name: 3
LayerMapping just transformed the three geometries from the SHP file from their
source spatial reference system (WGS84) to the spatial reference system of
the GeoDjango model (NAD83). If no spatial reference system is defined for
the layer, use the `source_srs` keyword with a SpatialReference object to
specify one.
"""
import sys
from datetime import date, datetime
from decimal import Decimal
from django.core.exceptions import ObjectDoesNotExist
from django.contrib.gis.db.models import GeometryField
from django.contrib.gis.db.backend import SpatialBackend
from django.contrib.gis.gdal import CoordTransform, DataSource, \
OGRException, OGRGeometry, OGRGeomType, SpatialReference
from django.contrib.gis.gdal.field import \
OFTDate, OFTDateTime, OFTInteger, OFTReal, OFTString, OFTTime
from django.contrib.gis.models import GeometryColumns, SpatialRefSys
from django.db import models, transaction
from django.contrib.localflavor.us.models import USStateField
# LayerMapping exceptions.
class LayerMapError(Exception): pass
class InvalidString(LayerMapError): pass
class InvalidDecimal(LayerMapError): pass
class InvalidInteger(LayerMapError): pass
class MissingForeignKey(LayerMapError): pass
class LayerMapping(object):
"A class that maps OGR Layers to GeoDjango Models."
# Acceptable 'base' types for a multi-geometry type.
MULTI_TYPES = {1 : OGRGeomType('MultiPoint'),
2 : OGRGeomType('MultiLineString'),
3 : OGRGeomType('MultiPolygon'),
}
# Acceptable Django field types and corresponding acceptable OGR
# counterparts.
FIELD_TYPES = {
models.AutoField : OFTInteger,
models.IntegerField : (OFTInteger, OFTReal, OFTString),
models.FloatField : (OFTInteger, OFTReal),
models.DateField : OFTDate,
models.DateTimeField : OFTDateTime,
models.EmailField : OFTString,
models.TimeField : OFTTime,
models.DecimalField : (OFTInteger, OFTReal),
models.CharField : OFTString,
models.SlugField : OFTString,
models.TextField : OFTString,
models.URLField : OFTString,
USStateField : OFTString,
models.XMLField : OFTString,
models.SmallIntegerField : (OFTInteger, OFTReal, OFTString),
models.PositiveSmallIntegerField : (OFTInteger, OFTReal, OFTString),
}
# The acceptable transaction modes.
TRANSACTION_MODES = {'autocommit' : transaction.autocommit,
'commit_on_success' : transaction.commit_on_success,
}
def __init__(self, model, data, mapping, layer=0,
source_srs=None, encoding=None,
transaction_mode='commit_on_success',
transform=True, unique=None):
"""
A LayerMapping object is initialized using the given Model (not an instance),
a DataSource (or string path to an OGR-supported data file), and a mapping
dictionary. See the module level docstring for more details and keyword
argument usage.
"""
# Getting the DataSource and the associated Layer.
if isinstance(data, basestring):
self.ds = DataSource(data)
else:
self.ds = data
self.layer = self.ds[layer]
# Setting the mapping & model attributes.
self.mapping = mapping
self.model = model
# Checking the layer -- intitialization of the object will fail if
# things don't check out before hand.
self.check_layer()
# Getting the geometry column associated with the model (an
# exception will be raised if there is no geometry column).
self.geo_col = self.geometry_column()
# Checking the source spatial reference system, and getting
# the coordinate transformation object (unless the `transform`
# keyword is set to False)
if transform:
self.source_srs = self.check_srs(source_srs)
self.transform = self.coord_transform()
else:
self.transform = transform
# Setting the encoding for OFTString fields, if specified.
if encoding:
# Making sure the encoding exists, if not a LookupError
# exception will be thrown.
from codecs import lookup
lookup(encoding)
self.encoding = encoding
else:
self.encoding = None
if unique:
self.check_unique(unique)
transaction_mode = 'autocommit' # Has to be set to autocommit.
self.unique = unique
else:
self.unique = None
# Setting the transaction decorator with the function in the
# transaction modes dictionary.
if transaction_mode in self.TRANSACTION_MODES:
self.transaction_decorator = self.TRANSACTION_MODES[transaction_mode]
self.transaction_mode = transaction_mode
else:
raise LayerMapError('Unrecognized transaction mode: %s' % transaction_mode)
#### Checking routines used during initialization ####
def check_fid_range(self, fid_range):
"This checks the `fid_range` keyword."
if fid_range:
if isinstance(fid_range, (tuple, list)):
return slice(*fid_range)
elif isinstance(fid_range, slice):
return fid_range
else:
raise TypeError
else:
return None
def check_layer(self):
"""
This checks the Layer metadata, and ensures that it is compatible
with the mapping information and model. Unlike previous revisions,
there is no need to increment through each feature in the Layer.
"""
# The geometry field of the model is set here.
# TODO: Support more than one geometry field / model. However, this
# depends on the GDAL Driver in use.
self.geom_field = False
self.fields = {}
# Getting lists of the field names and the field types available in
# the OGR Layer.
ogr_fields = self.layer.fields
ogr_field_types = self.layer.field_types
# Function for determining if the OGR mapping field is in the Layer.
def check_ogr_fld(ogr_map_fld):
try:
idx = ogr_fields.index(ogr_map_fld)
except ValueError:
raise LayerMapError('Given mapping OGR field "%s" not found in OGR Layer.' % ogr_map_fld)
return idx
# No need to increment through each feature in the model, simply check
# the Layer metadata against what was given in the mapping dictionary.
for field_name, ogr_name in self.mapping.items():
# Ensuring that a corresponding field exists in the model
# for the given field name in the mapping.
try:
model_field = self.model._meta.get_field(field_name)
except models.fields.FieldDoesNotExist:
raise LayerMapError('Given mapping field "%s" not in given Model fields.' % field_name)
# Getting the string name for the Django field class (e.g., 'PointField').
fld_name = model_field.__class__.__name__
if isinstance(model_field, GeometryField):
if self.geom_field:
raise LayerMapError('LayerMapping does not support more than one GeometryField per model.')
try:
gtype = OGRGeomType(ogr_name)
except OGRException:
raise LayerMapError('Invalid mapping for GeometryField "%s".' % field_name)
# Making sure that the OGR Layer's Geometry is compatible.
ltype = self.layer.geom_type
if not (gtype == ltype or self.make_multi(ltype, model_field)):
raise LayerMapError('Invalid mapping geometry; model has %s, feature has %s.' % (fld_name, gtype))
# Setting the `geom_field` attribute w/the name of the model field
# that is a Geometry.
self.geom_field = field_name
fields_val = model_field
elif isinstance(model_field, models.ForeignKey):
if isinstance(ogr_name, dict):
# Is every given related model mapping field in the Layer?
rel_model = model_field.rel.to
for rel_name, ogr_field in ogr_name.items():
idx = check_ogr_fld(ogr_field)
try:
rel_field = rel_model._meta.get_field(rel_name)
except models.fields.FieldDoesNotExist:
raise LayerMapError('ForeignKey mapping field "%s" not in %s fields.' %
(rel_name, rel_model.__class__.__name__))
fields_val = rel_model
else:
raise TypeError('ForeignKey mapping must be of dictionary type.')
else:
# Is the model field type supported by LayerMapping?
if not model_field.__class__ in self.FIELD_TYPES:
raise LayerMapError('Django field type "%s" has no OGR mapping (yet).' % fld_name)
# Is the OGR field in the Layer?
idx = check_ogr_fld(ogr_name)
ogr_field = ogr_field_types[idx]
# Can the OGR field type be mapped to the Django field type?
if not issubclass(ogr_field, self.FIELD_TYPES[model_field.__class__]):
raise LayerMapError('OGR field "%s" (of type %s) cannot be mapped to Django %s.' %
(ogr_field, ogr_field.__name__, fld_name))
fields_val = model_field
self.fields[field_name] = fields_val
def check_srs(self, source_srs):
"Checks the compatibility of the given spatial reference object."
if isinstance(source_srs, SpatialReference):
sr = source_srs
elif isinstance(source_srs, SpatialRefSys):
sr = source_srs.srs
elif isinstance(source_srs, (int, basestring)):
sr = SpatialReference(source_srs)
else:
# Otherwise just pulling the SpatialReference from the layer
sr = self.layer.srs
if not sr:
raise LayerMapError('No source reference system defined.')
else:
return sr
def check_unique(self, unique):
"Checks the `unique` keyword parameter -- may be a sequence or string."
if isinstance(unique, (list, tuple)):
# List of fields to determine uniqueness with
for attr in unique:
if not attr in self.mapping: raise ValueError
elif isinstance(unique, basestring):
# Only a single field passed in.
if unique not in self.mapping: raise ValueError
else:
raise TypeError('Unique keyword argument must be set with a tuple, list, or string.')
#### Keyword argument retrieval routines ####
def feature_kwargs(self, feat):
"""
Given an OGR Feature, this will return a dictionary of keyword arguments
for constructing the mapped model.
"""
# The keyword arguments for model construction.
kwargs = {}
# Incrementing through each model field and OGR field in the
# dictionary mapping.
for field_name, ogr_name in self.mapping.items():
model_field = self.fields[field_name]
if isinstance(model_field, GeometryField):
# Verify OGR geometry.
val = self.verify_geom(feat.geom, model_field)
elif isinstance(model_field, models.base.ModelBase):
# The related _model_, not a field was passed in -- indicating
# another mapping for the related Model.
val = self.verify_fk(feat, model_field, ogr_name)
else:
# Otherwise, verify OGR Field type.
val = self.verify_ogr_field(feat[ogr_name], model_field)
# Setting the keyword arguments for the field name with the
# value obtained above.
kwargs[field_name] = val
return kwargs
def unique_kwargs(self, kwargs):
"""
Given the feature keyword arguments (from `feature_kwargs`) this routine
will construct and return the uniqueness keyword arguments -- a subset
of the feature kwargs.
"""
if isinstance(self.unique, basestring):
return {self.unique : kwargs[self.unique]}
else:
return dict((fld, kwargs[fld]) for fld in self.unique)
#### Verification routines used in constructing model keyword arguments. ####
def verify_ogr_field(self, ogr_field, model_field):
"""
Verifies if the OGR Field contents are acceptable to the Django
model field. If they are, the verified value is returned,
otherwise the proper exception is raised.
"""
if (isinstance(ogr_field, OFTString) and
isinstance(model_field, (models.CharField, models.TextField))):
if self.encoding:
# The encoding for OGR data sources may be specified here
# (e.g., 'cp437' for Census Bureau boundary files).
val = unicode(ogr_field.value, self.encoding)
else:
val = ogr_field.value
if len(val) > model_field.max_length:
raise InvalidString('%s model field maximum string length is %s, given %s characters.' %
(model_field.name, model_field.max_length, len(val)))
elif isinstance(ogr_field, OFTReal) and isinstance(model_field, models.DecimalField):
try:
# Creating an instance of the Decimal value to use.
d = Decimal(str(ogr_field.value))
except:
raise InvalidDecimal('Could not construct decimal from: %s' % ogr_field.value)
# Getting the decimal value as a tuple.
dtup = d.as_tuple()
digits = dtup[1]
d_idx = dtup[2] # index where the decimal is
# Maximum amount of precision, or digits to the left of the decimal.
max_prec = model_field.max_digits - model_field.decimal_places
# Getting the digits to the left of the decimal place for the
# given decimal.
if d_idx < 0:
n_prec = len(digits[:d_idx])
else:
n_prec = len(digits) + d_idx
# If we have more than the maximum digits allowed, then throw an
# InvalidDecimal exception.
if n_prec > max_prec:
raise InvalidDecimal('A DecimalField with max_digits %d, decimal_places %d must round to an absolute value less than 10^%d.' %
(model_field.max_digits, model_field.decimal_places, max_prec))
val = d
elif isinstance(ogr_field, (OFTReal, OFTString)) and isinstance(model_field, models.IntegerField):
# Attempt to convert any OFTReal and OFTString value to an OFTInteger.
try:
val = int(ogr_field.value)
except:
raise InvalidInteger('Could not construct integer from: %s' % ogr_field.value)
else:
val = ogr_field.value
return val
def verify_fk(self, feat, rel_model, rel_mapping):
"""
Given an OGR Feature, the related model and its dictionary mapping,
this routine will retrieve the related model for the ForeignKey
mapping.
"""
# TODO: It is expensive to retrieve a model for every record --
# explore if an efficient mechanism exists for caching related
# ForeignKey models.
# Constructing and verifying the related model keyword arguments.
fk_kwargs = {}
for field_name, ogr_name in rel_mapping.items():
fk_kwargs[field_name] = self.verify_ogr_field(feat[ogr_name], rel_model._meta.get_field(field_name))
# Attempting to retrieve and return the related model.
try:
return rel_model.objects.get(**fk_kwargs)
except ObjectDoesNotExist:
raise MissingForeignKey('No ForeignKey %s model found with keyword arguments: %s' % (rel_model.__name__, fk_kwargs))
def verify_geom(self, geom, model_field):
"""
Verifies the geometry -- will construct and return a GeometryCollection
if necessary (for example if the model field is MultiPolygonField while
the mapped shapefile only contains Polygons).
"""
if self.make_multi(geom.geom_type, model_field):
# Constructing a multi-geometry type to contain the single geometry
multi_type = self.MULTI_TYPES[geom.geom_type.num]
g = OGRGeometry(multi_type)
g.add(geom)
else:
g = geom
# Transforming the geometry with our Coordinate Transformation object,
# but only if the class variable `transform` is set w/a CoordTransform
# object.
if self.transform: g.transform(self.transform)
# Returning the WKT of the geometry.
return g.wkt
#### Other model methods ####
def coord_transform(self):
"Returns the coordinate transformation object."
try:
# Getting the target spatial reference system
target_srs = SpatialRefSys.objects.get(srid=self.geo_col.srid).srs
# Creating the CoordTransform object
return CoordTransform(self.source_srs, target_srs)
except Exception, msg:
raise LayerMapError('Could not translate between the data source and model geometry: %s' % msg)
def geometry_column(self):
"Returns the GeometryColumn model associated with the geographic column."
# Getting the GeometryColumn object.
try:
db_table = self.model._meta.db_table
geo_col = self.geom_field
if SpatialBackend.name == 'oracle':
# Making upper case for Oracle.
db_table = db_table.upper()
geo_col = geo_col.upper()
gc_kwargs = {GeometryColumns.table_name_col() : db_table,
GeometryColumns.geom_col_name() : geo_col,
}
return GeometryColumns.objects.get(**gc_kwargs)
except Exception, msg:
raise LayerMapError('Geometry column does not exist for model. (did you run syncdb?):\n %s' % msg)
def make_multi(self, geom_type, model_field):
"""
Given the OGRGeomType for a geometry and its associated GeometryField,
determine whether the geometry should be turned into a GeometryCollection.
"""
return (geom_type.num in self.MULTI_TYPES and
model_field.__class__.__name__ == 'Multi%s' % geom_type.django)
def save(self, verbose=False, fid_range=False, step=False,
progress=False, silent=False, stream=sys.stdout, strict=False):
"""
Saves the contents from the OGR DataSource Layer into the database
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 _save(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.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.
m.save()
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 num_saved, num_feat
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:
num_feat, num_saved = _save(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.
_save()