def __getitem__(self, index):
slice_ = combine_slices(self._slice, fix_slice(index, self.shape))
scheme, netloc, path, query, fragment = urlsplit(self.url)
url = urlunsplit((
scheme, netloc, path + '.dods',
quote(self.id) + hyperslab(slice_) + '&' + query,
fragment))
resp, data = request(url)
dds, xdrdata = data.split('\nData:\n', 1)
dataset = DDSParser(dds).parse()
data = data2 = DapUnpacker(xdrdata, dataset).getvalue()
# Retrieve the data from any parent structure(s).
for var in walk(dataset):
if type(var) in (StructureType, DatasetType):
data = data[0]
elif var.id == self.id:
return data
# Some old servers return the wrong response. :-/
# I found a server that would return an array to a request
# for an array inside a grid (instead of a structure with
# the array); this will take care of it.
for var in walk(dataset):
if type(var) in (StructureType, DatasetType):
data2 = data2[0]
elif self.id.endswith(var.id):
return data2
def __getitem__(self, index):
slice_ = combine_slices(self._slice, fix_slice(index, self.shape))
scheme, netloc, path, query, fragment = urlsplit(self.url)
url = urlunsplit((scheme, netloc, path + '.dods',
self.id + hyperslab(slice_) + '&' + query, fragment))
resp, data = request(url)
dds, xdrdata = data.split('\nData:\n', 1)
dataset = DDSParser(dds).parse()
data = data2 = DapUnpacker(xdrdata, dataset).getvalue()
# Retrieve the data from any parent structure(s).
for var in walk(dataset):
if type(var) in (StructureType, DatasetType):
data = data[0]
elif var.id == self.id:
return data
# Some old servers return the wrong response. :-/
# I found a server that would return an array to a request
# for an array inside a grid (instead of a structure with
# the array); this will take care of it.
for var in walk(dataset):
if type(var) in (StructureType, DatasetType):
data2 = data2[0]
elif self.id.endswith(var.id):
return data2
def open_dods(url, get_metadata=False):
"""
Download data from a DODS response and build a dataset.
This function is useful to open "raw" URLs.
"""
resp, data = request(url)
dds, xdrdata = data.split('\nData:\n', 1)
dataset = DDSParser(dds).parse()
dataset.data = DapUnpacker(xdrdata, dataset).getvalue()
if get_metadata:
scheme, netloc, path, query, fragment = urlsplit(url)
dasurl = urlunsplit(
(scheme, netloc, path[:-5] + '.das', query, fragment))
resp, das = request(dasurl)
dataset = DASParser(das, dataset).parse()
return dataset
def _ddsdas(url):
"""
Build the dataset from the DDS+DAS responses.
This function builds the dataset object from the DDS and DAS
responses, adding Proxy objects to the variables.
"""
scheme, netloc, path, query, fragment = urlsplit(url)
ddsurl = urlunsplit(
(scheme, netloc, path + '.dds', query, fragment))
dasurl = urlunsplit(
(scheme, netloc, path + '.das', query, fragment))
respdds, dds = request(ddsurl)
respdas, das = request(dasurl)
# Build the dataset structure and attributes.
dataset = DDSParser(dds).parse()
dataset = DASParser(das, dataset).parse()
return dataset
def __iter__(self):
scheme, netloc, path, query, fragment = urlsplit(self.url)
id_ = ','.join('%s.%s' % (self.id, child) for child in self.children) or self.id
url = urlunsplit((
scheme, netloc, path + '.dods',
quote(id_) + hyperslab(self._slice) + '&' + query,
fragment))
resp, data = request(url)
dds, xdrdata = data.split('\nData:\n', 1)
dataset = DDSParser(dds).parse()
dataset.data = DapUnpacker(xdrdata, dataset).getvalue()
dataset._set_id()
# Strip any projections from the request id.
id_ = re.sub('\[.*?\]', '', self.id)
# And return the proper data.
for var in walk(dataset):
if var.id == id_:
data = var.data
if isinstance(var, SequenceType):
order = [var.keys().index(k) for k in self.children]
data = reorder(order, data, var._nesting_level)
return iter(data)
def __iter__(self):
scheme, netloc, path, query, fragment = urlsplit(self.url)
id_ = ','.join('%s.%s' % (self.id, child)
for child in self.children) or self.id
url = urlunsplit(
(scheme, netloc, path + '.dods',
id_ + hyperslab(self._slice) + '&' + query, fragment))
resp, data = request(url)
dds, xdrdata = data.split('\nData:\n', 1)
dataset = DDSParser(dds).parse()
dataset.data = DapUnpacker(xdrdata, dataset).getvalue()
dataset._set_id()
# Strip any projections from the request id.
id_ = re.sub('\[.*?\]', '', self.id)
# And return the proper data.
for var in walk(dataset):
if var.id == id_:
data = var.data
if isinstance(var, SequenceType):
order = [var.keys().index(k) for k in self.children]
data = reorder(order, data, var._nesting_level)
return iter(data)
