def grok_data(self):
# XXX when data is a csv/txt/xl file, we want to read timestamps in
# there too
# XXX hooks won't catch change to timestamps
if super(NPTSImportAdapter, self).grok_data():
return # already processed
numpy_array = self.grok_timestamps()
tstamp_data = Binary()
compressed_data = zlib.compress(pickle.dumps(numpy_array, protocol=2))
tstamp_data.write(compressed_data)
self.entity.cw_edited['timestamps'] = tstamp_data
self.entity.timestamps_array = numpy_array
def test_write(self):
b = Binary()
b.write(b'toto')
b.write(bytearray(b'toto'))
b.write(memoryview(b'toto'))
with self.assertRaises((AssertionError, TypeError)):
# TypeError is raised by BytesIO if python runs with -O
b.write(u'toto')
def grok_data(self):
""" self.data is something such as an excel file or CSV data or a pickled
numpy array or an already processed binary.
Ensure it's a pickle numpy array before storing object in db.
If data seems to be already processed, return True, else return False.
"""
entity = self.entity
try:
filename = entity.data.filename.lower()
except AttributeError:
data = entity.data
if isinstance(data, Binary):
return True
# if not isinstance(data, numpy.ndarray):
# raise TypeError('data is neither a Binary nor a numpy array (%s)' % type(data))
numpy_array = data
else:
adapter = self._cw.vreg['adapters'].select_or_none(
'source_to_numpy_array',
self._cw,
entity=entity,
filename=filename)
if adapter is None:
msg = self._cw._(
'Unsupported file type %s') % entity.data.filename
raise ValidationError(entity.eid, {'data': msg})
numpy_array = adapter.to_numpy_array(entity.data, filename)
if numpy_array.ndim != 1:
raise ValidationError(
entity.eid, {'data': _('data must be a 1-dimensional array')})
if numpy_array.size == 0:
raise ValidationError(
entity.eid, {'data': _('data must have at least one value')})
data = Binary()
compressed_data = zlib.compress(pickle.dumps(numpy_array, protocol=2))
data.write(compressed_data)
entity.cw_edited['data'] = data
entity.array = numpy_array
return False