def query(self, msg_type, query, *parameters):
'''Performs a query against a q service.
In typical use case, `query` is the name of the function to call and
`parameters` are its parameters. When `parameters` list is empty, the
query can be an arbitrary q expression (e.g. ``0 +/ til 100``).
Calls a anonymous function with a single parameter:
>>> q.query(qconnection.MessageType.SYNC,'{til x}', 10)
Executes a q expression:
>>> q.query(qconnection.MessageType.SYNC,'til 10')
:Parameters:
- `msg_type` (one of the constants defined in :class:`.MessageType`) -
type of the query to be executed
- `query` (`string`) - query to be executed
- `parameters` (`list` or `None`) - parameters for the query
:raises: :class:`.QConnectionException`, :class:`.QWriterException`
'''
if not self._connection:
raise QConnectionException('Connection is not established.')
if parameters and len(parameters) > 8:
raise QWriterException('Too many parameters.')
if not parameters or len(parameters) == 0:
self._writer.write(query, msg_type)
else:
self._writer.write([query] + list(parameters), msg_type)
def query(self, msg_type, query, *parameters):
if parameters and len(parameters) > 8:
raise QWriterException('Too many parameters.')
if not parameters or len(parameters) == 0:
self.transport.write(self._writer.write(query, msg_type))
else:
self.transport.write(
self._writer.write([query] + list(parameters), msg_type))
def _write_pandas_series(self, data, qtype=None):
if qtype is not None:
qtype = -abs(qtype)
if qtype is None and hasattr(data, 'meta'):
qtype = -abs(data.meta.qtype)
if qtype is None and 'meta' in data.attrs:
qtype = -abs(data.attrs['meta'].qtype)
if data.dtype == '|S1':
qtype = QCHAR
if qtype is None:
qtype = Q_TYPE.get(data.dtype.type, None)
if qtype is None and data.dtype.type in (numpy.datetime64,
numpy.timedelta64):
qtype = TEMPORAL_PY_TYPE.get(str(data.dtype), None)
if qtype is None:
# determinate type based on first element of the numpy array
qtype = Q_TYPE.get(type(data.iloc[0]), QGENERAL_LIST)
if qtype == QSTRING:
# assume we have a generic list of strings -> force representation as symbol list
qtype = QSYMBOL
if qtype is None:
raise QWriterException('Unable to serialize pandas series %s' %
data)
if qtype == QGENERAL_LIST:
self._write_generic_list(data.values)
elif qtype == QCHAR:
self._write_string(
data.replace(numpy.nan,
' ').values.astype(numpy.string_).tostring())
elif data.dtype.type not in (numpy.datetime64, numpy.timedelta64):
data = data.fillna(QNULLMAP[-abs(qtype)][1])
data = data.values
if PY_TYPE[qtype] != data.dtype:
data = data.astype(PY_TYPE[qtype])
self._write_list(data, qtype=qtype)
else:
data = data.values
data = data.astype(TEMPORAL_Q_TYPE[qtype])
self._write_list(data, qtype=qtype)
def _write_pandas_series(self, data, qtype=None):
if qtype is not None:
qtype = -abs(qtype)
if qtype is None and hasattr(data, 'meta'):
qtype = -abs(data.meta.qtype)
if data.dtype == '|S1':
qtype = QCHAR
if qtype is None:
qtype = Q_TYPE.get(data.dtype.type, None)
if qtype is None and data.dtype.type in (numpy.datetime64,
numpy.timedelta64):
qtype = TEMPORAL_PY_TYPE.get(str(data.dtype), None)
if qtype is None:
# determinate type based on first element of the numpy array
qtype = Q_TYPE.get(type(data[0]), QGENERAL_LIST)
if qtype is None:
raise QWriterException('Unable to serialize pandas series %s' %
data)
if qtype == QGENERAL_LIST:
self._write_generic_list(data.as_matrix())
elif qtype == QCHAR:
self._write_string(
data.replace(numpy.nan,
' ').as_matrix().astype(numpy.string_).tostring())
elif data.dtype.type not in (numpy.datetime64, numpy.timedelta64):
data = data.fillna(QNULLMAP[-abs(qtype)][1])
data = data.as_matrix()
if PY_TYPE[qtype] != data.dtype:
data = data.astype(PY_TYPE[qtype])
self._write_list(data, qtype=qtype)
else:
data = data.as_matrix()
data = data.astype(TEMPORAL_Q_TYPE[qtype])
self._write_list(data, qtype=qtype)