def _make_udt_tuple_type(cls, name, field_names):
# fallback to positional named, then unnamed tuples
# for CQL identifiers that aren't valid in Python,
try:
t = namedtuple(name, field_names)
except ValueError:
try:
t = namedtuple(name, util._positional_rename_invalid_identifiers(field_names))
log.warn("could not create a namedtuple for '%s' because one or more field names are not valid Python identifiers (%s); " \
"returning positionally-named fields" % (name, field_names))
except ValueError:
t = None
log.warn("could not create a namedtuple for '%s' because the name is not a valid Python identifier; " \
"will return tuples in its place" % (name,))
return t
def _make_udt_tuple_type(cls, name, field_names):
# fallback to positional named, then unnamed tuples
# for CQL identifiers that aren't valid in Python,
try:
t = namedtuple(name, field_names)
except ValueError:
try:
t = namedtuple(name, util._positional_rename_invalid_identifiers(field_names))
log.warn("could not create a namedtuple for '%s' because one or more field names are not valid Python identifiers (%s); " \
"returning positionally-named fields" % (name, field_names))
except ValueError:
t = None
log.warn("could not create a namedtuple for '%s' because the name is not a valid Python identifier; " \
"will return tuples in its place" % (name,))
return t
def named_tuple_factory(colnames, rows):
"""
Returns each row as a `namedtuple <https://docs.python.org/2/library/collections.html#collections.namedtuple>`_.
This is the default row factory.
Example::
>>> from cassandra.query import named_tuple_factory
>>> session = cluster.connect('mykeyspace')
>>> session.row_factory = named_tuple_factory
>>> rows = session.execute("SELECT name, age FROM users LIMIT 1")
>>> user = rows[0]
>>> # you can access field by their name:
>>> print "name: %s, age: %d" % (user.name, user.age)
name: Bob, age: 42
>>> # or you can access fields by their position (like a tuple)
>>> name, age = user
>>> print "name: %s, age: %d" % (name, age)
name: Bob, age: 42
>>> name = user[0]
>>> age = user[1]
>>> print "name: %s, age: %d" % (name, age)
name: Bob, age: 42
.. versionchanged:: 2.0.0
moved from ``cassandra.decoder`` to ``cassandra.query``
"""
clean_column_names = map(_clean_column_name, colnames)
try:
Row = namedtuple('Row', clean_column_names)
except Exception:
log.warning(
"Failed creating named tuple for results with column names %s (cleaned: %s) "
"(see Python 'namedtuple' documentation for details on name rules). "
"Results will be returned with positional names. "
"Avoid this by choosing different names, using SELECT \"<col name>\" AS aliases, "
"or specifying a different row_factory on your Session" %
(colnames, clean_column_names))
Row = namedtuple(
'Row', _positional_rename_invalid_identifiers(clean_column_names))
return [Row(*row) for row in rows]
def named_tuple_factory(colnames, rows):
"""
Returns each row as a `namedtuple <https://docs.python.org/2/library/collections.html#collections.namedtuple>`_.
This is the default row factory.
Example::
>>> from cassandra.query import named_tuple_factory
>>> session = cluster.connect('mykeyspace')
>>> session.row_factory = named_tuple_factory
>>> rows = session.execute("SELECT name, age FROM users LIMIT 1")
>>> user = rows[0]
>>> # you can access field by their name:
>>> print "name: %s, age: %d" % (user.name, user.age)
name: Bob, age: 42
>>> # or you can access fields by their position (like a tuple)
>>> name, age = user
>>> print "name: %s, age: %d" % (name, age)
name: Bob, age: 42
>>> name = user[0]
>>> age = user[1]
>>> print "name: %s, age: %d" % (name, age)
name: Bob, age: 42
.. versionchanged:: 2.0.0
moved from ``cassandra.decoder`` to ``cassandra.query``
"""
clean_column_names = map(_clean_column_name, colnames)
try:
Row = namedtuple("Row", clean_column_names)
except Exception:
log.warning(
"Failed creating named tuple for results with column names %s (cleaned: %s) "
"(see Python 'namedtuple' documentation for details on name rules). "
"Results will be returned with positional names. "
'Avoid this by choosing different names, using SELECT "<col name>" AS aliases, '
"or specifying a different row_factory on your Session" % (colnames, clean_column_names)
)
Row = namedtuple("Row", _positional_rename_invalid_identifiers(clean_column_names))
return [Row(*row) for row in rows]
