def _genrootclass(name):
"""Creates a new root metric class."""
class Cls(object):
dependencies = ()
@property
def schema(self):
"""Defines schema for root metric if provided."""
if self._schema is not None:
return self._schema
# fill in schema code
@property
def name(self):
"""Assigns a name to root metric object."""
return self.__class__.__name__
def __init__(self, db):
"""Constructor for root metric object in database."""
self._schema = None
self.db = db
def __call__(self, conds=None, *args, **kwargs):
"""Retrieves a root metric with given input conditions."""
if self.name not in self.db.tables:
return None
return self.db.query(self.name, conds=conds)
Cls.__name__ = str(name)
register_metric(Cls)
return Cls
def _genrootclass(name):
"""Creates a new root metric class."""
class Cls(object):
dependencies = ()
@property
def schema(self):
"""Defines schema for root metric if provided."""
if self._schema is not None:
return self._schema
# fill in schema code
@property
def name(self):
"""Assigns a name to root metric object."""
return self.__class__.__name__
def __init__(self, db):
"""Constructor for root metric object in database."""
self._schema = None
self.db = db
def __call__(self, conds=None, *args, **kwargs):
"""Retrieves a root metric with given input conditions."""
if self.name not in self.db.tables:
return None
return self.db.query(self.name, conds=conds)
Cls.__name__ = str(name)
register_metric(Cls)
return Cls
def _genmetricclass(f, name, depends, scheme):
"""Creates a new metric class with a given name, dependencies, and schema.
Parameters
----------
name : str
Metric name
depends : list of lists (table name, tuple of indices, column name)
Dependencies on other database tables (metrics or root metrics)
scheme : list of tuples (column name, data type)
Schema for metric
"""
if not isinstance(scheme, schemas.schema):
scheme = schemas.schema(scheme)
class Cls(Metric):
dependencies = depends
schema = scheme
func = staticmethod(f)
__doc__ = inspect.getdoc(f)
def __init__(self, db):
"""Constructor for metric object in database."""
super(Cls, self).__init__(db)
def __call__(self,
frames,
conds=None,
known_tables=None,
*args,
**kwargs):
"""Computes metric for given input data and conditions."""
# FIXME test if I already exist in the db, read in if I do
if known_tables is None:
known_tables = self.db.tables()
if self.name in known_tables:
return self.db.query(self.name, conds=conds)
return f(*frames)
Cls.__name__ = str(name)
register_metric(Cls)
return Cls
def _genmetricclass(f, name, depends, scheme):
"""Creates a new metric class with a given name, dependencies, and schema.
Parameters
----------
name : str
Metric name
depends : list of lists (table name, tuple of indices, column name)
Dependencies on other database tables (metrics or root metrics)
scheme : list of tuples (column name, data type)
Schema for metric
"""
if not isinstance(scheme, schemas.schema):
scheme = schemas.schema(scheme)
class Cls(Metric):
dependencies = depends
schema = scheme
func = staticmethod(f)
__doc__ = inspect.getdoc(f)
def __init__(self, db):
"""Constructor for metric object in database."""
super(Cls, self).__init__(db)
def __call__(self, frames, conds=None, known_tables=None, *args, **kwargs):
"""Computes metric for given input data and conditions."""
# FIXME test if I already exist in the db, read in if I do
if known_tables is None:
known_tables = self.db.tables()
if self.name in known_tables:
return self.db.query(self.name, conds=conds)
return f(*frames)
Cls.__name__ = str(name)
register_metric(Cls)
return Cls