def test_insert():
with test_csv.bayesdb_csv_stream(test_csv.csv_data) as (bdb, f):
bayeslite.bayesdb_read_csv(bdb, 't', f, header=True, create=True)
guess.bayesdb_guess_generator(bdb, 't_cc', 't', 'crosscat')
bdb.execute('initialize 2 models for t_cc')
bdb.execute('analyze t_cc for 1 iteration wait')
generator_id = core.bayesdb_get_generator(bdb, 't_cc')
row = (41, 'F', 96000, 73, 'data science', 2)
bqlfn.bayesdb_insert(bdb, generator_id, row)
def test_insert():
with test_csv.bayesdb_csv_stream(test_csv.csv_data) as (bdb, f):
bayeslite.bayesdb_read_csv(bdb, 't', f, header=True, create=True)
guess.bayesdb_guess_generator(bdb, 't_cc', 't', 'crosscat')
bdb.execute('initialize 2 models for t_cc')
bdb.execute('analyze t_cc for 1 iteration wait')
generator_id = core.bayesdb_get_generator(bdb, 't_cc')
row = (41, 'F', 96000, 73, 'data science', 2)
bqlfn.bayesdb_insert(bdb, generator_id, row)
def test_insert():
with test_csv.bayesdb_csv_stream(test_csv.csv_data) as (bdb, f):
bayeslite.bayesdb_read_csv(bdb, "t", f, header=True, create=True)
guess.bayesdb_guess_generator(bdb, "t_cc", "t", "crosscat")
bdb.execute("initialize 2 models for t_cc")
bdb.execute("analyze t_cc for 1 iteration wait")
generator_id = core.bayesdb_get_generator(bdb, "t_cc")
row = (41, "F", 96000, 73, "data science", 2)
bqlfn.bayesdb_insert(bdb, generator_id, row)
def dot_guess(self, line):
"""guess data generator
<generator> <table>
Create a generator named <generator> for the table <table>,
guessing the statistical types of the columns in <table>.
"""
# XXX Lousy, lousy tokenizer.
tokens = line.split()
if len(tokens) != 2:
self.stdout.write("Usage: .guess <generator> <table>\n")
return
generator = tokens[0]
table = tokens[1]
try:
guess.bayesdb_guess_generator(self._bdb, generator, table, self._metamodel)
except Exception:
self.stdout.write(traceback.format_exc())
def dot_guess(self, line):
'''guess data generator
<generator> <table>
Create a generator named <generator> for the table <table>,
guessing the statistical types of the columns in <table>.
'''
# XXX Lousy, lousy tokenizer.
tokens = line.split()
if len(tokens) != 2:
self.stdout.write('Usage: .guess <generator> <table>\n')
return
generator = tokens[0]
table = tokens[1]
try:
guess.bayesdb_guess_generator(self._bdb, generator, table,
self._metamodel)
except Exception:
self.stdout.write(traceback.format_exc())
def test_guess_generator():
bdb = bayeslite.bayesdb_open(builtin_metamodels=False)
bdb.sql_execute('CREATE TABLE t(x NUMERIC, y NUMERIC, z NUMERIC)')
a_z = range(ord('a'), ord('z') + 1)
aa_zz = ((c, d) for c in a_z for d in a_z)
data = ((chr(c) + chr(d), (c + d) % 2, math.sqrt(c + d)) for c, d in aa_zz)
for row in data:
bdb.sql_execute('INSERT INTO t (x, y, z) VALUES (?, ?, ?)', row)
cc = crosscat.LocalEngine.LocalEngine(seed=0)
metamodel = CrosscatMetamodel(cc)
bayeslite.bayesdb_register_metamodel(bdb, metamodel)
with pytest.raises(ValueError):
# No modelled columns. (x is key.)
bayesdb_guess_generator(bdb,
't_cc',
't',
'crosscat',
overrides=[('y', 'ignore'), ('z', 'ignore')])
bayesdb_guess_generator(bdb, 't_cc', 't', 'crosscat')
with pytest.raises(ValueError):
# Generator already exists.
bayesdb_guess_generator(bdb, 't_cc', 't', 'crosscat')
assert bdb.sql_execute('SELECT *'
' FROM bayesdb_generator_column').fetchall() == [
(1, 1, 'categorical'),
(1, 2, 'numerical'),
]
def test_guess_generator():
bdb = bayeslite.bayesdb_open(builtin_metamodels=False)
bdb.sql_execute('CREATE TABLE t(x NUMERIC, y NUMERIC, z NUMERIC)')
a_z = range(ord('a'), ord('z') + 1)
aa_zz = ((c, d) for c in a_z for d in a_z)
data = ((chr(c) + chr(d), (c + d) % 2, math.sqrt(c + d)) for c, d in aa_zz)
for row in data:
bdb.sql_execute('INSERT INTO t (x, y, z) VALUES (?, ?, ?)', row)
cc = crosscat.LocalEngine.LocalEngine(seed=0)
metamodel = CrosscatMetamodel(cc)
bayeslite.bayesdb_register_metamodel(bdb, metamodel)
with pytest.raises(ValueError):
# No modelled columns. (x is key.)
bayesdb_guess_generator(bdb, 't_cc', 't', 'crosscat',
overrides=[('y', 'ignore'), ('z', 'ignore')])
bayesdb_guess_generator(bdb, 't_cc', 't', 'crosscat')
with pytest.raises(ValueError):
# Generator already exists.
bayesdb_guess_generator(bdb, 't_cc', 't', 'crosscat')
assert bdb.sql_execute('SELECT *'
' FROM bayesdb_generator_column').fetchall() == [
(1, 1, 'categorical'),
(1, 2, 'numerical'),
]
