def execute_phrase(bdb, phrase, bindings=()):
"""Execute the BQL AST phrase `phrase` and return a cursor of results."""
if isinstance(phrase, ast.Parametrized):
n_numpar = phrase.n_numpar
nampar_map = phrase.nampar_map
phrase = phrase.phrase
assert 0 < n_numpar
else:
n_numpar = 0
nampar_map = None
# Ignore extraneous bindings. XXX Bad idea?
if ast.is_query(phrase):
# Compile the query in the transaction in case we need to
# execute subqueries to determine column lists. Compiling is
# a quick tree descent, so this should be fast.
out = compiler.Output(n_numpar, nampar_map, bindings)
with bdb.savepoint():
compiler.compile_query(bdb, phrase, out)
winders, unwinders = out.getwindings()
return execute_wound(bdb, winders, unwinders, out.getvalue(), out.getbindings())
if isinstance(phrase, ast.Begin):
txn.bayesdb_begin_transaction(bdb)
return empty_cursor(bdb)
if isinstance(phrase, ast.Rollback):
txn.bayesdb_rollback_transaction(bdb)
return empty_cursor(bdb)
if isinstance(phrase, ast.Commit):
txn.bayesdb_commit_transaction(bdb)
return empty_cursor(bdb)
if isinstance(phrase, ast.CreateTabAs):
assert ast.is_query(phrase.query)
with bdb.savepoint():
out = compiler.Output(n_numpar, nampar_map, bindings)
qt = sqlite3_quote_name(phrase.name)
temp = "TEMP " if phrase.temp else ""
ifnotexists = "IF NOT EXISTS " if phrase.ifnotexists else ""
out.write("CREATE %sTABLE %s%s AS " % (temp, ifnotexists, qt))
compiler.compile_query(bdb, phrase.query, out)
winders, unwinders = out.getwindings()
with compiler.bayesdb_wind(bdb, winders, unwinders):
bdb.sql_execute(out.getvalue(), out.getbindings())
return empty_cursor(bdb)
if isinstance(phrase, ast.CreateTabSim):
assert isinstance(phrase.simulation, ast.Simulate)
with bdb.savepoint():
if core.bayesdb_has_generator(bdb, phrase.name):
raise BQLError(bdb, "Name already defined as generator: %s" % (repr(phrase.name),))
if core.bayesdb_has_table(bdb, phrase.name):
raise BQLError(bdb, "Name already defined as table: %s" % (repr(phrase.name),))
if not core.bayesdb_has_generator_default(bdb, phrase.simulation.generator):
raise BQLError(bdb, "No such generator: %s" % (phrase.simulation.generator,))
generator_id = core.bayesdb_get_generator_default(bdb, phrase.simulation.generator)
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
table = core.bayesdb_generator_table(bdb, generator_id)
qn = sqlite3_quote_name(phrase.name)
qt = sqlite3_quote_name(table)
qgn = sqlite3_quote_name(phrase.simulation.generator)
column_names = phrase.simulation.columns
qcns = map(sqlite3_quote_name, column_names)
cursor = bdb.sql_execute("PRAGMA table_info(%s)" % (qt,))
column_sqltypes = {}
for _colno, name, sqltype, _nonnull, _default, _primary in cursor:
assert casefold(name) not in column_sqltypes
column_sqltypes[casefold(name)] = sqltype
assert 0 < len(column_sqltypes)
for column_name in column_names:
if casefold(column_name) not in column_sqltypes:
raise BQLError(
bdb,
"No such column"
" in generator %s table %s: %s"
% (repr(phrase.simulation.generator), repr(table), repr(column_name)),
)
for column_name, _expression in phrase.simulation.constraints:
if casefold(column_name) not in column_sqltypes:
raise BQLError(
bdb,
"No such column"
" in generator %s table %s: %s"
% (repr(phrase.simulation.generator), repr(table), repr(column_name)),
)
# XXX Move to compiler.py.
# XXX Copypasta of this in compile_simulate!
out = compiler.Output(n_numpar, nampar_map, bindings)
out.write("SELECT ")
with compiler.compiling_paren(bdb, out, "CAST(", " AS INTEGER)"):
compiler.compile_nobql_expression(bdb, phrase.simulation.nsamples, out)
out.write(", ")
with compiler.compiling_paren(bdb, out, "CAST(", " AS INTEGER)"):
compiler.compile_nobql_expression(bdb, phrase.simulation.modelno, out)
for _column_name, expression in phrase.simulation.constraints:
out.write(", ")
compiler.compile_nobql_expression(bdb, expression, out)
winders, unwinders = out.getwindings()
with compiler.bayesdb_wind(bdb, winders, unwinders):
cursor = bdb.sql_execute(out.getvalue(), out.getbindings()).fetchall()
assert len(cursor) == 1
nsamples = cursor[0][0]
assert isinstance(nsamples, int)
modelno = cursor[0][1]
assert modelno is None or isinstance(modelno, int)
constraints = [
(core.bayesdb_generator_column_number(bdb, generator_id, name), value)
for (name, _expression), value in zip(phrase.simulation.constraints, cursor[0][2:])
]
colnos = [core.bayesdb_generator_column_number(bdb, generator_id, name) for name in column_names]
bdb.sql_execute(
"CREATE %sTABLE %s%s (%s)"
% (
"TEMP " if phrase.temp else "",
"IF NOT EXISTS " if phrase.ifnotexists else "",
qn,
",".join(
"%s %s" % (qcn, column_sqltypes[casefold(column_name)])
for qcn, column_name in zip(qcns, column_names)
),
)
)
insert_sql = """
INSERT INTO %s (%s) VALUES (%s)
""" % (
qn,
",".join(qcns),
",".join("?" for qcn in qcns),
)
for row in bqlfn.bayesdb_simulate(
bdb, generator_id, constraints, colnos, modelno=modelno, numpredictions=nsamples
):
bdb.sql_execute(insert_sql, row)
return empty_cursor(bdb)
if isinstance(phrase, ast.DropTab):
with bdb.savepoint():
sql = "SELECT COUNT(*) FROM bayesdb_generator WHERE tabname = ?"
cursor = bdb.sql_execute(sql, (phrase.name,))
if 0 < cursor_value(cursor):
# XXX Automatically delete the generators? Generators
# are more interesting than triggers and indices, so
# automatic deletion is not obviously right.
raise BQLError(bdb, "Table still in use by generators: %s" % (repr(phrase.name),))
bdb.sql_execute("DELETE FROM bayesdb_column WHERE tabname = ?", (phrase.name,))
ifexists = "IF EXISTS " if phrase.ifexists else ""
qt = sqlite3_quote_name(phrase.name)
return bdb.sql_execute("DROP TABLE %s%s" % (ifexists, qt))
if isinstance(phrase, ast.AlterTab):
with bdb.savepoint():
table = phrase.table
if not core.bayesdb_has_table(bdb, table):
raise BQLError(bdb, "No such table: %s" % (repr(table),))
for cmd in phrase.commands:
if isinstance(cmd, ast.AlterTabRenameTab):
# If the names differ only in case, we have to do
# some extra work because SQLite will reject the
# table rename. Note that we may even have table
# == cmd.name here, but if the stored table name
# differs in case from cmd.name, we want to update
# it anyway.
if casefold(table) == casefold(cmd.name):
# Go via a temporary table.
temp = table + "_temp"
while core.bayesdb_has_table(bdb, temp) or core.bayesdb_has_generator(bdb, temp):
temp += "_temp"
rename_table(bdb, table, temp)
rename_table(bdb, temp, cmd.name)
else:
# Make sure nothing else has this name and
# rename it.
if core.bayesdb_has_table(bdb, cmd.name):
raise BQLError(bdb, "Name already defined as table" ": %s" % (repr(cmd.name),))
if core.bayesdb_has_generator(bdb, cmd.name):
raise BQLError(bdb, "Name already defined" " as generator: %s" % (repr(cmd.name),))
rename_table(bdb, table, cmd.name)
# Remember the new name for subsequent commands.
table = cmd.name
elif isinstance(cmd, ast.AlterTabRenameCol):
# XXX Need to deal with this in the compiler.
raise NotImplementedError("Renaming columns" " not yet implemented.")
# Make sure the old name exist and the new name does not.
old_folded = casefold(cmd.old)
new_folded = casefold(cmd.new)
if old_folded != new_folded:
if not core.bayesdb_table_has_column(bdb, table, cmd.old):
raise BQLError(bdb, "No such column in table %s" ": %s" % (repr(table), repr(cmd.old)))
if core.bayesdb_table_has_column(bdb, table, cmd.new):
raise BQLError(
bdb, "Column already exists" " in table %s: %s" % (repr(table), repr(cmd.new))
)
# Update bayesdb_column. Everything else refers
# to columns by (tabname, colno) pairs rather than
# by names.
update_column_sql = """
UPDATE bayesdb_column SET name = :new
WHERE tabname = :table AND name = :old
"""
total_changes = bdb.sqlite3.total_changes
bdb.sql_execute(update_column_sql, {"table": table, "old": cmd.old, "new": cmd.new})
assert bdb.sqlite3.total_changes - total_changes == 1
# ...except metamodels may have the (case-folded)
# name cached.
if old_folded != new_folded:
generators_sql = """
SELECT id FROM bayesdb_generator WHERE tabname = ?
"""
cursor = bdb.sql_execute(generators_sql, (table,))
for (generator_id,) in cursor:
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
metamodel.rename_column(bdb, generator_id, old_folded, new_folded)
elif isinstance(cmd, ast.AlterTabSetDefGen):
if not core.bayesdb_has_generator(bdb, cmd.generator):
raise BQLError(bdb, "No such generator: %s" % (repr(cmd.generator),))
generator_id = core.bayesdb_get_generator(bdb, cmd.generator)
unset_default_sql = """
UPDATE bayesdb_generator SET defaultp = 0
WHERE tabname = ? AND defaultp
"""
total_changes = bdb.sqlite3.total_changes
bdb.sql_execute(unset_default_sql, (table,))
assert bdb.sqlite3.total_changes - total_changes in (0, 1)
set_default_sql = """
UPDATE bayesdb_generator SET defaultp = 1 WHERE id = ?
"""
total_changes = bdb.sqlite3.total_changes
bdb.sql_execute(set_default_sql, (generator_id,))
assert bdb.sqlite3.total_changes - total_changes == 1
elif isinstance(cmd, ast.AlterTabUnsetDefGen):
unset_default_sql = """
UPDATE bayesdb_generator SET defaultp = 0
WHERE tabname = ? AND defaultp
"""
total_changes = bdb.sqlite3.total_changes
bdb.sql_execute(unset_default_sql, (table,))
assert bdb.sqlite3.total_changes - total_changes in (0, 1)
else:
assert False, "Invalid alter table command: %s" % (cmd,)
return empty_cursor(bdb)
if isinstance(phrase, ast.CreateGen):
# Find the metamodel.
if phrase.metamodel not in bdb.metamodels:
raise BQLError(bdb, "No such metamodel: %s" % (repr(phrase.metamodel),))
metamodel = bdb.metamodels[phrase.metamodel]
# Let the metamodel parse the schema itself and call
# create_generator with the modelled columns.
with bdb.savepoint():
def instantiate(columns):
return instantiate_generator(
bdb,
phrase.name,
phrase.table,
metamodel,
columns,
ifnotexists=phrase.ifnotexists,
default=phrase.default,
)
metamodel.create_generator(bdb, phrase.table, phrase.schema, instantiate)
# All done. Nothing to return.
return empty_cursor(bdb)
if isinstance(phrase, ast.DropGen):
with bdb.savepoint():
if not core.bayesdb_has_generator(bdb, phrase.name):
if phrase.ifexists:
return empty_cursor(bdb)
raise BQLError(bdb, "No such generator: %s" % (repr(phrase.name),))
generator_id = core.bayesdb_get_generator(bdb, phrase.name)
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
# Metamodel-specific destruction.
metamodel.drop_generator(bdb, generator_id)
# Drop the columns, models, and, finally, generator.
drop_columns_sql = """
DELETE FROM bayesdb_generator_column WHERE generator_id = ?
"""
bdb.sql_execute(drop_columns_sql, (generator_id,))
drop_model_sql = """
DELETE FROM bayesdb_generator_model WHERE generator_id = ?
"""
bdb.sql_execute(drop_model_sql, (generator_id,))
drop_generator_sql = """
DELETE FROM bayesdb_generator WHERE id = ?
"""
bdb.sql_execute(drop_generator_sql, (generator_id,))
return empty_cursor(bdb)
if isinstance(phrase, ast.AlterGen):
with bdb.savepoint():
generator = phrase.generator
if not core.bayesdb_has_generator(bdb, generator):
raise BQLError(bdb, "No such generator: %s" % (repr(generator),))
generator_id = core.bayesdb_get_generator(bdb, generator)
for cmd in phrase.commands:
if isinstance(cmd, ast.AlterGenRenameGen):
# Make sure nothing else has this name.
if casefold(generator) != casefold(cmd.name):
if core.bayesdb_has_table(bdb, cmd.name):
raise BQLError(bdb, "Name already defined as table" ": %s" % (repr(cmd.name),))
if core.bayesdb_has_generator(bdb, cmd.name):
raise BQLError(bdb, "Name already defined" " as generator: %s" % (repr(cmd.name),))
# Update bayesdb_generator. Everything else
# refers to it by id.
update_generator_sql = """
UPDATE bayesdb_generator SET name = ? WHERE id = ?
"""
total_changes = bdb.sqlite3.total_changes
bdb.sql_execute(update_generator_sql, (cmd.name, generator_id))
assert bdb.sqlite3.total_changes - total_changes == 1
# Remember the new name for subsequent commands.
generator = cmd.name
else:
assert False, "Invalid ALTER GENERATOR command: %s" % (repr(cmd),)
return empty_cursor(bdb)
if isinstance(phrase, ast.InitModels):
if not core.bayesdb_has_generator_default(bdb, phrase.generator):
raise BQLError(bdb, "No such generator: %s" % (phrase.generator,))
generator_id = core.bayesdb_get_generator_default(bdb, phrase.generator)
modelnos = range(phrase.nmodels)
model_config = None # XXX For now.
with bdb.savepoint():
# Find the model numbers. Omit existing ones for
# ifnotexists; reject existing ones otherwise.
if phrase.ifnotexists:
modelnos = set(
modelno for modelno in modelnos if not core.bayesdb_generator_has_model(bdb, generator_id, modelno)
)
else:
existing = set(
modelno for modelno in modelnos if core.bayesdb_generator_has_model(bdb, generator_id, modelno)
)
if 0 < len(existing):
raise BQLError(
bdb, "Generator %s already has models: %s" % (repr(phrase.generator), sorted(existing))
)
# Stop now if there's nothing to initialize.
if len(modelnos) == 0:
return
# Create the bayesdb_generator_model records.
modelnos = sorted(modelnos)
insert_model_sql = """
INSERT INTO bayesdb_generator_model
(generator_id, modelno, iterations)
VALUES (:generator_id, :modelno, :iterations)
"""
for modelno in modelnos:
bdb.sql_execute(insert_model_sql, {"generator_id": generator_id, "modelno": modelno, "iterations": 0})
# Do metamodel-specific initialization.
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
metamodel.initialize_models(bdb, generator_id, modelnos, model_config)
return empty_cursor(bdb)
if isinstance(phrase, ast.AnalyzeModels):
if not phrase.wait:
raise NotImplementedError("No background analysis -- use WAIT.")
# WARNING: It is the metamodel's responsibility to work in a
# transaction.
#
# WARNING: It is the metamodel's responsibility to update the
# iteration count in bayesdb_generator_model records.
#
# We do this so that the metamodel can save incremental
# progress in case of ^C in the middle.
#
# XXX Put these warning somewhere more appropriate.
if not core.bayesdb_has_generator_default(bdb, phrase.generator):
raise BQLError(bdb, "No such generator: %s" % (phrase.generator,))
generator_id = core.bayesdb_get_generator_default(bdb, phrase.generator)
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
# XXX Should allow parameters for iterations and ckpt/iter.
metamodel.analyze_models(
bdb,
generator_id,
modelnos=phrase.modelnos,
iterations=phrase.iterations,
max_seconds=phrase.seconds,
ckpt_iterations=phrase.ckpt_iterations,
ckpt_seconds=phrase.ckpt_seconds,
)
return empty_cursor(bdb)
if isinstance(phrase, ast.DropModels):
with bdb.savepoint():
generator_id = core.bayesdb_get_generator_default(bdb, phrase.generator)
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
modelnos = None
if phrase.modelnos is not None:
lookup_model_sql = """
SELECT COUNT(*) FROM bayesdb_generator_model
WHERE generator_id = :generator_id
AND modelno = :modelno
"""
modelnos = sorted(list(phrase.modelnos))
for modelno in modelnos:
cursor = bdb.sql_execute(lookup_model_sql, {"generator_id": generator_id, "modelno": modelno})
if cursor_value(cursor) == 0:
raise BQLError(
bdb, "No such model" " in generator %s: %s" % (repr(phrase.generator), repr(modelno))
)
metamodel.drop_models(bdb, generator_id, modelnos=modelnos)
if modelnos is None:
drop_models_sql = """
DELETE FROM bayesdb_generator_model WHERE generator_id = ?
"""
bdb.sql_execute(drop_models_sql, (generator_id,))
else:
drop_model_sql = """
DELETE FROM bayesdb_generator_model
WHERE generator_id = :generator_id
AND modelno = :modelno
"""
for modelno in modelnos:
bdb.sql_execute(drop_model_sql, {"generator_id": generator_id, "modelno": modelno})
return empty_cursor(bdb)
assert False # XXX
def execute_phrase(bdb, phrase, bindings=()):
"""Execute the BQL AST phrase `phrase` and return a cursor of results."""
if isinstance(phrase, ast.Parametrized):
n_numpar = phrase.n_numpar
nampar_map = phrase.nampar_map
phrase = phrase.phrase
assert 0 < n_numpar
else:
n_numpar = 0
nampar_map = None
# Ignore extraneous bindings. XXX Bad idea?
if ast.is_query(phrase):
# Compile the query in the transaction in case we need to
# execute subqueries to determine column lists. Compiling is
# a quick tree descent, so this should be fast.
out = compiler.Output(n_numpar, nampar_map, bindings)
with bdb.savepoint():
compiler.compile_query(bdb, phrase, out)
winders, unwinders = out.getwindings()
return execute_wound(bdb, winders, unwinders, out.getvalue(),
out.getbindings())
if isinstance(phrase, ast.Begin):
txn.bayesdb_begin_transaction(bdb)
return empty_cursor(bdb)
if isinstance(phrase, ast.Rollback):
txn.bayesdb_rollback_transaction(bdb)
return empty_cursor(bdb)
if isinstance(phrase, ast.Commit):
txn.bayesdb_commit_transaction(bdb)
return empty_cursor(bdb)
if isinstance(phrase, ast.CreateTabAs):
assert ast.is_query(phrase.query)
with bdb.savepoint():
out = compiler.Output(n_numpar, nampar_map, bindings)
qt = sqlite3_quote_name(phrase.name)
temp = 'TEMP ' if phrase.temp else ''
ifnotexists = 'IF NOT EXISTS ' if phrase.ifnotexists else ''
out.write('CREATE %sTABLE %s%s AS ' % (temp, ifnotexists, qt))
compiler.compile_query(bdb, phrase.query, out)
winders, unwinders = out.getwindings()
with compiler.bayesdb_wind(bdb, winders, unwinders):
bdb.sql_execute(out.getvalue(), out.getbindings())
return empty_cursor(bdb)
if isinstance(phrase, ast.CreateTabSim):
assert isinstance(phrase.simulation, ast.Simulate)
with bdb.savepoint():
if core.bayesdb_has_generator(bdb, phrase.name):
raise BQLError(
bdb, 'Name already defined as generator: %s' %
(repr(phrase.name), ))
if core.bayesdb_has_table(bdb, phrase.name):
raise BQLError(
bdb, 'Name already defined as table: %s' %
(repr(phrase.name), ))
if not core.bayesdb_has_generator_default(
bdb, phrase.simulation.generator):
raise BQLError(
bdb,
'No such generator: %s' % (phrase.simulation.generator, ))
generator_id = core.bayesdb_get_generator_default(
bdb, phrase.simulation.generator)
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
table = core.bayesdb_generator_table(bdb, generator_id)
qn = sqlite3_quote_name(phrase.name)
qt = sqlite3_quote_name(table)
qgn = sqlite3_quote_name(phrase.simulation.generator)
column_names = phrase.simulation.columns
qcns = map(sqlite3_quote_name, column_names)
cursor = bdb.sql_execute('PRAGMA table_info(%s)' % (qt, ))
column_sqltypes = {}
for _colno, name, sqltype, _nonnull, _default, _primary in cursor:
assert casefold(name) not in column_sqltypes
column_sqltypes[casefold(name)] = sqltype
assert 0 < len(column_sqltypes)
for column_name in column_names:
if casefold(column_name) not in column_sqltypes:
raise BQLError(
bdb, 'No such column'
' in generator %s table %s: %s' %
(repr(phrase.simulation.generator), repr(table),
repr(column_name)))
for column_name, _expression in phrase.simulation.constraints:
if casefold(column_name) not in column_sqltypes:
raise BQLError(
bdb, 'No such column'
' in generator %s table %s: %s' %
(repr(phrase.simulation.generator), repr(table),
repr(column_name)))
# XXX Move to compiler.py.
# XXX Copypasta of this in compile_simulate!
out = compiler.Output(n_numpar, nampar_map, bindings)
out.write('SELECT ')
with compiler.compiling_paren(bdb, out, 'CAST(', ' AS INTEGER)'):
compiler.compile_nobql_expression(bdb,
phrase.simulation.nsamples,
out)
out.write(', ')
with compiler.compiling_paren(bdb, out, 'CAST(', ' AS INTEGER)'):
compiler.compile_nobql_expression(bdb,
phrase.simulation.modelno,
out)
for _column_name, expression in phrase.simulation.constraints:
out.write(', ')
compiler.compile_nobql_expression(bdb, expression, out)
winders, unwinders = out.getwindings()
with compiler.bayesdb_wind(bdb, winders, unwinders):
cursor = bdb.sql_execute(out.getvalue(),
out.getbindings()).fetchall()
assert len(cursor) == 1
nsamples = cursor[0][0]
assert isinstance(nsamples, int)
modelno = cursor[0][1]
assert modelno is None or isinstance(modelno, int)
constraints = \
[(core.bayesdb_generator_column_number(bdb, generator_id, name),
value)
for (name, _expression), value in
zip(phrase.simulation.constraints, cursor[0][2:])]
colnos = \
[core.bayesdb_generator_column_number(bdb, generator_id, name)
for name in column_names]
bdb.sql_execute(
'CREATE %sTABLE %s%s (%s)' %
('TEMP ' if phrase.temp else '',
'IF NOT EXISTS ' if phrase.ifnotexists else '', qn, ','.join(
'%s %s' % (qcn, column_sqltypes[casefold(column_name)])
for qcn, column_name in zip(qcns, column_names))))
insert_sql = '''
INSERT INTO %s (%s) VALUES (%s)
''' % (qn, ','.join(qcns), ','.join('?' for qcn in qcns))
for row in bqlfn.bayesdb_simulate(bdb,
generator_id,
constraints,
colnos,
modelno=modelno,
numpredictions=nsamples):
bdb.sql_execute(insert_sql, row)
return empty_cursor(bdb)
if isinstance(phrase, ast.DropTab):
with bdb.savepoint():
sql = 'SELECT COUNT(*) FROM bayesdb_generator WHERE tabname = ?'
cursor = bdb.sql_execute(sql, (phrase.name, ))
if 0 < cursor_value(cursor):
# XXX Automatically delete the generators? Generators
# are more interesting than triggers and indices, so
# automatic deletion is not obviously right.
raise BQLError(
bdb, 'Table still in use by generators: %s' %
(repr(phrase.name), ))
bdb.sql_execute('DELETE FROM bayesdb_column WHERE tabname = ?',
(phrase.name, ))
ifexists = 'IF EXISTS ' if phrase.ifexists else ''
qt = sqlite3_quote_name(phrase.name)
return bdb.sql_execute('DROP TABLE %s%s' % (ifexists, qt))
if isinstance(phrase, ast.AlterTab):
with bdb.savepoint():
table = phrase.table
if not core.bayesdb_has_table(bdb, table):
raise BQLError(bdb, 'No such table: %s' % (repr(table), ))
for cmd in phrase.commands:
if isinstance(cmd, ast.AlterTabRenameTab):
# If the names differ only in case, we have to do
# some extra work because SQLite will reject the
# table rename. Note that we may even have table
# == cmd.name here, but if the stored table name
# differs in case from cmd.name, we want to update
# it anyway.
if casefold(table) == casefold(cmd.name):
# Go via a temporary table.
temp = table + '_temp'
while core.bayesdb_has_table(bdb, temp) or \
core.bayesdb_has_generator(bdb, temp):
temp += '_temp'
rename_table(bdb, table, temp)
rename_table(bdb, temp, cmd.name)
else:
# Make sure nothing else has this name and
# rename it.
if core.bayesdb_has_table(bdb, cmd.name):
raise BQLError(
bdb, 'Name already defined as table'
': %s' % (repr(cmd.name), ))
if core.bayesdb_has_generator(bdb, cmd.name):
raise BQLError(
bdb, 'Name already defined'
' as generator: %s' % (repr(cmd.name), ))
rename_table(bdb, table, cmd.name)
# Remember the new name for subsequent commands.
table = cmd.name
elif isinstance(cmd, ast.AlterTabRenameCol):
# XXX Need to deal with this in the compiler.
raise NotImplementedError('Renaming columns'
' not yet implemented.')
# Make sure the old name exist and the new name does not.
old_folded = casefold(cmd.old)
new_folded = casefold(cmd.new)
if old_folded != new_folded:
if not core.bayesdb_table_has_column(
bdb, table, cmd.old):
raise BQLError(
bdb, 'No such column in table %s'
': %s' % (repr(table), repr(cmd.old)))
if core.bayesdb_table_has_column(bdb, table, cmd.new):
raise BQLError(
bdb, 'Column already exists'
' in table %s: %s' %
(repr(table), repr(cmd.new)))
# Update bayesdb_column. Everything else refers
# to columns by (tabname, colno) pairs rather than
# by names.
update_column_sql = '''
UPDATE bayesdb_column SET name = :new
WHERE tabname = :table AND name = :old
'''
total_changes = bdb._sqlite3.totalchanges()
bdb.sql_execute(update_column_sql, {
'table': table,
'old': cmd.old,
'new': cmd.new,
})
assert bdb._sqlite3.totalchanges() - total_changes == 1
# ...except metamodels may have the (case-folded)
# name cached.
if old_folded != new_folded:
generators_sql = '''
SELECT id FROM bayesdb_generator WHERE tabname = ?
'''
cursor = bdb.sql_execute(generators_sql, (table, ))
for (generator_id, ) in cursor:
metamodel = core.bayesdb_generator_metamodel(
bdb, generator_id)
metamodel.rename_column(bdb, generator_id,
old_folded, new_folded)
elif isinstance(cmd, ast.AlterTabSetDefGen):
if not core.bayesdb_has_generator(bdb, cmd.generator):
raise BQLError(
bdb,
'No such generator: %s' % (repr(cmd.generator), ))
generator_id = core.bayesdb_get_generator(
bdb, cmd.generator)
bayesdb_schema_required(bdb, 6, "generator defaults")
unset_default_sql = '''
UPDATE bayesdb_generator SET defaultp = 0
WHERE tabname = ? AND defaultp
'''
total_changes = bdb._sqlite3.totalchanges()
bdb.sql_execute(unset_default_sql, (table, ))
assert bdb._sqlite3.totalchanges() - total_changes in (0,
1)
set_default_sql = '''
UPDATE bayesdb_generator SET defaultp = 1 WHERE id = ?
'''
total_changes = bdb._sqlite3.totalchanges()
bdb.sql_execute(set_default_sql, (generator_id, ))
assert bdb._sqlite3.totalchanges() - total_changes == 1
elif isinstance(cmd, ast.AlterTabUnsetDefGen):
unset_default_sql = '''
UPDATE bayesdb_generator SET defaultp = 0
WHERE tabname = ? AND defaultp
'''
total_changes = bdb._sqlite3.totalchanges()
bdb.sql_execute(unset_default_sql, (table, ))
assert bdb._sqlite3.totalchanges() - total_changes in (0,
1)
else:
assert False, 'Invalid alter table command: %s' % \
(cmd,)
return empty_cursor(bdb)
if isinstance(phrase, ast.CreateGen):
# Find the metamodel.
if phrase.metamodel not in bdb.metamodels:
raise BQLError(
bdb, 'No such metamodel: %s' % (repr(phrase.metamodel), ))
metamodel = bdb.metamodels[phrase.metamodel]
# Let the metamodel parse the schema itself and call
# create_generator with the modelled columns.
with bdb.savepoint():
if core.bayesdb_has_generator(bdb, phrase.name):
if not phrase.ifnotexists:
raise BQLError(
bdb, 'Name already defined as generator: %s' %
(repr(phrase.name), ))
else:
def instantiate(columns):
return instantiate_generator(bdb,
phrase.name,
phrase.table,
metamodel,
columns,
default=phrase.default)
metamodel.create_generator(bdb, phrase.table, phrase.schema,
instantiate)
# All done. Nothing to return.
return empty_cursor(bdb)
if isinstance(phrase, ast.DropGen):
with bdb.savepoint():
if not core.bayesdb_has_generator(bdb, phrase.name):
if phrase.ifexists:
return empty_cursor(bdb)
raise BQLError(bdb,
'No such generator: %s' % (repr(phrase.name), ))
generator_id = core.bayesdb_get_generator(bdb, phrase.name)
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
# Metamodel-specific destruction.
metamodel.drop_generator(bdb, generator_id)
# Drop the columns, models, and, finally, generator.
drop_columns_sql = '''
DELETE FROM bayesdb_generator_column WHERE generator_id = ?
'''
bdb.sql_execute(drop_columns_sql, (generator_id, ))
drop_model_sql = '''
DELETE FROM bayesdb_generator_model WHERE generator_id = ?
'''
bdb.sql_execute(drop_model_sql, (generator_id, ))
drop_generator_sql = '''
DELETE FROM bayesdb_generator WHERE id = ?
'''
bdb.sql_execute(drop_generator_sql, (generator_id, ))
return empty_cursor(bdb)
if isinstance(phrase, ast.AlterGen):
with bdb.savepoint():
generator = phrase.generator
if not core.bayesdb_has_generator(bdb, generator):
raise BQLError(bdb,
'No such generator: %s' % (repr(generator), ))
generator_id = core.bayesdb_get_generator(bdb, generator)
for cmd in phrase.commands:
if isinstance(cmd, ast.AlterGenRenameGen):
# Make sure nothing else has this name.
if casefold(generator) != casefold(cmd.name):
if core.bayesdb_has_table(bdb, cmd.name):
raise BQLError(
bdb, 'Name already defined as table'
': %s' % (repr(cmd.name), ))
if core.bayesdb_has_generator(bdb, cmd.name):
raise BQLError(
bdb, 'Name already defined'
' as generator: %s' % (repr(cmd.name), ))
# Update bayesdb_generator. Everything else
# refers to it by id.
update_generator_sql = '''
UPDATE bayesdb_generator SET name = ? WHERE id = ?
'''
total_changes = bdb._sqlite3.totalchanges()
bdb.sql_execute(update_generator_sql,
(cmd.name, generator_id))
assert bdb._sqlite3.totalchanges() - total_changes == 1
# Remember the new name for subsequent commands.
generator = cmd.name
else:
assert False, 'Invalid ALTER GENERATOR command: %s' % \
(repr(cmd),)
return empty_cursor(bdb)
if isinstance(phrase, ast.InitModels):
if not core.bayesdb_has_generator_default(bdb, phrase.generator):
raise BQLError(bdb, 'No such generator: %s' % (phrase.generator, ))
generator_id = core.bayesdb_get_generator_default(
bdb, phrase.generator)
modelnos = range(phrase.nmodels)
model_config = None # XXX For now.
with bdb.savepoint():
# Find the model numbers. Omit existing ones for
# ifnotexists; reject existing ones otherwise.
if phrase.ifnotexists:
modelnos = set(modelno for modelno in modelnos
if not core.bayesdb_generator_has_model(
bdb, generator_id, modelno))
else:
existing = set(modelno for modelno in modelnos
if core.bayesdb_generator_has_model(
bdb, generator_id, modelno))
if 0 < len(existing):
raise BQLError(
bdb, 'Generator %s already has models: %s' %
(repr(phrase.generator), sorted(existing)))
# Stop now if there's nothing to initialize.
if len(modelnos) == 0:
return
# Create the bayesdb_generator_model records.
modelnos = sorted(modelnos)
insert_model_sql = '''
INSERT INTO bayesdb_generator_model
(generator_id, modelno, iterations)
VALUES (:generator_id, :modelno, :iterations)
'''
for modelno in modelnos:
bdb.sql_execute(
insert_model_sql, {
'generator_id': generator_id,
'modelno': modelno,
'iterations': 0,
})
# Do metamodel-specific initialization.
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
metamodel.initialize_models(bdb, generator_id, modelnos,
model_config)
return empty_cursor(bdb)
if isinstance(phrase, ast.AnalyzeModels):
if not phrase.wait:
raise NotImplementedError('No background analysis -- use WAIT.')
# WARNING: It is the metamodel's responsibility to work in a
# transaction.
#
# WARNING: It is the metamodel's responsibility to update the
# iteration count in bayesdb_generator_model records.
#
# We do this so that the metamodel can save incremental
# progress in case of ^C in the middle.
#
# XXX Put these warning somewhere more appropriate.
if not core.bayesdb_has_generator_default(bdb, phrase.generator):
raise BQLError(bdb, 'No such generator: %s' % (phrase.generator, ))
generator_id = core.bayesdb_get_generator_default(
bdb, phrase.generator)
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
# XXX Should allow parameters for iterations and ckpt/iter.
metamodel.analyze_models(bdb,
generator_id,
modelnos=phrase.modelnos,
iterations=phrase.iterations,
max_seconds=phrase.seconds,
ckpt_iterations=phrase.ckpt_iterations,
ckpt_seconds=phrase.ckpt_seconds)
return empty_cursor(bdb)
if isinstance(phrase, ast.DropModels):
with bdb.savepoint():
generator_id = core.bayesdb_get_generator_default(
bdb, phrase.generator)
metamodel = core.bayesdb_generator_metamodel(bdb, generator_id)
modelnos = None
if phrase.modelnos is not None:
lookup_model_sql = '''
SELECT COUNT(*) FROM bayesdb_generator_model
WHERE generator_id = :generator_id
AND modelno = :modelno
'''
modelnos = sorted(list(phrase.modelnos))
for modelno in modelnos:
cursor = bdb.sql_execute(lookup_model_sql, {
'generator_id': generator_id,
'modelno': modelno,
})
if cursor_value(cursor) == 0:
raise BQLError(
bdb, 'No such model'
' in generator %s: %s' %
(repr(phrase.generator), repr(modelno)))
metamodel.drop_models(bdb, generator_id, modelnos=modelnos)
if modelnos is None:
drop_models_sql = '''
DELETE FROM bayesdb_generator_model WHERE generator_id = ?
'''
bdb.sql_execute(drop_models_sql, (generator_id, ))
else:
drop_model_sql = '''
DELETE FROM bayesdb_generator_model
WHERE generator_id = :generator_id
AND modelno = :modelno
'''
for modelno in modelnos:
bdb.sql_execute(drop_model_sql, {
'generator_id': generator_id,
'modelno': modelno,
})
return empty_cursor(bdb)
assert False # XXX
def dot_describe(self, line):
"""describe BayesDB entities
[table(s)|generator(s)|columns|model(s)] [<name>...]
Print a human-readable description of the specified BayesDB
entities.
"""
# XXX Lousy, lousy tokenizer.
tokens = line.split()
if len(tokens) == 0:
self.stdout.write("Usage: .describe table(s) [<table>...]\n")
self.stdout.write(" .describe generator(s) [<gen>...]\n")
self.stdout.write(" .describe columns <gen>\n")
self.stdout.write(" .describe model(s) <gen> [<model>...]\n")
return
if casefold(tokens[0]) == "table" or casefold(tokens[0]) == "tables":
params = None
qualifier = None
if len(tokens) == 1:
params = ()
qualifier = "1"
else:
params = tokens[1:]
qualifier = "(" + " OR ".join(["tabname = ?" for _p in params]) + ")"
ok = True
for table in params:
if not core.bayesdb_has_table(self._bdb, table):
self.stdout.write("No such table: %s\n" % (repr(table),))
ok = False
if not ok:
return
for table in params:
core.bayesdb_table_guarantee_columns(self._bdb, table)
sql = """
SELECT tabname, colno, name, shortname
FROM bayesdb_column
WHERE %s
ORDER BY tabname ASC, colno ASC
""" % (
qualifier,
)
with self._bdb.savepoint():
pretty.pp_cursor(self.stdout, self._bdb.execute(sql, params))
elif casefold(tokens[0]) == "generator" or casefold(tokens[0]) == "generators":
params = None
qualifier = None
if len(tokens) == 1:
params = ()
qualifier = "1"
else:
params = tokens[1:]
names = ",".join("?%d" % (i + 1,) for i in range(len(params)))
qualifier = """
(name IN ({names}) OR (defaultp AND tabname IN ({names})))
""".format(
names=names
)
ok = True
for generator in params:
if not core.bayesdb_has_generator_default(self._bdb, generator):
self.stdout.write("No such generator: %s\n" % (repr(generator),))
ok = False
if not ok:
return
sql = """
SELECT id, name, tabname, metamodel
FROM bayesdb_generator
WHERE %s
""" % (
qualifier,
)
with self._bdb.savepoint():
pretty.pp_cursor(self.stdout, self._bdb.sql_execute(sql, params))
elif casefold(tokens[0]) == "columns":
if len(tokens) != 2:
self.stdout.write("Describe columns of what generator?\n")
return
generator = tokens[1]
with self._bdb.savepoint():
if not core.bayesdb_has_generator_default(self._bdb, generator):
self.stdout.write("No such generator: %s\n" % (repr(generator),))
return
generator_id = core.bayesdb_get_generator_default(self._bdb, generator)
sql = """
SELECT c.colno AS colno, c.name AS name,
gc.stattype AS stattype, c.shortname AS shortname
FROM bayesdb_generator AS g,
(bayesdb_column AS c LEFT OUTER JOIN
bayesdb_generator_column AS gc
USING (colno))
WHERE g.id = ? AND g.id = gc.generator_id
AND g.tabname = c.tabname
ORDER BY colno ASC;
"""
cursor = self._bdb.sql_execute(sql, (generator_id,))
pretty.pp_cursor(self.stdout, cursor)
elif casefold(tokens[0]) == "model" or casefold(tokens[0]) == "models":
if len(tokens) < 2:
self.stdout.write("Describe models of what generator?\n")
return
generator = tokens[1]
with self._bdb.savepoint():
if not core.bayesdb_has_generator_default(self._bdb, generator):
self.stdout.write("No such generator: %s\n" % (repr(generator),))
return
generator_id = core.bayesdb_get_generator_default(self._bdb, generator)
qualifier = None
if len(tokens) == 2:
qualifier = "1"
else:
modelnos = []
for token in tokens[2:]:
try:
modelno = int(token)
except ValueError:
self.stdout.write("Invalid model number: %s\n" % (repr(token),))
return
else:
if not core.bayesdb_generator_has_model(self._bdb, generator_id, modelno):
self.stdout.write("No such model: %d\n" % (modelno,))
return
modelnos.append(modelno)
qualifier = "modelno IN (%s)" % (",".join(map(str, modelnos)))
sql = """
SELECT modelno, iterations FROM bayesdb_generator_model
WHERE generator_id = ? AND %s
""" % (
qualifier,
)
cursor = self._bdb.sql_execute(sql, (generator_id,))
pretty.pp_cursor(self.stdout, cursor)
else:
self.stdout.write("Usage: .describe table(s) [<table>...]\n")
self.stdout.write(" .describe generator(s) [<gen>...]\n")
self.stdout.write(" .describe columns <gen>\n")
self.stdout.write(" .describe model(s) <gen> [<model>...]\n")
def dot_describe(self, line):
'''describe BayesDB entities
[table(s)|generator(s)|columns|model(s)] [<name>...]
Print a human-readable description of the specified BayesDB
entities.
'''
# XXX Lousy, lousy tokenizer.
tokens = line.split()
if len(tokens) == 0:
self.stdout.write('Usage: .describe table(s) [<table>...]\n')
self.stdout.write(' .describe generator(s) [<gen>...]\n')
self.stdout.write(' .describe columns <gen>\n')
self.stdout.write(' .describe model(s) <gen> [<model>...]\n')
return
if casefold(tokens[0]) == 'table' or \
casefold(tokens[0]) == 'tables':
params = None
qualifier = None
if len(tokens) == 1:
params = ()
qualifier = '1'
else:
params = tokens[1:]
qualifier = \
'(' + ' OR '.join(['tabname = ?' for _p in params]) + ')'
ok = True
for table in params:
if not core.bayesdb_has_table(self._bdb, table):
self.stdout.write('No such table: %s\n' %
(repr(table),))
ok = False
if not ok:
return
for table in params:
core.bayesdb_table_guarantee_columns(self._bdb, table)
sql = '''
SELECT tabname, colno, name, shortname
FROM bayesdb_column
WHERE %s
ORDER BY tabname ASC, colno ASC
''' % (qualifier,)
with self._bdb.savepoint():
pretty.pp_cursor(self.stdout, self._bdb.execute(sql, params))
elif casefold(tokens[0]) == 'generator' or \
casefold(tokens[0]) == 'generators':
params = None
qualifier = None
if len(tokens) == 1:
params = ()
qualifier = '1'
else:
params = tokens[1:]
names = ','.join('?%d' % (i + 1,) for i in range(len(params)))
qualifier = '''
(name IN ({names}) OR (defaultp AND tabname IN ({names})))
'''.format(names=names)
ok = True
for generator in params:
if not core.bayesdb_has_generator_default(self._bdb,
generator):
self.stdout.write('No such generator: %s\n' %
(repr(generator),))
ok = False
if not ok:
return
sql = '''
SELECT id, name, tabname, metamodel
FROM bayesdb_generator
WHERE %s
''' % (qualifier,)
with self._bdb.savepoint():
pretty.pp_cursor(self.stdout,
self._bdb.sql_execute(sql, params))
elif casefold(tokens[0]) == 'columns':
if len(tokens) != 2:
self.stdout.write('Describe columns of what generator?\n')
return
generator = tokens[1]
with self._bdb.savepoint():
if not core.bayesdb_has_generator_default(self._bdb,
generator):
self.stdout.write('No such generator: %s\n' %
(repr(generator),))
return
generator_id = core.bayesdb_get_generator_default(self._bdb,
generator)
sql = '''
SELECT c.colno AS colno, c.name AS name,
gc.stattype AS stattype, c.shortname AS shortname
FROM bayesdb_generator AS g,
(bayesdb_column AS c LEFT OUTER JOIN
bayesdb_generator_column AS gc
USING (colno))
WHERE g.id = ? AND g.id = gc.generator_id
AND g.tabname = c.tabname
ORDER BY colno ASC;
'''
cursor = self._bdb.sql_execute(sql, (generator_id,))
pretty.pp_cursor(self.stdout, cursor)
elif casefold(tokens[0]) == 'model' or \
casefold(tokens[0]) == 'models':
if len(tokens) < 2:
self.stdout.write('Describe models of what generator?\n')
return
generator = tokens[1]
with self._bdb.savepoint():
if not core.bayesdb_has_generator_default(self._bdb,
generator):
self.stdout.write('No such generator: %s\n' %
(repr(generator),))
return
generator_id = core.bayesdb_get_generator_default(self._bdb,
generator)
qualifier = None
if len(tokens) == 2:
qualifier = '1'
else:
modelnos = []
for token in tokens[2:]:
try:
modelno = int(token)
except ValueError:
self.stdout.write('Invalid model number: %s\n' %
(repr(token),))
return
else:
if not core.bayesdb_generator_has_model(
self._bdb, generator_id, modelno):
self.stdout.write('No such model: %d\n' %
(modelno,))
return
modelnos.append(modelno)
qualifier = 'modelno IN (%s)' % \
(','.join(map(str, modelnos),))
sql = '''
SELECT modelno, iterations FROM bayesdb_generator_model
WHERE generator_id = ? AND %s
''' % (qualifier,)
cursor = self._bdb.sql_execute(sql, (generator_id,))
pretty.pp_cursor(self.stdout, cursor)
else:
self.stdout.write('Usage: .describe table(s) [<table>...]\n')
self.stdout.write(' .describe generator(s) [<gen>...]\n')
self.stdout.write(' .describe columns <gen>\n')
self.stdout.write(' .describe model(s) <gen> [<model>...]\n')
def dot_describe(self, line):
'''describe BayesDB entities
[table(s)|generator(s)|columns|model(s)] [<name>...]
Print a human-readable description of the specified BayesDB
entities.
'''
# XXX Lousy, lousy tokenizer.
tokens = line.split()
if len(tokens) == 0:
self.stdout.write('Usage: .describe table(s) [<table>...]\n')
self.stdout.write(' .describe generator(s) [<gen>...]\n')
self.stdout.write(' .describe columns <gen>\n')
self.stdout.write(' .describe model(s) <gen> [<model>...]\n')
return
if casefold(tokens[0]) == 'table' or \
casefold(tokens[0]) == 'tables':
params = None
qualifier = None
if len(tokens) == 1:
params = ()
qualifier = '1'
else:
params = tokens[1:]
qualifier = \
'(' + ' OR '.join(['tabname = ?' for _p in params]) + ')'
ok = True
for table in params:
if not core.bayesdb_has_table(self._bdb, table):
self.stdout.write('No such table: %s\n' %
(repr(table),))
ok = False
if not ok:
return
for table in params:
core.bayesdb_table_guarantee_columns(self._bdb, table)
sql = '''
SELECT tabname, colno, name, shortname
FROM bayesdb_column
WHERE %s
ORDER BY tabname ASC, colno ASC
''' % (qualifier,)
with self._bdb.savepoint():
pretty.pp_cursor(self.stdout, self._bdb.execute(sql, params))
elif casefold(tokens[0]) == 'generator' or \
casefold(tokens[0]) == 'generators':
params = None
qualifier = None
if len(tokens) == 1:
params = ()
qualifier = '1'
else:
params = tokens[1:]
names = ','.join('?%d' % (i + 1,) for i in range(len(params)))
qualifier = '''
(name IN ({names}) OR (defaultp AND tabname IN ({names})))
'''.format(names=names)
ok = True
for generator in params:
if not core.bayesdb_has_generator_default(self._bdb,
generator):
self.stdout.write('No such generator: %s\n' %
(repr(generator),))
ok = False
if not ok:
return
sql = '''
SELECT id, name, tabname, metamodel
FROM bayesdb_generator
WHERE %s
''' % (qualifier,)
with self._bdb.savepoint():
pretty.pp_cursor(self.stdout,
self._bdb.sql_execute(sql, params))
elif casefold(tokens[0]) == 'columns':
if len(tokens) != 2:
self.stdout.write('Describe columns of what generator?\n')
return
generator = tokens[1]
with self._bdb.savepoint():
if not core.bayesdb_has_generator_default(self._bdb,
generator):
self.stdout.write('No such generator: %s\n' %
(repr(generator),))
return
generator_id = core.bayesdb_get_generator_default(self._bdb,
generator)
sql = '''
SELECT c.colno AS colno, c.name AS name,
gc.stattype AS stattype, c.shortname AS shortname
FROM bayesdb_generator AS g,
(bayesdb_column AS c LEFT OUTER JOIN
bayesdb_generator_column AS gc
USING (colno))
WHERE g.id = ? AND g.id = gc.generator_id
AND g.tabname = c.tabname
ORDER BY colno ASC;
'''
cursor = self._bdb.sql_execute(sql, (generator_id,))
pretty.pp_cursor(self.stdout, cursor)
elif casefold(tokens[0]) == 'model' or \
casefold(tokens[0]) == 'models':
if len(tokens) < 2:
self.stdout.write('Describe models of what generator?\n')
return
generator = tokens[1]
with self._bdb.savepoint():
if not core.bayesdb_has_generator_default(self._bdb,
generator):
self.stdout.write('No such generator: %s\n' %
(repr(generator),))
return
generator_id = core.bayesdb_get_generator_default(self._bdb,
generator)
qualifier = None
if len(tokens) == 2:
qualifier = '1'
else:
modelnos = []
for token in tokens[2:]:
try:
modelno = int(token)
except ValueError:
self.stdout.write('Invalid model number: %s\n' %
(repr(token),))
return
else:
if not core.bayesdb_generator_has_model(
self._bdb, generator_id, modelno):
self.stdout.write('No such model: %d\n' %
(modelno,))
return
modelnos.append(modelno)
qualifier = 'modelno IN (%s)' % \
(','.join(map(str, modelnos),))
sql = '''
SELECT modelno, iterations FROM bayesdb_generator_model
WHERE generator_id = ? AND %s
''' % (qualifier,)
cursor = self._bdb.sql_execute(sql, (generator_id,))
pretty.pp_cursor(self.stdout, cursor)
else:
self.stdout.write('Usage: .describe table(s) [<table>...]\n')
self.stdout.write(' .describe generator(s) [<gen>...]\n')
self.stdout.write(' .describe columns <gen>\n')
self.stdout.write(' .describe model(s) <gen> [<model>...]\n')
