str) is not None and
version.parse(predictor_record.mindsdb_version)
< last_compatible_version):
predictor_record.update_status = 'available'
is_modified = True
if is_modified is True:
db.session.commit()
# endregion
for integration_name in datasource_interface.get_db_integrations(
sensitive_info=True):
print(f"Setting up integration: {integration_name}")
if datasource_interface.get_db_integration(integration_name).get(
'publish', False):
# do setup and register only if it is 'publish' integration
dbw.setup_integration(integration_name)
dbw.register_predictors(model_data_arr,
integration_name=integration_name)
for integration_name in config.get('integrations', {}):
try:
it = datasource_interface.get_db_integration(integration_name)
if it is not None:
datasource_interface.remove_db_integration(
integration_name)
print(f'Adding: {integration_name}')
datasource_interface.add_db_integration(
integration_name, config['integrations'][integration_name]
) # Setup for user `None`, since we don't need this for cloud
if config['integrations'][integration_name].get(
'publish', False) and not is_cloud:
'mysql': start_mysql,
'mongodb': start_mongo
}
archive_obsolete_predictors(config, '2.11.0')
mdb = NativeInterface(config)
cst = CustomModels(config)
remove_corrupted_predictors(config, mdb)
model_data_arr = get_all_models_meta_data(mdb, cst)
dbw = DatabaseWrapper(config)
for db_alias in config['integrations']:
dbw.setup_integration(db_alias)
dbw.register_predictors(model_data_arr)
for broken_name in [
name for name, connected in dbw.check_connections().items()
if connected is False
]:
log.error(
f'Error failed to integrate with database aliased: {broken_name}')
ctx = mp.get_context('spawn')
for api_name, api_data in apis.items():
print(f'{api_name} API: starting...')
try:
p = ctx.Process(target=start_functions[api_name],
