def __init__(self):
self.config = Config()
self.fs_store = FsSotre()
self.company_id = os.environ.get('MINDSDB_COMPANY_ID', None)
self.dir = self.config.paths['datasources']
self.mindsdb_native = NativeInterface()
def __init__(self, connection_info, advanced_info, topic_in, topic_out,
predictor, _type):
self.connection_info = connection_info
self.advanced_info = advanced_info
self.predictor = predictor
self.stream_in_name = topic_in
self.stream_out_name = topic_out
self.consumer = kafka.KafkaConsumer(
**self.connection_info, **self.advanced_info.get('consumer', {}))
self.consumer.subscribe(topics=[self.stream_in_name])
self.producer = kafka.KafkaProducer(
**self.connection_info, **self.advanced_info.get('producer', {}))
self.admin = kafka.KafkaAdminClient(**self.connection_info)
try:
self.topic = NewTopic(self.stream_out_name,
num_partitions=1,
replication_factor=1)
self.admin.create_topics([self.topic])
except kafka.errors.TopicAlreadyExistsError:
pass
self._type = _type
self.native_interface = NativeInterface()
self.format_flag = 'explain'
self.stop_event = Event()
self.company_id = os.environ.get('MINDSDB_COMPANY_ID', None)
self.caches = {}
if self._type == 'timeseries':
super().__init__(target=KafkaStream.make_timeseries_predictions,
args=(self, ))
else:
super().__init__(target=KafkaStream.make_prediction, args=(self, ))
def initialize_interfaces(app):
app.default_store = DataStore()
app.naitve_interface = NativeInterface()
app.custom_models = CustomModels()
app.dbw = DatabaseWrapper()
config = Config()
app.config_obj = config
def __init__(self):
self.config = Config()
self.fs_store = FsSotre()
self.company_id = os.environ.get('MINDSDB_COMPANY_ID', None)
self.dbw = DatabaseWrapper()
self.storage_dir = self.config['paths']['custom_models']
os.makedirs(self.storage_dir, exist_ok=True)
self.model_cache = {}
self.mindsdb_native = NativeInterface()
self.dbw = DatabaseWrapper()
def __init__(self, host, port, database, stream_in, stream_out, predictor, _type):
self.host = host
self.port = port
self.db = database
self.predictor = predictor
self.client = self._get_client()
self.stream_in_name = stream_in
self.stream_out_name = stream_out
self.stream_in = self.client.Stream(stream_in)
self.stream_out = self.client.Stream(stream_out)
self._type = _type
self.native_interface = NativeInterface()
self.format_flag = 'explain'
self.stop_event = Event()
self.company_id = os.environ.get('MINDSDB_COMPANY_ID', None)
super().__init__(target=RedisStream.make_prediction, args=(self,))
def __init__(self, config):
mongodb_config = config['api'].get('mongodb')
assert mongodb_config is not None, 'is no mongodb config!'
host = mongodb_config['host']
port = mongodb_config['port']
log.debug(f'start mongo server on {host}:{port}')
super().__init__((host, int(port)), MongoRequestHandler)
self.mindsdb_env = {
'config': config,
'data_store': DataStore(),
'mindsdb_native': NativeInterface()
}
respondersCollection = RespondersCollection()
opQueryResponder = OpQueryResponder(respondersCollection)
opMsgResponder = OpMsgResponder(respondersCollection)
opInsertResponder = OpInsertResponder(respondersCollection)
self.operationsHandlersMap = {
OP_QUERY: opQueryResponder,
OP_MSG: opMsgResponder,
OP_INSERT: opInsertResponder
}
respondersCollection.add(when={'drop': 'system.sessions'},
result={'ok': 1})
respondersCollection.add(when={'update': 'system.version'},
result={'ok': 1})
respondersCollection.add(
when={'setFeatureCompatibilityVersion': helpers.is_true},
result={'ok': 1})
# OpMSG=OrderedDict([('features', 1), ('$clusterTime', OrderedDict([('clusterTime', Timestamp(1599748325, 1)), ('signature', OrderedDict([('hash', b'\xb8\xc3\x03\x18\xca\xe6bh\xf0\xcb47,\x924\x8a >\xfc\x91'), ('keyId', 6870854312365391875)]))])), ('$configServerState', OrderedDict([('opTime', OrderedDict([('ts', Timestamp(1599748325, 1)), ('t', 1)]))])), ('$db', 'admin')])
respondersCollection.add(when={'features': helpers.is_true},
result={'ok': 1})
# OpMSG=OrderedDict([('serverStatus', 1), ('$clusterTime', OrderedDict([('clusterTime', Timestamp(1599748366, 1)), ('signature', OrderedDict([('hash', b'\xa1E}\xbbIU\xc2D\x95++\x82\x88\xb5\x84\xf5\xda)+B'), ('keyId', 6870854312365391875)]))])), ('$configServerState', OrderedDict([('opTime', OrderedDict([('ts', Timestamp(1599748366, 1)), ('t', 1)]))])), ('$db', 'admin')])
respondersCollection.add(when={'serverStatus': helpers.is_true},
result={'ok': 1})
# OpMSG=OrderedDict([('ismaster', 1), ('$db', 'admin'), ('$clusterTime', OrderedDict([('clusterTime', Timestamp(1599749031, 1)), ('signature', OrderedDict([('hash', b'6\x87\xd5Y\xa7\xc7\xcf$\xab\x1e\xa2{\xe5B\xe5\x99\xdbl\x8d\xf4'), ('keyId', 6870854312365391875)]))])), ('$client', OrderedDict([('application', OrderedDict([('name', 'MongoDB Shell')])), ('driver', OrderedDict([('name', 'MongoDB Internal Client'), ('version', '3.6.3')])), ('os', OrderedDict([('type', 'Linux'), ('name', 'Ubuntu'), ('architecture', 'x86_64'), ('version', '18.04')])), ('mongos', OrderedDict([('host', 'maxs-comp:27103'), ('client', '127.0.0.1:52148'), ('version', '3.6.3')]))])), ('$configServerState', OrderedDict([('opTime', OrderedDict([('ts', Timestamp(1599749031, 1)), ('t', 1)]))]))])
respondersCollection.responders += responders
def __init__(self, name, connection_info, advanced_info, stream_in, stream_out, predictor, _type):
self.stream_name = name
self.connection_info = connection_info
self.connection_info.update(advanced_info)
self.predictor = predictor
self.client = self._get_client()
self.stream_in_name = stream_in
self.stream_out_name = stream_out
self.stream_in = self.client.Stream(stream_in)
self.stream_out = self.client.Stream(stream_out)
self._type = _type
self.native_interface = NativeInterface()
self.format_flag = 'explain'
self.stop_event = Event()
self.company_id = os.environ.get('MINDSDB_COMPANY_ID', None)
if self._type == 'timeseries':
super().__init__(target=RedisStream.make_timeseries_predictions, args=(self,))
else:
super().__init__(target=RedisStream.make_predictions, args=(self,))
def __init__(self, name, connection_info, advanced_info, stream_in, stream_out, predictor, _type, **ts_params):
self.stream_name = name
self.connection_info = connection_info
self.connection_info.update(advanced_info)
self.predictor = predictor
self.client = self._get_client()
self.stream_in_name = stream_in
self.stream_out_name = stream_out
self.stream_in = self.client.Stream(stream_in)
self.stream_out = self.client.Stream(stream_out)
self._type = _type
self.native_interface = NativeInterface()
self.format_flag = 'explain'
self.stop_event = Event()
self.company_id = os.environ.get('MINDSDB_COMPANY_ID', None)
self.ts_params = ts_params
if self._type.lower() == StreamTypes.timeseries:
self.target = self.ts_params.get('target')
self.window = self.ts_params.get('window_size')
self.gb = self.ts_params.get('group_by')
self.dt = self.ts_params.get('order_by')
super().__init__(target=RedisStream.make_timeseries_predictions, args=(self,))
else:
super().__init__(target=RedisStream.make_predictions, args=(self,))
api: {
'port': config['api'][api]['port'],
'process': None,
'started': False
} for api in api_arr
}
if not ray_based:
apis['rcp'] = {'process': rpc_proc, 'started': True}
start_functions = {
'http': start_http,
'mysql': start_mysql,
'mongodb': start_mongo
}
mdb = NativeInterface()
cst = CustomModels()
model_data_arr = get_all_models_meta_data(mdb, cst)
dbw = DatabaseWrapper()
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}')
for api_name, api_data in apis.items():
if api_data['started']:
continue
def __init__(self, config):
self.config = Config()
self.mindsdb_native = NativeInterface()
self.custom_models = CustomModels()
self.ai_table = AITable_store()
self.default_store = DataStore()