def create_db_path(cls, db_path: Optional[str] = None, db_name: Optional[str] = None) -> str:
if db_path is not None:
return db_path
if db_name is not None:
return join(data_path(), f"{db_name}.sqlite")
else:
return join(data_path(), "hummingbot_trades.sqlite")
def append_to_csv(self, trade: TradeFill):
csv_filename = "trades_" + trade.config_file_path[:-4] + ".csv"
csv_path = os.path.join(data_path(), csv_filename)
field_names = tuple(trade.attribute_names_for_file_export())
field_data = tuple(getattr(trade, attr) for attr in field_names)
# adding extra field "age"
# // indicates order is a paper order so 'n/a'. For real orders, calculate age.
age = pd.Timestamp(int((trade.timestamp * 1e-3) -
(trade.order.creation_timestamp * 1e-3)),
unit='s').strftime('%H:%M:%S') if (
trade.order is not None
and "//" not in trade.order_id) else "n/a"
field_names += ("age", )
field_data += (age, )
if (os.path.exists(csv_path)
and (not self._csv_matches_header(csv_path, field_names))):
move(
csv_path, csv_path[:-4] + '_old_' +
pd.Timestamp.utcnow().strftime("%Y%m%d-%H%M%S") + ".csv")
if not os.path.exists(csv_path):
df_header = pd.DataFrame([field_names])
df_header.to_csv(csv_path, mode='a', header=False, index=False)
df = pd.DataFrame([field_data])
df.to_csv(csv_path, mode='a', header=False, index=False)
def append_to_csv(self, trade: TradeFill):
csv_filename = "trades_" + trade.config_file_path[:-4] + ".csv"
csv_path = os.path.join(data_path(), csv_filename)
field_names = ("exchange_trade_id", ) # id field should be first
field_names += tuple(attr for attr in dir(trade) if (
not self._is_protected_method(attr) and self._is_primitive_type(
getattr(trade, attr)) and (attr not in field_names)))
field_data = tuple(getattr(trade, attr) for attr in field_names)
# adding extra field "age"
# // indicates order is a paper order so 'n/a'. For real orders, calculate age.
age = pd.Timestamp(
int(trade.timestamp / 1e3 - int(trade.order_id[-16:]) / 1e6),
unit='s').strftime(
'%H:%M:%S') if "//" not in trade.order_id else "n/a"
field_names += ("age", )
field_data += (age, )
if (os.path.exists(csv_path)
and (not self._csv_matches_header(csv_path, field_names))):
move(
csv_path, csv_path[:-4] + '_old_' +
pd.Timestamp.utcnow().strftime("%Y%m%d-%H%M%S") + ".csv")
if not os.path.exists(csv_path):
df_header = pd.DataFrame([field_names])
df_header.to_csv(csv_path, mode='a', header=False, index=False)
df = pd.DataFrame([field_data])
df.to_csv(csv_path, mode='a', header=False, index=False)
def __init__(self, connection_type: SQLConnectionType, db_path: Optional[str] = None):
if db_path is None:
db_path = join(data_path(), "hummingbot_trades.sqlite")
if connection_type is SQLConnectionType.TRADE_FILLS:
self._engine: Engine = create_engine(f"sqlite:///{db_path}")
self._metadata: MetaData = self.get_declarative_base().metadata
self._metadata.create_all(self._engine)
self._session_cls = sessionmaker(bind=self._engine)
self._shared_session: Session = self._session_cls()
if connection_type is SQLConnectionType.TRADE_FILLS:
self.check_and_upgrade_trade_fills_db()
def append_to_csv(self, trade: TradeFill):
csv_file = "trades_" + trade.config_file_path[:-4] + ".csv"
csv_path = os.path.join(data_path(), csv_file)
# // indicates order is a paper order so 'n/a'. For real orders, calculate age.
age = "n/a"
if "//" not in trade.order_id:
age = pd.Timestamp(int(trade.timestamp / 1e3 - int(trade.order_id[-16:]) / 1e6), unit='s').strftime('%H:%M:%S')
if not os.path.exists(csv_path):
df_header = pd.DataFrame([["Config File", "Strategy", "Exchange", "Timestamp", "Market", "Base", "Quote",
"Trade", "Type", "Price", "Amount", "Fee", "Age", "Order ID", "Exchange Trade ID"]])
df_header.to_csv(csv_path, mode='a', header=False, index=False)
df = pd.DataFrame([[trade.config_file_path, trade.strategy, trade.market, trade.timestamp, trade.symbol, trade.base_asset, trade.quote_asset,
trade.trade_type, trade.order_type, trade.price, trade.amount, trade.trade_fee, age, trade.order_id, trade.exchange_trade_id]])
df.to_csv(csv_path, mode='a', header=False, index=False)
def __init__(self,
connection_type: SQLConnectionType,
db_path: Optional[str] = None):
if db_path is None:
db_path = join(data_path(), "hummingbot_trades.sqlite")
engine_options = {
"db_engine": global_config_map.get("db_engine").value,
"db_host": global_config_map.get("db_host").value,
"db_port": global_config_map.get("db_port").value,
"db_username": global_config_map.get("db_username").value,
"db_password": global_config_map.get("db_password").value,
"db_name": global_config_map.get("db_name").value,
"db_path": db_path
}
if connection_type is SQLConnectionType.TRADE_FILLS:
self._engine: Engine = self.get_db_engine(
engine_options.get("db_engine"), engine_options)
self._metadata: MetaData = self.get_declarative_base().metadata
self._metadata.create_all(self._engine)
# SQLite does not enforce foreign key constraint, but for others engines, we need to drop it.
# See: `hummingbot/market/markets_recorder.py`, at line 213.
with self._engine.begin() as conn:
inspector = inspect(conn)
for tname, fkcs in reversed(
inspector.get_sorted_table_and_fkc_names()):
if fkcs:
if not self._engine.dialect.supports_alter:
continue
for fkc in fkcs:
fk_constraint = ForeignKeyConstraint((), (),
name=fkc)
Table(tname, MetaData(), fk_constraint)
conn.execute(DropConstraint(fk_constraint))
self._session_cls = sessionmaker(bind=self._engine)
self._shared_session: Session = self._session_cls()
if connection_type is SQLConnectionType.TRADE_FILLS:
self.check_and_upgrade_trade_fills_db()
