Add Multi-Instrument Rotation Trading Example with Controller for Bin…

…ance

examples/live/binance/binance_futures_testnet_ema_cross_with_instrument_selector.py

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+#!/usr/bin/env python3
+# -------------------------------------------------------------------------------------------------
+#  Copyright (C) 2015-2024 Nautech Systems Pty Ltd. All rights reserved.
+#  https://nautechsystems.io
+#
+#  Licensed under the GNU Lesser General Public License Version 3.0 (the "License");
+#  You may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at https://www.gnu.org/licenses/lgpl-3.0.en.html
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+# -------------------------------------------------------------------------------------------------
+
+
+from decimal import Decimal
+from datetime import datetime
+
+from nautilus_trader.adapters.binance.common.enums import BinanceAccountType
+from nautilus_trader.adapters.binance.config import (
+    BinanceDataClientConfig,
+    BinanceExecClientConfig,
+)
+from nautilus_trader.adapters.binance.factories import (
+    BinanceLiveDataClientFactory,
+    BinanceLiveExecClientFactory,
+)
+from nautilus_trader.cache.config import CacheConfig
+from nautilus_trader.config import (
+    ImportableControllerConfig,
+    InstrumentProviderConfig,
+    LiveExecEngineConfig,
+    LoggingConfig,
+    TradingNodeConfig,
+)
+from nautilus_trader.live.node import TradingNode
+from nautilus_trader.model.data import BarType
+from nautilus_trader.model.identifiers import InstrumentId, TraderId
+
+
+# *** THIS IS A TEST STRATEGY WITH NO ALPHA ADVANTAGE WHATSOEVER. ***
+# *** IT IS NOT INTENDED TO BE USED TO TRADE LIVE WITH REAL MONEY. ***
+
+# Configure the trading node
+config_node = TradingNodeConfig(
+    trader_id=TraderId("TESTER-001"),
+    logging=LoggingConfig(log_level="INFO"),
+    exec_engine=LiveExecEngineConfig(
+        # debug=True,
+        reconciliation=True,
+        reconciliation_lookback_mins=1440,
+        # snapshot_orders=True,
+        # snapshot_positions=True,
+        # snapshot_positions_interval_secs=5.0,
+    ),
+    cache=CacheConfig(
+        # database=DatabaseConfig(timeout=2),
+        timestamps_as_iso8601=True,
+        flush_on_start=False,
+    ),
+    # message_bus=MessageBusConfig(
+    #     database=DatabaseConfig(timeout=2),
+    #     timestamps_as_iso8601=True,
+    #     use_instance_id=False,
+    #     # types_filter=[QuoteTick],
+    #     stream_per_topic=False,
+    #     external_streams=["bybit"],
+    #     autotrim_mins=30,
+    # ),
+    controller = ImportableControllerConfig(
+        controller_path="nautilus_trader.examples.strategies.simple_insturment_selector_controller:BinanceFutureInstrumentSelectorController",
+        config_path="nautilus_trader.examples.strategies.simple_insturment_selector_controller:BinanceFutureInstrumentSelectorControllerConfig",
+        config={
+            "interval_secs": 3600,
+            "min_notional_threshold": 6,
+            "quote_asset": "USDT",
+            "onboard_date_filter_type": "range",
+            "onboard_date_reference_date": datetime(2024, 1, 1),
+            "onboard_date_end_date": datetime(2024, 6, 1),
+        },
+    ),
+    data_clients={
+        "BINANCE": BinanceDataClientConfig(
+            api_key=None,  # 'BINANCE_API_KEY' env var
+            api_secret=None,  # 'BINANCE_API_SECRET' env var
+            account_type=BinanceAccountType.USDT_FUTURE,
+            base_url_http=None,  # Override with custom endpoint
+            base_url_ws=None,  # Override with custom endpoint
+            us=False,  # If client is for Binance US
+            testnet=True,  # If client uses the testnet
+            instrument_provider=InstrumentProviderConfig(load_all=True),
+        ),
+    },
+    exec_clients={
+        "BINANCE": BinanceExecClientConfig(
+            api_key=None,  # 'BINANCE_API_KEY' env var
+            api_secret=None,  # 'BINANCE_API_SECRET' env var
+            account_type=BinanceAccountType.USDT_FUTURE,
+            base_url_http=None,  # Override with custom endpoint
+            base_url_ws=None,  # Override with custom endpoint
+            us=False,  # If client is for Binance US
+            testnet=True,  # If client uses the testnet
+            instrument_provider=InstrumentProviderConfig(load_all=True),
+            use_position_ids=False,
+            max_retries=3,
+            retry_delay=1.0,
+        ),
+    },
+    timeout_connection=30.0,
+    timeout_reconciliation=10.0,
+    timeout_portfolio=10.0,
+    timeout_disconnection=10.0,
+    timeout_post_stop=5.0,
+)
+
+# Instantiate the node with a configuration
+node = TradingNode(config=config_node)
+
+# Register your client factories with the node (can take user-defined factories)
+node.add_data_client_factory("BINANCE", BinanceLiveDataClientFactory)
+node.add_exec_client_factory("BINANCE", BinanceLiveExecClientFactory)
+node.build()
+
+
+# Stop and dispose of the node with SIGINT/CTRL+C
+if __name__ == "__main__":
+    try:
+        node.run()
+    finally:
+        node.dispose()

nautilus_trader/examples/strategies/simple_binance_symbols_filter.py

@@ -0,0 +1,121 @@
+# -------------------------------------------------------------------------------------------------
+#  Copyright (C) 2015-2024 Nautech Systems Pty Ltd. All rights reserved.
+#  https://nautechsystems.io
+#
+#  Licensed under the GNU Lesser General Public License Version 3.0 (the "License");
+#  You may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at https://www.gnu.org/licenses/lgpl-3.0.en.html
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+# -------------------------------------------------------------------------------------------------
+
+import json
+from datetime import datetime, timedelta
+from typing import Optional, Tuple
+
+import pandas as pd
+import requests
+
+
+def extract_symbol_info(api_url: str = "https://fapi.binance.com/fapi/v1/exchangeInfo") -> Tuple[Optional[pd.DataFrame], Optional[str]]:
+    """Fetch and extract symbol info from Binance Futures API and return it as a DataFrame.
+    
+    Args:
+    - api_url (str): The API URL to fetch data from (default: Binance Futures API).
+
+    Returns:
+    - Tuple containing the DataFrame and an optional error message.
+    """
+    try:
+        # Send a GET request to the Binance API
+        response = requests.get(api_url)
+        response.raise_for_status()
+
+        # Load the JSON response
+        json_data = response.json()
+
+        # Extract symbols data from JSON
+        symbols = json_data['symbols']
+        df = pd.DataFrame(symbols)
+
+        # Filter DataFrame for 'PERPETUAL' contract type and 'TRADING' status
+        df = df[(df['contractType'] == 'PERPETUAL') & (df['status'] == 'TRADING')]
+
+        return df, None
+
+    except requests.exceptions.RequestException as e:
+        return None, f"Request error: {e}"
+    except json.JSONDecodeError:
+        return None, "Error decoding JSON"
+    except KeyError as e:
+        return None, f"Unexpected JSON structure, missing key: {e}"
+
+
+def select_with_quoteAsset(df: pd.DataFrame, quoteAsset: str) -> pd.DataFrame:
+    """Filter DataFrame for products with a specific quote asset.
+
+    Args:
+    - df (pd.DataFrame): The DataFrame to filter.
+    - quoteAsset (str): The quote asset to filter by.
+
+    Returns:
+    - pd.DataFrame: Filtered DataFrame.
+    """
+    return df[df['quoteAsset'] == quoteAsset]
+
+def select_with_min_notional(df: pd.DataFrame, min_notional_threshold: float) -> pd.DataFrame:
+    """Add a min_notional column to the DataFrame and filter it based on a threshold.
+
+    Args:
+    - df (pd.DataFrame): The DataFrame to process.
+    - min_notional_threshold (float): The threshold to filter min_notional values.
+
+    Returns:
+    - pd.DataFrame: DataFrame with min_notional columns and filtered values.
+    """
+    # Extract 'MIN_NOTIONAL' from filters and set it in the DataFrame
+    df = df.copy()
+    df['min_notional'] = df['filters'].apply(lambda x: next(
+        (float(filter_item.get('notional', 0)) for filter_item in x if filter_item.get('filterType') == 'MIN_NOTIONAL'), 0))
+    # Filter the DataFrame where min_notional is less than the threshold
+    return df[df['min_notional'] < min_notional_threshold]
+
+
+def filter_with_onboard_date(df: pd.DataFrame, 
+                             filter_type: str, 
+                             reference_date: datetime, 
+                             end_date: datetime = None) -> pd.DataFrame:
+    """Filter the DataFrame based on onboardDate according to the specified criteria.
+
+    Args:
+    - df (pd.DataFrame): The DataFrame containing the onboardDate column.
+    - filter_type (str): The type of filter to apply. Can be 'before', 'range', or 'after'.
+    - reference_date (datetime): The date to use for filtering.
+    - end_date (datetime, optional): The end date for 'range' filter type. Required if filter_type is 'range'.
+
+    Returns:
+    - pd.DataFrame: Filtered DataFrame based on the specified filter type and dates.
+    """
+    # Convert onboardDate from milliseconds timestamp to datetime
+    df = df.copy()
+    df['onboardDate_convert'] = pd.to_datetime(df['onboardDate'], unit='ms')
+
+    if filter_type == 'before':
+        # Filter the DataFrame for onboardDate earlier than the reference date
+        filtered_df = df[df['onboardDate_convert'] < reference_date]
+    elif filter_type == 'range':
+        if end_date is None:
+            raise ValueError("end_date must be provided for 'range' filter type.")
+        # Filter the DataFrame for onboardDate within the specified date range
+        filtered_df = df[(df['onboardDate_convert'] >= reference_date) & (df['onboardDate_convert'] <= end_date)]
+    elif filter_type == 'after':
+        # Filter the DataFrame for onboardDate later than the reference date
+        filtered_df = df[df['onboardDate_convert'] > reference_date]
+    else:
+        raise ValueError("filter_type must be one of 'before', 'range', or 'after'.")
+
+    return filtered_df