513 lines
23 KiB
Python
513 lines
23 KiB
Python
import logging
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import pandas as pd
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from DataCache_v3 import DataCache
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from indicators import Indicators
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from trade import Trades
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import datetime as dt
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import json
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import uuid
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import traceback
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from typing import Any
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from PythonGenerator import PythonGenerator
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from StrategyInstance import StrategyInstance
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# Configure logging
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logger = logging.getLogger(__name__)
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class Strategies:
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def __init__(self, data_cache: DataCache, trades: Trades, indicators: Indicators):
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"""
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Initializes the Strategies class.
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:param data_cache: Instance of DataCache to manage cache and database interactions.
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:param trades: Reference to the trades object that maintains trading actions and data.
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:param indicators: Reference to the Indicators manager.
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"""
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self.data_cache = data_cache # Database interaction instance
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self.trades = trades
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self.indicators_manager = indicators
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# Create a cache for strategies with necessary columns
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self.data_cache.create_cache(name='strategies',
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cache_type='table',
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size_limit=500,
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eviction_policy='deny',
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default_expiration=dt.timedelta(hours=24),
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columns=["id", "creator", "name", "workspace", "code", "stats", "public", "fee",
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"tbl_key", "strategy_components"])
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# Create a cache for strategy contexts to store strategy states and settings
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self.data_cache.create_cache(
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name='strategy_contexts',
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cache_type='table',
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size_limit=1000,
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eviction_policy='deny',
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default_expiration=dt.timedelta(hours=24),
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columns=[
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"strategy_instance_id", # Unique identifier for the strategy instance
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"flags", # JSON-encoded string to store flags
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"profit_loss", # Float value for tracking profit/loss
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"active", # Boolean or Integer (1/0) for active status
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"paused", # Boolean or Integer (1/0) for paused status
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"exit", # Boolean or Integer (1/0) for exit status
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"exit_method", # String defining exit method
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"start_time" # ISO-formatted datetime string for start time
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]
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)
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# Initialize default settings
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self.default_timeframe = '5m'
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self.default_exchange = 'Binance'
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self.default_symbol = 'BTCUSD'
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self.active_instances: dict[tuple[int, str], StrategyInstance] = {} # Key: (user_id, strategy_id)
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def _save_strategy(self, strategy_data: dict, default_source: dict) -> dict:
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"""
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Saves a strategy to the cache and database. Handles both creation and editing.
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:param strategy_data: A dictionary containing strategy data such as name, code, workspace, etc.
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:param default_source: The default source for undefined sources in the strategy.
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:return: A dictionary containing success or failure information.
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"""
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is_edit = 'tbl_key' in strategy_data
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try:
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if is_edit:
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# Editing an existing strategy
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tbl_key = strategy_data['tbl_key']
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existing_strategy = self.data_cache.get_rows_from_datacache(
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cache_name='strategies',
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filter_vals=[('tbl_key', tbl_key)]
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)
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if existing_strategy.empty:
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return {"success": False, "message": "Strategy not found."}
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else:
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# Creating a new strategy
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# Generate a unique identifier first
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tbl_key = str(uuid.uuid4())
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# Check if a strategy with the same name already exists for this user
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filter_conditions = [
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('creator', strategy_data.get('creator')),
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('name', strategy_data['name'])
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]
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existing_strategy = self.data_cache.get_rows_from_datacache(
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cache_name='strategies',
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filter_vals=filter_conditions
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)
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if not existing_strategy.empty:
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return {"success": False, "message": "A strategy with this name already exists"}
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# Validate and serialize 'workspace' (XML string)
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workspace_data = strategy_data.get('workspace')
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if not isinstance(workspace_data, str) or not workspace_data.strip():
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return {"success": False, "message": "Invalid or empty workspace data"}
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# Serialize 'stats' field
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try:
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stats_data = strategy_data.get('stats', {})
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stats_serialized = json.dumps(stats_data)
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except (TypeError, ValueError):
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return {"success": False, "message": "Invalid stats data format"}
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default_source = default_source.copy()
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strategy_id = tbl_key
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# Extract and validate 'code' as a dictionary
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code = strategy_data.get('code')
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if isinstance(code, str):
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try:
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strategy_json = json.loads(code)
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if not isinstance(strategy_json, dict):
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return {"success": False, "message": "'code' must be a JSON object."}
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except json.JSONDecodeError:
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return {"success": False, "message": "Invalid JSON format for 'code'."}
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elif isinstance(code, dict):
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strategy_json = code
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# Serialize 'code' to JSON string
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try:
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serialized_code = json.dumps(code)
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strategy_data['code'] = serialized_code
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except (TypeError, ValueError):
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return {"success": False, "message": "Unable to serialize 'code' field."}
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else:
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return {"success": False, "message": "'code' must be a JSON string or dictionary."}
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# Initialize PythonGenerator
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python_generator = PythonGenerator(default_source, strategy_id)
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# Generate strategy components (code, indicators, data_sources, flags)
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strategy_components = python_generator.generate(strategy_json)
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# Add the combined strategy components to the data to be stored
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strategy_data['strategy_components'] = json.dumps(strategy_components)
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if is_edit:
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# Editing existing strategy
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tbl_key = strategy_data['tbl_key']
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# Prepare the columns and values for the update
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columns = (
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"creator", "name", "workspace", "code", "stats", "public", "fee", "tbl_key", "strategy_components"
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)
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values = (
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strategy_data.get('creator'),
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strategy_data['name'],
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workspace_data, # Use the validated workspace data
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strategy_data['code'],
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stats_serialized, # Serialized stats
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bool(strategy_data.get('public', 0)),
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float(strategy_data.get('fee', 0.0)),
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tbl_key,
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strategy_data['strategy_components'] # Serialized strategy components
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)
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# Update the strategy in the database and cache
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self.data_cache.modify_datacache_item(
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cache_name='strategies',
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filter_vals=[('tbl_key', tbl_key)],
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field_names=columns,
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new_values=values,
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key=tbl_key,
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overwrite='tbl_key' # Use 'tbl_key' to identify the entry to overwrite
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)
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# Return success message
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return {"success": True, "message": "Strategy updated successfully"}
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else:
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# Creating new strategy
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# Insert the strategy into the database and cache
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self.data_cache.insert_row_into_datacache(
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cache_name='strategies',
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columns=(
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"creator", "name", "workspace", "code", "stats",
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"public", "fee", 'tbl_key', 'strategy_components'
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),
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values=(
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strategy_data.get('creator'),
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strategy_data['name'],
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strategy_data['workspace'],
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strategy_data['code'],
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stats_serialized,
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bool(strategy_data.get('public', 0)),
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float(strategy_data.get('fee', 0.0)),
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tbl_key,
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strategy_data['strategy_components']
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)
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)
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# Construct the saved strategy data to return
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saved_strategy = {
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"id": tbl_key, # Assuming tbl_key is used as a unique identifier
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"creator": strategy_data.get('creator'),
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"name": strategy_data['name'],
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"workspace": workspace_data, # Original workspace data
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"code": strategy_data['code'],
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"stats": stats_data,
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"public": bool(strategy_data.get('public', 0)),
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"fee": float(strategy_data.get('fee', 0.0))
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}
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# If everything is successful, return a success message along with the saved strategy data
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return {
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"success": True,
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"message": "Strategy created and saved successfully",
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"strategy": saved_strategy # Include the strategy data
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}
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except Exception as e:
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# Catch any exceptions and return a failure message
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# Log the exception with traceback for debugging
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logger.error(f"Failed to save strategy: {e}", exc_info=True)
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traceback.print_exc()
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operation = "update" if is_edit else "create"
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return {"success": False, "message": f"Failed to {operation} strategy: {str(e)}"}
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def new_strategy(self, strategy_data: dict, default_source: dict) -> dict:
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"""
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Add a new strategy to the cache and database.
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:param default_source: The default source for undefined sources in the strategy.
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:param strategy_data: A dictionary containing strategy data such as name, code, and workspace.
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:return: A dictionary containing success or failure information.
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"""
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return self._save_strategy(strategy_data, default_source)
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def edit_strategy(self, strategy_data: dict, default_source: dict) -> dict:
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"""
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Updates an existing strategy in the cache and database.
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:param default_source: The default source for undefined sources in the strategy.
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:param strategy_data: A dictionary containing the updated strategy data.
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:return: A dictionary containing success or failure information.
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"""
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return self._save_strategy(strategy_data, default_source)
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def delete_strategy(self, user_id: int, name: str) -> dict:
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try:
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self.data_cache.remove_row_from_datacache(
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cache_name='strategies',
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filter_vals=[('creator', user_id), ('name', name)]
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)
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return {"success": True, "message": "Strategy deleted successfully."}
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except Exception as e:
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logger.error(f"Failed to delete strategy '{name}' for user '{user_id}': {e}", exc_info=True)
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return {"success": False, "message": f"Failed to delete strategy: {str(e)}"}
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def get_all_strategy_names(self, user_id: int) -> list | None:
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"""
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Return a list of all strategy names stored in the cache or database.
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"""
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# Fetch all strategy names from the cache or database
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strategies_df = self.get_all_strategies(user_id, 'df')
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if not strategies_df.empty:
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return strategies_df['name'].tolist()
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return None
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def get_all_strategies(self, user_id: int, form: str):
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"""
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Return stored strategies in various formats.
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:param user_id: the id of the user making the request.
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:param form: The desired format ('obj', 'json', or 'dict').
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:return: A list of strategies in the requested format.
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"""
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valid_forms = {'df', 'json', 'dict'}
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if form not in valid_forms:
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raise ValueError(f"Invalid form '{form}'. Expected one of {valid_forms}.")
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# Fetch all public strategies and user's strategies from the cache or database
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public_df = self.data_cache.get_rows_from_datacache(cache_name='strategies', filter_vals=[('public', 1)])
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user_df = self.data_cache.get_rows_from_datacache(cache_name='strategies', filter_vals=[('creator', user_id),
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('public', 0)])
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# Concatenate the two DataFrames (rows from public and user-created strategies)
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strategies_df = pd.concat([public_df, user_df], ignore_index=True)
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# Return None if no strategies found
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if strategies_df.empty:
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return None
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# Return the strategies in the requested format
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if form == 'df':
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return strategies_df
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elif form == 'json':
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return strategies_df.to_json(orient='records')
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elif form == 'dict':
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return strategies_df.to_dict('records')
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def get_strategy_by_name(self, user_id: int, name: str) -> dict[str, Any] | None:
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"""
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Retrieve a strategy object by name.
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:param user_id: The ID of the user making the request.
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:param name: The name of the strategy to retrieve.
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:return: The strategy DataFrame row if found, otherwise None.
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"""
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# Fetch all strategies (public and user-specific) as a DataFrame
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strategies_df = self.get_all_strategies(user_id, 'df')
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# Ensure that strategies_df is not None
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if strategies_df is None:
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return None
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# Filter the DataFrame to find the strategy by name (exact match)
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name = name
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filtered_strategies = strategies_df.query('name == @name')
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# Return None if no matching strategy is found
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if filtered_strategies.empty:
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return None
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# Get the strategy row as a dictionary
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strategy_row = filtered_strategies.iloc[0].to_dict()
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# Deserialize the 'strategy_components' field
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try:
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strategy_components = json.loads(strategy_row.get('strategy_components', '{}'))
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except json.JSONDecodeError:
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strategy_components = {}
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strategy_row['strategy_components'] = strategy_components
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# If 'code' is stored as a JSON string, deserialize it
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if isinstance(strategy_row.get('code'), str):
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strategy_row['code'] = json.loads(strategy_row['code'])
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return strategy_row
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def update_strategy_stats(self, strategy_id: str, profit_loss: float) -> None:
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"""
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Updates the strategy's statistics based on the latest profit or loss.
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:param strategy_id: Identifier of the strategy.
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:param profit_loss: Latest profit or loss from strategy execution.
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"""
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try:
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# Fetch the current stats
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strategy = self.data_cache.get_rows_from_datacache(cache_name='strategies',
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filter_vals=[('tbl_key', strategy_id)])
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if strategy.empty:
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logger.warning(f"Strategy ID {strategy_id} not found for stats update.")
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return
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strategy_row = strategy.iloc[0].to_dict()
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current_stats = json.loads(strategy_row.get('stats', '{}'))
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# Update stats
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current_stats['num_trades'] = current_stats.get('num_trades', 0) + 1
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current_stats['total_position'] = current_stats.get('total_position', 0.0) + profit_loss
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current_stats['total_position_value'] = current_stats.get('total_position_value', 0.0) + profit_loss
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# Serialize and update in datacache
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self.data_cache.modify_datacache_item(cache_name='strategies', filter_vals=[('tbl_key', strategy_id)],
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field_names=('stats',), new_values=(json.dumps(current_stats),),
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key=strategy_id, overwrite='tbl_key')
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logger.info(f"Updated stats for strategy {strategy_id}: {current_stats}")
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except Exception as e:
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logger.error(f"Error updating stats for strategy '{strategy_id}': {e}", exc_info=True)
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def execute_strategy(self, strategy_data: dict[str, Any]) -> dict[str, Any]:
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"""
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Executes a strategy based on the provided strategy data.
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:param strategy_data: A dictionary containing strategy details.
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:return: A dictionary indicating success or failure with relevant messages.
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"""
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try:
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# Extract identifiers
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strategy_id = strategy_data.get('id') or strategy_data.get('tbl_key')
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strategy_name = strategy_data.get('name')
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user_id = strategy_data.get('creator')
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if not strategy_id or not strategy_name or not user_id:
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return {"success": False, "message": "Strategy data is incomplete."}
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# Generate a deterministic strategy_instance_id
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strategy_instance_id = f"{user_id}_{strategy_name}"
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instance_key = (user_id, strategy_id) # Unique key for the strategy-user pair
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# Retrieve or create StrategyInstance
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if instance_key not in self.active_instances:
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generated_code = strategy_data.get('strategy_components', {}).get('generated_code', '')
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if not generated_code:
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return {"success": False, "message": "No 'next()' method defined for the strategy."}
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# Instantiate StrategyInstance
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strategy_instance = StrategyInstance(
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strategy_instance_id=strategy_instance_id,
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strategy_id=strategy_id,
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strategy_name=strategy_name,
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user_id=user_id,
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generated_code=generated_code,
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data_cache=self.data_cache,
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indicators=self.indicators_manager,
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trades=self.trades
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)
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# Store in active_instances
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self.active_instances[instance_key] = strategy_instance
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logger.debug(f"Created new StrategyInstance '{strategy_instance_id}' for strategy '{strategy_id}'.")
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else:
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strategy_instance = self.active_instances[instance_key]
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logger.debug(
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f"Retrieved existing StrategyInstance '{strategy_instance_id}' for strategy '{strategy_id}'.")
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# Execute the strategy
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execution_result = strategy_instance.execute()
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if execution_result.get('success'):
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profit_loss = execution_result.get('profit_loss', 0.0)
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self.update_strategy_stats(strategy_id, profit_loss)
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logger.info(f"Strategy '{strategy_id}' executed successfully with profit/loss: {profit_loss}")
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# Check if exit was initiated
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if strategy_instance.exit:
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# Check if all trades are closed
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if self.trades.all_trades_closed(strategy_id):
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logger.info(f"Strategy '{strategy_id}' has successfully exited all trades.")
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# Remove from active_instances
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del self.active_instances[instance_key]
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# Optionally, mark the strategy as inactive in the database
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self.data_cache.modify_datacache_item(
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cache_name='strategies',
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filter_vals=[('tbl_key', strategy_id)],
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field_names=('active',),
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new_values=(False,),
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key=strategy_id,
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overwrite='tbl_key'
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)
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else:
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logger.info(
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f"Strategy '{strategy_id}' is exiting. Remaining trades will be closed in subsequent executions.")
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return {"success": True, "strategy_profit_loss": profit_loss}
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else:
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error_message = execution_result.get('message', 'Unknown error.')
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logger.error(f"Strategy '{strategy_id}' execution failed: {error_message}")
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return {"success": False, "message": f"Strategy execution failed: {error_message}"}
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except Exception as e:
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logger.error(f"Unexpected error in execute_strategy: {e}")
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traceback.print_exc()
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return {"success": False, "message": f"Unexpected error: {str(e)}"}
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def update(self):
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"""
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Loops through and executes all activated strategies.
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"""
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try:
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active_strategies = self.data_cache.get_rows_from_datacache('strategies', [('active', True)])
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if active_strategies.empty:
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logger.info("No active strategies to execute.")
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return # No active strategies to execute
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for _, strategy_data in active_strategies.iterrows():
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self.execute_strategy(strategy_data)
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except Exception as e:
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logger.error(f"Error updating strategies: {e}", exc_info=True)
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traceback.print_exc()
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def update_stats(self, strategy_id: str, stats: dict) -> None:
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"""
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Updates the strategy's statistics with the provided stats.
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:param strategy_id: Identifier of the strategy (tbl_key).
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:param stats: Dictionary containing statistics to update.
|
|
"""
|
|
try:
|
|
# Fetch the current strategy data
|
|
strategy = self.data_cache.get_rows_from_datacache(
|
|
cache_name='strategies',
|
|
filter_vals=[('tbl_key', strategy_id)]
|
|
)
|
|
|
|
if strategy.empty:
|
|
logger.warning(f"Strategy ID {strategy_id} not found for stats update.")
|
|
return
|
|
|
|
strategy_row = strategy.iloc[0].to_dict()
|
|
current_stats = json.loads(strategy_row.get('stats', '{}'))
|
|
|
|
# Merge the new stats with existing stats
|
|
current_stats.update(stats)
|
|
|
|
# Serialize the updated stats
|
|
updated_stats_serialized = json.dumps(current_stats)
|
|
|
|
# Update the stats in the data cache
|
|
self.data_cache.modify_datacache_item(
|
|
cache_name='strategies',
|
|
filter_vals=[('tbl_key', strategy_id)],
|
|
field_names=('stats',),
|
|
new_values=(updated_stats_serialized,),
|
|
key=strategy_id,
|
|
overwrite='tbl_key'
|
|
)
|
|
|
|
logger.info(f"Updated stats for strategy '{strategy_id}': {current_stats}")
|
|
|
|
except Exception as e:
|
|
logger.error(f"Error updating stats for strategy '{strategy_id}': {e}", exc_info=True) |