Source code for tradeexecutor.analysis.fee_analyser

"""Analyser trading fees."""
import numpy as np
import pandas as pd

from tradeexecutor.state.state import State
from import TradeExecution

[docs]def analyse_trading_fees( state: State, ) -> pd.DataFrame: """Create a table containing trading fees for every trade. :return: DataFrame with the following columns. - strategy_cycle_at - pair_ticker - trade_type ("buy" or "sell") - pair_id - value_usd - fee_tier - fees_paid_usd - fees_paid_pct - fees_estimated_usd - fees_estimated_pct """ rows = [] trade: TradeExecution for trade in state.portfolio.get_all_trades(): pair = trade.pair type = "buy" if trade.is_buy() else "sell" estimated_fees = trade.lp_fees_estimated or 0 row = { "strategy_cycle_at": trade.strategy_cycle_at, "pair_id": pair.internal_id, "pair_ticker": pair.get_ticker(), "trade_type": type, "value_usd": trade.get_value(), "fee_tier": trade.fee_tier, "fees_paid_usd": trade.get_fees_paid(), "fees_paid_pct": trade.get_fees_paid() / trade.get_value(), "fees_estimated_usd": estimated_fees, "fees_estimated_pct": estimated_fees / trade.get_value(), } rows.append(row) return pd.DataFrame(rows)
[docs]def create_pair_trading_fee_summary_table(analysis: pd.DataFrame) -> pd.DataFrame: """Creates a summary table that break down trading fees per pair and trade type. :param analysis: DataFrame of all trades analysed. Output from :py:func:`analyse_trading_fees`. """ # agg_funcs = { "fee_tier": [np.max, np.min], "value_usd": [np.sum, np.max, np.min, np.mean], "fees_paid_usd": [np.sum, np.max, np.min, np.mean], "fees_paid_pct": [np.max, np.min, np.mean], "fees_estimated_usd": [np.max, np.min, np.mean], "fees_estimated_pct": [np.max, np.min, np.mean], } return pd.pivot_table( analysis, index=['pair_ticker', 'trade_type'], values=['fee_tier', 'value_usd', 'fees_paid_usd', 'fees_paid_pct', 'fees_estimated_usd', 'fees_estimated_pct'], aggfunc=agg_funcs)