Ergonomy fixes to backtest command (#1132)

- Small usability improvements
- Clean backtest report for warnings
- Add `decide_trades()` messages to the backtesting report template
- Add asset weight allocation to the backtesting report  template

tests/lagoon/conftest.py

@@ -413,7 +413,7 @@ def vault_strategy_universe(
 @pytest.fixture()
 def automated_lagoon_vault(
     web3,
-    deployer_local_account,
+    deployer_hot_wallet,
     asset_manager,
     multisig_owners,
     uniswap_v2,
@@ -425,7 +425,7 @@ def automated_lagoon_vault(
     """
 
     chain_id = web3.eth.chain_id
-    deployer = deployer_local_account
+    deployer = deployer_hot_wallet
 
     parameters = LagoonDeploymentParameters(
         underlying=USDC_NATIVE_TOKEN[chain_id],
@@ -528,10 +528,16 @@ def uniswap_v3(web3) -> UniswapV3Deployment:
 
 
 @pytest.fixture()
-def deployer_local_account(web3) -> LocalAccount:
+def deployer_hot_wallet(web3) -> HotWallet:
     """Account that we use for Lagoon deployment"""
     hot_wallet = HotWallet.create_for_testing(web3, eth_amount=1)
-    return hot_wallet.account
+    return hot_wallet
+
+
+@pytest.fixture()
+def deployer_local_account(deployer_hot_wallet) -> LocalAccount:
+    """Account that we use for Lagoon deployment"""
+    return deployer_hot_wallet.account
 
 
 @pytest.fixture()

tradeexecutor/analysis/multi_asset_benchmark.py

@@ -344,7 +344,7 @@ def compare_strategy_backtest_to_multiple_assets(
             index=index
         )
 
-    prices_table = prices_table.applymap(lambda x: f"{x:.2f}" if isinstance(x, (float, np.float64)) else x)
+    prices_table = prices_table.map(lambda x: f"{x:.2f}" if isinstance(x, (float, np.float64)) else x)
     prices_table = prices_table.fillna("-")
 
     table = pd.concat([table, prices_table])

tradeexecutor/analysis/weights.py

@@ -14,14 +14,16 @@
 
 
 def calculate_asset_weights(
-        state: State,
+    state: State,
 ) -> pd.Series:
     """Get timeline of asset weights for a backtest.
 
     - Designed for visualisation / human readable output
 
     - Might not handle complex cases correctly
 
+    - Uses portfolio positions as the input
+
     :return:
         Pandas Series of asset weights
 
@@ -69,11 +71,11 @@ def calculate_asset_weights(
 
 
 def visualise_weights(
-        weights_series: pd.Series,
-        normalised=True,
-        color_palette=colors.qualitative.Light24,
-        template="plotly_dark",
-        include_reserves=True,
+    weights_series: pd.Series,
+    normalised=True,
+    color_palette=colors.qualitative.Light24,
+    template="plotly_dark",
+    include_reserves=True,
 ) -> Figure:
     """Draw a chart of weights.
 

tradeexecutor/backtest/backtest_report_template.ipynb

@@ -333,6 +333,34 @@
     "collapsed": false
    }
   },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "# Asset weights\n",
+    "\n",
+    "Show weights of different assets during the backtest period."
+   ]
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "from tradeexecutor.analysis.weights import calculate_asset_weights, visualise_weights\n",
+    "\n",
+    "weights_series = calculate_asset_weights(state)\n",
+    "\n",
+    "fig = visualise_weights(\n",
+    "    weights_series,\n",
+    "    normalised=False,\n",
+    "    include_reserves=True,\n",
+    "    template=\"plotly_white\"\n",
+    ")\n",
+    "fig.show()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "source": [
@@ -362,6 +390,39 @@
     "collapsed": false
    }
   },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "# Trade notes \n",
+    "\n",
+    "Examine the trade notes of the last few decision cycles in the backtest. "
+   ]
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "messages = state.visualisation.get_messages_tail(3)\n",
+    "\n",
+    "if len(messages) > 0:\n",
+    "    table = pd.Series(\n",
+    "        data=list(messages.values()),\n",
+    "        index=list(messages.keys()),\n",
+    "    )\n",
+    "    \n",
+    "    df = table.to_frame()\n",
+    "    \n",
+    "    display(df.style.set_properties(**{\n",
+    "        'text-align': 'left',\n",
+    "        'white-space': 'pre-wrap',\n",
+    "    }))\n",
+    "else:\n",
+    "    print(\"No trade notes available: decide_trades() did not call add_message()\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "source": [
@@ -380,6 +441,8 @@
    "source": [
     "from tradeexecutor.analysis.trade_analyser import expand_timeline\n",
     "\n",
+    "limit = 100\n",
+    "\n",
     "if universe.has_lending_data():\n",
     "    print(\"TODO: Currently disabled for lending-based strategies. Need to add lending data export.\")\n",
     "else:\n",
@@ -389,7 +452,11 @@
     "            universe.universe.exchanges,\n",
     "            universe.universe.pairs,\n",
     "            timeline)\n",
-    "\n",
+    "    \n",
+    "    if len(expanded_timeline) > limit:\n",
+    "        print(f\"We have {len(expanded_timeline)} entries, displaying only last {limit}\")\n",
+    "        expanded_timeline = expanded_timeline.iloc[-limit:]\n",
+    "    \n",
     "    # Do not truncate the row output\n",
     "    with pd.option_context(\"display.max_row\", None):\n",
     "        display(apply_styles(expanded_timeline))"

tradeexecutor/cli/commands/backtest.py

@@ -162,6 +162,7 @@ def loop():
             execution_context=standalone_backtest_execution_context,
             max_workers=max_workers,
             cache_path=cache_path,
+            verbose=not unit_testing,
         )
         return result
 

tradeexecutor/cli/result.py

@@ -1,6 +1,7 @@
 """Simple command line based backtesting result display."""
 import traceback
 
+import pandas as pd
 from IPython.core.display_functions import display
 
 from tradeexecutor.analysis.trade_analyser import build_trade_analysis
@@ -29,7 +30,8 @@ def display_backtesting_results(
     analysis = build_trade_analysis(state.portfolio)
     try:
         summary = analysis.calculate_summary_statistics(state=state)
-        display(summary.to_dataframe(format_headings=False))
+        with pd.option_context('display.max_rows', None, 'display.max_columns', None):
+            display(summary.to_dataframe(format_headings=False))
     except Exception as e:
         print("Could not calculate summary:", e)
         traceback.print_exc()
@@ -41,7 +43,8 @@ def display_backtesting_results(
             strategy_universe,
             display=True,
         )
-        display(portfolio_comparison)
+        with pd.option_context('display.max_rows', None, 'display.max_columns', None):
+            display(portfolio_comparison)
 
     key_metrics = calculate_key_metrics(
         State(),

tradeexecutor/strategy/alpha_model.py

@@ -16,6 +16,7 @@
 from dataclasses_json import dataclass_json
 
 from tradeexecutor.state.size_risk import SizeRisk
+from tradeexecutor.strategy.execution_context import ExecutionContext
 from tradeexecutor.strategy.size_risk_model import SizeRiskModel
 from tradingstrategy.types import PrimaryKey
 
@@ -1072,6 +1073,7 @@ def generate_rebalance_trades_and_triggers(
         individual_rebalance_min_threshold: USDollarAmount = 0.0,
         use_spot_for_long=True,
         invidiual_rebalance_min_threshold=None,
+        execution_context: ExecutionContext = None,
     ) -> List[TradeExecution]:
         """Generate the trades that will rebalance the portfolio.
 
@@ -1104,6 +1106,9 @@ def generate_rebalance_trades_and_triggers(
 
             If set False, use leveraged long.
 
+        :param execution_context:
+            Needed to tune down print/log/state file clutter when backtesting thousands of trades.
+
         :return:
             List of trades we need to execute to reach the target portfolio.
             The sells are sorted always before buys.
@@ -1275,6 +1280,14 @@ def generate_rebalance_trades_and_triggers(
                         # Increase or decrease the position for the target pair
                         # Open new position if needed.
                         logger.info("Adjusting spot position")
+
+                        # For long backtests, state file is filled with these notes,
+                        # so we only enable for live trading
+                        notes = ""
+                        if execution_context:
+                            if execution_context.mode.is_live_trading():
+                                notes = f"Resizing position, trade based on signal: {signal} as {self.timestamp}"
+
                         position_rebalance_trades += position_manager.adjust_position(
                             synthetic,
                             dollar_diff,
@@ -1284,7 +1297,7 @@ def generate_rebalance_trades_and_triggers(
                             take_profit=signal.take_profit,
                             trailing_stop_loss=signal.trailing_stop_loss,
                             override_stop_loss=self.override_stop_loss,
-                            notes="Rebalance for signal {signal}"
+                            notes=notes,
                         )
                     else:
                         raise NotImplementedError(f"Leveraged long missing w/leverage {signal.leverage}, {signal.get_flip_label()}: {signal}")

tradeexecutor/strategy/pandas_trader/strategy_input.py

@@ -5,7 +5,6 @@
 
 import logging
 from dataclasses import dataclass
-from functools import lru_cache
 from typing import Callable
 
 import cachetools
@@ -24,7 +23,6 @@
 from tradingstrategy.candle import CandleSampleUnavailable
 from tradingstrategy.liquidity import LiquidityDataUnavailable
 from tradingstrategy.pair import HumanReadableTradingPairDescription
-from tradingstrategy.timebucket import TimeBucket
 from tradingstrategy.utils.time import get_prior_timestamp, ZERO_TIMEDELTA
 
 logger = logging.getLogger(__name__)
@@ -468,6 +466,8 @@ def create_indicators(parameters: StrategyParameters, indicators: IndicatorSet,
                     raise IndicatorDataNotFoundWithinDataTolerance(
                         f"Asked indicator {name}. Data delay tolerance is {data_delay_tolerance}, but the delay was longer {distance}.\n"
                         f"Our timestamp {self.timestamp}, fixed timestamp {shifted_ts}, data available at {before_match_timestamp}.\n"
+                        f"First indicator entry {series.index[0]}, last indicator entry {series.index[-1]}.\n"
+                        f"If your indicator data is gappy, make sure you use reindex() or ffill() to fill the gaps.\n"
                     )
 
                 value = before_match

tradeexecutor/visual/equity_curve.py

@@ -363,9 +363,11 @@ def visualise_returns_distribution(
     """
 
     qs = import_quantstats_wrapped()
-    fig = qs.plots.distribution(
-        returns,
-        show=False)
+    with warnings.catch_warnings():  #  DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display
+        warnings.simplefilter(action='ignore', category=FutureWarning)
+        fig = qs.plots.distribution(
+            returns,
+            show=False)
     return fig