diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index b7ca24b..f6ea47c 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -11,21 +11,20 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 + - name: Install uv + uses: astral-sh/setup-uv@v5 with: + enable-cache: true python-version: "3.11" - name: Install dependencies - run: | - python -m pip install --upgrade pip - python -m pip install -e ".[dev]" + run: uv sync --extra dev - name: Run mypy - run: mypy tradedesk + run: uv run mypy tradedesk - name: Run ruff - run: ruff check tradedesk + run: uv run ruff check tradedesk test: name: Test Python ${{ matrix.python-version }} @@ -39,20 +38,19 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 + - name: Install uv + uses: astral-sh/setup-uv@v5 with: + enable-cache: true python-version: ${{ matrix.python-version }} - - name: Install - run: | - python -m pip install --upgrade pip - python -m pip install -e ".[dev]" + - name: Install dependencies + run: uv sync --extra dev - name: Run tests with coverage run: | - pytest \ + uv run pytest \ --cov=tradedesk \ --cov-report=term-missing \ --cov-report=xml \ - --cov-fail-under=80 + --cov-fail-under=85 \ No newline at end of file diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml index 815f9cc..3d1a1b3 100644 --- a/.github/workflows/publish.yml +++ b/.github/workflows/publish.yml @@ -18,16 +18,13 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Set up Python - uses: actions/setup-python@v5 + - name: Install uv + uses: astral-sh/setup-uv@v5 with: python-version: "3.14" - - name: Install build dependencies - run: python -m pip install --upgrade build - - name: Build package - run: python -m build + run: uv build - name: Publish to PyPI uses: pypa/gh-action-pypi-publish@release/v1 diff --git a/AGENTS.md b/AGENTS.md index edece52..8ced8aa 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -1,45 +1,3 @@ -## Project Overview - -**tradedesk** is the shared research and orchestration layer that underpins multiple trading implementations. It provides common abstractions for data handling, backtesting, portfolio orchestration, analytics, and experiment management. - -This codebase is **not broker-specific**. It exists to: - -* Enable fast, repeatable strategy research -* Provide realistic portfolio-level backtesting -* Act as the canonical home for shared logic and metrics - -Downstream projects should depend on *tradedesk*; *tradedesk* should not depend on them. - ---- - -## Primary Responsibilities - -Agents should treat *tradedesk* as responsible for: - -* Backtest orchestration and experiment flow -* Strategy-agnostic portfolio logic -* Trade recording, ledgers, and metrics -* Naming, configuration, and reproducibility conventions -* Research-grade correctness over execution convenience - -If logic is reusable across brokers or execution environments, it likely belongs here. - ---- - -## Current Objectives - -Typical work includes: - -* Closing meaningful unit test coverage gaps -* Hardening portfolio and analytics logic -* Simplifying or clarifying orchestration flows -* Removing legacy or leaked execution concerns -* Ensuring deterministic, explainable backtest results - -Backward compatibility is **not required** unless explicitly stated. - ---- - ## Preferred Way of Working ### Incremental and Focused @@ -57,18 +15,14 @@ Backward compatibility is **not required** unless explicitly stated. ### Pragmatic Testing * Tests should defend correctness, not chase coverage -* Prioritise: - - * Portfolio aggregation logic - * Metrics and statistics - * Edge cases and boundary conditions * Avoid brittle, over-specified tests +* Use `pytest` not `unittest` ### Communication Style * Concise, technical, professional * Minimal narration -* Challenge assumptions where appropriate +* Challenge assumptions - constructive dialog and pushback is expected --- @@ -76,10 +30,7 @@ Backward compatibility is **not required** unless explicitly stated. * Use latest stable Python and dependencies * Follow current documentation and APIs -* No `from __future__ import ...` unless warranted -* Prefer clarity and correctness over abstraction -* Avoid premature generalisation -* Code should meet `ruff check` and `mypy --strict` requirements +* Code should pass `ruff check` and `mypy --strict` requirements * Create commit messages for git following "Conventional Commits" and the current style of the project's git log * Do not add author lines to git commits * Follow the intentions of the domain architecture encoded in `pyproject.toml` @@ -89,37 +40,5 @@ Backward compatibility is **not required** unless explicitly stated. When running code or commands: -* Use the `.venv` directory in the root of the relevant project - ---- - -## Domain Assumptions - -Agents are expected to understand: - -* Backtesting mechanics and common biases -* Portfolio-level statistics and drawdown analysis -* Event-driven strategy evaluation -* The difference between research code and execution code - -If a design choice trades realism for speed or simplicity, it should be explicit. - ---- - -## What to Avoid - -* Broker- or API-specific logic -* Leaking execution assumptions into research layers -* Over-engineering for hypothetical future needs -* Large rewrites without alignment - ---- - -## Success Criteria - -An agent is succeeding if it: - -* Increases confidence in backtest results -* Improves clarity of portfolio and metrics logic -* Makes research workflows faster and safer -* Keeps the codebase cleanly reusable downstream +* Use `uv` instead of `pip` +* Always use the `.venv` directory in the root of the project diff --git a/README.md b/README.md index 4a9c31e..4882510 100644 --- a/README.md +++ b/README.md @@ -1,111 +1,139 @@ -# tradedesk ![CI Build](https://github.com/radiusred/tradedesk/actions/workflows/ci.yml/badge.svg) [![PyPI Version](https://img.shields.io/pypi/v/tradedesk?label=PyPI)](https://pypi.python.org/pypi/tradedesk) -## What tradedesk is +# tradedesk -`tradedesk` is a lightweight Python framework for developing, backtesting, and running systematic trading strategies across multiple data providers and execution environments. +tradedesk is an event-driven trading framework for building, running, +and evaluating systematic trading strategies across both backtesting and live +broker environments. It provides: -* A consistent strategy lifecycle -* Explicit separation between market data, strategy logic, and execution -* Minimal and flexible portfolio management types -* Deterministic [backtesting](./docs/backtesting_guide.md) with identical strategy code -* Live and DEMO execution via provider-specific clients +- Event-based strategy execution +- Unified backtest and live broker runtime model +- Market data aggregation and indicator framework +- Portfolio orchestration and risk management +- Trade recording, metrics, and reporting + +The framework is designed so that strategies react to events --- not +broker implementations --- enabling the same strategy code to run +unchanged in both backtest and live environments. + + +## Core Concepts + +### Event-Driven Architecture + +All major subsystems communicate via events: -It is designed for research, validation, and controlled deployment of trading strategies rather than high-frequency or ultra-low-latency trading. +- Market data events (ticks, candles) +- Strategy events (signals) +- Execution events (orders, fills) +- Portfolio events (position updates) +- Recording events (trade lifecycle) -## What tradedesk is not +As a user, you primarily: -`tradedesk` is intentionally *not*: +- Implement a strategy that reacts to candle updates +- Optionally subscribe to events for custom analytics or logging -* A signal marketplace -* A turnkey trading bot -* A performance-optimised HFT engine -It REQUIRES the user to accept responsibility for strategy design, risk management, and operational controls. +## Basic Strategy Structure -## High-level architecture +A strategy derives from the base strategy class and implements candle +handling logic. -At a high level, `tradedesk` consists of four layers: +Typical flow: -1. **Providers** – Interfaces to external data/execution sources (e.g. IG, historical backtest data) -2. **Clients** – Concrete implementations that fetch data and place orders -3. **Strategies** – User-defined trading logic responding to market events -4. **Runner** – Orchestrates lifecycle, subscriptions, warmup, and shutdown +1. Market data arrives (tick or candle) +2. Aggregation produces candles +3. Strategy receives `on_candle_update` +4. Strategy emits order requests +5. Execution layer processes orders +6. Portfolio updates positions +7. Recording captures trade lifecycle -Market data flows from the provider into the strategy, which emits execution decisions back through the client. -## Core concepts +## Running a Backtest -### Strategy lifecycle +Backtesting uses the same event model as live trading. -A strategy progresses through the following phases: +High-level flow: -1. Construction -2. Subscription registration -3. Warmup (optional but strongly recommended) -4. Live or replayed market data handling -5. Order execution -6. Graceful shutdown +- CSV or historical provider feeds market data +- Backtest runner drives event loop +- Strategy executes normally +- Portfolio and recording operate identically to live mode -### Subscriptions +See `docs/backtesting_guide.md` for detailed usage. -Strategies explicitly declare their required data via subscriptions: -* **MarketSubscription** – Tick-level price updates (bid/offer) -* **ChartSubscription** – Aggregated candle data for a given timeframe +## Live Trading (IG) -Only subscribed data is delivered to the strategy. +The IG execution module provides: -### Warmup +- REST client for order management +- Streaming price integration +- Position synchronization +- Retry and resilience handling -Warmup allows a strategy to request historical data before live execution begins in order to initialise indicator state and internal windows. +Your strategy remains unchanged --- only the execution configuration +differs. -A strategy that does not warm up must be robust to partially initialised indicators and delayed signal readiness. -### Backtest vs live execution +## Portfolio & Risk -The same strategy code can be run against: +The portfolio subsystem: -* A live or DEMO provider -* A deterministic [backtest](./docs/backtesting_guide.md) client that replays historical data +- Tracks positions +- Applies risk policies +- Reconciles fills +- Emits portfolio events -Differences between environments are isolated to the client layer. +Risk controls can reject or modify orders before execution. -## Supported providers -* **IG** – Live and DEMO trading via REST and streaming APIs -* **BacktestClient** – Deterministic replay of historical data +## Recording & Reporting -Historical data acquisition is handled by a companion project: +The recording subsystem: -* `tradedesk-dukascopy` +- Tracks trades and equity curves +- Computes excursions and performance metrics +- Generates structured reports -## Quick start +Users can subscribe to recording events for custom reporting pipelines. -1. Install dependencies -2. Write or select a strategy -3. Choose a client ([backtest](./docs/backtesting_guide.md) or live) -4. Run via the `tradedesk` runner -Detailed tutorials are provided in the documentation guides listed below. +## Typical Project Structure -## Project status and guarantees -* APIs are evolving as the framework matures -* Prior to a 1.0 release, there is NO guarantee of backward compatibility between - minor versions of the framework -* The framework prioritises correctness and clarity over performance + my_strategy/ + strategy.py + run_backtest.py + config.py -## Further reading -* `docs/indicators.md` – Indicator concepts and mathematical foundations -* `docs/strategy_writing_guide.md` – Step-by-step strategy tutorial -* `docs/backtesting_guide.md` – Methodology for rigorous backtesting +## Installation +Install using your preferred environment manager. Ensure Python 3.11+. + + +## Documentation + +See the `docs/` directory for: + +- Backtesting guide +- Strategy guide +- Portfolio guide +- Indicator guide +- Aggregation guide +- Risk management guide +- Metrics guide + + +tradedesk is designed for clarity, determinism, and event-level +transparency. --- ## License @@ -114,3 +142,4 @@ Licensed under the Apache License, Version 2.0. See: [https://www.apache.org/licenses/LICENSE-2.0](https://www.apache.org/licenses/LICENSE-2.0) Copyright 2026 [Radius Red Ltd.](https://github.com/radiusred) + diff --git a/docs/aggregation_guide.md b/docs/aggregation_guide.md index 12bd508..f169631 100644 --- a/docs/aggregation_guide.md +++ b/docs/aggregation_guide.md @@ -52,7 +52,7 @@ Use `choose_base_period()` to automatically select an appropriate base period fo from tradedesk.aggregation import choose_base_period # Default: Uses common broker periods (SECOND, 1MINUTE, 5MINUTE, HOUR) -base = choose_base_period("15MINUTE") # Returns "5MINUTE" +base = choose_base_period("15MINUTE") # Returns "1MINUTE" base = choose_base_period("7MINUTE") # Returns "1MINUTE" base = choose_base_period("HOUR") # Returns "HOUR" diff --git a/docs/backtesting_guide.md b/docs/backtesting_guide.md index c1e5946..52981b2 100644 --- a/docs/backtesting_guide.md +++ b/docs/backtesting_guide.md @@ -1,323 +1,242 @@ -# Backtesting Strategies with tradedesk +# Backtesting Guide ---- - -## Purpose of this guide - -This document describes a rigorous, repeatable methodology for backtesting trading strategies using the `tradedesk` framework. - -It focuses on: -- correctness of methodology, -- limitations of historical simulation, -- disciplined interpretation of results, -- practical workflows that keep strategy code identical between backtest and live/DEMO. - -It does **not** attempt to optimise strategies or suggest profitable configurations. - ---- - -## What a backtest is (and is not) - -A backtest is a controlled simulation of a strategy over historical market data. - -A backtest can: -- validate that strategy logic behaves as intended, -- expose implementation bugs, -- provide comparative metrics between versions of the same strategy. +This guide covers running backtests with tradedesk using candle data loaded from +CSV files or supplied in-memory. -A backtest cannot: -- predict future performance, -- eliminate model risk, -- compensate for poor data quality or unrealistic execution assumptions. +By the end you will have: -Backtests are most useful as a **development instrument**: they tell you whether the implementation is coherent and whether performance is stable under controlled variation. +- A working strategy +- A CSV-driven backtest via `run_portfolio` +- A full recorded backtest via `run_backtest` (with metrics and trade output) ---- - -## Define a testable hypothesis - -Before writing code or running a backtest, state a hypothesis in operational terms: - -- **Premise**: what market behaviour are you exploiting? -- **Entry condition**: what observable data implies the premise holds? -- **Exit condition**: when is the premise no longer true? -- **Risk control**: how does the strategy fail closed? - -Example (structure, not a recommendation): - -- Premise: short bursts of momentum after volatility compression -- Entry: momentum oscillator crosses threshold while volatility is below a percentile -- Exit: time stop or ATR stop -- Risk control: no entry unless stop distance is computable; one position per epic - -This matters because it prevents retrofitting explanations to results. +The same strategy runs live against a broker without modification. --- -## Historical data requirements - -Backtests are only as reliable as their input data. +## 1. Project Structure -Minimum requirements (non-negotiable if you want results to mean anything): -- **Timestamp integrity**: monotonic event ordering per instrument. -- **Timezone clarity**: a single, explicit timezone for all inputs. -- **Granularity match**: if the strategy is tick-driven, candle-only data implies approximation. -- **Gap visibility**: missing periods must be detectable (and ideally logged). - -Recommended: -- Bid/offer (or mid + spread model) explicitly represented. -- Corporate action / contract roll awareness for instruments where it applies (indices/futures-style CFDs). +``` +my_backtest/ + strategy.py + run_backtest.py + candles.csv +``` --- -## Obtaining historical data - -Historical data acquisition is intentionally separated from the core framework. +## 2. Candle CSV Format -The companion project [`tradedesk-dukascopy`](https://github.com/radiusred/tradedesk-dukascopy) is responsible for: -- downloading historical data, -- caching and gap-filling, -- exporting to formats that are convenient for backtests. +``` +timestamp,open,high,low,close,volume +2025-01-01T00:00:00Z,1.2500,1.2510,1.2490,1.2505,1000 +2025-01-01T00:05:00Z,1.2505,1.2520,1.2500,1.2515,800 +``` -This guide assumes you already have historical candles and/or tick/quote series available locally. +Fields `volume` and `tick_count` are optional. +Timestamps may use `-` or `/` as date separators, with or without a trailing `Z`. --- -## Backtest architecture in tradedesk - -Backtesting in `tradedesk` uses a dedicated client (`BacktestClient`) that replays data deterministically through the same strategy callbacks used in live execution. +## 3. Implement a Strategy -Core properties: -- identical strategy code paths (same class, same callbacks), -- deterministic ordering, -- explicit configuration of what is replayed (candles, ticks/quotes, or both). - -The practical implication: if you need special “backtest mode” logic inside a strategy, it should be isolated and justified. - ---- +```python +# strategy.py +import logging +from tradedesk.strategy import BaseStrategy +from tradedesk.marketdata import CandleClosedEvent, ChartSubscription -## Event ordering and determinism +log = logging.getLogger(__name__) -Two ordering rules matter in practice: -1. **No lookahead**: a strategy must not observe information that would not exist at that time (e.g., reading candle close values before the candle has closed). -2. **Stable replay**: given the same input series, results must be identical run-to-run. +class SimpleMomentumStrategy(BaseStrategy): -If you cannot reproduce results exactly with the same inputs, treat the backtest as invalid until you can. + SUBSCRIPTIONS = [ChartSubscription("CS.D.GBPUSD.TODAY.IP", "5MINUTE")] ---- + async def on_candle_close(self, event: CandleClosedEvent) -> None: + candle = event.candle -## Warmup in backtests + if candle.close > candle.open: + log.info("Bullish candle — would buy") + # await self.client.place_market_order(event.instrument, "BUY", size=1.0) + elif candle.close < candle.open: + log.info("Bearish candle — would sell") + # await self.client.place_market_order(event.instrument, "SELL", size=1.0) -Indicators and windowed logic require warmup. Warmup must be handled explicitly: - -- Warmup data is used to initialise state. -- Performance metrics must be computed on the evaluation window **after** warmup. -- Warmup length should exceed the largest lookback *plus* any additional state windows (e.g., regime windows, volume filters). + # Store candle in chart history (default behaviour) + await super().on_candle_close(event) +``` -Typical approach: -- Load a longer historical period than you intend to evaluate. -- Use the early portion as warmup. -- Start recording metrics only after warmup completes. +Key points: -If your strategy can trade before warmup completes, that is an implementation smell. Prefer fail-closed behaviour for entries. +- Declare subscriptions via `SUBSCRIPTIONS` (or pass them to `__init__`). +- `on_candle_close` fires for each completed candle. +- Call `super().on_candle_close(event)` to keep chart history up to date. +- `self.client.place_market_order(instrument, "BUY" | "SELL", size)` places orders. --- -## Candle-only backtesting - -Candle-only datasets are common and useful, but impose constraints: +## 4. Simple Backtest with `run_portfolio` -- Intrabar path is unknown. -- Stops cannot be simulated exactly without assumptions. -- Tick-driven indicators (e.g., MACD updated per tick) must be approximated. +Use `run_portfolio` for a quick, no-frills backtest that exercises the same +code path as live trading. -Common approximation techniques: -- **Boundary synthetic ticks**: inject a synthetic tick at candle open (or close) to drive tick-based logic. -- **Stop checks via extremes**: approximate stop execution using candle high/low. +```python +# run_backtest.py +from tradedesk import SimplePortfolio, run_portfolio +from tradedesk.execution.backtest.client import BacktestClient -Be explicit: candle-only results are not “wrong”, but they are conditional on the approximation model. You must interpret them accordingly. +from strategy import SimpleMomentumStrategy ---- -## Execution realism and modelling assumptions +def client_factory(): + return BacktestClient.from_csv( + "candles.csv", + instrument="CS.D.GBPUSD.TODAY.IP", + period="5MINUTE", + ) -Backtests simplify execution. You should choose assumptions deliberately and document them. -### Spread +run_portfolio( + portfolio_factory=lambda c: SimplePortfolio(c, SimpleMomentumStrategy(c)), + client_factory=client_factory, + setup_logging=True, +) -At minimum: -- use bid/offer series if available, or -- apply a fixed spread model to a mid price. +# Inspect results +client = client_factory() # create a fresh client to inspect (or capture it above) +``` -### Slippage +To capture the client for inspection, use a closure: -If you do not model slippage, you are assuming: -- immediate fills at the observed price, -- no adverse selection. +```python +created = {} -That assumption is optimistic for market orders. If you want conservative tests, add slippage (even a small constant) or widen the spread. +def client_factory(): + c = BacktestClient.from_csv("candles.csv", instrument="CS.D.GBPUSD.TODAY.IP", period="5MINUTE") + created["client"] = c + return c -### Stops +run_portfolio( + portfolio_factory=lambda c: SimplePortfolio(c, SimpleMomentumStrategy(c)), + client_factory=client_factory, +) -Stops are not guaranteed fills at the stop level in live markets, particularly during gaps. Candle-only stop modelling is especially optimistic/pessimistic depending on how you fill. +client = created["client"] +print(f"Trades: {len(client.trades)}") +print(f"Positions: {client.positions}") +print(f"Realised PnL: {client.realised_pnl}") +``` --- -## A practical backtest workflow - -This section shows a practical workflow with code. The examples assume: -- you already have candle history in memory or loaded from disk, -- you use `BacktestClient` to replay data, -- you run the strategy through the standard runner. - -### Step 1: Assemble history inputs +## 5. In-Memory Backtest -`BacktestClient.from_history()` accepts a dictionary keyed by `(epic, timeframe)` with a list of candles. - -Example (in-memory): +Supply candles directly without a CSV: ```python -from tradedesk import Candle -from tradedesk.providers.backtest.client import BacktestClient - -epic = "IX.D.FTSE.DAILY.IP" -timeframe = "5MINUTE" +from tradedesk.types import Candle -candles = [ - Candle(timestamp="2025-01-02T08:00:00Z", open=7500, high=7502, low=7498, close=7501, volume=123, tick_count=0), - # ... -] +history = { + ("CS.D.GBPUSD.TODAY.IP", "5MINUTE"): [ + Candle(timestamp="2025-01-01T00:00:00Z", open=1.25, high=1.26, low=1.24, close=1.255), + Candle(timestamp="2025-01-01T00:05:00Z", open=1.255, high=1.27, low=1.25, close=1.265), + ] +} -history = {(epic, timeframe): candles} -client = BacktestClient.from_history(history) -``` - -If you are loading from disk, do that in your own code (or via `tradedesk-dukascopy`) and normalise into the same structure. - -### Step 2: Configure the strategy spec - -Backtests should use the same strategy class as live. Configure via `strategy_specs`: - -```python -from tradedesk import run_strategies -from ig_trader.macd_trails_mfi_strategy import MacdTrailsMfiStrategy -from ig_trader.config import StrategyConfig -from ig_trader.epic_state import EpicState +created = {} def client_factory(): - return client - -strategy_specs = [ - ( - MacdTrailsMfiStrategy, - { - "epics": [epic], - "timeframe": timeframe, - "size": 1.0, - # Backtest knobs if required (example: candle-only approximations) - "candle_only_backtest": True, - "candle_only_spread": 1.0, - "state_factory": lambda e: EpicState( - epic=e, - config=StrategyConfig(max_hold_bars=6, atr_stop_mult=2.0), - ), - }, - ) -] -``` + c = BacktestClient.from_history(history) + created["client"] = c + return c -### Step 3: Run deterministically - -```python -run_strategies( - strategy_specs=strategy_specs, +run_portfolio( + portfolio_factory=lambda c: SimplePortfolio(c, SimpleMomentumStrategy(c)), client_factory=client_factory, - log_level="INFO", ) ``` -Because `BacktestClient` is deterministic, repeated runs with identical inputs should produce identical trades and metrics. - ---- - -## Measuring outcomes - -Backtests require a consistent metrics interface. The goal is not “one metric”, but a coherent set: - -- number of trades / round trips, -- win rate and payoff asymmetry, -- profit factor and expectancy, -- maximum drawdown and final equity, -- average hold time (if meaningful for your strategy). - -### Record metrics before you run - -Define what you will compare **before** executing the run: -- baseline version vs change, -- one parameter changed at a time, -- fixed evaluation window. - -If you decide what to measure after you see results, you are already drifting toward overfitting. - --- -## Sensitivity analysis - -A strategy that only works for one instrument, one timeframe, and one specific parameter set is likely brittle. +## 6. Full Backtest with Metrics (`run_backtest`) -Minimum sensitivity checks: -- adjacent timeframes (e.g., 5m vs 10m), -- related instruments (e.g., FTSE vs US500), -- small parameter perturbations (±10–20%). +`run_backtest` wraps `run_portfolio` and adds: -If performance collapses under small perturbations, treat the “edge” as unproven. +- Trade ledger written to CSV +- Equity curve tracking +- Excursion (MAE/MFE) computation +- A `Metrics` object returned with summary statistics ---- +```python +import asyncio +from pathlib import Path -## Common backtesting pitfalls +from tradedesk import SimplePortfolio +from tradedesk.execution.backtest.runner import BacktestSpec, run_backtest -### Lookahead bias +from strategy import SimpleMomentumStrategy -Using candle close values to decide trades “inside” the candle. -Mitigation: -- ensure entry signals only use information available at that decision time, -- enforce strict event ordering (ticks first, candle close after). +async def main(): + spec = BacktestSpec( + instrument="CS.D.GBPUSD.TODAY.IP", + period="5MINUTE", + candle_csv=Path("candles.csv"), + half_spread_adjustment=0.5, # add half the spread to BID-sourced candles + ) -### Data snooping / overfitting + metrics = await run_backtest( + spec=spec, + out_dir=Path("output"), + portfolio_factory=lambda c: SimplePortfolio(c, SimpleMomentumStrategy(c)), + ) -Repeatedly tuning parameters until performance looks good. + print(f"Trades: {metrics.trades}") + print(f"Round trips: {metrics.round_trips}") + print(f"Win rate: {metrics.win_rate:.1%}") + print(f"Avg hold (min): {metrics.avg_hold_minutes:.1f}") + print(f"Final equity: {metrics.final_equity:.2f}") + print(f"Max drawdown: {metrics.max_drawdown:.2f}") + print(f"Profit factor: {metrics.profit_factor:.2f}") -Mitigation: -- out-of-sample evaluation windows, -- predefined metrics and acceptance criteria, -- sensitivity analysis. -### Silent data gaps +if __name__ == "__main__": + asyncio.run(main()) +``` -Missing periods that are interpreted as “no movement”. +Output artefacts are written to `out_dir/`: -Mitigation: -- gap detection in the data pipeline, -- explicit handling of missing ranges. +| File | Contents | +|------|----------| +| `trades.csv` | One row per fill: timestamp, direction, price, size | +| `equity.csv` | Equity curve snapshots | --- -## From backtest to DEMO +## 7. What Happens Internally -Treat DEMO as a separate validation stage: -- event ordering differences (streaming vs replay), -- broker execution constraints (minimum sizes, rejections), -- connectivity/transient failure handling. +When `run_portfolio` (or `portfolio.run()`) executes: -A strategy that backtests well but fails basic invariants in DEMO is not ready for live deployment, regardless of backtest performance. +1. `SessionStartedEvent` fires — strategy `warmup()` is called +2. `SessionReadyEvent` fires — post-warmup checks run +3. BacktestStreamer replays candles in sequence +4. Each completed candle calls `portfolio._handle_event(CandleClosedEvent)`: + - Publishes the event to the dispatcher (recording subscribers react here) + - Calls `portfolio.on_candle_close(event)` → `strategy.on_candle_close(event)` +5. `BacktestClient.place_market_order` simulates fills at the candle's close price +6. `SessionEndedEvent` fires on completion --- -## License +## 8. Switching to Live Trading -Licensed under the Apache License, Version 2.0. -See: https://www.apache.org/licenses/LICENSE-2.0 +Replace the `client_factory` — the strategy and portfolio are unchanged: -Copyright 2026 [Radius Red Ltd.](https://github.com/radiusred) +```python +from tradedesk.execution.ig import IGClient + +run_portfolio( + portfolio_factory=lambda c: SimplePortfolio(c, SimpleMomentumStrategy(c)), + client_factory=IGClient, +) +``` diff --git a/docs/examples/log_price_strategy.py b/docs/examples/log_price_strategy.py index dc7e71a..e316702 100644 --- a/docs/examples/log_price_strategy.py +++ b/docs/examples/log_price_strategy.py @@ -6,21 +6,19 @@ - How to subclass BaseStrategy - How to declare which EPICs to monitor - How to process price updates -- How to run the strategy +- How to run the strategy live or against a backtest -Usage: +Usage (live): IG_API_KEY=... IG_USERNAME=... IG_PASSWORD=... IG_ENVIRONMENT=DEMO \ python ./log_price_strategy.py -Requirements: - - .env file with IG credentials in the project root - - tradedesk library installed +Usage (backtest): + python ./log_price_strategy.py --backtest """ -import json import logging -from tradedesk import run_strategies +from tradedesk import SimplePortfolio, run_portfolio from tradedesk.execution.ig.client import IGClient from tradedesk.marketdata.instrument import MarketData from tradedesk.marketdata.subscriptions import MarketSubscription @@ -32,47 +30,35 @@ class LogPriceStrategy(BaseStrategy): """ Simple strategy that logs every price change. - + This is primarily used for: - Testing the infrastructure - - Monitoring market activity + - Monitoring market activity - Debugging connectivity issues - Learning how to build strategies - + Production strategies would implement actual trading logic in on_price_update() (signal generation, position management, risk management, etc.) """ - + # Declare which EPICs this strategy wants to monitor SUBSCRIPTIONS = [MarketSubscription("CS.D.GBPUSD.TODAY.IP")] - def __init__(self, client: IGClient): - """ - Initialize the logging strategy. - - Args: - client: Authenticated IG client - """ + def __init__(self, client): super().__init__(client) self._last_mid: float | None = None - + async def on_price_update(self, market_data: MarketData) -> None: - """ - Log the price update to stdout as structured JSON. - - Only logs when the mid price changes to reduce noise. - """ + """Log the price update. Only logs when the mid price changes.""" mid = (market_data.bid + market_data.offer) / 2 - - # Only log when mid price changes + if self._last_mid is None or mid != self._last_mid: self._last_mid = mid - - # Log as structured JSON for easy parsing - log.warning("price_update %s", json.dumps(market_data)) + log.info("price_update %s", market_data) + if __name__ == "__main__": - run_strategies( - strategy_specs=[LogPriceStrategy], + run_portfolio( + portfolio_factory=lambda c: SimplePortfolio(c, LogPriceStrategy(c)), client_factory=IGClient, ) diff --git a/docs/examples/momentum_strategy.py b/docs/examples/momentum_strategy.py index c01835b..25d42f1 100644 --- a/docs/examples/momentum_strategy.py +++ b/docs/examples/momentum_strategy.py @@ -1,20 +1,26 @@ -# examples/momentum.py +# examples/momentum_strategy.py """ Simple momentum strategy example. -Usage: +Tracks short-term price momentum across two FX instruments and logs signals. +Order execution is commented out — uncomment to place real trades. + +Usage (live): IG_API_KEY=... IG_USERNAME=... IG_PASSWORD=... IG_ENVIRONMENT=DEMO \ python ./momentum_strategy.py - + +Usage (backtest from CSV): + python ./momentum_strategy.py --backtest """ + import logging from collections import deque +from pathlib import Path -from tradedesk import BaseStrategy, run_strategies -from tradedesk.execution import Client +from tradedesk import SimplePortfolio, run_portfolio from tradedesk.execution.ig import IGClient -from tradedesk.marketdata.instrument import MarketData -from tradedesk.marketdata.subscriptions import MarketSubscription +from tradedesk.marketdata import MarketData, MarketSubscription +from tradedesk.strategy import BaseStrategy log = logging.getLogger(__name__) @@ -22,83 +28,70 @@ class MomentumStrategy(BaseStrategy): """ Tracks price momentum and generates signals. - - This is a simplified example - real strategies would include: + + This is a simplified example — real strategies would include: - Proper position sizing - Risk management - Stop losses - Order execution - """ - - # Declare which instruments to monitor + SUBSCRIPTIONS = [ MarketSubscription("CS.D.GBPUSD.TODAY.IP"), MarketSubscription("CS.D.EURUSD.TODAY.IP"), ] - def __init__(self, client: Client, config: dict = None, lookback: int = 10): - """ - Initialize momentum strategy. - - Args: - client: Authenticated IG client or Backtest client - config: Optional configuration dict - lookback: Number of price updates to track for momentum - """ - super().__init__(client, config) + def __init__(self, client, lookback: int = 10): + super().__init__(client) self.lookback = lookback - - # Track price history per instrument instruments = [sub.instrument for sub in self.SUBSCRIPTIONS] self.price_history: dict[str, deque] = { instrument: deque(maxlen=lookback) for instrument in instruments } - - async def on_price_update(self, market_data: MarketData) -> None: - """Process price update and check for signals.""" + async def on_price_update(self, market_data: MarketData) -> None: + """Process price update and check for momentum signals.""" mid = (market_data.bid + market_data.offer) / 2 instrument = market_data.instrument - # Store price - if instrument in self.price_history: - self.price_history[instrument].append(mid) - else: - # Instrument not in our list, ignore + if instrument not in self.price_history: return - # Need full history for momentum calculation + self.price_history[instrument].append(mid) + if len(self.price_history[instrument]) < self.lookback: return - # Calculate simple momentum prices = list(self.price_history[instrument]) momentum = (prices[-1] - prices[0]) / prices[0] - log.debug( - "Momentum for %s: %.5f (from %.5f to %.5f)", - instrument, momentum, prices[0], prices[-1] - ) - - # Generate signals (in production, would place actual orders) - if momentum > 0.001: # 10 pips up - log.info("🟢 %s momentum UP: %.5f", instrument, momentum) + log.debug("Momentum %s: %.5f", instrument, momentum) + + if momentum > 0.001: + log.info("UP signal: %s momentum=%.5f", instrument, momentum) # await self.client.place_market_order(instrument, "BUY", size=1.0) - elif momentum < -0.001: # 10 pips down - log.info("🔴 %s momentum DOWN: %.5f", instrument, momentum) + elif momentum < -0.001: + log.info("DOWN signal: %s momentum=%.5f", instrument, momentum) # await self.client.place_market_order(instrument, "SELL", size=1.0) + if __name__ == "__main__": - # choose which client to run the strategy via.. - - cf = IGClient - # cf = lambda: BacktestClient.from_market_csvs({ - # "CS.D.GBPUSD.TODAY.IP": "gbpusd_ticks.csv", - # "CS.D.EURUSD.TODAY.IP": "eurusd_ticks.csv", - # }) - - run_strategies( - strategy_specs=[MomentumStrategy], - client_factory=cf, + import sys + + if "--backtest" in sys.argv: + from tradedesk.execution.backtest.client import BacktestClient + + def client_factory(): + return BacktestClient.from_market_csvs( + { + "CS.D.GBPUSD.TODAY.IP": Path("gbpusd_ticks.csv"), + "CS.D.EURUSD.TODAY.IP": Path("eurusd_ticks.csv"), + } + ) + else: + client_factory = IGClient + + run_portfolio( + portfolio_factory=lambda c: SimplePortfolio(c, MomentumStrategy(c)), + client_factory=client_factory, log_level="DEBUG", ) diff --git a/pyproject.toml b/pyproject.toml index 55597bc..7c55fdf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -27,6 +27,7 @@ dependencies = [ "lightstreamer-client-lib>=2.0", "python-dotenv>=1.0", "numpy>=2.4.0", + "jinja2>=3.1.0", ] [project.optional-dependencies] diff --git a/tests/execution/backtest/test_backtest_csv.py b/tests/execution/backtest/test_backtest_csv.py index 39377a7..62fe3d2 100644 --- a/tests/execution/backtest/test_backtest_csv.py +++ b/tests/execution/backtest/test_backtest_csv.py @@ -3,7 +3,7 @@ import pytest -from tradedesk import run_strategies +from tradedesk import SimplePortfolio, run_portfolio from tradedesk.execution.backtest.client import BacktestClient from tradedesk.execution.backtest.streamer import _parse_ts from tradedesk.marketdata.events import CandleClosedEvent @@ -75,8 +75,8 @@ def factory(): return c with patch("sys.exit") as _: - run_strategies( - strategy_specs=[TradeOnFirstLast], + run_portfolio( + portfolio_factory=lambda c: SimplePortfolio(c, TradeOnFirstLast(c)), client_factory=factory, setup_logging=False, ) @@ -160,8 +160,10 @@ def factory(): return c with patch("sys.exit") as _: - run_strategies( - strategy_specs=[MomentumLike], client_factory=factory, setup_logging=False + run_portfolio( + portfolio_factory=lambda c: SimplePortfolio(c, MomentumLike(c)), + client_factory=factory, + setup_logging=False, ) # Verify at least one UP for GBP and one DOWN for EUR occurred diff --git a/tests/execution/backtest/test_backtest_provider.py b/tests/execution/backtest/test_backtest_provider.py index 12d4446..19cb048 100644 --- a/tests/execution/backtest/test_backtest_provider.py +++ b/tests/execution/backtest/test_backtest_provider.py @@ -2,7 +2,7 @@ import pytest -from tradedesk import Direction, run_strategies +from tradedesk import Direction, SimplePortfolio, run_portfolio from tradedesk.execution.backtest.client import BacktestClient from tradedesk.marketdata.events import CandleClosedEvent from tradedesk.marketdata.instrument import MarketData @@ -78,8 +78,8 @@ def factory(): # Avoid sys.exit() if something goes wrong; we want a clean test failure instead. with patch("sys.exit") as _: - run_strategies( - strategy_specs=[TradeOnFirstLast], + run_portfolio( + portfolio_factory=lambda c: SimplePortfolio(c, TradeOnFirstLast(c)), client_factory=factory, setup_logging=False, ) diff --git a/tests/execution/backtest/test_backtest_runner.py b/tests/execution/backtest/test_backtest_runner.py index 7b66c07..7218550 100644 --- a/tests/execution/backtest/test_backtest_runner.py +++ b/tests/execution/backtest/test_backtest_runner.py @@ -24,7 +24,6 @@ def mock_register_subscriber(): @pytest.fixture def mock_compute_metrics(): with patch("tradedesk.execution.backtest.runner.compute_metrics") as mock: - # Return a dummy metrics object mock.return_value = MagicMock( trades=10, round_trips=5, @@ -40,25 +39,14 @@ def mock_compute_metrics(): yield mock -@pytest.fixture -def mock_dispatcher(): - with patch("tradedesk.execution.backtest.runner.get_dispatcher") as mock: - dispatcher = MagicMock() - dispatcher.publish = AsyncMock() - mock.return_value = dispatcher - yield mock - - @pytest.mark.asyncio async def test_run_backtest_spread_adjustment( - mock_client_cls, mock_register_subscriber, mock_compute_metrics, mock_dispatcher, tmp_path + mock_client_cls, mock_register_subscriber, mock_compute_metrics, tmp_path ): """Test that half_spread_adjustment modifies candle OHLC.""" - # Setup mock client instance client_instance = mock_client_cls.from_csv.return_value client_instance.start = AsyncMock() - # Setup a candle series candle = MagicMock(spec=Candle) candle.open = 100.0 candle.high = 105.0 @@ -83,21 +71,17 @@ async def test_run_backtest_spread_adjustment( half_spread_adjustment=0.5, ) - # Dummy strategy - strat = MagicMock() - strat._handle_event = AsyncMock() + mock_portfolio = MagicMock() + mock_portfolio.run = AsyncMock() - # Mock recorders to avoid instantiation issues with patch("tradedesk.execution.backtest.runner.EquityRecorder"), \ patch("tradedesk.execution.backtest.runner.ProgressLogger"), \ patch("tradedesk.execution.backtest.runner.build_candle_index"), \ patch("tradedesk.execution.backtest.runner.ExcursionComputer"), \ - patch("tradedesk.execution.backtest.runner.TradeLedger"), \ - patch("tradedesk.execution.order_handler.OrderExecutionHandler"): + patch("tradedesk.execution.backtest.runner.TradeLedger"): - await run_backtest(spec=spec, out_dir=tmp_path, strategy_factory=lambda c: strat) + await run_backtest(spec=spec, out_dir=tmp_path, portfolio_factory=lambda c: mock_portfolio) - # Verify adjustment assert candle.open == 100.5 assert candle.high == 105.5 assert candle.low == 95.5 @@ -106,7 +90,7 @@ async def test_run_backtest_spread_adjustment( @pytest.mark.asyncio async def test_run_backtest_event_driven_recording( - mock_client_cls, mock_register_subscriber, mock_compute_metrics, mock_dispatcher, tmp_path + mock_client_cls, mock_register_subscriber, mock_compute_metrics, tmp_path ): """Test that event-driven recording is set up correctly.""" client_instance = mock_client_cls.from_csv.return_value @@ -120,30 +104,27 @@ async def test_run_backtest_event_driven_recording( instrument="TEST", period="1MIN", candle_csv=Path("dummy.csv") ) - # Mock all recorder classes and dependencies + mock_portfolio = MagicMock() + mock_portfolio.run = AsyncMock() + with patch("tradedesk.execution.backtest.runner.EquityRecorder") as mock_equity_recorder, \ patch("tradedesk.execution.backtest.runner.ProgressLogger"), \ patch("tradedesk.execution.backtest.runner.build_candle_index"), \ patch("tradedesk.execution.backtest.runner.ExcursionComputer") as mock_excursion, \ - patch("tradedesk.execution.backtest.runner.TradeLedger"), \ - patch("tradedesk.execution.order_handler.OrderExecutionHandler"): + patch("tradedesk.execution.backtest.runner.TradeLedger"): await run_backtest( - spec=spec, out_dir=tmp_path, strategy_factory=lambda c: MagicMock() + spec=spec, out_dir=tmp_path, portfolio_factory=lambda c: mock_portfolio ) - # Verify recorders were instantiated mock_equity_recorder.assert_called_once() mock_excursion.assert_called_once() - - # Verify session events were published - dispatcher_instance = mock_dispatcher.return_value - assert dispatcher_instance.publish.call_count >= 2 # SessionStarted and SessionEnded + mock_portfolio.run.assert_awaited_once() @pytest.mark.asyncio async def test_run_backtest_metrics_output( - mock_client_cls, mock_register_subscriber, mock_compute_metrics, mock_dispatcher, tmp_path + mock_client_cls, mock_register_subscriber, mock_compute_metrics, tmp_path ): """Test that metrics are computed and returned as Metrics object.""" client_instance = mock_client_cls.from_csv.return_value @@ -155,19 +136,19 @@ async def test_run_backtest_metrics_output( spec = BacktestSpec(instrument="TEST", period="1MIN", candle_csv=Path("dummy.csv")) - # Mock all dependencies + mock_portfolio = MagicMock() + mock_portfolio.run = AsyncMock() + with patch("tradedesk.execution.backtest.runner.EquityRecorder"), \ patch("tradedesk.execution.backtest.runner.ProgressLogger"), \ patch("tradedesk.execution.backtest.runner.build_candle_index"), \ patch("tradedesk.execution.backtest.runner.ExcursionComputer"), \ - patch("tradedesk.execution.backtest.runner.TradeLedger"), \ - patch("tradedesk.execution.order_handler.OrderExecutionHandler"): + patch("tradedesk.execution.backtest.runner.TradeLedger"): result = await run_backtest( - spec=spec, out_dir=tmp_path, strategy_factory=lambda c: MagicMock() + spec=spec, out_dir=tmp_path, portfolio_factory=lambda c: mock_portfolio ) - # Verify result is a Metrics object with expected attributes assert result.trades == 10 assert result.round_trips == 5 assert result.final_equity == 10500.0 diff --git a/tests/execution/test_client.py b/tests/execution/test_client.py index 9e2e466..b4d34e9 100644 --- a/tests/execution/test_client.py +++ b/tests/execution/test_client.py @@ -241,8 +241,12 @@ async def test_quantise_size_with_decimal_step(self, mock_aiohttp_session): assert await client.quantise_size("IX.D.DOW.DAILY.IP", 0.055) == 0.05 @pytest.mark.asyncio - async def test_quantise_size_no_step_returns_original(self, mock_aiohttp_session): - """Test that quantise_size returns original size when no minDealSize is defined.""" + async def test_quantise_size_no_step_rounds_to_2dp(self, mock_aiohttp_session): + """When minDealSize is absent, quantise_size rounds to 2 dp as a safe fallback. + + Previously this returned the raw float unchanged, but that caused IG to reject + orders with HTTP 400 "validation.number.too-many-decimal-places.request.size". + """ with patch("aiohttp.ClientSession", return_value=mock_aiohttp_session): client = IGClient() @@ -250,7 +254,7 @@ async def test_quantise_size_no_step_returns_original(self, mock_aiohttp_session client._instrument_metadata["TEST.EPIC"] = {"dealingRules": {}} size = 1.759110721932789 - assert await client.quantise_size("TEST.EPIC", size) == size + assert await client.quantise_size("TEST.EPIC", size) == round(size, 2) @pytest.mark.asyncio async def test_quantise_size_fetches_metadata_if_not_cached( diff --git a/tests/execution/test_ig_client_retry_logic.py b/tests/execution/test_ig_client_retry_logic.py index 8338f58..45220e0 100644 --- a/tests/execution/test_ig_client_retry_logic.py +++ b/tests/execution/test_ig_client_retry_logic.py @@ -1,4 +1,4 @@ -from unittest.mock import AsyncMock +from unittest.mock import AsyncMock, MagicMock import pytest @@ -13,6 +13,20 @@ def __init__(self, status: int, body): async def json(self): return self._body + async def __aenter__(self): + return self + + async def __aexit__(self, *args): + pass + + +def _make_session(resp: FakeResp) -> MagicMock: + """Return a minimal mock ClientSession whose request() is a CM yielding resp.""" + session = MagicMock() + session.headers = {} + session.request = MagicMock(return_value=resp) + return session + @pytest.mark.asyncio async def test_handle_retry_logic_raises_on_rate_limit(): @@ -57,3 +71,99 @@ async def test_confirm_deal_retries_404_deal_not_found_then_succeeds(): res = await c.confirm_deal("ABC", timeout_s=1.0, poll_s=0.0) assert res["dealStatus"] == "ACCEPTED" assert c._request.await_count == 2 + + +# --------------------------------------------------------------------------- +# _request: null / non-dict JSON body +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_request_returns_empty_dict_when_json_body_is_null(): + """_request must return {} when resp.json() is None (e.g. IG returns null body). + + Before the fix _request returned None, which propagated into confirm_deal + and caused: AttributeError: 'NoneType' object has no attribute 'get' + """ + c = IGClient() + c._session = _make_session(FakeResp(status=200, body=None)) + + result = await c._request("GET", "/confirms/FAKE") + + assert result == {} + assert isinstance(result, dict) + + +@pytest.mark.asyncio +async def test_request_returns_empty_dict_when_json_body_is_non_dict(): + """_request must return {} for any non-dict JSON (list, scalar, etc.).""" + c = IGClient() + c._session = _make_session(FakeResp(status=200, body=["unexpected", "list"])) + + result = await c._request("GET", "/some/path") + + assert result == {} + assert isinstance(result, dict) + + +@pytest.mark.asyncio +async def test_confirm_deal_null_body_raises_timeout_not_attribute_error(): + """confirm_deal with a null confirm response must raise TimeoutError, not AttributeError. + + Before the fix: _request returned None → payload.get() → AttributeError. + After the fix: _request returns {} → dealStatus never set → TimeoutError. + """ + c = IGClient() + # Simulate the fixed _request always returning {} (null body scenario) + c._request = AsyncMock(return_value={}) + + with pytest.raises(TimeoutError): + await c.confirm_deal("REF", timeout_s=0.01, poll_s=0.0) + + +@pytest.mark.asyncio +async def test_quantise_size_null_dealing_rules(): + """quantise_size falls back to 2 dp when dealingRules is null. + + IG DEMO can return {"dealingRules": null, ...}. Rather than passing a raw + float with 15 decimal places to the broker (which returns HTTP 400 + "validation.number.too-many-decimal-places.request.size"), we round to 2 dp. + """ + c = IGClient() + # Snapshot with explicit null dealingRules (as IG DEMO sometimes returns) + c.get_instrument_metadata = AsyncMock( + return_value={"dealingRules": None, "instrument": {}} + ) + + result = await c.quantise_size("CS.D.GBPUSD.TODAY.IP", 1.0) + assert result == 1.0 + + +@pytest.mark.asyncio +async def test_quantise_size_null_min_deal_size(): + """quantise_size falls back to 2 dp when minDealSize is present but null.""" + c = IGClient() + c.get_instrument_metadata = AsyncMock( + return_value={"dealingRules": {"minDealSize": None}} + ) + + result = await c.quantise_size("CS.D.GBPUSD.TODAY.IP", 0.5) + assert result == 0.5 + + +@pytest.mark.asyncio +async def test_quantise_size_null_dealing_rules_truncates_long_float(): + """When dealingRules is null, a raw float with many decimal places is rounded to 2 dp. + + Regression test: commit 30bc110 changed the null-check from dict.get(key, {}) to + `or {}`, which prevented an AttributeError but silently returned the unquantised + float (e.g. 9.544888884913714), causing IG to reject it with HTTP 400 + "validation.number.too-many-decimal-places.request.size". + """ + c = IGClient() + c.get_instrument_metadata = AsyncMock( + return_value={"dealingRules": None, "instrument": {}} + ) + + result = await c.quantise_size("CS.D.USDJPY.TODAY.IP", 9.544888884913714) + assert result == 9.54 diff --git a/tests/execution/test_ig_config.py b/tests/execution/test_ig_config.py index cd7bcce..58dfc62 100644 --- a/tests/execution/test_ig_config.py +++ b/tests/execution/test_ig_config.py @@ -1,4 +1,4 @@ -# tests/test_config.py +# tests/execution/test_ig_config.py """ Tests for the config module. """ @@ -16,7 +16,6 @@ class TestSettings: def test_default_values(self): """Test that Settings has correct default values.""" - # Temporarily clear environment variables with patch.dict(os.environ, {}, clear=True): test_settings = Settings() @@ -42,43 +41,51 @@ def test_environment_variable_loading(self): assert test_settings.ig_password == "test-pass" assert test_settings.ig_environment == "LIVE" - def test_validation_success(self): - """Test successful validation with all required values.""" - test_settings = Settings() - test_settings.ig_api_key = "test-key" - test_settings.ig_username = "test-user" - test_settings.ig_password = "test-pass" - test_settings.ig_environment = "DEMO" - - # Should not raise an exception - test_settings.validate() - - def test_validation_missing_values(self): - """Test validation raises error for missing values.""" - test_settings = Settings() - test_settings.ig_api_key = "" - test_settings.ig_username = "test-user" - test_settings.ig_password = "" - - with pytest.raises(ValueError) as exc_info: + def test_validation_success_via_env(self): + """Test successful validation when environment variables are set.""" + env_vars = { + "IG_API_KEY": "test-key", + "IG_USERNAME": "test-user", + "IG_PASSWORD": "test-pass", + "IG_ENVIRONMENT": "DEMO", + } + + with patch.dict(os.environ, env_vars, clear=True): + test_settings = Settings() + # Should not raise an exception test_settings.validate() - assert "IG_API_KEY" in str(exc_info.value) - assert "IG_PASSWORD" in str(exc_info.value) + def test_validation_missing_values_via_env(self): + """Test validation raises error for missing values (using env).""" + env_vars = { + "IG_USERNAME": "test-user", + # IG_API_KEY and IG_PASSWORD intentionally omitted + } + + with patch.dict(os.environ, env_vars, clear=True): + test_settings = Settings() + with pytest.raises(ValueError) as exc_info: + test_settings.validate() - def test_validation_invalid_environment(self): - """Test validation raises error for invalid environment.""" - test_settings = Settings() - test_settings.ig_api_key = "test-key" - test_settings.ig_username = "test-user" - test_settings.ig_password = "test-pass" - test_settings.ig_environment = "INVALID" # Invalid value + assert "IG_API_KEY" in str(exc_info.value) + assert "IG_PASSWORD" in str(exc_info.value) - with pytest.raises(ValueError) as exc_info: - test_settings.validate() + def test_validation_invalid_environment_via_env(self): + """Test validation raises error for invalid environment (using env).""" + env_vars = { + "IG_API_KEY": "test-key", + "IG_USERNAME": "test-user", + "IG_PASSWORD": "test-pass", + "IG_ENVIRONMENT": "INVALID", + } + + with patch.dict(os.environ, env_vars, clear=True): + test_settings = Settings() + with pytest.raises(ValueError) as exc_info: + test_settings.validate() - assert "IG_ENVIRONMENT" in str(exc_info.value) - assert "must be 'DEMO' or 'LIVE'" in str(exc_info.value) + assert "IG_ENVIRONMENT" in str(exc_info.value) + assert "must be 'DEMO' or 'LIVE'" in str(exc_info.value) def test_global_settings_instance(self): """Test that the global settings instance is created.""" diff --git a/tests/execution/test_order_handler.py b/tests/execution/test_order_handler.py index f6cb24f..8325bca 100644 --- a/tests/execution/test_order_handler.py +++ b/tests/execution/test_order_handler.py @@ -32,6 +32,7 @@ async def test_request_order_success(): size=1.0, currency="USD", force_open=True, + exit_reason="", ) diff --git a/tests/recording/test_ledger.py b/tests/recording/test_ledger.py index 30f2575..da5d731 100644 --- a/tests/recording/test_ledger.py +++ b/tests/recording/test_ledger.py @@ -4,8 +4,10 @@ import pytest +from tradedesk.recording.excursions import CandleIndex, build_candle_index from tradedesk.recording.ledger import TradeLedger, trade_rows_from_trades from tradedesk.recording.types import EquityRecord, RecordingMode, TradeRecord +from tradedesk.types import Candle # --------------------------------------------------------------------------- # Helpers @@ -194,11 +196,161 @@ def test_write_batch(self, tmp_path): ledger.write(out) assert (out / "trades.csv").exists() assert (out / "round_trips.csv").exists() + assert (out / "metrics.csv").exists() assert (out / "equity.csv").exists() assert (out / "equity_daily.csv").exists() assert (out / "exposure.csv").exists() assert (out / "opportunity.csv").exists() + def test_write_round_trips_csv_with_excursions(self, tmp_path): + """MFE/MAE columns populated when candle_indices provided.""" + ledger = TradeLedger() + ledger.record_trade( + _trade(direction="BUY", price=150.0, ts="2025-01-15T12:00:00Z") + ) + ledger.record_trade( + _trade(direction="SELL", price=155.0, ts="2025-01-15T13:00:00Z") + ) + candles = [ + Candle(timestamp="2025-01-15T12:00:00Z", open=150, high=158, low=149, close=152), + Candle(timestamp="2025-01-15T13:00:00Z", open=152, high=156, low=151, close=155), + ] + ledger.candle_indices["USDJPY"] = build_candle_index(candles) + + path = tmp_path / "round_trips.csv" + ledger.write_round_trips_csv(path) + rows = _read_csv(path) + assert len(rows) == 1 + assert rows[0]["mfe_pnl"] != "" + assert float(rows[0]["mfe_points"]) > 0 + + def test_write_round_trips_csv_without_excursions(self, tmp_path): + """MFE/MAE columns blank when no candle_indices.""" + ledger = TradeLedger() + ledger.record_trade( + _trade(direction="BUY", price=150.0, ts="2025-01-15T12:00:00Z") + ) + ledger.record_trade( + _trade(direction="SELL", price=155.0, ts="2025-01-15T13:00:00Z") + ) + path = tmp_path / "round_trips.csv" + ledger.write_round_trips_csv(path) + rows = _read_csv(path) + assert len(rows) == 1 + # 14-column header present + assert "mfe_points" in rows[0] + assert "mae_pnl" in rows[0] + # Values blank + assert rows[0]["mfe_pnl"] == "" + assert rows[0]["mae_pnl"] == "" + + def test_write_round_trips_csv_partial_excursions(self, tmp_path): + """Only instruments with candle_indices get MFE/MAE data.""" + ledger = TradeLedger() + # Instrument A: entry + exit + ledger.record_trade( + _trade(instrument="AAA", direction="BUY", price=100.0, ts="2025-01-15T12:00:00Z") + ) + ledger.record_trade( + _trade(instrument="AAA", direction="SELL", price=110.0, ts="2025-01-15T13:00:00Z") + ) + # Instrument B: entry + exit + ledger.record_trade( + _trade(instrument="BBB", direction="BUY", price=200.0, ts="2025-01-15T12:00:00Z") + ) + ledger.record_trade( + _trade(instrument="BBB", direction="SELL", price=210.0, ts="2025-01-15T13:00:00Z") + ) + # Only provide candle index for AAA + candles_a = [ + Candle(timestamp="2025-01-15T12:00:00Z", open=100, high=115, low=98, close=105), + Candle(timestamp="2025-01-15T13:00:00Z", open=105, high=112, low=104, close=110), + ] + ledger.candle_indices["AAA"] = build_candle_index(candles_a) + + path = tmp_path / "round_trips.csv" + ledger.write_round_trips_csv(path) + rows = _read_csv(path) + assert len(rows) == 2 + aaa = next(r for r in rows if r["instrument"] == "AAA") + bbb = next(r for r in rows if r["instrument"] == "BBB") + assert aaa["mfe_pnl"] != "" + assert bbb["mfe_pnl"] == "" + + def test_write_metrics_csv_basic(self, tmp_path): + """Metrics CSV has PORTFOLIO row and per-instrument row.""" + ledger = TradeLedger() + ledger.record_equity(_equity(ts="2025-01-15T12:00:00Z", eq=0.0)) + ledger.record_trade( + _trade(direction="BUY", price=150.0, ts="2025-01-15T12:00:00Z") + ) + ledger.record_trade( + _trade(direction="SELL", price=160.0, ts="2025-01-15T13:00:00Z") + ) + ledger.record_equity(_equity(ts="2025-01-15T13:00:00Z", eq=10.0)) + + path = tmp_path / "metrics.csv" + ledger.write_metrics_csv(path) + rows = _read_csv(path) + instruments = [r["instrument"] for r in rows] + assert "PORTFOLIO" in instruments + assert "USDJPY" in instruments + assert len(rows) == 2 + + def test_write_metrics_csv_multiple_instruments(self, tmp_path): + """Metrics CSV has PORTFOLIO + one row per instrument.""" + ledger = TradeLedger() + ledger.record_equity(_equity(ts="2025-01-15T12:00:00Z", eq=0.0)) + for inst in ["AAA", "BBB"]: + ledger.record_trade( + _trade(instrument=inst, direction="BUY", price=100.0, ts="2025-01-15T12:00:00Z") + ) + ledger.record_trade( + _trade(instrument=inst, direction="SELL", price=105.0, ts="2025-01-15T13:00:00Z") + ) + ledger.record_equity(_equity(ts="2025-01-15T13:00:00Z", eq=10.0)) + + path = tmp_path / "metrics.csv" + ledger.write_metrics_csv(path) + rows = _read_csv(path) + assert len(rows) == 3 + instruments = {r["instrument"] for r in rows} + assert instruments == {"PORTFOLIO", "AAA", "BBB"} + + def test_write_metrics_csv_empty_ledger(self, tmp_path): + """Empty ledger produces metrics.csv with header and PORTFOLIO row.""" + ledger = TradeLedger() + path = tmp_path / "metrics.csv" + ledger.write_metrics_csv(path) + rows = _read_csv(path) + assert len(rows) == 1 + assert rows[0]["instrument"] == "PORTFOLIO" + + def test_write_metrics_csv_broker_mode(self, tmp_path): + """BROKER mode subtracts initial_balance from PORTFOLIO final_equity.""" + ledger = TradeLedger( + mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0 + ) + # Record trades + ledger.record_trade( + _trade(direction="BUY", price=100.0, size=1.0, ts="2025-01-15T12:00:00Z") + ) + ledger.record_trade( + _trade(direction="SELL", price=110.0, size=1.0, ts="2025-01-15T13:00:00Z") + ) + # In broker mode, record_equity is ignored, but we need equity for compute_metrics. + # The ledger computes synthetic equity internally. For write_metrics_csv, + # we add equity rows manually to test the subtraction logic. + ledger.equity.append(_equity(ts="2025-01-15T12:00:00Z", eq=10000.0)) + ledger.equity.append(_equity(ts="2025-01-15T13:00:00Z", eq=10010.0)) + + path = tmp_path / "metrics.csv" + ledger.write_metrics_csv(path) + rows = _read_csv(path) + portfolio = next(r for r in rows if r["instrument"] == "PORTFOLIO") + # PnL should be 10 (10010 - 10000), not 10010 + assert float(portfolio["final_equity"]) == pytest.approx(10.0) + # --------------------------------------------------------------------------- # TradeLedger – broker mode diff --git a/tests/recording/test_report.py b/tests/recording/test_report.py new file mode 100644 index 0000000..719d9a4 --- /dev/null +++ b/tests/recording/test_report.py @@ -0,0 +1,141 @@ +import csv +from pathlib import Path + +from tradedesk.recording import report + + +def _write_csv(path: Path, headers: list[str], rows: list[dict[str, str]]) -> None: + path.parent.mkdir(parents=True, exist_ok=True) + with open(path, "w", newline="") as f: + writer = csv.DictWriter(f, fieldnames=headers) + writer.writeheader() + writer.writerows(rows) + + +def test_prepare_monthly_data_values_are_iterable(): + rt_rows = [ + { + "instrument": "com.example.inst1", + "exit_ts": "2026-01-15T12:00:00Z", + "pnl": "10.50", + "entry_ts": "2026-01-15T11:00:00Z", + "hold_minutes": "60", + "direction": "long", + }, + { + "instrument": "com.example.inst1", + "exit_ts": "2026-01-20T12:00:00Z", + "pnl": "-5.25", + "entry_ts": "2026-01-20T11:00:00Z", + "hold_minutes": "60", + "direction": "short", + }, + ] + + inst_data = {"com.example.inst1": rt_rows} + monthly = report._prepare_monthly_data(rt_rows, inst_data) + + assert hasattr(monthly, "rows") + assert isinstance(monthly.rows, list) + assert len(monthly.rows) >= 1 + + row = monthly.rows[0] + assert hasattr(row, "values") + assert isinstance(row.values, list) + assert all(isinstance(v, str) for v in row.values) + + assert hasattr(monthly, "totals") + assert isinstance(monthly.totals.values, list) + + +def test_generate_analysis_report_creates_file(tmp_path: Path): + out = tmp_path + metrics_path = out / "metrics.csv" + round_trips_path = out / "round_trips.csv" + + metrics_headers = [ + "instrument", + "final_equity", + "max_dd", + "win_rate", + "profit_factor", + "expectancy", + "round_trips", + "fills", + "avg_hold_min", + ] + + metrics_rows = [ + { + "instrument": "PORTFOLIO", + "final_equity": "1500", + "max_dd": "-50", + "win_rate": "0.6", + "profit_factor": "1.5", + "expectancy": "0.5", + "round_trips": "2", + "fills": "10", + "avg_hold_min": "30", + }, + { + "instrument": "com.example.inst1", + "final_equity": "500", + "max_dd": "-20", + "win_rate": "0.55", + "profit_factor": "1.2", + "expectancy": "0.3", + "round_trips": "2", + "fills": "5", + "avg_hold_min": "45", + }, + ] + + _write_csv(metrics_path, metrics_headers, metrics_rows) + + rt_headers = [ + "instrument", + "exit_ts", + "pnl", + "entry_ts", + "hold_minutes", + "direction", + "mfe_pnl", + "mae_pnl", + "exit_reason", + ] + + rt_rows = [ + { + "instrument": "com.example.inst1", + "exit_ts": "2026-01-15T12:00:00Z", + "pnl": "10.5", + "entry_ts": "2026-01-15T11:00:00Z", + "hold_minutes": "60", + "direction": "long", + "mfe_pnl": "15", + "mae_pnl": "-2", + "exit_reason": "", + }, + { + "instrument": "com.example.inst1", + "exit_ts": "2026-01-20T12:00:00Z", + "pnl": "-5.25", + "entry_ts": "2026-01-20T11:00:00Z", + "hold_minutes": "60", + "direction": "short", + "mfe_pnl": "8", + "mae_pnl": "-3", + "exit_reason": "market_order", + }, + ] + + _write_csv(round_trips_path, rt_headers, rt_rows) + + # Should not raise + report.generate_analysis_report(out) + + report_file = out / "analysis.md" + assert report_file.exists() + content = report_file.read_text() + # basic sanity checks + assert "Monthly" in content or "Months" in content or "2026-01" in content diff --git a/tests/recording/test_subscriber.py b/tests/recording/test_subscriber.py index 143dbdb..950d746 100644 --- a/tests/recording/test_subscriber.py +++ b/tests/recording/test_subscriber.py @@ -1,10 +1,19 @@ import asyncio from datetime import datetime, timezone +from pathlib import Path +from unittest.mock import patch -from tradedesk.events import get_dispatcher, reset_dispatcher -from tradedesk.recording.events import PositionClosedEvent, PositionOpenedEvent +import pytest + +from tradedesk.events import SessionEndedEvent, SessionStartedEvent, get_dispatcher, reset_dispatcher +from tradedesk.recording.events import ( + PositionClosedEvent, + PositionOpenedEvent, + ReportingCompleteEvent, +) from tradedesk.recording.ledger import TradeLedger -from tradedesk.recording.subscriber import register_recording_subscriber +from tradedesk.recording.subscriber import RecordingSubscriber, register_recording_subscriber +from tradedesk.recording.types import EquityRecord, TradeRecord def test_position_closed_records_entry_and_exit_trades() -> None: @@ -94,3 +103,239 @@ def test_position_closed_without_opened_records_exit_only() -> None: assert exit_trade.instrument == "EURUSD" assert exit_trade.direction == "BUY" # Opposite of SELL position assert exit_trade.price == 1.1900 + + +# --------------------------------------------------------------------------- +# handle_session_started +# --------------------------------------------------------------------------- + + +def test_session_started_creates_timestamped_output_dir(tmp_path: Path) -> None: + """SessionStartedEvent creates a timestamped subdirectory under the base output dir.""" + ts = datetime(2024, 6, 15, 9, 30, 0, tzinfo=timezone.utc) + sub = RecordingSubscriber(output_dir=tmp_path) + + sub.handle_session_started(SessionStartedEvent(timestamp=ts)) + + expected = tmp_path / "20240615_093000" + assert expected.is_dir() + assert sub._run_output_dir == expected + + +def test_session_started_no_output_dir_is_noop() -> None: + """When no output_dir is configured, session start does nothing.""" + sub = RecordingSubscriber() + + sub.handle_session_started(SessionStartedEvent()) + + assert sub._run_output_dir is None + + +def test_session_started_via_dispatcher(tmp_path: Path) -> None: + """SessionStartedEvent dispatched through the event bus reaches the subscriber.""" + reset_dispatcher() + ts = datetime(2024, 3, 1, 12, 0, 0, tzinfo=timezone.utc) + + register_recording_subscriber(output_dir=tmp_path) + + asyncio.run(get_dispatcher().publish(SessionStartedEvent(timestamp=ts))) + + assert (tmp_path / "20240301_120000").is_dir() + + +# --------------------------------------------------------------------------- +# handle_session_ended +# --------------------------------------------------------------------------- + + +def _make_subscriber_with_trades( + tmp_path: Path, +) -> RecordingSubscriber: + """Helper: create a subscriber that has an active run dir and some trades.""" + sub = RecordingSubscriber(output_dir=tmp_path) + ts = datetime(2024, 1, 1, 0, 0, 0, tzinfo=timezone.utc) + sub.handle_session_started(SessionStartedEvent(timestamp=ts)) + + sub.ledger.record_equity( + EquityRecord(timestamp="2024-01-01T00:00:00+00:00", equity=0.0) + ) + sub.ledger.record_trade( + TradeRecord( + timestamp="2024-01-01T00:00:00+00:00", + instrument="EURUSD", + direction="BUY", + size=1.0, + price=1.20, + ) + ) + sub.ledger.record_trade( + TradeRecord( + timestamp="2024-01-01T01:00:00+00:00", + instrument="EURUSD", + direction="SELL", + size=1.0, + price=1.21, + ) + ) + sub.ledger.record_equity( + EquityRecord(timestamp="2024-01-01T01:00:00+00:00", equity=10.0) + ) + return sub + + +@pytest.mark.asyncio +async def test_session_ended_writes_ledger_files(tmp_path: Path) -> None: + """SessionEndedEvent writes all expected CSV files to the run output directory.""" + sub = _make_subscriber_with_trades(tmp_path) + run_dir = sub._run_output_dir + assert run_dir is not None + + with patch("tradedesk.recording.subscriber.get_dispatcher") as mock_disp: + mock_disp.return_value.publish = _noop_publish + await sub.handle_session_ended(SessionEndedEvent()) + + assert (run_dir / "trades.csv").exists() + assert (run_dir / "round_trips.csv").exists() + assert (run_dir / "metrics.csv").exists() + assert (run_dir / "equity.csv").exists() + + +async def _noop_publish(event: object) -> None: + """Stub for dispatcher.publish so ReportingCompleteEvent doesn't propagate.""" + pass + + +@pytest.mark.asyncio +async def test_session_ended_emits_reporting_complete_event(tmp_path: Path) -> None: + """SessionEndedEvent always emits a ReportingCompleteEvent at the end.""" + reset_dispatcher() + sub = _make_subscriber_with_trades(tmp_path) + + received: list[ReportingCompleteEvent] = [] + + async def capture(evt: ReportingCompleteEvent) -> None: + received.append(evt) + + get_dispatcher().subscribe(ReportingCompleteEvent, capture) + + await sub.handle_session_ended(SessionEndedEvent()) + + assert len(received) == 1 + assert isinstance(received[0], ReportingCompleteEvent) + + +@pytest.mark.asyncio +async def test_session_ended_no_output_dir_still_logs_metrics(tmp_path: Path) -> None: + """When no output_dir is set, metrics are computed but no files are written.""" + sub = RecordingSubscriber() # no output_dir + sub.ledger.record_equity( + EquityRecord(timestamp="2024-01-01T00:00:00+00:00", equity=0.0) + ) + sub.ledger.record_trade( + TradeRecord( + timestamp="2024-01-01T00:00:00+00:00", + instrument="EURUSD", + direction="BUY", + size=1.0, + price=1.20, + ) + ) + sub.ledger.record_trade( + TradeRecord( + timestamp="2024-01-01T01:00:00+00:00", + instrument="EURUSD", + direction="SELL", + size=1.0, + price=1.21, + ) + ) + + with patch("tradedesk.recording.subscriber.get_dispatcher") as mock_disp: + mock_disp.return_value.publish = _noop_publish + # Should not raise even though there's nowhere to write + await sub.handle_session_ended(SessionEndedEvent()) + + # No files created (no run dir) + assert sub._run_output_dir is None + + +@pytest.mark.asyncio +async def test_session_ended_no_trades_skips_report(tmp_path: Path) -> None: + """When no trades exist, the report generation step is skipped.""" + sub = RecordingSubscriber(output_dir=tmp_path) + ts = datetime(2024, 1, 1, 0, 0, 0, tzinfo=timezone.utc) + sub.handle_session_started(SessionStartedEvent(timestamp=ts)) + + with patch("tradedesk.recording.subscriber.get_dispatcher") as mock_disp: + mock_disp.return_value.publish = _noop_publish + await sub.handle_session_ended(SessionEndedEvent()) + + run_dir = sub._run_output_dir + assert run_dir is not None + # analysis.md should not be created when there are no trades + assert not (run_dir / "analysis.md").exists() + + +@pytest.mark.asyncio +async def test_session_ended_ledger_write_failure_does_not_prevent_completion( + tmp_path: Path, +) -> None: + """If ledger.write() raises, the handler still emits ReportingCompleteEvent.""" + reset_dispatcher() + sub = _make_subscriber_with_trades(tmp_path) + + received: list[ReportingCompleteEvent] = [] + + async def capture(evt: ReportingCompleteEvent) -> None: + received.append(evt) + + get_dispatcher().subscribe(ReportingCompleteEvent, capture) + + with patch.object(sub.ledger, "write", side_effect=OSError("disk full")): + await sub.handle_session_ended(SessionEndedEvent()) + + # ReportingCompleteEvent still emitted despite the write failure + assert len(received) == 1 + + +@pytest.mark.asyncio +async def test_session_ended_via_dispatcher(tmp_path: Path) -> None: + """Full integration: SessionEndedEvent via the event bus writes files.""" + reset_dispatcher() + sub = register_recording_subscriber(output_dir=tmp_path) + + start_ts = datetime(2024, 1, 1, 0, 0, 0, tzinfo=timezone.utc) + await get_dispatcher().publish(SessionStartedEvent(timestamp=start_ts)) + + sub.ledger.record_equity( + EquityRecord(timestamp="2024-01-01T00:00:00+00:00", equity=0.0) + ) + sub.ledger.record_trade( + TradeRecord( + timestamp="2024-01-01T00:00:00+00:00", + instrument="EURUSD", + direction="BUY", + size=1.0, + price=1.20, + ) + ) + sub.ledger.record_trade( + TradeRecord( + timestamp="2024-01-01T01:00:00+00:00", + instrument="EURUSD", + direction="SELL", + size=1.0, + price=1.21, + ) + ) + sub.ledger.record_equity( + EquityRecord(timestamp="2024-01-01T01:00:00+00:00", equity=10.0) + ) + + await get_dispatcher().publish(SessionEndedEvent()) + + run_dir = tmp_path / "20240101_000000" + assert run_dir.is_dir() + assert (run_dir / "trades.csv").exists() + assert (run_dir / "metrics.csv").exists() + assert (run_dir / "round_trips.csv").exists() diff --git a/tests/strategy/test_event_dispatch.py b/tests/strategy/test_event_dispatch.py index a46f34b..3fb9702 100644 --- a/tests/strategy/test_event_dispatch.py +++ b/tests/strategy/test_event_dispatch.py @@ -4,6 +4,8 @@ from tradedesk.marketdata.events import CandleClosedEvent from tradedesk.marketdata.instrument import MarketData +from tradedesk.marketdata.subscriptions import ChartSubscription +from tradedesk.portfolio.simple import SimplePortfolio from tradedesk.strategy.base import BaseStrategy from tradedesk.types import Candle @@ -11,23 +13,21 @@ class Strat(BaseStrategy): SUBSCRIPTIONS = [] - def __init__(self, client): - super().__init__(client) - self.on_price_update_mock = AsyncMock() - self.on_candle_update_mock = AsyncMock() - async def on_price_update(self, md: MarketData): - await self.on_price_update_mock(md) + pass + - async def on_candle_close(self, cc: CandleClosedEvent): - await self.on_candle_update_mock(cc) - await super().on_candle_close(cc) +def make_portfolio(client=None): + """Create a SimplePortfolio wrapping a minimal strategy.""" + client = client or MagicMock() + strategy = Strat(client) + return SimplePortfolio(client, strategy) @pytest.mark.asyncio async def test_handle_event_marketdata_updates_last_update_and_dispatches(): - s = Strat(MagicMock()) - before = s.last_update + portfolio = make_portfolio() + before = portfolio.last_update event = MarketData( instrument="EPIC", @@ -37,24 +37,22 @@ async def test_handle_event_marketdata_updates_last_update_and_dispatches(): raw={"foo": "bar"}, ) - await s._handle_event(event) + await portfolio._handle_event(event) - assert s.last_update >= before - s.on_price_update_mock.assert_awaited_once() + assert portfolio.last_update >= before @pytest.mark.asyncio async def test_handle_event_candleclose_dispatches_and_uses_default_storage(): - # ensure chart storage path is covered: add a chart by defining a chart subscription - from tradedesk.marketdata.subscriptions import ChartSubscription - class S(BaseStrategy): SUBSCRIPTIONS = [ChartSubscription("EPIC", "5MINUTE")] - async def on_price_update(self, market_databid, offer, timestamp, raw_data): + async def on_price_update(self, market_data): pass - s = S(MagicMock()) + client = MagicMock() + strategy = S(client) + portfolio = SimplePortfolio(client, strategy) candle = Candle( timestamp="2025-12-28T00:00:00Z", @@ -67,15 +65,16 @@ async def on_price_update(self, market_databid, offer, timestamp, raw_data): ) event = CandleClosedEvent(instrument="EPIC", timeframe="5MINUTE", candle=candle) - await s._handle_event(event) + await portfolio._handle_event(event) + # The default on_candle_close in BaseStrategy stores the candle in chart history key = ("EPIC", "5MINUTE") - assert key in s.charts - assert s.charts[key].get_candles()[-1] == candle + assert key in strategy.charts + assert strategy.charts[key].get_candles()[-1] == candle @pytest.mark.asyncio async def test_handle_event_rejects_unknown_type(): - s = Strat(MagicMock()) + portfolio = make_portfolio() with pytest.raises(TypeError): - await s._handle_event(object()) # type: ignore[arg-type] + await portfolio._handle_event(object()) # type: ignore[arg-type] diff --git a/tests/strategy/test_run_streaming.py b/tests/strategy/test_run_streaming.py index 14e6494..522d925 100644 --- a/tests/strategy/test_run_streaming.py +++ b/tests/strategy/test_run_streaming.py @@ -6,6 +6,7 @@ from tradedesk.execution.ig import price_streamer from tradedesk.execution.ig.price_streamer import Lightstreamer from tradedesk.marketdata.subscriptions import ChartSubscription, MarketSubscription +from tradedesk.portfolio.simple import SimplePortfolio class FakeUpdate: @@ -99,7 +100,8 @@ def ls_factory(url: str, adapter: str): "get_streamer": lambda self: Lightstreamer(self), }, ) - strat = Strat(data_provider=ClientStub()) + client_stub = ClientStub() + strat = Strat(data_provider=client_stub) seen_market = [] seen_candles = [] @@ -114,7 +116,8 @@ async def on_candle_close(cc): strat.on_price_update = on_price_update # type: ignore strat.on_candle_close = on_candle_close # type: ignore - task = asyncio.create_task(strat._run_streaming()) + portfolio = SimplePortfolio(client_stub, strat) + task = asyncio.create_task(portfolio._run_streaming()) try: # Wait for LS client instance and subscriptions diff --git a/tests/strategy/test_strategy.py b/tests/strategy/test_strategy.py index ae796b0..97d778c 100644 --- a/tests/strategy/test_strategy.py +++ b/tests/strategy/test_strategy.py @@ -5,24 +5,13 @@ import asyncio from datetime import datetime -from unittest.mock import AsyncMock, MagicMock, patch +from unittest.mock import MagicMock import pytest -from tradedesk.execution.ig.price_streamer import Lightstreamer from tradedesk.marketdata.subscriptions import MarketSubscription from tradedesk.strategy.base import BaseStrategy -# Optional import -try: - from lightstreamer.client import ( # type: ignore[import-untyped] - LightstreamerClient, - Subscription, - ) -except Exception: # pragma: no cover - LightstreamerClient = None - Subscription = None - class TestBaseStrategy: """Test the BaseStrategy base class.""" @@ -43,199 +32,9 @@ async def on_price_update(self, market_databid, offer, timestamp, raw_data): strategy = TestStrategy(mock_client) assert strategy.client == mock_client - assert strategy.POLL_INTERVAL == 5 assert strategy.watchdog_threshold == 60 assert isinstance(strategy.last_update, datetime) - @pytest.mark.asyncio - async def test_run_without_lightstreamer(self): - """Test strategy falls back to polling when Lightstreamer unavailable.""" - mock_client = MagicMock() - mock_client.get_market_snapshot = AsyncMock( - return_value={"snapshot": {"bid": 1.2345, "offer": 1.2347}} - ) - - class TestStrategy(BaseStrategy): - SUBSCRIPTIONS = [MarketSubscription("CS.D.EURUSD.CFD.IP")] - - def __init__(self, client): - super().__init__(client) - self.updates = [] - - async def on_price_update(self, market_data): - self.updates.append( - (market_data.instrument, market_data.bid, market_data.offer) - ) - - strategy = TestStrategy(mock_client) - - # Mock _has_streamer() to return False - with patch.object(strategy, "_has_streamer", return_value=False): - # Run for a short time then cancel - task = asyncio.create_task(strategy.run()) - await asyncio.sleep(0.1) - task.cancel() - - try: - await task - except asyncio.CancelledError: - pass - - # Should have called get_market_snapshot at least once - mock_client.get_market_snapshot.assert_called_with("CS.D.EURUSD.CFD.IP") - - # Should have received updates - assert len(strategy.updates) > 0 - - @pytest.mark.asyncio - async def test_polling_mode(self): - """Test polling mode functionality.""" - mock_client = MagicMock() - - updates = [] - - class TestStrategy(BaseStrategy): - SUBSCRIPTIONS = [ - MarketSubscription("CS.D.EURUSD.CFD.IP"), - MarketSubscription("CS.D.GBPUSD.CFD.IP"), - ] - - async def on_price_update(self, market_data): - updates.append( - { - "instrument": market_data.instrument, - "bid": market_data.bid, - "offer": market_data.offer, - } - ) - - strategy = TestStrategy(mock_client) - strategy.POLL_INTERVAL = 0.1 # Fast polling for test - - # Mock different snapshots for each EPIC - mock_client.get_market_snapshot = AsyncMock( - side_effect=[ - {"snapshot": {"bid": 1.1000, "offer": 1.1002}}, # First EURUSD - {"snapshot": {"bid": 1.3000, "offer": 1.3002}}, # First GBPUSD - { - "snapshot": {"bid": 1.1001, "offer": 1.1003} - }, # Second EURUSD (changed) - {"snapshot": {"bid": 1.3000, "offer": 1.3002}}, # Second GBPUSD (same) - ] - ) - - # Run polling for a short time - task = asyncio.create_task(strategy._run_polling()) - await asyncio.sleep(0.25) # Enough for two polling cycles - task.cancel() - - try: - await task - except asyncio.CancelledError: - pass - - # Should have received updates for price changes only - # EURUSD changed, GBPUSD didn't change on second poll - assert len(updates) == 3 # First EURUSD, First GBPUSD, Second EURUSD - - # Verify instrument order in updates - assert updates[0]["instrument"] == "CS.D.EURUSD.CFD.IP" - assert updates[1]["instrument"] == "CS.D.GBPUSD.CFD.IP" - assert updates[2]["instrument"] == "CS.D.EURUSD.CFD.IP" - - @pytest.mark.asyncio - async def test_polling_mode_exception_handling(self): - """Test polling mode handles exceptions gracefully.""" - mock_client = MagicMock() - - updates = [] - - class TestStrategy(BaseStrategy): - SUBSCRIPTIONS = [MarketSubscription("CS.D.EURUSD.CFD.IP")] - - async def on_price_update(self, market_data): - updates.append("update") - - strategy = TestStrategy(mock_client) - strategy.POLL_INTERVAL = 0.1 - - # Mock an exception on first call, success on second - mock_client.get_market_snapshot = AsyncMock( - side_effect=[ - Exception("Network error"), - {"snapshot": {"bid": 1.1000, "offer": 1.1002}}, - ] - ) - - with patch("logging.Logger.exception") as mock_exception: - task = asyncio.create_task(strategy._run_polling()) - await asyncio.sleep(0.15) - task.cancel() - - try: - await task - except asyncio.CancelledError: - pass - - # Exception should have been logged - mock_exception.assert_called_once() - # But polling should continue and eventually succeed - assert len(updates) == 1 - - @pytest.mark.asyncio - async def test_streaming_mode_setup(self, mock_lightstreamer): - """Test Lightstreamer streaming mode setup.""" - mock_client = MagicMock() - mock_client.ls_url = "https://demo-apd.marketdatasystems.com" - mock_client.ls_cst = "CST_TOKEN" - mock_client.ls_xst = "XST_TOKEN" - mock_client.client_id = "CLIENT123" - mock_client.account_id = "ACCOUNT123" # fallback path used in streamer - - # Provide the streamer via the new client API - - mock_client.get_streamer = lambda: Lightstreamer(mock_client) - - class TestStrategy(BaseStrategy): - SUBSCRIPTIONS = [MarketSubscription("CS.D.EURUSD.CFD.IP")] - - async def on_price_update(self, market_databid, offer, timestamp, raw_data): - pass - - strategy = TestStrategy(mock_client) - - mock_ls_info = mock_lightstreamer - - # Patch the Lightstreamer module (not tradedesk.strategy) - import lightstreamer.client as ls_client_module # type: ignore[import] - - ls_client_module.LightstreamerClient = lambda *args, **kwargs: mock_ls_info[ - "client" - ] - ls_client_module.Subscription = lambda *args, **kwargs: mock_ls_info[ - "subscription" - ] - - # Run streaming for a moment then cancel - task = asyncio.create_task(strategy._run_streaming()) - await asyncio.sleep(0.1) - task.cancel() - - try: - await task - except asyncio.CancelledError: - pass - - # Verify Lightstreamer client was configured - mock_ls_info["client"].connectionDetails.setUser.assert_called_with("CLIENT123") - mock_ls_info["client"].connectionDetails.setPassword.assert_called_with( - "CST-CST_TOKEN|XST-XST_TOKEN" - ) - mock_ls_info["client"].connect.assert_called_once() - mock_ls_info["subscription"].addListener.assert_called_once() - mock_ls_info["client"].subscribe.assert_called_once() - - class TestConcreteStrategy: """Test with a concrete strategy implementation.""" diff --git a/tests/test_runner.py b/tests/test_runner.py index 3f4907c..2747298 100644 --- a/tests/test_runner.py +++ b/tests/test_runner.py @@ -3,229 +3,111 @@ Tests for the runner module. """ -from types import SimpleNamespace from unittest.mock import AsyncMock, MagicMock, patch import pytest -from tradedesk.runner import _run_strategies_async, configure_logging, run_strategies -from tradedesk.strategy.base import BaseStrategy +from tradedesk.portfolio.base import BasePortfolio +from tradedesk.runner import configure_logging, run_portfolio -class TestRunner: - """Test the strategy runner.""" +class MinimalPortfolio(BasePortfolio): + async def on_candle_close(self, event): + pass + +class TestConfigureLogging: def test_configure_logging_defaults(self): - """Test logging configuration works when no handlers exist.""" import logging - # Clear existing handlers to simulate clean slate root_logger = logging.getLogger() root_logger.handlers.clear() configure_logging("DEBUG") - # Should have added a handler assert root_logger.level == logging.DEBUG assert len(root_logger.handlers) == 1 assert isinstance(root_logger.handlers[0], logging.StreamHandler) def test_configure_logging_respects_existing(self): - """Test logging configuration does NOT overwrite existing handlers.""" import logging root_logger = logging.getLogger() root_logger.handlers.clear() - # Manually add a handler dummy_handler = logging.NullHandler() root_logger.addHandler(dummy_handler) root_logger.setLevel(logging.WARNING) - # Try to configure logging (should perform no-op) configure_logging("DEBUG") - # Level should NOT have changed to DEBUG assert root_logger.level == logging.WARNING - # Should NOT have added a StreamHandler assert len(root_logger.handlers) == 1 assert root_logger.handlers[0] == dummy_handler def test_configure_logging_force(self): - """Test logging configuration CAN force overwrite.""" import logging root_logger = logging.getLogger() root_logger.handlers.clear() - # Manually add a handler root_logger.addHandler(logging.NullHandler()) - # Force configure configure_logging("DEBUG", force=True) - # Should have wiped NullHandler and added StreamHandler assert root_logger.level == logging.DEBUG assert len(root_logger.handlers) == 1 assert isinstance(root_logger.handlers[0], logging.StreamHandler) - @pytest.mark.asyncio - async def test_run_strategies_async_empty(self): - """Test running empty strategy list.""" - mock_client = AsyncMock() - mock_client.close = AsyncMock() - - with patch("tradedesk.runner.log.warning") as mock_warning: - await _run_strategies_async([], mock_client) - - mock_warning.assert_called_with("No strategies to run") - - @pytest.mark.asyncio - async def test_run_strategies_async_single(self): - """Test running a single strategy.""" - mock_strategy = MagicMock() - mock_strategy.subscriptions = [SimpleNamespace(instrument="CS.D.EURUSD.CFD.IP")] - mock_strategy.__class__.__name__ = "TestStrategy" - mock_strategy.run = AsyncMock() - - # Create a proper async mock for client - mock_client = AsyncMock() - mock_client.close = AsyncMock() - with patch("tradedesk.runner.log.info") as mock_info: - await _run_strategies_async([mock_strategy], mock_client) - - # Check if any call matches our expected format - found = False - for actual_call in mock_info.call_args_list: - try: - # Check if this is the "Loaded ..." call - if ( - len(actual_call[0]) >= 5 - and actual_call[0][0] - == "Loaded %s monitoring %d instrument%s: %s" - and actual_call[0][1] == "TestStrategy" - and actual_call[0][2] == 1 - ): - found = True - break - except (IndexError, AttributeError): - continue - - assert found, "Expected log call not found" - - # Verify strategy was run - mock_strategy.run.assert_awaited_once() - - @pytest.mark.asyncio - async def test_run_strategies_async_multiple(self): - """Test running multiple strategies.""" - mock_strategy1 = MagicMock() - mock_strategy1.subscriptions = [ - SimpleNamespace(instrument="CS.D.EURUSD.CFD.IP") - ] - mock_strategy1.__class__.__name__ = "Strategy1" - mock_strategy1.run = AsyncMock() - - mock_strategy2 = MagicMock() - mock_strategy2.subscriptions = [ - SimpleNamespace(instrument="CS.D.GBPUSD.CFD.IP") - ] - mock_strategy2.__class__.__name__ = "Strategy2" - mock_strategy2.run = AsyncMock() - - # Create a proper async mock for client - mock_client = AsyncMock() +class TestRunPortfolio: + def test_run_portfolio_calls_portfolio_run(self): + """Portfolio's run() is awaited.""" + mock_client = MagicMock() + mock_client.start = AsyncMock() mock_client.close = AsyncMock() - with patch("tradedesk.runner.log.info") as mock_info: - await _run_strategies_async([mock_strategy1, mock_strategy2], mock_client) - - # Both strategies should have been run - mock_strategy1.run.assert_awaited_once() - mock_strategy2.run.assert_awaited_once() - - # Check logging - simpler approach - call_strings = [str(call_obj) for call_obj in mock_info.call_args_list] - - # Look for our expected calls in the call strings - found_strategy1 = False - found_strategy2 = False - - for call_str in call_strings: - if "Strategy1" in call_str and "CS.D.EURUSD.CFD.IP" in call_str: - found_strategy1 = True - if "Strategy2" in call_str and "CS.D.GBPUSD.CFD.IP" in call_str: - found_strategy2 = True - - assert found_strategy1, "Expected log for Strategy1 not found" - assert found_strategy2, "Expected log for Strategy2 not found" - - def test_run_strategies_invalid_config(self): - """Runner exits if a strategy fails to instantiate, and closes the client.""" - - class BoomStrategy(BaseStrategy): - def __init__(self, client, **kwargs): - super().__init__(client, **kwargs) - raise ValueError("Missing credentials") + mock_portfolio = MagicMock() + mock_portfolio.run = AsyncMock() - async def on_price_update(self, market_databid, offer, timestamp, raw_data): - pass + run_portfolio( + portfolio_factory=lambda c: mock_portfolio, + client_factory=lambda: mock_client, + setup_logging=False, + ) - client = MagicMock() - client.start = AsyncMock() - client.close = AsyncMock() + mock_client.start.assert_awaited_once() + mock_portfolio.run.assert_awaited_once() + mock_client.close.assert_awaited_once() - with patch("sys.exit") as mock_exit: - run_strategies( - strategy_specs=[BoomStrategy], - client_factory=lambda: client, - setup_logging=False, - ) - - mock_exit.assert_called_with(1) - client.start.assert_awaited_once() - client.close.assert_awaited_once() - - def test_run_strategies_client_error(self): - """Runner exits if a strategy run task errors, and closes the client.""" - - class ErrorStrategy(BaseStrategy): - async def on_price_update(self, market_databid, offer, timestamp, raw_data): - pass - - async def run(self): - raise Exception("Auth failed") + def test_run_portfolio_client_error_exits(self): + """Runner exits with code 1 if portfolio.run() raises.""" + mock_client = MagicMock() + mock_client.start = AsyncMock() + mock_client.close = AsyncMock() - client = MagicMock() - client.start = AsyncMock() - client.close = AsyncMock() + mock_portfolio = MagicMock() + mock_portfolio.run = AsyncMock(side_effect=Exception("broker error")) with patch("sys.exit") as mock_exit: - run_strategies( - strategy_specs=[ErrorStrategy], - client_factory=lambda: client, + run_portfolio( + portfolio_factory=lambda c: mock_portfolio, + client_factory=lambda: mock_client, setup_logging=False, ) mock_exit.assert_called_with(1) - client.start.assert_awaited_once() - client.close.assert_awaited_once() - - def test_run_strategies_keyboard_interrupt(self): - """Test graceful handling of KeyboardInterrupt.""" + mock_client.close.assert_awaited_once() - class MockStrategy(BaseStrategy): - async def on_price_update(self, market_databid, offer, timestamp, raw_data): - pass - - client = MagicMock() - client.close = AsyncMock() - - # Force asyncio.run(...) in runner to raise KeyboardInterrupt + def test_run_portfolio_keyboard_interrupt(self): + """Graceful handling of KeyboardInterrupt.""" with patch("asyncio.run", side_effect=KeyboardInterrupt()): with patch("logging.Logger.info") as mock_info: - run_strategies(client, [MockStrategy], setup_logging=False) + run_portfolio( + portfolio_factory=lambda c: MagicMock(), + client_factory=lambda: MagicMock(), + setup_logging=False, + ) mock_info.assert_any_call( "Interrupted by user - shutting down gracefully" diff --git a/tradedesk/__init__.py b/tradedesk/__init__.py index 84d3877..7cad526 100644 --- a/tradedesk/__init__.py +++ b/tradedesk/__init__.py @@ -10,11 +10,13 @@ from .events import ( DomainEvent, SessionEndedEvent, + SessionReadyEvent, SessionStartedEvent, event, get_dispatcher, ) -from .runner import run_strategies +from .portfolio import BasePortfolio, Portfolio, SimplePortfolio +from .runner import run_portfolio from .types import ( Candle, DataProvider, @@ -24,20 +26,24 @@ StreamConsumer, ) -__version__ = "0.4.0" +__version__ = "0.5.0" __all__ = [ "__version__", + "BasePortfolio", "Candle", "DataProvider", "Direction", "DomainEvent", "OrderRequest", "OrderResult", + "Portfolio", "SessionEndedEvent", + "SessionReadyEvent", "SessionStartedEvent", + "SimplePortfolio", "StreamConsumer", "event", "get_dispatcher", - "run_strategies", + "run_portfolio", ] diff --git a/tradedesk/events.py b/tradedesk/events.py index 87bca04..e924279 100644 --- a/tradedesk/events.py +++ b/tradedesk/events.py @@ -31,6 +31,11 @@ class SessionEndedEvent(DomainEvent): """Event fired when a backtest or live session ends.""" pass +@event +class SessionReadyEvent(DomainEvent): + """Fired after all SessionStartedEvent handlers complete (warmup + reconciliation done).""" + pass + class EventDispatcher: """Async event dispatcher for domain events. diff --git a/tradedesk/execution/backtest/client.py b/tradedesk/execution/backtest/client.py index ed637d2..a8ca8ec 100644 --- a/tradedesk/execution/backtest/client.py +++ b/tradedesk/execution/backtest/client.py @@ -369,6 +369,8 @@ async def place_market_order( size: float, currency: str = "USD", force_open: bool = True, + exit_reason: str = "", + **kwargs: Any, ) -> dict[str, Any]: if not self._started: raise RuntimeError("BacktestClient not started") @@ -443,7 +445,7 @@ async def place_market_order( entry_price=pos.entry_price, exit_price=price, pnl=closed_pnl, - exit_reason="market_order", + exit_reason=exit_reason or "market_order", timestamp=parse_timestamp(self._current_timestamp or ""), ) ) @@ -485,9 +487,12 @@ async def place_market_order_confirmed( size: float, currency: str = "USD", force_open: bool = True, + exit_reason: str = "", + **kwargs: Any, ) -> dict[str, Any]: return await self.place_market_order( - instrument, direction, size, currency=currency, force_open=force_open + instrument, direction, size, currency=currency, force_open=force_open, + exit_reason=exit_reason, **kwargs ) async def get_positions(self) -> list["BrokerPosition"]: diff --git a/tradedesk/execution/backtest/runner.py b/tradedesk/execution/backtest/runner.py index c9c9730..b3cee96 100644 --- a/tradedesk/execution/backtest/runner.py +++ b/tradedesk/execution/backtest/runner.py @@ -1,11 +1,15 @@ # tradedesk/execution/backtest/runner.py -"""Event-driven backtest runner - replaces harness.py wrapper pattern.""" +"""Event-driven backtest runner.""" + +from __future__ import annotations from dataclasses import dataclass from pathlib import Path -from typing import Callable +from typing import TYPE_CHECKING, Callable + +if TYPE_CHECKING: + from tradedesk.portfolio.base import BasePortfolio -from tradedesk.events import SessionEndedEvent, SessionStartedEvent, get_dispatcher from tradedesk.recording import ( EquityRecorder, ExcursionComputer, @@ -17,7 +21,6 @@ register_recording_subscriber, trade_rows_from_trades, ) -from tradedesk.types import StreamConsumer from .client import BacktestClient @@ -38,33 +41,22 @@ async def run_backtest( *, spec: BacktestSpec, out_dir: Path, - strategy_factory: Callable[[BacktestClient], StreamConsumer], + portfolio_factory: Callable[[BacktestClient], BasePortfolio], ) -> Metrics: """ Event-driven backtest runner. - Replaces harness.py with clean event-driven architecture: - - No wrapping of strategy._handle_event - - Event-driven recorders subscribe to domain events - - Recording happens transparently through RecordingSubscriber - - Equity sampling via EquityRecorder - - Live excursion tracking via ExcursionComputer - - Contract: - - Replays candles from CSV via BacktestClient/BacktestStreamer - - Creates event-driven recorders that subscribe to events - - Records trades/equity via RecordingSubscriber + TradeLedger - - Writes artefacts via TradeLedger.write(out_dir) - - Computes metrics from ledger state - - Returns Metrics object + Sets up recording infrastructure, then delegates the full session lifecycle + to the portfolio (warmup via SessionStartedEvent, streaming, SessionEndedEvent). Args: spec: BacktestSpec with instrument, period, CSV path, etc. - out_dir: Directory to write CSV artefacts - strategy_factory: Callable that creates a StreamConsumer given a client + out_dir: Directory to write CSV artefacts. + portfolio_factory: Callable that receives a BacktestClient and returns + an initialised BasePortfolio. Returns: - Metrics object with performance statistics + Metrics object with performance statistics. """ # Create backtest client and load candles raw_client = BacktestClient.from_csv( @@ -72,11 +64,6 @@ async def run_backtest( ) await raw_client.start() - # Wire event-driven order execution - from tradedesk.execution.order_handler import OrderExecutionHandler - - _order_handler = OrderExecutionHandler(raw_client) # noqa: F841 - # Apply half-spread adjustment if specified (e.g., BID -> MID normalization) adj = float(spec.half_spread_adjustment or 0.0) if adj: @@ -105,17 +92,9 @@ async def run_backtest( candle_index = build_candle_index(all_candles) _excursion_computer = ExcursionComputer(candle_index) - # Create strategy - strategy = strategy_factory(raw_client) - - # Publish session started event - await get_dispatcher().publish(SessionStartedEvent()) - - # Run backtest (streamer emits events, recorders react) - await streamer.run(strategy) - - # Publish session ended event (triggers metrics computation) - await get_dispatcher().publish(SessionEndedEvent()) + # Create portfolio and run the full session lifecycle + portfolio = portfolio_factory(raw_client) + await portfolio.run() # Compute and return metrics equity_rows = [{"timestamp": e.timestamp, "equity": str(e.equity)} for e in ledger.equity] diff --git a/tradedesk/execution/backtest/streamer.py b/tradedesk/execution/backtest/streamer.py index 657f999..fc65290 100644 --- a/tradedesk/execution/backtest/streamer.py +++ b/tradedesk/execution/backtest/streamer.py @@ -87,6 +87,7 @@ async def run(self, consumer: Any) -> None: instrument=cseries.instrument, timeframe=cseries.period, candle=c, + timestamp=ts, ), ) ) diff --git a/tradedesk/execution/client.py b/tradedesk/execution/client.py index 5c831e6..c451f9a 100644 --- a/tradedesk/execution/client.py +++ b/tradedesk/execution/client.py @@ -57,6 +57,8 @@ async def place_market_order( size: float, currency: str = "USD", force_open: bool = True, + exit_reason: str = "", + **kwargs: Any, ) -> dict[str, Any]: """Place a market order without requiring confirmation. @@ -69,6 +71,9 @@ async def place_market_order( currency: The currency code (default "USD"). force_open: If True, opens a new position even if an opposing position exists (netting vs hedging). + exit_reason: Strategy-provided reason for closing (e.g. "regime_off", + "stop_loss"). Propagated to PositionClosedEvent for recording. + **kwargs: Additional broker-specific parameters. Returns: A dictionary containing the deal reference or order ID. @@ -83,6 +88,8 @@ async def place_market_order_confirmed( size: float, currency: str = "USD", force_open: bool = True, + exit_reason: str = "", + **kwargs: Any, ) -> dict[str, Any]: """Place a market order and confirm its execution. @@ -95,6 +102,9 @@ async def place_market_order_confirmed( currency: The currency code (default "USD"). force_open: If True, opens a new position even if an opposing position exists. + exit_reason: Strategy-provided reason for closing (e.g. "regime_off", + "stop_loss"). Propagated to PositionClosedEvent for recording. + **kwargs: Additional broker-specific parameters. Returns: A dictionary containing the full deal confirmation details. diff --git a/tradedesk/execution/ig/client.py b/tradedesk/execution/ig/client.py index a15139b..19ca483 100644 --- a/tradedesk/execution/ig/client.py +++ b/tradedesk/execution/ig/client.py @@ -93,8 +93,12 @@ async def start(self) -> None: """Initialize the client and authenticate.""" if self._session is None: self._session = aiohttp.ClientSession(headers=self.headers) - await self._authenticate() - + try: + await self._authenticate() + except Exception as _e: + await self.close() # Ensure session is closed on failure + raise + async def close(self) -> None: """Close the session.""" if self._session: @@ -231,7 +235,7 @@ async def _handle_v3_auth(self, body: dict[str, Any]) -> None: Handles Version 3 Authentication (OAuth). Warning: Does NOT support Lightstreamer. """ - oauth_token = body.get("oauthToken", {}) + oauth_token = body.get("oauthToken") or {} access_token = oauth_token.get("access_token") if not access_token: @@ -340,8 +344,8 @@ async def _request( f"IG request failed: HTTP {resp.status}: {err_body}" ) - result: dict[str, Any] = await resp.json() - return result + result = await resp.json() + return result if isinstance(result, dict) else {} except aiohttp.ClientError as e: log.error("Request failed: %s %s - %s", method, url, e) @@ -354,7 +358,9 @@ async def _handle_retry_logic( # 1. Check if it's a rate limit (unrecoverable) try: body = await resp.json() - if body.get("errorCode") == "error.public-api.exceeded-api-key-allowance": + if isinstance(body, dict) and body.get("errorCode") == ( + "error.public-api.exceeded-api-key-allowance" + ): raise RuntimeError("IG API rate limit exceeded.") except (ValueError, KeyError): pass @@ -468,12 +474,17 @@ async def quantise_size(self, epic: str, size: float) -> float: """ metadata = await self.get_instrument_metadata(epic) - dealing_rules = metadata.get("dealingRules", {}) - min_value = dealing_rules.get("minDealSize", {}).get("value") + dealing_rules = metadata.get("dealingRules") or {} + min_value = (dealing_rules.get("minDealSize") or {}).get("value") - # If no minimum deal size defined, return the original size + # If no minimum deal size defined (IG can return dealingRules: null), + # fall back to 2 decimal places to avoid "too-many-decimal-places" rejections. if min_value is None: - return float(size) + log.warning( + "No minDealSize in dealing rules for %s — falling back to 2 dp rounding", + epic, + ) + return round(float(size), 2) # Infer step size from the decimal places in minDealSize # e.g., 0.04 (2 decimals) -> step = 0.01 @@ -524,8 +535,8 @@ async def get_positions(self) -> list["BrokerPosition"]: result: list[BrokerPosition] = [] for p in positions: - market = p.get("market", {}) - position = p.get("position", {}) + market = p.get("market") or {} + position = p.get("position") or {} result.append( BrokerPosition( instrument=market.get("epic", ""), @@ -557,7 +568,7 @@ async def get_account_balance(self) -> "AccountBalance": f"Account {self.account_id} not found in /accounts response" ) - bal = current.get("balance", {}) + bal = current.get("balance") or {} return AccountBalance( balance=float(bal.get("balance", 0)), deposit=float(bal.get("deposit", 0)), @@ -573,9 +584,11 @@ async def place_market_order( size: float, currency: str = "GBP", force_open: bool = False, + exit_reason: str = "", expiry: str = "-", time_in_force: str = "FILL_OR_KILL", guaranteed_stop: bool = False, + **kwargs: Any, ) -> dict[str, Any]: """ Submit a simple OTC market order. @@ -673,11 +686,13 @@ async def place_market_order_confirmed( size: float, currency: str = "GBP", force_open: bool = False, + exit_reason: str = "", time_in_force: str = "FILL_OR_KILL", expiry: str = "-", guaranteed_stop: bool = False, confirm_timeout_s: float = 10.0, confirm_poll_s: float = 0.25, + **kwargs: Any, ) -> dict[str, Any]: res = await self.place_market_order( instrument=instrument, diff --git a/tradedesk/execution/ig/settings.py b/tradedesk/execution/ig/settings.py index fd5bd57..8a4cbf9 100644 --- a/tradedesk/execution/ig/settings.py +++ b/tradedesk/execution/ig/settings.py @@ -15,33 +15,33 @@ """ import os -from dataclasses import dataclass from typing import Literal -@dataclass class Settings: """ Global settings for the tradedesk library. - Values are loaded from environment variables on initialization. - Users can override these programmatically if needed: - - from tradedesk.config import settings - settings.ig_api_key = "custom_key" + Values are read from environment variables on each access, so env vars + set after import (e.g. via export_ig_env_from_config) are picked up + correctly. """ - ig_api_key: str = "" - ig_username: str = "" - ig_password: str = "" - ig_environment: Literal["DEMO", "LIVE"] = "DEMO" + @property + def ig_api_key(self) -> str: + return os.getenv("IG_API_KEY", "") + + @property + def ig_username(self) -> str: + return os.getenv("IG_USERNAME", "") + + @property + def ig_password(self) -> str: + return os.getenv("IG_PASSWORD", "") - def __post_init__(self) -> None: - # Populate from environment at import-time. - self.ig_api_key = os.getenv("IG_API_KEY", "") - self.ig_username = os.getenv("IG_USERNAME", "") - self.ig_password = os.getenv("IG_PASSWORD", "") - self.ig_environment = os.getenv("IG_ENVIRONMENT", self.ig_environment).upper() # type: ignore + @property + def ig_environment(self) -> Literal["DEMO", "LIVE"]: + return os.getenv("IG_ENVIRONMENT", "DEMO").upper() # type: ignore[return-value] def validate(self) -> None: missing: list[str] = [] @@ -64,5 +64,5 @@ def validate(self) -> None: ) -# Global settings instance - loaded when module is imported +# Global settings instance settings = Settings() diff --git a/tradedesk/execution/order_handler.py b/tradedesk/execution/order_handler.py index 3f25911..320ef83 100644 --- a/tradedesk/execution/order_handler.py +++ b/tradedesk/execution/order_handler.py @@ -107,6 +107,7 @@ async def _execute(self, request: OrderRequest) -> OrderResult: size=q_size, currency=request.currency, force_open=request.force_open, + exit_reason=request.exit_reason, ) # Extract fill price (IG uses "level"; others may use "price") diff --git a/tradedesk/portfolio/__init__.py b/tradedesk/portfolio/__init__.py index 7b3fa8b..ea30802 100644 --- a/tradedesk/portfolio/__init__.py +++ b/tradedesk/portfolio/__init__.py @@ -1,5 +1,6 @@ """Portfolio management for multi-instrument trading.""" +from .base import BasePortfolio, Portfolio from .config import BacktestPortfolioConfig, LivePortfolioConfig, PortfolioConfig from .events import event from .journal import JournalEntry, PositionJournal @@ -13,6 +14,7 @@ ) from .risk import EqualSplitRiskPolicy, RiskAllocationPolicy, atr_normalised_size from .runner import PortfolioRunner +from .simple import SimplePortfolio from .types import ( Instrument, PortfolioStrategy, @@ -22,12 +24,14 @@ __all__ = [ "BacktestPortfolioConfig", + "BasePortfolio", "DiscrepancyType", "EqualSplitRiskPolicy", "Instrument", "InstrumentWindow", "JournalEntry", "LivePortfolioConfig", + "Portfolio", "PortfolioConfig", "PortfolioRunner", "PortfolioStrategy", @@ -37,6 +41,7 @@ "ReconciliationManager", "ReconciliationResult", "RiskAllocationPolicy", + "SimplePortfolio", "StrategySpec", "WeightedRollingTracker", "atr_normalised_size", diff --git a/tradedesk/portfolio/base.py b/tradedesk/portfolio/base.py new file mode 100644 index 0000000..c1be98a --- /dev/null +++ b/tradedesk/portfolio/base.py @@ -0,0 +1,96 @@ +"""Base classes for portfolio-level orchestration.""" + +import asyncio +import logging +from abc import ABC, abstractmethod +from datetime import datetime, timezone +from typing import Protocol + +from tradedesk.events import ( + SessionEndedEvent, + SessionReadyEvent, + SessionStartedEvent, + get_dispatcher, +) +from tradedesk.execution import Client, OrderExecutionHandler +from tradedesk.marketdata import ( + CandleClosedEvent, + ChartSubscription, + MarketData, + MarketDataReceivedEvent, + MarketSubscription, +) + +log = logging.getLogger(__name__) + + +class Portfolio(Protocol): + """Protocol for the top-level portfolio container.""" + + async def run(self) -> None: ... + + +class BasePortfolio(ABC): + """Abstract base for portfolio-level orchestrators. + + Subclasses implement on_candle_close() and compose PortfolioRunner, + ReconciliationManager, etc. in __init__. + + The full session lifecycle is managed here: + - SessionStartedEvent fires first (triggers strategy warmup and + startup reconciliation for any ReconciliationManager instances) + - SessionReadyEvent fires next (triggers post_warmup_check) + - Streaming begins + - SessionEndedEvent fires on exit + """ + + def __init__(self, client: Client) -> None: + self._client = client + self.last_update = datetime.now(timezone.utc) + self.subscriptions: list[MarketSubscription | ChartSubscription] = [] + self.watchdog_threshold: float = 60.0 + + @abstractmethod + async def on_candle_close(self, event: CandleClosedEvent) -> None: + """Process a completed candle. Subclasses delegate to PortfolioRunner or + individual strategy on_candle_close as appropriate.""" + ... + + async def on_price_update(self, data: MarketData) -> None: + """Handle a tick-level price update. Subclasses may override.""" + pass + + async def _handle_event(self, event: object) -> None: + """StreamConsumer interface — called by the streamer on each market event.""" + dispatcher = get_dispatcher() + if isinstance(event, CandleClosedEvent): + await dispatcher.publish(event) + await self.on_candle_close(event) + elif isinstance(event, MarketData): + await dispatcher.publish(MarketDataReceivedEvent(data=event)) + await self.on_price_update(event) + else: + raise TypeError(f"Unsupported event type: {type(event)!r}") + self.last_update = datetime.now(timezone.utc) + + async def run(self) -> None: + """Full lifecycle: wire services → startup events → stream → shutdown.""" + _order_handler = OrderExecutionHandler(self._client) # noqa: F841 + try: + await get_dispatcher().publish(SessionStartedEvent()) + await get_dispatcher().publish(SessionReadyEvent()) + await self._run_streaming() + finally: + await get_dispatcher().publish(SessionEndedEvent()) + + async def _run_streaming(self) -> None: + streamer = self._client.get_streamer() + if streamer is not None: + await streamer.run(self) + else: + log.info("No streamer available — polling mode") + await self._run_polling() + + async def _run_polling(self) -> None: + """Subclasses may override for polling fallback. Default waits forever.""" + await asyncio.Future() diff --git a/tradedesk/portfolio/config.py b/tradedesk/portfolio/config.py index 61ba587..8362f77 100644 --- a/tradedesk/portfolio/config.py +++ b/tradedesk/portfolio/config.py @@ -15,7 +15,7 @@ class PortfolioConfig: atr_risk_mult: float min_size: float max_size: float - base_period: str + base_period: str | None @dataclass(frozen=True) @@ -33,7 +33,7 @@ def from_raw( half_spread_adjustment: float, risk: dict[str, Any], sizing: dict[str, Any], - base_period: str, + base_period: str | None, ) -> BacktestPortfolioConfig: """Validate and construct from raw config dicts. diff --git a/tradedesk/portfolio/reconciliation.py b/tradedesk/portfolio/reconciliation.py index 3ca8c0d..a90126f 100644 --- a/tradedesk/portfolio/reconciliation.py +++ b/tradedesk/portfolio/reconciliation.py @@ -5,8 +5,8 @@ from enum import Enum from typing import Any, cast -from ..events import DomainEvent, get_dispatcher -from ..execution import BrokerPosition +from ..events import DomainEvent, SessionReadyEvent, SessionStartedEvent, get_dispatcher +from ..execution import BrokerPosition, OrderCompletedEvent from ..marketdata import CandleClosedEvent from ..types import Direction from .journal import JournalEntry, PositionJournal @@ -250,16 +250,29 @@ def __init__( self._candle_count: int = 0 self._recently_changed_instruments: set[str] = set() self._enable_event_subscription = enable_event_subscription + self._restored_instruments: set[str] = set() # Self-subscribe to events if enabled if enable_event_subscription: dispatcher = get_dispatcher() + dispatcher.subscribe(SessionStartedEvent, self._on_session_started) + dispatcher.subscribe(SessionReadyEvent, self._on_session_ready) dispatcher.subscribe(CandleClosedEvent, self._on_candle_closed) + dispatcher.subscribe(OrderCompletedEvent, self._on_order_completed) log.debug( - "ReconciliationManager subscribed to CandleClosedEvent (target_period=%s)", + "ReconciliationManager subscribed to session and candle events (target_period=%s)", target_period, ) + async def _on_session_started(self, event: SessionStartedEvent) -> None: + """Run startup reconciliation when the portfolio session begins.""" + self._restored_instruments = await self.reconcile_on_startup() + + async def _on_session_ready(self, event: SessionReadyEvent) -> None: + """Run post-warmup checks once warmup and reconciliation are complete.""" + if self._restored_instruments: + await self.post_warmup_check(self._restored_instruments) + async def _on_candle_closed(self, event: DomainEvent) -> None: """Handle target-period candle events for periodic reconciliation.""" if ( @@ -274,7 +287,6 @@ async def _on_candle_closed(self, event: DomainEvent) -> None: # Check if reconciliation needed if self._should_reconcile_now(): await self.periodic_reconcile() - await self.log_margin_status() def _should_reconcile_now(self) -> bool: """Internal check if reconciliation threshold reached (without incrementing).""" @@ -282,6 +294,9 @@ def _should_reconcile_now(self) -> bool: self._journal is not None and self._candle_count % self._reconcile_interval == 0 ) + + async def _on_order_completed(self, _event: OrderCompletedEvent) -> None: + await self.log_margin_status() # ------------------------------------------------------------------ # Startup reconciliation diff --git a/tradedesk/portfolio/simple.py b/tradedesk/portfolio/simple.py new file mode 100644 index 0000000..925baf9 --- /dev/null +++ b/tradedesk/portfolio/simple.py @@ -0,0 +1,34 @@ +"""Simple single-strategy portfolio with no risk allocation.""" + +from tradedesk.execution import Client +from tradedesk.marketdata import CandleClosedEvent, MarketData +from tradedesk.strategy import BaseStrategy + +from .base import BasePortfolio + + +class SimplePortfolio(BasePortfolio): + """Portfolio that wraps a single strategy with no risk allocation. + + The strategy handles its own warmup via SessionStartedEvent (subscribed in + BaseStrategy.__init__). The portfolio's sole job is to forward candle events. + + Example:: + + def portfolio_factory(client): + strategy = MyStrategy(client) + return SimplePortfolio(client, strategy) + + run_portfolio(portfolio_factory, client_factory) + """ + + def __init__(self, client: Client, strategy: BaseStrategy) -> None: + super().__init__(client) + self._strategy = strategy + self.subscriptions = strategy.subscriptions + + async def on_price_update(self, data: MarketData) -> None: + await self._strategy.on_price_update(data) + + async def on_candle_close(self, event: CandleClosedEvent) -> None: + await self._strategy.on_candle_close(event) diff --git a/tradedesk/portfolio/types.py b/tradedesk/portfolio/types.py index 65281a7..96cff4c 100644 --- a/tradedesk/portfolio/types.py +++ b/tradedesk/portfolio/types.py @@ -6,7 +6,7 @@ """ from dataclasses import dataclass -from typing import TYPE_CHECKING, Any, NewType, Protocol +from typing import TYPE_CHECKING, Any, Callable, NewType, Protocol if TYPE_CHECKING: from ..execution import PositionTracker @@ -35,7 +35,7 @@ class StrategySpec: instrument: str period: str - strategy_cls: type + strategy_cls: Callable[..., Any] kwargs: dict[str, Any] diff --git a/tradedesk/recording/ledger.py b/tradedesk/recording/ledger.py index 9f87e47..073feaa 100644 --- a/tradedesk/recording/ledger.py +++ b/tradedesk/recording/ledger.py @@ -6,7 +6,13 @@ from tradedesk.time_utils import parse_timestamp -from .metrics import round_trips_from_fills +from .excursions import CandleIndex, compute_excursions +from .metrics import ( + Metrics, + compute_metrics, + equity_rows_from_round_trips, + round_trips_from_fills, +) from .opportunity import OpportunityRecorder from .types import EquityRecord, RecordingMode, TradeRecord @@ -40,6 +46,7 @@ class TradeLedger: _open_positions: dict[str, dict[str, Any]] = field( default_factory=dict ) # Track positions for P&L calc + candle_indices: dict[str, CandleIndex] = field(default_factory=dict) _last_equity_date: str | None = None # Track last daily equity write (YYYY-MM-DD) def __post_init__(self) -> None: @@ -56,9 +63,9 @@ def write(self, out_dir: Path) -> None: out_dir.mkdir(parents=True, exist_ok=True) if self.mode == RecordingMode.BACKTEST: - # Backtest: write all 6 files self.write_trades_csv(out_dir / "trades.csv") self.write_round_trips_csv(out_dir / "round_trips.csv") + self.write_metrics_csv(out_dir / "metrics.csv") self.write_equity_csv(out_dir / "equity.csv") self.write_equity_daily_csv(out_dir / "equity_daily.csv") self.write_exposure_csv(out_dir / "exposure.csv") @@ -110,12 +117,15 @@ def write_trades_csv(self, path: Path) -> None: ) def write_round_trips_csv(self, path: Path) -> None: - """Write reconstructed round trips. + """Write reconstructed round trips with optional MFE/MAE excursions. This is derived from trades.csv fills using the same pairing logic as metrics. + When ``self.candle_indices`` contains a :class:`CandleIndex` for a trip's + instrument, MFE/MAE columns are populated; otherwise they are left blank. Output schema: - instrument,direction,entry_ts,exit_ts,entry_price,exit_price,size,pnl,hold_minutes,exit_reason + instrument,direction,entry_ts,exit_ts,entry_price,exit_price,size,pnl, + hold_minutes,exit_reason,mfe_points,mae_points,mfe_pnl,mae_pnl """ path.parent.mkdir(parents=True, exist_ok=True) @@ -147,6 +157,10 @@ def write_round_trips_csv(self, path: Path) -> None: "pnl", "hold_minutes", "exit_reason", + "mfe_points", + "mae_points", + "mfe_pnl", + "mae_pnl", ] ) @@ -159,6 +173,18 @@ def write_round_trips_csv(self, path: Path) -> None: except Exception: hold = "" + mfe_pts: float | str = "" + mae_pts: float | str = "" + mfe_pnl_val: float | str = "" + mae_pnl_val: float | str = "" + idx = self.candle_indices.get(t.instrument) + if idx is not None: + exc = compute_excursions(trip=t, idx=idx) + mfe_pts = round(exc.mfe_points, 2) + mae_pts = round(exc.mae_points, 2) + mfe_pnl_val = round(exc.mfe_pnl, 2) + mae_pnl_val = round(exc.mae_pnl, 2) + w.writerow( [ t.instrument, @@ -171,9 +197,87 @@ def write_round_trips_csv(self, path: Path) -> None: round(t.pnl, 2), hold, t.exit_reason or "", + mfe_pts, + mae_pts, + mfe_pnl_val, + mae_pnl_val, ] ) + def write_metrics_csv(self, path: Path) -> None: + """Write per-instrument and portfolio-aggregate performance metrics. + + Output schema: + instrument,fills,round_trips,final_equity,max_dd,win_rate,avg_win, + avg_loss,profit_factor,expectancy,avg_hold_min + """ + path.parent.mkdir(parents=True, exist_ok=True) + + equity_rows = [ + {"timestamp": e.timestamp, "equity": str(e.equity)} for e in self.equity + ] + trade_rows = trade_rows_from_trades(self.trades) + + m = compute_metrics( + equity_rows=equity_rows, trade_rows=trade_rows, reporting_scale=1.0 + ) + + # For BROKER mode, equity includes initial_balance; subtract to get PnL + portfolio_pnl = m.final_equity + if self.mode == RecordingMode.BROKER: + portfolio_pnl -= self.initial_balance + + header = [ + "instrument", + "fills", + "round_trips", + "final_equity", + "max_dd", + "win_rate", + "avg_win", + "avg_loss", + "profit_factor", + "expectancy", + "avg_hold_min", + ] + + def _metrics_row( + label: str, + met: Metrics, + pnl_override: float | None = None + ) -> list[object]: + return [ + label, + met.trades, + met.round_trips, + round(pnl_override if pnl_override is not None else met.final_equity, 2), + round(met.max_drawdown, 2), + round(met.win_rate, 2), + round(met.avg_win, 2), + round(met.avg_loss, 2), + round(met.profit_factor, 2), + round(met.expectancy, 2), + round(met.avg_hold_minutes, 2), + ] + + with path.open("w", newline="") as f: + w = csv.writer(f) + w.writerow(header) + w.writerow(_metrics_row("PORTFOLIO", m, pnl_override=portfolio_pnl)) + + # Per-instrument breakdown + instruments = sorted({t.instrument for t in self.trades}) + for inst in instruments: + inst_trades = [r for r in trade_rows if r["instrument"] == inst] + trips = round_trips_from_fills(inst_trades) + inst_equity = equity_rows_from_round_trips(trips, starting_equity=0.0) + inst_m = compute_metrics( + equity_rows=inst_equity, + trade_rows=inst_trades, + reporting_scale=1.0, + ) + w.writerow(_metrics_row(inst, inst_m)) + def write_equity_csv(self, path: Path) -> None: path.parent.mkdir(parents=True, exist_ok=True) with path.open("w", newline="") as f: diff --git a/tradedesk/recording/metrics.py b/tradedesk/recording/metrics.py index bc90670..d552c4b 100644 --- a/tradedesk/recording/metrics.py +++ b/tradedesk/recording/metrics.py @@ -37,7 +37,7 @@ class Metrics: expectancy: float max_drawdown: float final_equity: float - avg_hold_minutes: float | None + avg_hold_minutes: float exits_by_reason: dict[str, int] diff --git a/tradedesk/recording/report-template.j2 b/tradedesk/recording/report-template.j2 new file mode 100644 index 0000000..68ea09d --- /dev/null +++ b/tradedesk/recording/report-template.j2 @@ -0,0 +1,223 @@ +# Instrument Performance Analysis + +## 1. Overall Performance by Instrument + +| Instrument | Final PnL | Max DD | Win Rate | P.Factor | Trades | +|------------|-----------|--------|----------|----------|--------| +{% for m in portfolio_metrics -%} +| **{{ m.instrument }}** | {{ "%.2f"|format(m.final_equity|float) }} | {{ "%.2f"|format(m.max_dd|float) }} | {{ "%.1f"|format(m.win_rate|float * 100) }}% | {{ "%.2f"|format(m.profit_factor|float) }} | {{ m.round_trips }} | +{% endfor -%} +{% for m in instrument_metrics -%} +| {{ m.instrument }} | {{ "%.2f"|format(m.final_equity|float) }} | {{ "%.2f"|format(m.max_dd|float) }} | {{ "%.1f"|format(m.win_rate|float * 100) }}% | {{ "%.2f"|format(m.profit_factor|float) }} | {{ m.round_trips }} | +{% endfor %} + +## 2. Performance Statistics Across Instruments + +| Metric | Mean | Std | Min | Median | Max | +|--------|------|-----|-----|--------|-----| +{% for row in stats_table -%} +| {{ row.metric }} | {{ "%.2f"|format(row.mean) }} | {{ "%.2f"|format(row.std) }} | {{ "%.2f"|format(row.min) }} | {{ "%.2f"|format(row.median) }} | {{ "%.2f"|format(row.max) }} | +{% endfor %} + +**Coefficient of Variation (CV = std/mean):** + +{% for row in cv_data -%} +- {{ row.metric }}: {{ "%.2f"|format(row.cv) }}% +{% endfor %} + +## 3. Return Consistency Analysis + +*Consistency Rankings (lower CV = more consistent returns):* + +| Instrument | Mean PnL | Std PnL | CV% | Median | IQR | Outliers% | +|------------|----------|---------|-----|--------|-----|-----------| +{% for row in consistency_data -%} +| {{ row.instrument }} | {{ "%.2f"|format(row.mean_pnl) }} | {{ "%.2f"|format(row.std_pnl) }} | {{ "%.1f"|format(row.cv_pnl) }} | {{ "%.2f"|format(row.median_pnl) }} | {{ "%.2f"|format(row.iqr) }} | {{ "%.1f"|format(row.outlier_pct) }}% | +{% endfor %} + +## 4. Volatility Classification + +{% if volatility.median is defined %} +**Low Volatility (CV < {{ "%.1f"|format(volatility.median) }}%):** {{ volatility.low|join(', ') }} + +**High Volatility (CV >= {{ "%.1f"|format(volatility.median) }}%):** {{ volatility.high|join(', ') }} +{% endif %} + +## 5. Exposure Distribution + +| Instrument | Fills | Trades | Avg Hold | % of Trades | +|------------|-------|--------|----------|-------------| +{% for row in exposure_data -%} +| {{ row.instrument }} | {{ row.fills }} | {{ row.trades }} | {{ "%.1f"|format(row.avg_hold) }}m | {{ "%.1f"|format(row.pct_trades) }}% | +{% endfor %} + +## 6. Risk-Adjusted Performance + +| Instrument | Return/Risk | DD Ratio | PnL | Std | +|------------|-------------|----------|-----|-----| +{% for row in risk_adj_data -%} +| {{ row.instrument }} | {{ "%.2f"|format(row.return_per_risk) }} | {{ "%.2f"|format(row.dd_ratio) }} | {{ "%.2f"|format(row.final_equity) }} | {{ "%.2f"|format(row.std_pnl) }} | +{% endfor %} + +{% if similarity.matrix_rows %} +## 7. Performance Profile Comparison + +*Performance Profile Similarity (Euclidean Distance):* +Lower values = more similar performance profiles + +{% if similarity.min_pair %} +**Most Similar Pair:** {{ similarity.min_pair[0] }} ↔ {{ similarity.min_pair[1] }} ({{ "%.2f"|format(similarity.min_dist) }}) +{% endif %} + +{% if similarity.max_pair %} +**Most Different Pair:** {{ similarity.max_pair[0] }} ↔ {{ similarity.max_pair[1] }} ({{ "%.2f"|format(similarity.max_dist) }}) +{% endif %} + +### Similarity Matrix + +| | {{ similarity.matrix_headers|join(' | ') }} | +|{{ (similarity.matrix_headers|length + 1) * "---|" }} +{% for row in similarity.matrix_rows -%} +| {{ row.instrument }} | {{ row.dists|join(' | ') }} | +{% endfor %} +{% endif %} + +## 8. Time-Based Performance Evolution + +{% for row in evolution_data -%} +### {{ row.instrument }} + +- Final Cumulative PnL: **{{ "%.2f"|format(row.final_pnl) }}** +- Peak PnL: **{{ "%.2f"|format(row.peak_pnl) }}** +- Max Drawdown: **{{ "%.2f"|format(row.max_dd) }}** +- Trades in Drawdown: **{{ row.dd_count }}** ({{ "%.1f"|format(row.dd_pct) }}%) + +{% endfor %} + +## 9. Key Insights + +### Performance Dispersion + +- Best performer: **{{ insights.best.instrument }}** ({{ "%.2f"|format(insights.best.val) }}) +- Worst performer: **{{ insights.worst.instrument }}** ({{ "%.2f"|format(insights.worst.val) }}) +- Range: **{{ "%.2f"|format(insights.range) }}** +- CV: **{{ "%.2f"|format(insights.cv) }}%** + +{% if insights.consistent %} +### Return Consistency + +- Most consistent: **{{ insights.consistent.most.instrument }}** (CV: {{ "%.2f"|format(insights.consistent.most.cv) }}%) +- Least consistent: **{{ insights.consistent.least.instrument }}** (CV: {{ "%.2f"|format(insights.consistent.least.cv) }}%) +{% endif %} + +{% if insights.risk %} +### Risk-Adjusted Performance + +- Best return/risk: **{{ insights.risk.best_return.instrument }}** ({{ "%.2f"|format(insights.risk.best_return.val) }}) +- Best recovery ratio: **{{ insights.risk.best_recovery.instrument }}** ({{ "%.2f"|format(insights.risk.best_recovery.val) }}) +{% endif %} + +### Exposure Distribution + +- Most traded: **{{ insights.exposure.most.instrument }}** ({{ insights.exposure.most.count }} round trips, {{ "%.1f"|format(insights.exposure.most.pct) }}%) +- Least traded: **{{ insights.exposure.least.instrument }}** ({{ insights.exposure.least.count }} round trips, {{ "%.1f"|format(insights.exposure.least.pct) }}%) +- Exposure concentration (CV): **{{ "%.2f"|format(insights.exposure.cv) }}%** + +--- + +# Additional Temporal and Win/Loss Analysis + +## 1. Win/Loss Pattern Analysis + +| Instrument | Wins | Losses | Win% | Avg Win | Avg Loss | Win/Loss | +|------------|------|--------|------|---------|----------|----------| +{% for row in win_loss_data -%} +| {{ row.instrument }} | {{ row.wins }} | {{ row.losses }} | {{ "%.1f"|format(row.win_pct) }}% | {{ "%.2f"|format(row.avg_win) }} | {{ "%.2f"|format(row.avg_loss) }} | {{ "%.2f"|format(row.ratio) }} | +{% endfor %} + +## 2. Winning/Losing Streak Analysis + +| Instrument | Max Win Streak | Max Loss Streak | Current | +|------------|----------------|-----------------|---------| +{% for row in streak_data -%} +| {{ row.instrument }} | {{ row.max_win }} | {{ row.max_loss }} | {{ row.current }} | +{% endfor %} + +## 3. Monthly Performance Breakdown + +| Month | {{ monthly_data.headers|join(' | ') }} | Total | +|-------|{{ monthly_data.headers|length * "------|" }}------| +{% for row in monthly_data.rows -%} +| {{ row.month }} | {{ row.values|join(' | ') }} | {{ "%.2f"|format(row.total) }} | +{% endfor -%} +| **Total** | {{ monthly_data.totals.values|join(' | ') }} | **{{ "%.2f"|format(monthly_data.totals.grand) }}** | + +## 4. Hold Time Analysis + +| Instrument | Avg Hold | Min Hold | Max Hold | Std Hold | +|------------|----------|----------|----------|----------| +{% for row in hold_time_data -%} +| {{ row.instrument }} | {{ "%.1f"|format(row.avg) }}m | {{ "%.1f"|format(row.min) }}m | {{ "%.1f"|format(row.max) }}m | {{ "%.1f"|format(row.std) }}m | +{% endfor %} + +## 5. Best and Worst Trades per Instrument + +{% for row in best_worst_trades -%} +### {{ row.instrument }} + +**Best Trade:** PnL={{ "%.2f"|format(row.best.pnl) }}, Entry={{ row.best.entry_ts[:10] }}, Hold={{ "%.0f"|format(row.best.hold_minutes) }}m, Direction={{ row.best.direction }} + +**Worst Trade:** PnL={{ "%.2f"|format(row.worst.pnl) }}, Entry={{ row.worst.entry_ts[:10] }}, Hold={{ "%.0f"|format(row.worst.hold_minutes) }}m, Direction={{ row.worst.direction }} + +{% endfor %} + +## 6. Maximum Favorable/Adverse Excursion (MFE/MAE) Analysis + +{% if mfe_mae_data %} +| Instrument | Avg MFE | Avg MAE | MFE/PnL | MAE/PnL | +|------------|---------|---------|---------|---------| +{% for row in mfe_mae_data -%} +| {{ row.instrument }} | {{ "%.2f"|format(row.avg_mfe) }} | {{ "%.2f"|format(row.avg_mae) }} | {{ "%.2f"|format(row.mfe_ratio) }} | {{ "%.2f"|format(row.mae_ratio) }} | +{% endfor %} + +*Note: MFE/PnL ratio shows potential capture (higher = better)* + +*MAE/PnL ratio shows adverse risk (lower abs value = better)* +{% else %} +*(MFE/MAE data not available -- candle index was not provided)* +{% endif %} + +## 7. Long vs Short Performance + +| Instrument | Long Cnt | Short Cnt | Long PnL | Short PnL | Bias | +|------------|----------|-----------|----------|-----------|------| +{% for row in long_short_data -%} +| {{ row.instrument }} | {{ row.long_cnt }} | {{ row.short_cnt }} | {{ "%.2f"|format(row.long_pnl) }} | {{ "%.2f"|format(row.short_pnl) }} | {{ row.bias }} | +{% endfor %} + +## 8. Exit Reason Breakdown + +{% if not exit_reasons.available %} +*(exit_reason not available — backtest predates exit_reason propagation)* +{% else %} +### Portfolio Exit Reason Summary + +| Exit Reason | Count | % | Total PnL | Avg PnL | Win% | +|-------------|-------|---|-----------|---------|------| +{% for row in exit_reasons.portfolio -%} +| {{ row.reason }} | {{ row.count }} | {{ "%.1f"|format(row.pct) }}% | {{ "%.2f"|format(row.total_pnl) }} | {{ "%.2f"|format(row.avg_pnl) }} | {{ "%.1f"|format(row.win_rate) }}% | +{% endfor %} + +### Exit Reasons by Instrument + +{% for inst in exit_reasons.instruments -%} +#### {{ inst.short_name }} + +| Exit Reason | Count | % | Total PnL | Avg PnL | Win% | +|-------------|-------|---|-----------|---------|------| +{% for row in inst.rows -%} +| {{ row.reason }} | {{ row.count }} | {{ "%.1f"|format(row.pct) }}% | {{ "%.2f"|format(row.total_pnl) }} | {{ "%.2f"|format(row.avg_pnl) }} | {{ "%.1f"|format(row.win_rate) }}% | +{% endfor %} + +{% endfor %} +{% endif %} diff --git a/tradedesk/recording/report.py b/tradedesk/recording/report.py new file mode 100644 index 0000000..d0ace83 --- /dev/null +++ b/tradedesk/recording/report.py @@ -0,0 +1,762 @@ +"""Performance analysis report generation for backtest results using Jinja2 templates.""" + +import csv +import math +from collections import defaultdict +from datetime import datetime +from pathlib import Path +from types import SimpleNamespace +from typing import Any + +from jinja2 import Environment, FileSystemLoader + + +def calc_stats(values: list[float]) -> dict[str, float]: + """Calculate summary statistics for a list of values.""" + n = len(values) + if n == 0: + return { + "count": 0, + "mean": 0.0, + "std": 0.0, + "min": 0.0, + "p25": 0.0, + "median": 0.0, + "p75": 0.0, + "max": 0.0, + } + + mean_val = sum(values) / n + variance = sum((x - mean_val) ** 2 for x in values) / n + std_dev = math.sqrt(variance) + sorted_vals = sorted(values) + + return { + "count": n, + "mean": mean_val, + "std": std_dev, + "min": sorted_vals[0], + "p25": sorted_vals[n // 4], + "median": sorted_vals[n // 2], + "p75": sorted_vals[3 * n // 4], + "max": sorted_vals[-1], + } + + +def standardize(values: list[float]) -> list[float]: + """Standardize values using z-score normalization.""" + if not values: + return [] + mean_val = sum(values) / len(values) + variance = sum((x - mean_val) ** 2 for x in values) / len(values) + std_dev = math.sqrt(variance) + return [(x - mean_val) / std_dev if std_dev > 0 else 0 for x in values] + + +def euclidean_distance( + p1: dict[str, float], p2: dict[str, float], metric_keys: list[str] +) -> float: + """Calculate Euclidean distance between two performance profiles.""" + z_keys = [f"{key}_z" for key in metric_keys] + return math.sqrt( + sum((p1[zk] - p2[zk]) ** 2 for zk in z_keys if zk in p1 and zk in p2) + ) + + +def _read_csv(path: Path) -> list[dict[str, str]]: + with open(path, "r") as f: + reader = csv.DictReader(f) + return list(reader) + + +def _ensure_instrument_field(rows: list[dict[str, str]]) -> None: + """Ensure each row has an 'instrument' key (backcompat with old CSVs using 'epic').""" + for r in rows: + if "epic" in r and "instrument" not in r: + r["instrument"] = r["epic"] + + +def _prepare_overall_performance( + metrics: list[dict[str, str]], +) -> tuple[list[dict[str, str]], list[dict[str, str]], list[dict[str, str]]]: + portfolio_metrics = [m for m in metrics if m.get("instrument") == "PORTFOLIO"] + instrument_metrics = [m for m in metrics if m.get("instrument") != "PORTFOLIO"] + sorted_instruments = sorted( + instrument_metrics, + key=lambda x: float(x.get("final_equity", 0)), + reverse=True, + ) + return portfolio_metrics, instrument_metrics, sorted_instruments + + +def _prepare_stats_table( + metrics: list[dict[str, str]], +) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]: + metrics_cols = { + "final_equity": [float(m.get("final_equity", 0)) for m in metrics], + "max_dd": [float(m.get("max_dd", 0)) for m in metrics], + "win_rate": [float(m.get("win_rate", 0)) for m in metrics], + "profit_factor": [float(m.get("profit_factor", 0)) for m in metrics], + "expectancy": [float(m.get("expectancy", 0)) for m in metrics], + } + + stats_table = [] + cv_data = [] + for col, values in metrics_cols.items(): + stats = calc_stats(values) + stats_table.append({"metric": col, **stats}) + cv = (stats["std"] / abs(stats["mean"])) * 100 if stats["mean"] != 0 else 0 + cv_data.append({"metric": col, "cv": cv}) + return stats_table, cv_data + + +def _prepare_consistency_data(round_trips: list[dict[str, str]]) -> list[dict[str, Any]]: + inst_pnls: defaultdict[str, list[float]] = defaultdict(list) + for rt in round_trips: + inst_pnls[rt["instrument"]].append(float(rt["pnl"])) + + consistency_data: list[dict[str, Any]] = [] + for inst, pnls in inst_pnls.items(): + pnl_stats = calc_stats(pnls) + cv_pnl = (pnl_stats["std"] / pnl_stats["mean"] * 100) if pnl_stats["mean"] != 0 else 0 + iqr = pnl_stats["p75"] - pnl_stats["p25"] + lower_bound = pnl_stats["p25"] - 1.5 * iqr + upper_bound = pnl_stats["p75"] + 1.5 * iqr + outliers = sum(1 for p in pnls if p < lower_bound or p > upper_bound) + outlier_pct = (outliers / len(pnls)) * 100 + + consistency_data.append( + { + "instrument": inst, + "mean_pnl": pnl_stats["mean"], + "std_pnl": pnl_stats["std"], + "cv_pnl": cv_pnl, + "median_pnl": pnl_stats["median"], + "iqr": iqr, + "outlier_pct": outlier_pct, + } + ) + consistency_data.sort(key=lambda x: float(x["cv_pnl"])) + return consistency_data + + +def _classify_volatility(consistency_data: list[dict[str, Any]]) -> dict[str, Any]: + volatility: dict[str, Any] = {} + cv_values = [float(cd["cv_pnl"]) for cd in consistency_data] + if cv_values: + cv_median = sorted(cv_values)[len(cv_values) // 2] + low_vol = [ + str(cd["instrument"]) for cd in consistency_data if float(cd["cv_pnl"]) < cv_median + ] + high_vol = [ + str(cd["instrument"]) for cd in consistency_data if float(cd["cv_pnl"]) >= cv_median + ] + volatility = {"median": cv_median, "low": low_vol, "high": high_vol} + return volatility + + +def _prepare_exposure_data(metrics: list[dict[str, str]]) -> tuple[list[dict[str, Any]], int]: + total_round_trips = sum(int(m.get("round_trips", 0)) for m in metrics) + exposure_data = [] + for m in sorted( + metrics, key=lambda x: int(x.get("round_trips", 0)), reverse=True + ): + pct_trades = ( + (int(m.get("round_trips", 0)) / total_round_trips) * 100 + ) if total_round_trips else 0 + exposure_data.append( + { + "instrument": m.get("instrument"), + "fills": int(m.get("fills", 0)), + "trades": int(m.get("round_trips", 0)), + "avg_hold": float(m.get("avg_hold_min", 0)), + "pct_trades": pct_trades, + } + ) + return exposure_data, total_round_trips + + +def _prepare_risk_adj_data( + metrics: list[dict[str, str]], consistency_data: list[dict[str, Any]] +) -> list[dict[str, Any]]: + risk_adj_data: list[dict[str, Any]] = [] + for m in metrics: + inst = m.get("instrument") + cd = next((c for c in consistency_data if c["instrument"] == inst), None) + if cd: + return_per_risk = ( + float(m.get("final_equity", 0)) / float(cd["std_pnl"]) + ) if float(cd["std_pnl"]) > 0 else 0 + dd_ratio = ( + float(m.get("final_equity", 0)) / abs(float(m.get("max_dd", 0))) + ) if float(m.get("max_dd", 0)) != 0 else 0 + risk_adj_data.append( + { + "instrument": inst, + "final_equity": float(m.get("final_equity", 0)), + "max_dd": float(m.get("max_dd", 0)), + "std_pnl": cd["std_pnl"], + "return_per_risk": return_per_risk, + "dd_ratio": dd_ratio, + } + ) + risk_adj_data.sort(key=lambda x: x["return_per_risk"], reverse=True) + return risk_adj_data + + +def _prepare_similarity( + metrics: list[dict[str, str]], consistency_data: list[dict[str, Any]] +) -> dict[str, Any]: + similarity: dict[str, Any] = {} + if len(consistency_data) < 2: + return similarity + + profile_metrics: dict[str, dict[str, Any]] = {} + for m in metrics: + inst = m.get("instrument") + cd = next((c for c in consistency_data if c["instrument"] == inst), None) + if cd is None or inst is None: + continue + profile_metrics[inst] = { + "final_equity": float(m.get("final_equity", 0)), + "win_rate": float(m.get("win_rate", 0)), + "profit_factor": float(m.get("profit_factor", 0)), + "expectancy": float(m.get("expectancy", 0)), + "cv_pnl": cd["cv_pnl"], + } + + metric_keys = ["final_equity", "win_rate", "profit_factor", "expectancy", "cv_pnl"] + instruments = list(profile_metrics.keys()) + + for key in metric_keys: + values = [profile_metrics[inst][key] for inst in instruments] + standardized = standardize(values) + for i, inst in enumerate(instruments): + profile_metrics[inst][f"{key}_z"] = standardized[i] + + if len(instruments) < 2: + return similarity + + min_dist = float("inf") + max_dist = 0.0 + min_pair = None + max_pair = None + + for i, inst1 in enumerate(instruments): + for inst2 in instruments[i + 1 :]: + dist = euclidean_distance( + profile_metrics[inst1], profile_metrics[inst2], metric_keys + ) + if dist < min_dist: + min_dist = dist + min_pair = (inst1, inst2) + if dist > max_dist: + max_dist = dist + max_pair = (inst1, inst2) + + matrix_headers = [ + inst.split(".")[2] if "." in inst else inst for inst in instruments + ] + matrix_rows: list[dict[str, Any]] = [] + for inst1 in instruments: + dists: list[str] = [] + for inst2 in instruments: + dist = ( + euclidean_distance( + profile_metrics[inst1], profile_metrics[inst2], metric_keys + ) + if inst1 != inst2 + else 0 + ) + dists.append(f"{dist:.2f}") + matrix_rows.append( + { + "instrument": inst1.split(".")[2] if "." in inst1 else inst1, + "dists": dists, + } + ) + + similarity = { + "min_pair": min_pair, + "min_dist": min_dist, + "max_pair": max_pair, + "max_dist": max_dist, + "matrix_headers": matrix_headers, + "matrix_rows": matrix_rows, + } + return similarity + + +def _build_instrument_data( + round_trips: list[dict[str, str]], +) -> dict[str, list[dict[str, str]]]: + inst_data: defaultdict[str, list[dict[str, str]]] = defaultdict(list) + for rt in round_trips: + inst_data[rt["instrument"]].append(rt) + return dict(inst_data) + + +def _prepare_evolution_data( + inst_data: dict[str, list[dict[str, str]]], +) -> list[dict[str, Any]]: + evolution_data = [] + for inst in sorted(inst_data.keys()): + inst_trips = [ + (datetime.fromisoformat(rt["exit_ts"].replace("Z", "+00:00")), float(rt["pnl"])) + for rt in inst_data[inst] + ] + inst_trips.sort() + if not inst_trips: + continue + + cum_pnl = [] + running_total = 0.0 + for _, pnl in inst_trips: + running_total += pnl + cum_pnl.append(running_total) + + running_max = [] + max_so_far = cum_pnl[0] + for pnl in cum_pnl: + max_so_far = max(max_so_far, pnl) + running_max.append(max_so_far) + + drawdowns = [cum - mx for cum, mx in zip(cum_pnl, running_max)] + max_dd = min(drawdowns) + in_drawdown = sum(1 for dd in drawdowns if dd < 0) + + evolution_data.append({ + "instrument": inst, + "final_pnl": cum_pnl[-1], + "peak_pnl": max(running_max), + "max_dd": max_dd, + "dd_count": in_drawdown, + "dd_pct": (in_drawdown / len(inst_trips) * 100), + }) + return evolution_data + + +def _prepare_insights( + metrics: list[dict[str, str]], + consistency_data: list[dict[str, Any]], + risk_adj_data: list[dict[str, Any]], + total_round_trips: int, +) -> dict[str, Any]: + insights: dict[str, Any] = {} + final_equities = [float(m.get("final_equity", 0)) for m in metrics] + if not final_equities: + return insights + + best_idx = final_equities.index(max(final_equities)) + worst_idx = final_equities.index(min(final_equities)) + equity_range = max(final_equities) - min(final_equities) + equity_stats = calc_stats(final_equities) + equity_cv = ( + (equity_stats["std"] / equity_stats["mean"]) * 100 + ) if equity_stats["mean"] != 0 else 0 + + insights = { + "best": { + "instrument": metrics[best_idx]["instrument"], + "val": final_equities[best_idx], + }, + "worst": { + "instrument": metrics[worst_idx]["instrument"], + "val": final_equities[worst_idx], + }, + "range": equity_range, + "cv": equity_cv, + } + + if consistency_data: + most_consistent = min(consistency_data, key=lambda x: abs(float(x["cv_pnl"]))) + least_consistent = max(consistency_data, key=lambda x: abs(float(x["cv_pnl"]))) + insights["consistent"] = { + "most": { + "instrument": most_consistent["instrument"], + "cv": most_consistent["cv_pnl"], + }, + "least": { + "instrument": least_consistent["instrument"], + "cv": least_consistent["cv_pnl"], + }, + } + + if risk_adj_data: + best_risk_adj = max(risk_adj_data, key=lambda x: x["return_per_risk"]) + best_dd_ratio = max(risk_adj_data, key=lambda x: x["dd_ratio"]) + insights["risk"] = { + "best_return": { + "instrument": best_risk_adj["instrument"], + "val": best_risk_adj["return_per_risk"], + }, + "best_recovery": { + "instrument": best_dd_ratio["instrument"], + "val": best_dd_ratio["dd_ratio"], + }, + } + + max_trades = max(metrics, key=lambda x: int(x.get("round_trips", 0))) + min_trades = min(metrics, key=lambda x: int(x.get("round_trips", 0))) + max_pct = ( + (int(max_trades.get("round_trips", 0)) / total_round_trips) * 100 + ) if total_round_trips else 0 + min_pct = ( + (int(min_trades.get("round_trips", 0)) / total_round_trips) * 100 + ) if total_round_trips else 0 + trade_pcts = [ + (int(m.get("round_trips", 0)) / total_round_trips * 100) if total_round_trips else 0 + for m in metrics + ] + exposure_stats = calc_stats(trade_pcts) + exposure_cv = ( + (exposure_stats["std"] / exposure_stats["mean"]) * 100 + ) if exposure_stats["mean"] != 0 else 0 + insights["exposure"] = { + "most": { + "instrument": max_trades["instrument"], + "count": max_trades["round_trips"], + "pct": max_pct, + }, + "least": { + "instrument": min_trades["instrument"], + "count": min_trades["round_trips"], + "pct": min_pct, + }, + "cv": exposure_cv, + } + + return insights + + +def _prepare_additional_analysis( + inst_data: dict[str, list[dict[str, str]]], + round_trips: list[dict[str, str]], +) -> tuple[ + list[dict[str, Any]], + list[dict[str, Any]], + list[dict[str, Any]], + list[dict[str, Any]], + list[dict[str, Any]], + list[dict[str, Any]], +]: + win_loss_data = [] + streak_data = [] + hold_time_data = [] + best_worst_trades = [] + mfe_mae_data = [] + long_short_data = [] + + for inst in sorted(inst_data.keys()): + trips = inst_data[inst] + wins = [float(rt["pnl"]) for rt in trips if float(rt["pnl"]) > 0] + losses = [float(rt["pnl"]) for rt in trips if float(rt["pnl"]) < 0] + + avg_win = sum(wins) / len(wins) if wins else 0 + avg_loss = sum(losses) / len(losses) if losses else 0 + win_loss_ratio = avg_win / abs(avg_loss) if avg_loss != 0 else 0 + win_loss_data.append( + { + "instrument": inst, + "wins": len(wins), + "losses": len(losses), + "win_pct": (len(wins) / len(trips)) * 100 if trips else 0, + "avg_win": avg_win, + "avg_loss": avg_loss, + "ratio": win_loss_ratio, + } + ) + + trips_sorted = sorted( + trips, key=lambda x: datetime.fromisoformat(x["exit_ts"].replace("Z", "+00:00")) + ) + max_win_streak = max_loss_streak = current_win_streak = current_loss_streak = 0 + for rt in trips_sorted: + pnl = float(rt["pnl"]) + if pnl > 0: + current_win_streak += 1 + current_loss_streak = 0 + max_win_streak = max(max_win_streak, current_win_streak) + else: + current_loss_streak += 1 + current_win_streak = 0 + max_loss_streak = max(max_loss_streak, current_loss_streak) + last_pnl = float(trips_sorted[-1]["pnl"]) if trips_sorted else 0 + current_state = (f"W:{current_win_streak}" if last_pnl > 0 else f"L:{current_loss_streak}") + streak_data.append( + { + "instrument": inst, + "max_win": max_win_streak, + "max_loss": max_loss_streak, + "current": current_state, + } + ) + + hold_times = [float(rt.get("hold_minutes", 0)) for rt in trips] + avg_hold = sum(hold_times) / len(hold_times) if hold_times else 0 + variance = ( + sum((x - avg_hold) ** 2 for x in hold_times) / len(hold_times) + ) if hold_times else 0 + hold_time_data.append( + { + "instrument": inst, + "avg": avg_hold, + "min": min(hold_times) if hold_times else 0, + "max": max(hold_times) if hold_times else 0, + "std": variance ** 0.5, + } + ) + + best = max(trips, key=lambda x: float(x["pnl"])) + worst = min(trips, key=lambda x: float(x["pnl"])) + best_worst_trades.append( + { + "instrument": inst, + "best": { + "pnl": float(best["pnl"]), + "entry_ts": best["entry_ts"], + "hold_minutes": float(best["hold_minutes"]), + "direction": best["direction"], + }, + "worst": { + "pnl": float(worst["pnl"]), + "entry_ts": worst["entry_ts"], + "hold_minutes": float(worst["hold_minutes"]), + "direction": worst["direction"], + }, + } + ) + + trips_with_mfe = [rt for rt in trips if rt.get("mfe_pnl", "") not in ("", None)] + if trips_with_mfe: + total_mfe_pnl = sum(float(rt["mfe_pnl"]) for rt in trips_with_mfe) + total_mae_pnl = sum(float(rt["mae_pnl"]) for rt in trips_with_mfe) + total_pnl = sum(float(rt["pnl"]) for rt in trips) + mfe_mae_data.append( + { + "instrument": inst, + "avg_mfe": total_mfe_pnl / len(trips), + "avg_mae": total_mae_pnl / len(trips), + "mfe_ratio": total_mfe_pnl / total_pnl if total_pnl != 0 else 0, + "mae_ratio": total_mae_pnl / total_pnl if total_pnl != 0 else 0, + } + ) + + long_trades = [rt for rt in trips if rt.get("direction", "").lower() == "long"] + short_trades = [rt for rt in trips if rt.get("direction", "").lower() == "short"] + long_pnl = sum(float(rt["pnl"]) for rt in long_trades) + short_pnl = sum(float(rt["pnl"]) for rt in short_trades) + if long_pnl + short_pnl != 0: + long_bias = (long_pnl / (long_pnl + short_pnl)) * 100 + else: + long_bias = 50 + bias_str = ( + f"L{long_bias:.0f}%" + if long_bias > 55 + else (f"S{100 - long_bias:.0f}%" if long_bias < 45 else "Neutral") + ) + long_short_data.append( + { + "instrument": inst, + "long_cnt": len(long_trades), + "short_cnt": len(short_trades), + "long_pnl": long_pnl, + "short_pnl": short_pnl, + "bias": bias_str, + } + ) + + return ( + win_loss_data, + streak_data, + hold_time_data, + best_worst_trades, + mfe_mae_data, + long_short_data, + ) + + +def _prepare_monthly_data( + round_trips: list[dict[str, str]], + inst_data: dict[str, list[dict[str, str]]], +) -> SimpleNamespace: + monthly_pnl: defaultdict[str, defaultdict[str, float]] = defaultdict( + lambda: defaultdict(float) + ) + for rt in round_trips: + exit_dt = datetime.fromisoformat(rt["exit_ts"].replace("Z", "+00:00")) + month_key = exit_dt.strftime("%Y-%m") + monthly_pnl[month_key][rt["instrument"]] += float(rt["pnl"]) + + months = sorted(monthly_pnl.keys()) + instruments = sorted(inst_data.keys()) + short_names = { + inst: inst.split(".")[2] if "." in inst else inst for inst in instruments + } + monthly_rows = [] + grand_total = 0.0 + inst_totals: defaultdict[str, float] = defaultdict(float) + + for month in months: + values = [] + month_total = 0.0 + for inst in instruments: + pnl = monthly_pnl[month].get(inst, 0) + values.append(f"{pnl:.2f}") + month_total += pnl + inst_totals[inst] += pnl + monthly_rows.append(SimpleNamespace(month=month, values=values, total=month_total)) + grand_total += month_total + + monthly_data = SimpleNamespace( + headers=[short_names[inst] for inst in instruments], + rows=monthly_rows, + totals=SimpleNamespace( + values=[f"**{inst_totals[inst]:.2f}**" for inst in instruments], grand=grand_total + ), + ) + return monthly_data + + +def _prepare_exit_reasons( + round_trips: list[dict[str, str]], + inst_data: dict[str, list[dict[str, str]]], +) -> dict[str, Any]: + has_exit_reasons = any( + rt.get("exit_reason", "") not in ("", "market_order") for rt in round_trips + ) + exit_reasons: dict[str, Any] = { + "available": has_exit_reasons, + "portfolio": [], + "instruments": [], + } + if not has_exit_reasons: + return exit_reasons + + reason_stats: dict[str, dict[str, Any]] = defaultdict( + lambda: {"count": 0, "total_pnl": 0.0, "wins": 0} + ) + for rt in round_trips: + reason = rt.get("exit_reason", "unknown") or "unknown" + pnl = float(rt["pnl"]) + reason_stats[reason]["count"] += 1 + reason_stats[reason]["total_pnl"] += pnl + if pnl > 0: + reason_stats[reason]["wins"] += 1 + + total_count = sum(v["count"] for v in reason_stats.values()) + + def reason_key(r: str) -> float: + return float(reason_stats[r]["total_pnl"]) + + for reason in sorted(reason_stats, key=reason_key, reverse=True): + s = reason_stats[reason] + exit_reasons["portfolio"].append( + { + "reason": reason, + "count": s["count"], + "pct": (s["count"] / total_count) * 100 if total_count else 0, + "total_pnl": s["total_pnl"], + "avg_pnl": s["total_pnl"] / s["count"] if s["count"] else 0, + "win_rate": (s["wins"] / s["count"]) * 100 if s["count"] else 0, + } + ) + + for inst in sorted(inst_data.keys()): + inst_reasons: dict[str, dict[str, Any]] = defaultdict( + lambda: {"count": 0, "total_pnl": 0.0, "wins": 0} + ) + trips = inst_data[inst] + for rt in trips: + reason = rt.get("exit_reason", "unknown") or "unknown" + pnl = float(rt["pnl"]) + inst_reasons[reason]["count"] += 1 + inst_reasons[reason]["total_pnl"] += pnl + if pnl > 0: + inst_reasons[reason]["wins"] += 1 + + inst_total = sum(v["count"] for v in inst_reasons.values()) + inst_rows = [] + + def inst_key(r: str) -> float: + return float(inst_reasons[r]["total_pnl"]) + + for reason in sorted(inst_reasons, key=inst_key, reverse=True): + s = inst_reasons[reason] + inst_rows.append( + { + "reason": reason, + "count": s["count"], + "pct": (s["count"] / inst_total) * 100 if inst_total else 0, + "total_pnl": s["total_pnl"], + "avg_pnl": s["total_pnl"] / s["count"] if s["count"] else 0, + "win_rate": (s["wins"] / s["count"]) * 100 if s["count"] else 0, + } + ) + exit_reasons["instruments"].append( + {"short_name": inst.split(".")[2] if "." in inst else inst, "rows": inst_rows} + ) + + return exit_reasons + + +def generate_analysis_report(output_dir: str | Path) -> None: + output_path = Path(output_dir) + metrics_file = output_path / "metrics.csv" + round_trips_file = output_path / "round_trips.csv" + report_file = output_path / "analysis.md" + template_file = "report-template.j2" + + metrics = _read_csv(metrics_file) + _ensure_instrument_field(metrics) + round_trips = _read_csv(round_trips_file) + _ensure_instrument_field(round_trips) + + portfolio_metrics, instrument_metrics, sorted_instruments = ( + _prepare_overall_performance(metrics) + ) + stats_table, cv_data = _prepare_stats_table(metrics) + consistency_data = _prepare_consistency_data(round_trips) + volatility = _classify_volatility(consistency_data) + exposure_data, total_round_trips = _prepare_exposure_data(metrics) + risk_adj_data = _prepare_risk_adj_data(metrics, consistency_data) + similarity = _prepare_similarity(metrics, consistency_data) + inst_data = _build_instrument_data(round_trips) + evolution_data = _prepare_evolution_data(inst_data) + insights = _prepare_insights( + metrics, consistency_data, risk_adj_data, total_round_trips + ) + win_loss_data, streak_data, hold_time_data, best_worst_trades, mfe_mae_data, long_short_data = ( + _prepare_additional_analysis(inst_data, round_trips) + ) + monthly_data = _prepare_monthly_data(round_trips, inst_data) + exit_reasons = _prepare_exit_reasons(round_trips, inst_data) + + context = { + "portfolio_metrics": portfolio_metrics, + "instrument_metrics": sorted_instruments, + "stats_table": stats_table, + "cv_data": cv_data, + "consistency_data": consistency_data, + "volatility": volatility, + "exposure_data": exposure_data, + "risk_adj_data": risk_adj_data, + "similarity": similarity, + "evolution_data": evolution_data, + "insights": insights, + "win_loss_data": win_loss_data, + "streak_data": streak_data, + "monthly_data": monthly_data, + "hold_time_data": hold_time_data, + "best_worst_trades": best_worst_trades, + "mfe_mae_data": mfe_mae_data, + "long_short_data": long_short_data, + "exit_reasons": exit_reasons, + } + + env = Environment(loader=FileSystemLoader(str(Path(__file__).parent))) + template = env.get_template(template_file) + rendered = template.render(**context) + + with open(report_file, "w") as f: + f.write(rendered) diff --git a/tradedesk/recording/subscriber.py b/tradedesk/recording/subscriber.py index 0a6d439..db9b5b0 100644 --- a/tradedesk/recording/subscriber.py +++ b/tradedesk/recording/subscriber.py @@ -96,6 +96,16 @@ async def handle_session_ended(self, event: SessionEndedEvent) -> None: else: log.info("No trades recorded in session") + # Generate analysis report if we have an output directory and trades + if self._run_output_dir is not None and self.ledger.trades: + try: + from .report import generate_analysis_report + + generate_analysis_report(self._run_output_dir) + log.info(f"Analysis report written to {self._run_output_dir / 'analysis.md'}") + except Exception: + log.exception("Failed to generate analysis report") + # Emit completion event await get_dispatcher().publish(ReportingCompleteEvent()) diff --git a/tradedesk/runner.py b/tradedesk/runner.py index 945476b..2665c9a 100644 --- a/tradedesk/runner.py +++ b/tradedesk/runner.py @@ -1,15 +1,14 @@ """ -Strategy orchestration and execution. +Portfolio orchestration and execution. """ import asyncio import logging import sys from collections.abc import Callable -from typing import Any -from tradedesk.execution import Client, OrderExecutionHandler -from tradedesk.strategy import BaseStrategy +from tradedesk.execution import Client +from tradedesk.portfolio.base import BasePortfolio log = logging.getLogger(__name__) @@ -45,179 +44,66 @@ def configure_logging(level: str = "INFO", force: bool = False) -> None: root_logger.addHandler(handler) -def _instruments_from_subscriptions(strategy: BaseStrategy) -> list[str]: - instruments: list[str] = [] - seen = set() - - for sub in getattr(strategy, "subscriptions", []) or []: - instrument = getattr(sub, "instrument", None) - if instrument and instrument not in seen: - seen.add(instrument) - instruments.append(instrument) - - return instruments - - -async def _run_strategies_async( - strategy_instances: list[BaseStrategy], client: Client -) -> None: - """ - Run multiple strategies concurrently. - - Notes: - - Task cancellation/cleanup is handled in a finally block so it runs on: - * normal completion - * CancelledError - * KeyboardInterrupt propagating through asyncio.run(main()) - * any other exception - """ - if not strategy_instances: - log.warning("No strategies to run") - return - - for strategy in strategy_instances: - instruments = _instruments_from_subscriptions(strategy) - log.info( - "Loaded %s monitoring %d instrument%s: %s", - strategy.__class__.__name__, - len(instruments), - "s" if len(instruments) != 1 else "", - ", ".join(instruments) if instruments else "(none)", - ) - - all_instruments = set() - for strategy in strategy_instances: - all_instruments.update(_instruments_from_subscriptions(strategy)) - - if all_instruments: - log.info("Total unique instruments to monitor: %d", len(all_instruments)) - else: - log.warning("No instruments defined in any strategy - nothing to monitor") - - tasks = [asyncio.create_task(strategy.run()) for strategy in strategy_instances] - - try: - await asyncio.gather(*tasks) - except asyncio.CancelledError: - # Ensure a friendly log line when cancellation is the reason. - log.info("Strategies cancelled") - raise - finally: - # Always attempt to stop strategies cleanly. - for task in tasks: - if not task.done(): - task.cancel() - - # Drain tasks; swallow exceptions to avoid masking the original failure/cancel. - await asyncio.gather(*tasks, return_exceptions=True) - - -def _instantiate_strategies( - client: Client, strategy_specs: list[Any] -) -> list[BaseStrategy]: - """ - Instantiate strategies. - - strategy_specs entries can be: - - a BaseStrategy subclass (old format) - - a tuple of (StrategyClass, kwargs_dict) (new format) - """ - strategy_instances: list[BaseStrategy] = [] - - for spec in strategy_specs: - if isinstance(spec, tuple): - strategy_class, kwargs = spec - log.debug("Strategy %s kwargs=%s", strategy_class.__name__, kwargs) - instance = strategy_class(client, **kwargs) - else: - strategy_class = spec - instance = strategy_class(client) - - strategy_instances.append(instance) - - return strategy_instances - - -async def _async_run_strategies( - client: Client, - strategy_specs: list[Any], - log_level: str | None = None, - setup_logging: bool = True, +async def _async_run_portfolio( + portfolio_factory: Callable[[Client], BasePortfolio], + client_factory: Callable[[], Client], + log_level: str | None, + setup_logging: bool, ) -> None: if setup_logging: configure_logging(log_level or "INFO") log.info("=" * 70) - log.info("Tradedesk Strategy Runner") + log.info("Tradedesk Portfolio Runner") log.info("=" * 70) + client = client_factory() + await client.start() try: - # Wire up event-driven order execution before strategies start. - _order_handler = OrderExecutionHandler(client) # noqa: F841 - - strategy_instances = _instantiate_strategies(client, strategy_specs) - - log.info("Starting strategies...") - log.info("-" * 70) - - await _run_strategies_async(strategy_instances, client) - + portfolio = portfolio_factory(client) + await portfolio.run() finally: - # Always close the client even if strategy instantiation fails. await client.close() + log.info("=" * 70) + log.info("Tradedesk shut down complete") + log.info("=" * 70) -async def _async_run_with_client_factory( - client_factory: Callable[[], Client], - strategy_specs: list[Any], - log_level: str | None = None, - setup_logging: bool = True, -) -> None: - client = client_factory() - await client.start() - await _async_run_strategies( - client, - strategy_specs, - log_level=log_level, - setup_logging=setup_logging, - ) - - -def run_strategies( - strategy_specs: list[Any], +def run_portfolio( + portfolio_factory: Callable[[Client], BasePortfolio], client_factory: Callable[[], Client], log_level: str | None = None, setup_logging: bool = True, ) -> None: """ - Run one or more strategies against a live data provider. + Run a portfolio against a live data provider. - This is the main synchronous entry point for the `tradedesk` runner. - It manages the asyncio event loop and the lifecycle of the provider - client and strategies. + This is the main synchronous entry point for tradedesk. It manages the + asyncio event loop and the full lifecycle of the client and portfolio. The framework will: - - Construct the provider client via `client_factory()`. - - Await `client.start()` to authenticate and connect. - - Instantiate and run all strategies concurrently. - - Await `client.close()` on graceful shutdown or error. + - Construct the provider client via ``client_factory()``. + - Await ``client.start()`` to authenticate and connect. + - Construct the portfolio via ``portfolio_factory(client)``. + - Await ``portfolio.run()`` which fires lifecycle events and streams. + - Await ``client.close()`` on shutdown or error. Args: - strategy_specs: A list of strategy specifications. Each spec can be - a `BaseStrategy` subclass, or a tuple of `(StrategyClass, kwargs)`. - client_factory: A callable that returns an unstarted `Client` instance. - log_level: The logging level to configure (e.g., "INFO", "DEBUG"). - If `None`, defaults to "INFO". - setup_logging: If `True`, configures the root logger. Set to `False` - if the application handles its own logging setup. + portfolio_factory: Callable that receives the started ``Client`` and + returns an initialised (but not yet running) ``BasePortfolio``. + client_factory: Callable that returns an unstarted ``Client`` instance. + log_level: Logging level (e.g. ``"INFO"``, ``"DEBUG"``). Defaults to + ``"INFO"``. + setup_logging: If ``True``, configures the root logger. Set to + ``False`` if the application handles its own logging setup. """ exit_code = 0 try: asyncio.run( - _async_run_with_client_factory( + _async_run_portfolio( + portfolio_factory=portfolio_factory, client_factory=client_factory, - strategy_specs=strategy_specs, log_level=log_level, setup_logging=setup_logging, ) @@ -229,13 +115,12 @@ def run_strategies( log.info("Interrupted by user - shutting down gracefully") except Exception as e: - log.exception("Fatal error in strategy runner: %s", e) + if log.getEffectiveLevel() <= logging.DEBUG: + log.exception("Fatal error in portfolio runner", exc_info=e) + else: + log.error("Fatal error in portfolio runner: %s", e) + log.error("Run with DEBUG logging for more details") exit_code = 1 - finally: - log.info("=" * 70) - log.info("Tradedesk shut down complete") - log.info("=" * 70) - if exit_code: sys.exit(exit_code) diff --git a/tradedesk/strategy/base.py b/tradedesk/strategy/base.py index 7a3251f..eac6ce5 100644 --- a/tradedesk/strategy/base.py +++ b/tradedesk/strategy/base.py @@ -2,29 +2,22 @@ """ Base strategy framework for trading strategies. -Provides infrastructure for: -- Lightstreamer streaming (real-time price feeds) -- REST polling fallback (for testing/backup) -- Multi-instrument subscription management - Strategies implement trading logic by subclassing BaseStrategy and -overriding on_price_update() and/or on_candle_update(). +overriding on_price_update() and/or on_candle_close(). """ import abc -import asyncio import logging from datetime import datetime, timezone from enum import Enum -from tradedesk.events import get_dispatcher +from tradedesk.events import SessionStartedEvent, get_dispatcher from tradedesk.marketdata import ( CandleClosedEvent, ChartHistory, ChartSubscription, Indicator, MarketData, - MarketDataReceivedEvent, MarketSubscription, ) @@ -73,9 +66,6 @@ async def on_candle_close(self, candle_close): # Subclasses should define which data streams they want SUBSCRIPTIONS: list[MarketSubscription | ChartSubscription] = [] - # Default polling interval when streamer is unavailable - POLL_INTERVAL = 5 # seconds - def __init__( self, data_provider: DataProvider | None = None, @@ -121,6 +111,8 @@ def __init__( self.__class__.__name__, ) + get_dispatcher().subscribe(SessionStartedEvent, self._on_session_started) + def _chart_key(self, sub: ChartSubscription) -> tuple[str, str]: return (sub.instrument, sub.period) @@ -261,9 +253,6 @@ def prime_chart(self, sub: ChartSubscription, candles: list[Candle]) -> None: for ind in indicators: ind.update(candle) - def _has_streamer(self) -> bool: - return self.client.get_streamer() is not None # type: ignore[union-attr] - async def on_price_update(self, market_data: MarketData) -> None: """ Handle a tick-level price update for a subscribed instrument. @@ -295,125 +284,10 @@ async def on_candle_close(self, candle_close: CandleClosedEvent) -> None: if key in self.charts: self.charts[key].add_candle(candle_close.candle) - async def run(self) -> None: - """ - Start the strategy; runs until cancelled. - - Note: This method is typically called by the runner, not directly. - The runner orchestrates multiple strategies with a shared connection. - """ - # Build display string for subscriptions - sub_display = [] - for sub in self.subscriptions: - if isinstance(sub, MarketSubscription): - sub_display.append(f"MARKET:{sub.instrument}") - elif isinstance(sub, ChartSubscription): - sub_display.append(f"CHART:{sub.instrument}:{sub.period}") - - log.info("%s started for %s", self.__class__.__name__, ", ".join(sub_display)) - + async def _on_session_started(self, event: SessionStartedEvent) -> None: + """Run warmup when the portfolio fires SessionStartedEvent.""" try: await self.warmup() except Exception: log.exception("Warmup failed; continuing without warmup") - # Check if Lightstreamer is available - if self._has_streamer(): - await self._run_streaming() - else: - log.info("Falling back to polling mode (Lightstreamer not available)") - await self._run_polling() - - async def _run_polling(self) -> None: - """ - Fallback polling mode - fetches market snapshots at regular intervals. - Used when Lightstreamer is unavailable (typically in tests). - - Note: Only polls MARKET subscriptions, not CHART subscriptions. - """ - if self._data_provider is None: - log.error("Cannot poll without data provider") - return - - # Only poll market subscriptions - market_instruments = [ - sub.instrument - for sub in self.subscriptions - if isinstance(sub, MarketSubscription) - ] - - if not market_instruments: - log.warning("No market subscriptions to poll") - await asyncio.Future() # Wait forever - return - - last_prices: dict[str, float | None] = { - instrument: None for instrument in market_instruments - } - - while True: - for instrument in market_instruments: - try: - snapshot = await self._data_provider.get_market_snapshot(instrument) - bid = float(snapshot["snapshot"]["bid"]) - offer = float(snapshot["snapshot"]["offer"]) - mid = (bid + offer) / 2 - - # Only notify on price changes - if last_prices[instrument] != mid: - last_prices[instrument] = mid - timestamp = ( - datetime.now(timezone.utc).isoformat(timespec="seconds") - + "Z" - ) - market_data = MarketData( - instrument=instrument, - bid=bid, - offer=offer, - timestamp=timestamp, - raw=snapshot, - ) - await self.on_price_update(market_data) - - except Exception: - log.exception("Failed to fetch market snapshot for %s", instrument) - - await asyncio.sleep(self.POLL_INTERVAL) - - async def _run_streaming(self) -> None: - streamer = self.client.get_streamer() # type: ignore[union-attr] - assert streamer is not None, "No streamer available" - await streamer.run(self) - - async def _handle_event(self, event: object) -> None: - """ - Internal event dispatcher - bridges to event bus and callbacks. - - Streamer implementations should call this method only. It: - 1. Dispatches events to the global event bus (for event-driven handlers) - 2. Calls existing strategy callbacks (for backwards compatibility) - 3. Updates common bookkeeping (e.g. last_update) - """ - # Get the global event dispatcher - dispatcher = get_dispatcher() - - # Dispatch to event bus AND call callbacks - # (Callbacks are for strategy logic; event bus is for cross-cutting concerns) - if isinstance(event, MarketData): - # Wrap MarketData in event and dispatch to event bus - await dispatcher.publish(MarketDataReceivedEvent(data=event)) - # Call callback (stores candles in chart history, strategy logic) - await self.on_price_update(event) - - elif isinstance(event, CandleClosedEvent): - # Dispatch event to event bus - await dispatcher.publish(event) - # Call callback (stores candles in chart history, strategy logic) - await self.on_candle_close(event) - - else: - # Defensive: should never happen unless someone extends events incorrectly. - raise TypeError(f"Unsupported event type: {type(event)!r}") - - # Update watchdog - self.last_update = datetime.now(timezone.utc) diff --git a/tradedesk/types.py b/tradedesk/types.py 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