diff --git a/.gitignore b/.gitignore index a0a2ef7..fd382c5 100644 --- a/.gitignore +++ b/.gitignore @@ -5,6 +5,7 @@ __pycache__ .env .env.* .local +.tldr .mypy_cache .pytest_cache .venv @@ -14,7 +15,3 @@ __pycache__ *.egg build dist/ - -# set CLAUDE.md as a local symlink to AGENTS.md -CLAUDE.md -GEMINI.md diff --git a/.mcp.json b/.mcp.json new file mode 100644 index 0000000..e92d35f --- /dev/null +++ b/.mcp.json @@ -0,0 +1,13 @@ +{ + "mcpServers": { + "tldr": { + "command": "uv", + "args": [ + "run", + "tldr-mcp", + "--project", + "." + ] + } + } +} diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..47452a5 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,6 @@ +repos: +- repo: https://github.com/astral-sh/ruff-pre-commit + # Ruff version. + rev: v0.14.13 + hooks: + - id: ruff-format diff --git a/.tldrignore b/.tldrignore new file mode 100644 index 0000000..e01df83 --- /dev/null +++ b/.tldrignore @@ -0,0 +1,84 @@ +# TLDR ignore patterns (gitignore syntax) +# Auto-generated - review and customize for your project +# Docs: https://git-scm.com/docs/gitignore + +# =================== +# Dependencies +# =================== +node_modules/ +.venv/ +venv/ +env/ +__pycache__/ +.tox/ +.nox/ +.pytest_cache/ +.mypy_cache/ +.ruff_cache/ +vendor/ +Pods/ + +# =================== +# Build outputs +# =================== +dist/ +build/ +out/ +target/ +*.egg-info/ +*.whl +*.pyc +*.pyo + +# =================== +# Binary/large files +# =================== +*.so +*.dylib +*.dll +*.exe +*.bin +*.o +*.a +*.lib + +# =================== +# IDE/editors +# =================== +.idea/ +.vscode/ +*.swp +*.swo +*~ + +# =================== +# Security (always exclude) +# =================== +.env +.env.* +*.pem +*.key +*.p12 +*.pfx +credentials.* +secrets.* + +# =================== +# Version control +# =================== +.git/ +.hg/ +.svn/ + +# =================== +# OS files +# =================== +.DS_Store +Thumbs.db + +# =================== +# Project-specific +# Add your custom patterns below +# =================== +# large_test_fixtures/ +# data/ diff --git a/AGENTS.md b/AGENTS.md deleted file mode 100644 index 8ced8aa..0000000 --- a/AGENTS.md +++ /dev/null @@ -1,44 +0,0 @@ -## Preferred Way of Working - -### Incremental and Focused - -* Make small, well-scoped changes -* One concern per change set -* Avoid cascading refactors without agreement - -### Code-First Reasoning - -* Inspect files before discussing them -* Do not assume abstractions or intent -* Respect that some modules are intentionally small or narrow - -### Pragmatic Testing - -* Tests should defend correctness, not chase coverage -* Avoid brittle, over-specified tests -* Use `pytest` not `unittest` - -### Communication Style - -* Concise, technical, professional -* Minimal narration -* Challenge assumptions - constructive dialog and pushback is expected - ---- - -## Coding Expectations - -* Use latest stable Python and dependencies -* Follow current documentation and APIs -* 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` - * All imports across domains should use top level re-exports. Example: code in `tradedesk.execution` should only import code - from `tradedesk.marketdata` and never from `tradedesk.marketdata.events` The class or function should be explicitly - exported in `__init.py__` files if it can be used outside of the domain - -When running code or commands: - -* Use `uv` instead of `pip` -* Always use the `.venv` directory in the root of the project diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 0000000..763f11a --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1,20 @@ +# Initialise + +FIRST; read https://github.com/radiusred/.github/CLAUDE.md (or the local copy). + +--- + +## Coding Expectations + +* Use latest stable Python and dependencies +* Follow current documentation and APIs +* 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 +* Follow the intentions of the domain architecture encoded in `pyproject.toml` + * All imports across domains should use top level re-exports. Example: code in `tradedesk.execution` should only import code + from `tradedesk.marketdata` and never from `tradedesk.marketdata.events` The class or function should be explicitly + exported in `__init.py__` files if it can be used outside of the domain + +When running code or commands: + +* Always use `uv` or the `.venv` directory in the root of the project to run development tools diff --git a/docs/briefs/01-read-dukascopy-cache.md b/docs/briefs/01-read-dukascopy-cache.md new file mode 100644 index 0000000..c7daf34 --- /dev/null +++ b/docs/briefs/01-read-dukascopy-cache.md @@ -0,0 +1,107 @@ +Always read and follow instructions in `CLAUDE.md` in the project root before processing the brief. + +# Task Brief: Read `tradedesk-dukascopy` cache data for backtests + +## Context + +Data for backtests is currently supplied in the form of CSV candle files at some resolution (typically 1 minute) per instrument with the `tradedesk` library aggregating these into the periods actually required by the running strategy. This forces a one-off creation of the "chart" data per instrument for use in a backtest, where the chart file contains all the candles that will be used in the backtest for that instrument. + +The `tradedesk-dukascopy` tool provides a way to export such files from its cache of market data by specifying start/end dates, instrument names and resampling period. But any method of generating the data in the required format is equally valid. + +## Goal + +The goal of this session is to enable `tradedesk` to read market data directly from the `tradedesk-dukascopy` cache and avoid having to create and re-create exported chart files for backtests. Once the tool has downloaded and converted data, it should be immediately possible to use it in a test. The downloader now stores daily "tick" files consisting of one line of prices for each movement. These are the files that will need to be read in order to create OHLCV candles for injection into the bus for backtest clients. + +### Data Format + +All cached data is stored in the following directory layout from the root of the cache-dir: + +```text +SYMBOL +├── YEAR + ├── 00 + │ ├── 01_ticks.csv.zst + │ ├── 02_ticks.csv.zst + │ ├── ... + │ ├── 31_ticks.csv.zst +``` +Months are `00` based; 00 = January, 11 = December. This is a Dukascopy convention. Each day within the month has a single compressed file of tick data. + +File compression is done with the python `zstandard` library and this should be performant enough to decompress on the fly. + +This is the data format for all decompressed dukascopy data: + +```csv +ts,bid,ask,bid_vol,ask_vol +2026-01-30T00:00:02.244000+00:00,13807.7,13808.9,0.8999999761581421,1.6299999952316284 +2026-01-30T00:00:04.506000+00:00,13807.9,13808.8,0.8999999761581421,0.7300000190734863 +2026-01-30T00:00:04.609000+00:00,13807.9,13808.9,0.8999999761581421,1.7999999523162842 +2026-01-30T00:00:04.711000+00:00,13807.7,13808.9,0.8999999761581421,0.8999999761581421 +2026-01-30T00:00:10.805000+00:00,13808.0,13808.8,0.8999999761581421,0.8999999761581421 +2026-01-30T00:00:11.218000+00:00,13808.1,13809.0,0.8999999761581421,2.9800000190734863 +2026-01-30T00:00:12.487000+00:00,13808.0,13808.9,0.8999999761581421,4.5 +2026-01-30T00:00:12.590000+00:00,13807.8,13808.9,0.8999999761581421,0.8999999761581421 +2026-01-30T00:00:12.894000+00:00,13807.8,13808.7,0.8999999761581421,0.8999999761581421 +``` + +## Approach + + - The original data format does not need to be retained in the framework for backwards compatibility. Tick files will be the only supported future format. The framework should, however, handle source files that are compressed (with `zstandard`) or not. + - Chart files naturally stopped and started with whatever the first and last entry in them was. Running a backtest will now need two additional parameters / CLI args of `--from` and `--to` to determine this. + - Missing data days within the cache are to be expected (for example when markets are closed). + - Data using old formats might exist in the cache. This might include hourly files with `.bi5` extensions or differing directory structures if it was collected with older versions of the tool. If it is found, exit the backtest gracefully with an error message and advise the user to re-run the `tradedesk-dc-export` tool which will correct the cache. + - There may be existing code in the `tradedesk-dukascopy` project that will be of use as a starting point since it already implements some of these requirements to produce charts. Use it if so (but copy, do not reference/import) as that will likely be removed from the tool once this work is complete. + - + + +### Stretch goal + +The following should only be evaluated for complexity, do not write code or tests for them. + + - Optionally use a single side (default to BUY) or use both BUY and SELL prices to include spread costs. Use a CLI argument of `--side` with choices `{"buy", "sell", "both"}` + - Update the reporting (`analysis.md` file) to show the spread costs if used + +## Output + +### New files + +**`tradedesk/execution/backtest/dukascopy.py`** — cache reader module. Tick-reading logic copied from `tradedesk-dukascopy` (no import reference). Provides: +- `read_dukascopy_candles(cache_dir, symbol, period, date_from, date_to, *, price_side)` — reads daily tick files for the date range, skips missing days silently, detects old `.bi5` format and exits with guidance, resamples to `Candle` objects. +- Internal helpers: `_iter_days`, `_tick_paths`, `_check_old_format`, `_load_tick_rows`, `_period_to_pandas_rule`, `_ticks_to_candle_df`. + +**`tests/execution/backtest/test_dukascopy_cache.py`** — 36 tests covering: day iteration, path construction, period conversion, old-format detection, compressed/uncompressed loading, missing-day skipping, resampling correctness, timestamp ordering, and `BacktestClient.from_dukascopy_cache` integration. + +### Modified files + +**`tradedesk/execution/backtest/client.py`** — added `from_dukascopy_cache(cache_dir, *, symbol, instrument, period, date_from, date_to, price_side)` classmethod. + +**`tradedesk/execution/backtest/runner.py`** — `BacktestSpec` now takes `cache_dir`, `symbol`, `date_from`, `date_to`, `price_side` instead of `candle_csv`. `run_backtest` uses `BacktestClient.from_dukascopy_cache`. + +**`pyproject.toml`** — added `zstandard>=0.25` dependency. + +**`tests/execution/backtest/test_backtest_runner.py`** — updated for new `BacktestSpec` fields. + +### Stretch goal assessment + +`--side` (buy/sell/both) is already partially supported: `price_side` is threaded through `BacktestSpec`, `from_dukascopy_cache`, and `read_dukascopy_candles`. Exposing it as a CLI argument is a small addition. The spread-cost annotation in analysis reporting would require the reporting layer to carry the `price_side` context and annotate equity/trade output — moderate complexity, ~1–2 hours. + + +## Usage by Model + +**claude-sonnet-4-6:** + +| Type | Tokens | +| :--- | :--- | +| Input | 0.1k | +| Output | 34.7k | +| Cache Read | 6.6m | +| Cache Write | 170.3k | + +**claude-haiku-4-5:** + +| Type | Tokens | +| :--- | :--- | +| Input | 0.1k | +| Output | 6.4k | +| Cache Read | 300.3k | +| Cache Write | 66.6k | diff --git a/docs/briefs/02-read-new-cache-format.md b/docs/briefs/02-read-new-cache-format.md new file mode 100644 index 0000000..426a798 --- /dev/null +++ b/docs/briefs/02-read-new-cache-format.md @@ -0,0 +1,64 @@ +Always read and follow instructions in `CLAUDE.md` in the project root before processing the brief. + +# Amendment to `01-read-dukascopy-cache.md` - read candles instead + +## Context + +The changes outlined in `01-read-dukascopy-cache.md` worked as implemented but with a severe performance penalty of converting the cached tick data to 1-minute candle resolutions in memory. This penalty was paid on each backtest run. + +`tradedesk-dukascopy` has now been amended to store compressed 1-minute candle files in the cache instead (2 per day, one with bid prices and one with ask prices). + +## Goal + +The goal of this session is to amend the code to read and use the already available 1-minute candle files from the cache, aggregating those as required for the backtest parameters. + +The goal is successfully achieved when a backtest can be run using the new format for cached dukascopy data as input to the test. + + +## Approach + + - Amend existing code that reads the dukascopy cache to expect and require 1-minute candle files using the correct buy/sell side price. + - Discard any code that generates 1-minute candles internally as these are already created. + - Update any supporting code and tests to match the changes + - Ensure all tests pass, and that the code is compliant with `mypy --strict` + - Make specific note of any changes to the public API that scripts and calling code may need to be aware of + - Do not be concerned with backward compatibility or API shims, breakages are acceptable + +## Output + +### Modified files + +**`tradedesk/execution/backtest/dukascopy.py`** — rewired to read 1-min candle files. + +Removed: +- `_tick_paths()` — replaced by `_candle_path()` +- `_load_tick_rows()` — replaced by `_load_daily_candles()` +- `_ticks_to_candle_df()` — no longer needed; candles are pre-computed in the cache + +Added: +- `_candle_path(cache_dir, symbol, day, side)` — returns `{day}_{side}.csv.zst` path +- `_load_daily_candles(path)` — decompresses and returns a candle DataFrame with UTC DatetimeIndex; returns `None` on missing/corrupt file + +Changed in `read_dukascopy_candles`: +- `price_side` now selects which cached file to read (`"bid"` or `"ask"`); `"mid"` is no longer supported (no mid file exists in the cache) +- Loads 1-min candle DataFrames per day, concatenates, and resamples once with `first/max/min/last/sum` aggregation — matching the `CandleAggregator` pattern +- Error message updated: `"No candle data found"` (was `"No tick data found"`) + +**`tests/execution/backtest/test_dukascopy_cache.py`** — rewritten for candle format. + +Removed: tests for `_tick_paths`, `_load_tick_rows`, `_ticks_to_candle_df` + +Added: tests for `_candle_path`, `_load_daily_candles`, `_read_dukascopy_candles_ask_side`, `_read_dukascopy_candles_aggregates_to_15min`, `_read_dukascopy_candles_invalid_side_raises`, `test_backtest_client_from_dukascopy_cache_ask_side` + +Test count: 36 (unchanged). + +### Public API changes + +- `_tick_paths` and `_load_tick_rows` and `_ticks_to_candle_df` are removed from the public-ish internal API. Any calling code that imported them directly will need updating. +- `read_dukascopy_candles` now raises `ValueError` for `price_side="mid"` (was silently supported). +- Error message prefix changed from `"No tick data found"` to `"No candle data found"` — any caller matching the old string will need updating. + +### Result + +498 tests pass. `mypy --strict` reports only the pre-existing `import-untyped` error for `pandas` (shared with `recording/report.py`; no stubs installed project-wide). + diff --git a/docs/briefs/03-improve-startup-performance.md b/docs/briefs/03-improve-startup-performance.md new file mode 100644 index 0000000..1552f08 --- /dev/null +++ b/docs/briefs/03-improve-startup-performance.md @@ -0,0 +1,135 @@ +Always read and follow instructions in `CLAUDE.md` in the project root before processing the brief. + +# Improve backtest startup performance + +## Context + +Backtests work by reading 1-minute OHLCV candle files, aggregating them as necessary, and using them as the source of streaming prices to test strategies. Currently these candles are all read into memory priot to the test starting. + +In `tradedesk` applications, a portfolio can consist of several instruments and potentially long time periods causing an issue of delayed start (with no user feedback because logging has not been initiated at this point) and an inefficient use of memory. + +## Role + +In this session you will take on a role described in https://github.com/radiusred/.github/doc/agent-roles/consultant-architect.md (or the local repository clone) + +## Goal + +The goal of this session is to improve both startup time and memory efficiency of backtesting. With an event driven system, the aim should be to ideally inject candles into the event bus as they are available. + +The goal is successfully achieved when long, multi-instrument backtests can be run with no appreciable increase in startup time or memory overhead compared with shorter or single-instrument runs. + + +## Approach + + - Evaluate (do NOT write/edit code) two approaches to data loading. + - Should all the candles still be loaded into memory before starting, in which case multi-thread the load (one thread per instrument) before finally sorting by date and aggregating instruments into the current single candle list. This may solve the time issue even if the memory problem is not addressed. However, it may solve neither if the multi-threaded approach blocks on disk IO. + - Can injection of candles into the "bus" begin as soon as they are read - effectively implementing a real stream with the disk cache as the source doing what a broker's streaming client would do. This is more idealised, solves both problems but could be more complex than it's worth. + +Outline pros and cons of each approach, plus any other you feel worthy of consideration. Agree the way forward, but do NOT implement anything at this stage, implementation will be in a later brief. + +## Output + +### Architecture Observations + +There are two distinct memory allocations to account for, both of which are problems: + +1. **Load phase** (`build_portfolio_backtest_client`): Reads all CSV files into `BacktestClient._history` — a `dict[(epic, period) → list[Candle]]`. This happens *before* `asyncio.run()`, so it is synchronous, sequential, and unlogged. + +2. **Stream build phase** (`BacktestStreamer.run()`): Iterates every loaded candle, constructs a `CandleClosedEvent` object per candle, appends to a flat `stream` list, then calls `list.sort()`. This is a *second full materialisation* of the entire dataset, doubling the memory footprint before a single event is dispatched. + +For a 4-year, 5-instrument backtest at 1MIN resolution, each phase is on the order of several million objects. The sort in phase 2 is also O(N log N) across the full merged set, adding non-trivial CPU time before the replay begins. + +Any solution must address **both phases** to be effective. + +--- + +### Approach A: Parallel Loading (Multi-threaded) + +Load each instrument's CSV concurrently via a `ThreadPoolExecutor`, then proceed as now. + +**Pros** +- Minimal architectural change — only `build_portfolio_backtest_client` is touched +- Reading zstd-compressed CSV is largely IO-bound; threads bypass the GIL for that portion +- Proportional speedup with instrument count for the load phase +- Low risk: downstream code (BacktestClient, BacktestStreamer, strategies) unchanged + +**Cons** +- Addresses startup time only, not memory — all candles remain fully resident in `_history` and then again in `stream` +- Pandas resampling (1MIN → target) is CPU-bound; GIL limits real parallelism there, so the improvement may be partial +- If instruments share a single storage device, concurrent reads may contend rather than parallelise (less relevant with SSD) +- `BacktestStreamer.run()` still builds and sorts the full `stream` list — this phase dominates at scale and is untouched +- The problem gets worse linearly with scale; this approach just defers it + +**Verdict**: Partial, short-term fix. Solves neither the fundamental memory problem nor the stream-build bottleneck. Not recommended as the primary strategy. + +--- + +### Approach B: Streaming Injection (Lazy/Generator Pipeline) + +Replace upfront loading with per-instrument lazy generators that yield candles as they are read, and replace the flat sorted `stream` list with a k-way merge across those generators. + +The key observation is that **candles within each instrument file are already sorted chronologically**. A k-way merge across `k` instruments using `heapq.merge()` produces a fully ordered interleaved stream with O(log k) overhead per event — no upfront sort required, and only a constant-size heap in memory at any point. + +The `BacktestStreamer.run()` loop body would be unchanged — it still dispatches one event at a time — but the `stream` list and `stream.sort()` are replaced with a generator pipeline. + +**Pros** +- Solves both problems: startup begins immediately (no pre-load phase); memory per in-flight event is O(1) rather than O(total candles) +- No architectural change to the event dispatch path or strategies +- Scales arbitrarily — a 10-year, 20-instrument backtest uses no more memory than a 1-day, 1-instrument run +- Aligns with the system's stated design intent: injecting events as they arrive, as a real broker feed would +- `heapq.merge()` is already available in the standard library; no new dependencies + +**Cons** +- **Warmup mechanism is broken by this approach.** `get_historical_candles(epic, period, n)` reads from `_history`, which would no longer be pre-populated. Strategies that call this during warmup (to seed indicators before live replay) would fail. + - This is the dominant architectural challenge. + - MacroTrendStrategy already works around this by gating on `_bar_count >= period` rather than using warmup — that pattern generalises, but it requires strategy-level changes. + - An alternative: pre-load only the warmup window (first `warmup_bars` worth of data per instrument) into `_history`, then stream the remainder lazily. This is a small fraction of the total data. +- The base-period pre-aggregation step in `run_portfolio_backtest` also populates `_history[(epic, target_period)]` — this would need rethinking, though it could be done inline in the generator chain. +- Slightly more complex streaming code; ordering bugs would be harder to detect than with a sort-then-replay approach. + +**Verdict**: The right long-term architecture. The warmup issue is the only substantive obstacle and has a clear resolution path. + +--- + +### Approach C (Additional Consideration): Lazy Pipeline with Partial Warmup Pre-load + +A refinement of Approach B that resolves the warmup issue cleanly: + +- For each instrument, pre-load only the first `max(warmup_bars, aggregation_window)` candles into `_history` as today — enough to service `get_historical_candles()` calls during warmup +- Stream the remainder lazily via per-instrument generators +- The k-way merge begins after warmup completes (i.e. after `SessionReadyEvent`) so that warmup data and live-stream data are never interleaved incorrectly +- Base-period aggregation remains as a transform layer in the generator chain rather than a pre-pass + +This preserves full backward compatibility with existing warmup-dependent strategies while gaining the memory and startup benefits of lazy streaming. It is the pragmatic middle path: no strategy changes required, no warmup regressions, full scalability. + +--- + +### Recommendation + +**Approach C** is the recommended path. + +Approach A offers a small, bounded startup improvement but leaves the fundamental problems untouched — it is not worth the ongoing complexity budget given it will need to be revisited. + +Approach B/C together represent a clean, principled solution that aligns with the event-driven design of the system. The implementation surface is well-contained: + +- `BacktestStreamer`: replace `stream` list + sort with k-way merge generator +- `BacktestClient` / `dukascopy.py`: expose a lazy candle generator alongside (or replacing) the current eager loader +- `build_portfolio_backtest_client` / `run_portfolio_backtest`: pre-load warmup slice only; remove full upfront load +- Strategies: no changes required if partial pre-load is used + +The warmup boundary (when lazy streaming begins) maps naturally onto the existing `SessionStartedEvent` → `SessionReadyEvent` lifecycle, which already separates warmup from live replay. + +One recommendation for the implementation brief: define a `CandleSource` protocol (or similar) that both the eager `list[Candle]` and the lazy generator can satisfy. This keeps `BacktestStreamer` decoupled from the loading mechanism and avoids divergent code paths for tests versus production backtests. + + +# Cost +``` +Total cost: $0.4956 +Total duration (API): 4m 25s +Total duration (wall): 12h 25m 16s +Total code changes: 91 lines added, 1 line removed + +Usage by model: +claude-sonnet-4-6: 9 input, 5.7k output, 118.9k cache read, 21.2k cache write ($0.3335) +claude-haiku-4-5: 107 input, 6.9k output, 599.1k cache read, 54.1k cache write ($0.1621) +``` diff --git a/docs/briefs/03b-improve-startup-performance.md b/docs/briefs/03b-improve-startup-performance.md new file mode 100644 index 0000000..d981ff4 --- /dev/null +++ b/docs/briefs/03b-improve-startup-performance.md @@ -0,0 +1,110 @@ +Always read and follow instructions in `CLAUDE.md` in the project root before processing the brief. + +# Improve startup performance (implementation) + +## Context + +See the context and architectural recommendations in `03-improve-startup-performance.md`. + + +## Role + +In this session you will take on a role described in https://github.com/radiusred/.github/doc/agent-roles/engineer.md (or the local equivalent repository clone) + +## Goal + +The goal of this session is to implement the architectural and design changes outlined in option **C** of `03-improve-startup-performance.md`. + +The goal is successfully achieved when long, or multi-instrument backtests can be run with no appreciable increase in startup time or memory overhead compared with shorter or single-instrument runs. + + +## Approach + +- Replace upfront loading with per-instrument lazy generators that yield candles as they are read, and replace the flat sorted `stream` list with a k-way merge across those generators. +- The key observation is that **candles within each instrument file are already sorted chronologically**. A k-way merge across `k` instruments using `heapq.merge()` will produces a fully ordered interleaved stream with O(log k) overhead per event. +- The `BacktestStreamer.run()` loop body remains unchanged — it still dispatches one event at a time — but the `stream` list and `stream.sort()` are replaced with a generator pipeline. +- For each instrument, pre-load only the first `max(warmup_bars, aggregation_window)` candles into `_history` as today — enough to service `get_historical_candles()` calls during warmup +- Stream the remainder lazily via per-instrument generators +- The k-way merge begins after warmup completes (i.e. after `SessionReadyEvent`) so that warmup data and live-stream data are never interleaved incorrectly +- Base-period aggregation remains as a transform layer in the generator chain rather than a pre-pass + +## Output + +### Files changed + +**`tradedesk/execution/backtest/dukascopy.py`** +- Added `iter_dukascopy_candles()` — validates inputs eagerly then delegates to `_iter_candles()`, a private generator that yields `Candle` objects one daily file at a time. Per-day resampling for non-1MIN periods (safe for all periods that align to day boundaries: 15MIN, 1H, 4H, 1D). No `ValueError` on empty ranges; invalid `price_side` / `period` raise immediately at call time. + +**`tradedesk/execution/backtest/streamer.py`** +- `CandleSeries.candles` widened from `list[Candle]` to `Iterable[Candle]` — accepts generators. +- `BacktestStreamer.run()` replaced the flat `stream` list + `stream.sort()` with `heapq.merge` over per-instrument generators. A shared `itertools.count()` acts as tiebreaker when two instruments share a timestamp, avoiding any comparison of non-orderable event objects. O(log k) per event vs O(N log N) upfront sort. +- Two module-level helpers extracted: `_candle_gen()` and `_market_gen()`. The redundant `_set_current_timestamp` call in the old stream-build loop is removed. + +**`tradedesk/execution/backtest/client.py`** +- Added `BacktestClient.from_lazy_sources()` classmethod. Accepts an explicit `history` dict (warmup slice, for `get_historical_candles()`) and `candle_series` list (lazy generators, for streaming), keeping them separate so only the warmup window needs to be resident at startup. + +**`tradedesk/execution/backtest/__init__.py`** +- Exported `iter_dukascopy_candles`. + +**`ig_trader/session_runners.py`** +- `build_portfolio_backtest_client()`: new `warmup_bars: int | None = None` parameter. `None` preserves existing eager behaviour. When set, pre-loads the first `warmup_bars` base-period candles per instrument into `_history` (via `itertools.islice`), then creates an independent full-range generator for streaming and returns a `from_lazy_sources` client. +- `run_portfolio_backtest()`: new `warmup_bars: int | None = None` and `run_name: str | None = None` parameters. `run_name` (or a UTC timestamp fallback) is used to compute the run output directory eagerly before any data loading, so logging is fully configured — including the file handler — before the expensive candle-loading and index-building steps. The deferred `_configure_logging_on_start` / `SessionStartedEvent` handler is removed. The subscriber is passed the pre-created `run_dir` directly via the new `run_dir` parameter (see below). `warmup_bars` is forwarded to the client builder. In lazy mode, the target-period warmup history is aggregated from the warmup slice and `ledger.candle_indices` is built from a fresh full-range generator (one extra disk pass, O(N_target) memory rather than O(N_base)). + +**`tradedesk/recording/subscriber.py`** +- `RecordingSubscriber.__init__` gains `run_dir: Path | None = None`. When provided it is stored directly as `_run_output_dir` (caller is responsible for creating the directory); `handle_session_started` skips directory creation and just logs the path. +- `register_recording_subscriber` gains the matching `run_dir` kwarg and passes it through. + +**`ig_trader/scripts/run_portfolio.py`** +- `--name` arg description updated to document the output-directory-naming behaviour (falls back to timestamp when omitted). +- `--warmup-bars N` arg added (`dest=warmup_bars`). Enables lazy loading when set. +- Both args forwarded to `run_portfolio_backtest`. + +### Tests added + +- `tests/execution/backtest/test_dukascopy_cache.py`: 9 new tests for `iter_dukascopy_candles` — single day, parity with eager `read_dukascopy_candles`, empty range, invalid `price_side` / `period` raise eagerly, ask side, 15MIN resampling, missing-day skip, laziness check. +- `tests/execution/backtest/test_streamer.py` (new file, 7 tests): `CandleSeries` with a generator, single-series order, two-instrument interleaving, 5-instrument k-way sort, lazy generator consumption, `from_lazy_sources` history and streamer behaviour. + +**514 tradedesk tests pass, 223 ig_trader tests pass.** + +### Usage + +```bash +# Named run with lazy loading (first log line appears immediately): +python -m scripts.run_portfolio \ + --target backtest \ + --from 2022-01-01 --to 2026-01-01 \ + --name my-run \ + --warmup-bars 300 +``` + +```python +# Programmatic equivalent: +run_portfolio_backtest( + cfg=cfg, + raw_cfg=raw_cfg, + specs=specs, + log_level="INFO", + run_name="my-run", # output written to back_tests/my-run/ + warmup_bars=300, # pre-load first 300 base-period candles per instrument +) +``` + +`warmup_bars=300` with `base_period="1MIN"` pre-loads ~300 1MIN candles per instrument into `_history` for strategy warmup. The remainder of the date range is streamed lazily. Memory stays O(k) where k is the number of instruments, rather than O(N × k). + +### Design notes + +- The approach is fully backward-compatible: passing `warmup_bars=None` (the default) preserves existing eager behaviour with zero code-path changes for existing callers. +- The k-way merge starts from the beginning of the date range (i.e. it does not gate on `SessionReadyEvent`). This is correct because `BacktestStreamer` runs after `SessionStartedEvent` / `SessionReadyEvent` have already fired in `BasePortfolio.run()`. Warmup (`get_historical_candles`) and streaming are already fully separate lifecycle phases. +- The warmup `_history` slice represents the start of the backtest period rather than the end (the previous eager approach seeded indicators from the final N bars of the full dataset — a subtle correctness issue for long backtests that this implementation resolves). +- Root cause of the silent startup delay: logging was deferred to a `SessionStartedEvent` handler so the subscriber could supply the timestamped directory to the file handler. This fired inside `run_portfolio()`, after all data loading and index building. Fix: compute the run directory eagerly from `run_name` (or timestamp), create it immediately, configure logging fully, then pass the directory to the subscriber via `run_dir` so it reuses rather than recreates it. + +# Cost +``` +Total cost: $6.56 +Total duration (API): 16m 44s +Total duration (wall): 6h 22m 51s +Total code changes: 687 lines added, 77 lines removed +Usage by model: +claude-sonnet-4-6: 68 input, 58.2k output, 5.2m cache read, 380.4k cache write ($6.44) +claude-haiku-4-5: 47 input, 5.4k output, 272.4k cache read, 49.5k cache write ($0.1160) +``` diff --git a/docs/briefs/04-add-control-equity-graph.md b/docs/briefs/04-add-control-equity-graph.md new file mode 100644 index 0000000..54845b4 --- /dev/null +++ b/docs/briefs/04-add-control-equity-graph.md @@ -0,0 +1,43 @@ +Always read and follow instructions in `CLAUDE.md` in the project root before processing the brief. + +# Add control line to equity graph on analysis report + +## Context + +`tradedesk/recording/report.py` generates a human readable report after each backtest and includes a number of generated charts. One of these charts shows the equity curve built up from the `equity_daily.csv` file (lines 715-791 of `report.py`). + +## Role + +In this session you will take on a role described in https://github.com/radiusred/.github/doc/agent-roles/engineer.md (or the local equivalent repository clone) + +## Goal + +The goal of this session is to enhance the equity curve chart by adding a second line showing a control instrument for comparison. This instrument will be the FTSE 100. + +The goal is successfully achieved when the chart shows the equity curve from the backtest in the current colour (or any strong colour) and on the same axis, with the same scale, a line showing the equivalent FTSE performance in a muted grey (hex colour #888). + + +## Approach + + - For the same period (`--from` and `--to`) as the backtest, calculate the daily increment/decrement of the FTSE + - this is a normalised line that always starts at 0 (zero) on the `--from` date of the backtest. + - each subsequent day is the difference between the current day's close price and the previous day's close. + - the net effect is an equity curve that models what would have happened if a LONG position of size 1.0 had been opened on day 1 of the test and closed on the final day of the test. + - plot this series on the same chart that is generated for the portfolio's equity_daily series + - use chart data available in the local dukascopy cache (`--cache-dir`) with an instrument name of `GBRIDXGBP` + +## Output + +Four files modified across two projects: + +**`tradedesk`:** + +- `tradedesk/execution/backtest/__init__.py` — exported `read_dukascopy_candles` +- `tradedesk/recording/report.py` — added `cache_dir: Path | None = None` to `_prepare_graphs` and `generate_analysis_report`; equity curve section now loads GBRIDXGBP daily candles when `cache_dir` is provided, computes a normalised cumulative series starting at 0, and plots it as a second line in `#888888` +- `tradedesk/recording/subscriber.py` — added `cache_dir` parameter to `RecordingSubscriber.__init__` and `register_recording_subscriber`; passes it through to `generate_analysis_report` + +**`ig_trader`:** + +- `ig_trader/session_runners.py` — passes `cache_dir=cfg.cache_dir` to `register_recording_subscriber` in the backtest runner + +**Logic:** daily close prices are resampled from GBRIDXGBP 1-minute Dukascopy data; the control series is `[0, Δclose₁, Δclose₁+Δclose₂, ...]`, equivalent to holding a size-1 long position from the first day of the backtest. The date range is derived from the equity curve's own timestamps so no additional parameters are needed at the call site. Failures silently warn and omit the control line rather than crashing the report. diff --git a/docs/examples/ig_smoke_trade.py b/docs/examples/ig_smoke_trade.py index 17813e4..dc10d8b 100644 --- a/docs/examples/ig_smoke_trade.py +++ b/docs/examples/ig_smoke_trade.py @@ -49,7 +49,9 @@ async def _get_positions(client: IGClient) -> dict[str, Any]: async def main() -> int: parser = argparse.ArgumentParser() parser.add_argument("--epic", required=True, help="IG EPIC to trade") - parser.add_argument("--size", type=float, default=1.0, help="Size (stake for SB, contracts for CFD)") + parser.add_argument( + "--size", type=float, default=1.0, help="Size (stake for SB, contracts for CFD)" + ) parser.add_argument("--open-direction", choices=["BUY", "SELL"], default="BUY") parser.add_argument("--log-level", default="INFO") parser.add_argument("--skip-positions", action="store_true", help="Skip GET /positions checks") @@ -86,7 +88,9 @@ async def main() -> int: before = await _get_positions(client) log.info("Positions (before):\n%s", _pretty(before)) - log.info("Placing OPEN %s %s size=%s force_open=%s", epic, open_dir, size, args.force_open) + log.info( + "Placing OPEN %s %s size=%s force_open=%s", epic, open_dir, size, args.force_open + ) open_confirm = await client.place_market_order_confirmed( epic=epic, direction=open_dir, @@ -104,7 +108,13 @@ async def main() -> int: log.error("OPEN rejected: %s", reason) return 1 - log.info("Placing CLOSE %s %s size=%s force_open=%s (netting unless force_open=True)", epic, close_dir, size, args.force_open) + log.info( + "Placing CLOSE %s %s size=%s force_open=%s (netting unless force_open=True)", + epic, + close_dir, + size, + args.force_open, + ) close_confirm = await client.place_market_order_confirmed( epic=epic, direction=close_dir, @@ -117,7 +127,9 @@ async def main() -> int: log.info("CLOSE confirm:\n%s", _pretty(close_confirm)) if (close_confirm.get("dealStatus") or "").upper() != "ACCEPTED": - reason = close_confirm.get("reason") or close_confirm.get("rejectReason") or "UNKNOWN" + reason = ( + close_confirm.get("reason") or close_confirm.get("rejectReason") or "UNKNOWN" + ) log.error("CLOSE rejected: %s", reason) return 1 diff --git a/pyproject.toml b/pyproject.toml index 7c55fdf..9941338 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -28,6 +28,12 @@ dependencies = [ "python-dotenv>=1.0", "numpy>=2.4.0", "jinja2>=3.1.0", + "pandas>=3.0.1", + "zstandard>=0.25", + "seaborn>=0.13.2", + "matplotlib>=3.10.8", + "pandas-stubs[dev]>=3.0.0.260204", + "types-seaborn[dev]>=0.13.2.20251221", ] [project.optional-dependencies] @@ -39,6 +45,7 @@ dev = [ "responses>=0.25", "pytest-asyncio>=0.23", "pytest-cov>=7.0", + "llm-tldr[dev]>=1.5.2", ] [project.urls] diff --git a/tests/conftest.py b/tests/conftest.py index 485d767..f012218 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -88,12 +88,8 @@ def mock_aiohttp_session(mock_http_response): def mock_lightstreamer(): """Mock Lightstreamer client and subscription.""" with ( - patch( - "tradedesk.execution.ig.price_streamer.LightstreamerClient" - ) as mock_ls_client_class, - patch( - "tradedesk.execution.ig.price_streamer.Subscription" - ) as mock_subscription_class, + patch("tradedesk.execution.ig.price_streamer.LightstreamerClient") as mock_ls_client_class, + patch("tradedesk.execution.ig.price_streamer.Subscription") as mock_subscription_class, ): # Create mock LightstreamerClient instance mock_ls_client = MagicMock() diff --git a/tests/execution/backtest/test_backtest_csv.py b/tests/execution/backtest/test_backtest_csv.py index 62fe3d2..d76bc83 100644 --- a/tests/execution/backtest/test_backtest_csv.py +++ b/tests/execution/backtest/test_backtest_csv.py @@ -6,9 +6,8 @@ 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 from tradedesk.marketdata.instrument import MarketData -from tradedesk.marketdata.subscriptions import ChartSubscription, MarketSubscription +from tradedesk.marketdata.subscriptions import MarketSubscription from tradedesk.strategy.base import BaseStrategy @@ -41,52 +40,6 @@ async def test_backtest_trade_has_timestamp(): assert client.trades[0].timestamp == "2025-01-01T00:00:00Z" -def test_backtest_from_csv_replays_and_trades(tmp_path: Path): - csv_path = tmp_path / "candles.csv" - csv_path.write_text( - "timestamp,open,high,low,close,volume\n" - "2025-12-28T00:00:00Z,10,10,10,10,0\n" - "2025-12-28T00:05:00Z,11,11,11,11,0\n" - "2025-12-28T00:10:00Z,12,12,12,12,0\n" - ) - - created = {} - - class TradeOnFirstLast(BaseStrategy): - SUBSCRIPTIONS = [ChartSubscription("EPIC", "5MINUTE")] - - async def on_price_update(self, market_data: MarketData): - pass - - async def on_candle_close(self, candle_close: CandleClosedEvent): - if candle_close.candle.close == 10: - await self.client.place_market_order( - instrument=candle_close.instrument, direction="BUY", size=1.0 - ) - if candle_close.candle.close == 12: - await self.client.place_market_order( - instrument=candle_close.instrument, direction="SELL", size=1.0 - ) - await super().on_candle_close(candle_close) - - def factory(): - c = BacktestClient.from_csv(csv_path, instrument="EPIC", period="5MINUTE") - created["client"] = c - return c - - with patch("sys.exit") as _: - run_portfolio( - portfolio_factory=lambda c: SimplePortfolio(c, TradeOnFirstLast(c)), - client_factory=factory, - setup_logging=False, - ) - - client: BacktestClient = created["client"] # type: ignore[assignment] - assert len(client.trades) == 2 - assert client.realised_pnl == 2.0 - assert client.positions == {} - - def test_backtest_market_csvs_drive_price_updates_and_signals(tmp_path: Path): gbp = tmp_path / "gbp.csv" eur = tmp_path / "eur.csv" @@ -130,9 +83,7 @@ class MomentumLike(BaseStrategy): def __init__(self, client, lookback=10): super().__init__(client) self.lookback = lookback - self.prices: dict[str, list[float]] = { - s.instrument: [] for s in self.SUBSCRIPTIONS - } + self.prices: dict[str, list[float]] = {s.instrument: [] for s in self.SUBSCRIPTIONS} self.signals: list[tuple[str, str]] = [] async def on_price_update(self, md: MarketData): @@ -166,8 +117,6 @@ def factory(): setup_logging=False, ) - # Verify at least one UP for GBP and one DOWN for EUR occurred - # (The strategy instance is internal; so assert indirectly via client mark prices after replay) client = created["client"] assert client._mark_price["CS.D.GBPUSD.TODAY.IP"] > 1.25 assert client._mark_price["CS.D.EURUSD.TODAY.IP"] < 1.10 diff --git a/tests/execution/backtest/test_backtest_provider.py b/tests/execution/backtest/test_backtest_provider.py index 19cb048..4587b1b 100644 --- a/tests/execution/backtest/test_backtest_provider.py +++ b/tests/execution/backtest/test_backtest_provider.py @@ -104,9 +104,7 @@ def factory(): async def test_backtest_rejects_direction_enum_without_conversion(): """Test that passing Direction enum directly to place_market_order is rejected.""" candles = [ - Candle( - timestamp="2025-12-28T00:00:00Z", open=100, high=100, low=100, close=100 - ), + Candle(timestamp="2025-12-28T00:00:00Z", open=100, high=100, low=100, close=100), ] client = BacktestClient.from_history({("TEST", "1MINUTE"): candles}) await client.start() @@ -124,12 +122,8 @@ async def test_backtest_rejects_direction_enum_without_conversion(): async def test_backtest_accepts_direction_with_to_order_side(): """Test that using Direction.to_order_side() works correctly.""" candles = [ - Candle( - timestamp="2025-12-28T00:00:00Z", open=100, high=100, low=100, close=100 - ), - Candle( - timestamp="2025-12-28T00:05:00Z", open=110, high=110, low=110, close=110 - ), + Candle(timestamp="2025-12-28T00:00:00Z", open=100, high=100, low=100, close=100), + Candle(timestamp="2025-12-28T00:05:00Z", open=110, high=110, low=110, close=110), ] client = BacktestClient.from_history({("TEST", "5MINUTE"): candles}) await client.start() diff --git a/tests/execution/backtest/test_backtest_runner.py b/tests/execution/backtest/test_backtest_runner.py index 7218550..d964fae 100644 --- a/tests/execution/backtest/test_backtest_runner.py +++ b/tests/execution/backtest/test_backtest_runner.py @@ -1,5 +1,6 @@ """Tests for tradedesk.execution.backtest.runner.""" +from datetime import date from pathlib import Path from unittest.mock import AsyncMock, MagicMock, patch @@ -39,12 +40,23 @@ def mock_compute_metrics(): yield mock +def _make_spec(cache_dir: Path = Path("/cache")) -> BacktestSpec: + return BacktestSpec( + instrument="TEST", + period="1MIN", + cache_dir=cache_dir, + symbol="EURUSD", + date_from=date(2025, 1, 1), + date_to=date(2025, 1, 31), + ) + + @pytest.mark.asyncio async def test_run_backtest_spread_adjustment( mock_client_cls, mock_register_subscriber, mock_compute_metrics, tmp_path ): """Test that half_spread_adjustment modifies candle OHLC.""" - client_instance = mock_client_cls.from_csv.return_value + client_instance = mock_client_cls.from_dukascopy_cache.return_value client_instance.start = AsyncMock() candle = MagicMock(spec=Candle) @@ -67,19 +79,23 @@ async def test_run_backtest_spread_adjustment( spec = BacktestSpec( instrument="TEST", period="1MIN", - candle_csv=Path("dummy.csv"), + cache_dir=tmp_path, + symbol="EURUSD", + date_from=date(2025, 1, 1), + date_to=date(2025, 1, 31), half_spread_adjustment=0.5, ) 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"): - + 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"), + ): await run_backtest(spec=spec, out_dir=tmp_path, portfolio_factory=lambda c: mock_portfolio) assert candle.open == 100.5 @@ -93,29 +109,26 @@ async def test_run_backtest_event_driven_recording( 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 + client_instance = mock_client_cls.from_dukascopy_cache.return_value client_instance.start = AsyncMock() streamer = MagicMock() streamer._candle_series = [] streamer.run = AsyncMock() client_instance.get_streamer.return_value = streamer - spec = BacktestSpec( - instrument="TEST", period="1MIN", candle_csv=Path("dummy.csv") - ) + spec = _make_spec(tmp_path) 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"): - - await run_backtest( - spec=spec, out_dir=tmp_path, portfolio_factory=lambda c: mock_portfolio - ) + 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"), + ): + await run_backtest(spec=spec, out_dir=tmp_path, portfolio_factory=lambda c: mock_portfolio) mock_equity_recorder.assert_called_once() mock_excursion.assert_called_once() @@ -127,24 +140,25 @@ async def test_run_backtest_metrics_output( 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 + client_instance = mock_client_cls.from_dukascopy_cache.return_value client_instance.start = AsyncMock() streamer = MagicMock() streamer._candle_series = [] streamer.run = AsyncMock() client_instance.get_streamer.return_value = streamer - spec = BacktestSpec(instrument="TEST", period="1MIN", candle_csv=Path("dummy.csv")) + spec = _make_spec(tmp_path) 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"): - + 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"), + ): result = await run_backtest( spec=spec, out_dir=tmp_path, portfolio_factory=lambda c: mock_portfolio ) @@ -154,3 +168,18 @@ async def test_run_backtest_metrics_output( assert result.final_equity == 10500.0 assert result.win_rate == 0.6 assert result.avg_hold_minutes == 15.0 + + +def test_backtest_spec_defaults(): + spec = BacktestSpec( + instrument="GBPUSD", + period="15MIN", + cache_dir=Path("/data/cache"), + symbol="GBPUSD", + date_from=date(2025, 1, 1), + date_to=date(2025, 12, 31), + ) + assert spec.price_side == "bid" + assert spec.size == 1.0 + assert spec.half_spread_adjustment == 0.0 + assert spec.reporting_scale == 1.0 diff --git a/tests/execution/backtest/test_dukascopy_cache.py b/tests/execution/backtest/test_dukascopy_cache.py new file mode 100644 index 0000000..205263a --- /dev/null +++ b/tests/execution/backtest/test_dukascopy_cache.py @@ -0,0 +1,482 @@ +"""Tests for tradedesk.execution.backtest.dukascopy.""" + +from __future__ import annotations + +from datetime import date +from pathlib import Path + +import pandas as pd +import pytest +import zstandard as zstd + +from tradedesk.execution.backtest.client import BacktestClient +from tradedesk.execution.backtest.dukascopy import ( + _candle_path, + _check_old_format, + _iter_days, + _load_daily_candles, + _period_to_pandas_rule, + iter_dukascopy_candles, + read_dukascopy_candles, +) + +# --------------------------------------------------------------------------- +# Helpers +# --------------------------------------------------------------------------- + + +def _make_candle_csv(rows: list[tuple[str, float, float, float, float, float]]) -> str: + lines = ["timestamp,open,high,low,close,volume"] + for ts, o, h, l, c, v in rows: + lines.append(f"{ts},{o},{h},{l},{c},{v}") + return "\n".join(lines) + "\n" + + +def _write_candle_file( + path: Path, rows: list[tuple[str, float, float, float, float, float]] +) -> None: + """Write a compressed daily candle file.""" + path.parent.mkdir(parents=True, exist_ok=True) + content = _make_candle_csv(rows).encode("utf-8") + cctx = zstd.ZstdCompressor(level=3) + path.write_bytes(cctx.compress(content)) + + +def _sample_candle_rows(day: date) -> list[tuple[str, float, float, float, float, float]]: + """Two 1-min candles for a given day.""" + return [ + (f"{day.isoformat()} 00:00:00+00:00", 1.1000, 1.1005, 1.0998, 1.1001, 1.7), + (f"{day.isoformat()} 00:01:00+00:00", 1.1001, 1.1008, 1.1000, 1.1005, 2.3), + ] + + +# --------------------------------------------------------------------------- +# _iter_days +# --------------------------------------------------------------------------- + + +def test_iter_days_single() -> None: + assert _iter_days(date(2025, 1, 5), date(2025, 1, 5)) == [date(2025, 1, 5)] + + +def test_iter_days_range() -> None: + result = _iter_days(date(2025, 1, 1), date(2025, 1, 3)) + assert result == [date(2025, 1, 1), date(2025, 1, 2), date(2025, 1, 3)] + + +def test_iter_days_month_boundary() -> None: + result = _iter_days(date(2025, 1, 30), date(2025, 2, 2)) + assert result == [ + date(2025, 1, 30), + date(2025, 1, 31), + date(2025, 2, 1), + date(2025, 2, 2), + ] + + +# --------------------------------------------------------------------------- +# _candle_path +# --------------------------------------------------------------------------- + + +def test_candle_path_january() -> None: + cache = Path("/cache") + assert _candle_path(cache, "EURUSD", date(2025, 1, 5), "bid") == Path( + "/cache/EURUSD/2025/00/05_bid.csv.zst" + ) + assert _candle_path(cache, "EURUSD", date(2025, 1, 5), "ask") == Path( + "/cache/EURUSD/2025/00/05_ask.csv.zst" + ) + + +def test_candle_path_december() -> None: + cache = Path("/cache") + assert _candle_path(cache, "USDJPY", date(2025, 12, 31), "bid") == Path( + "/cache/USDJPY/2025/11/31_bid.csv.zst" + ) + + +def test_candle_path_year_boundary() -> None: + cache = Path("/cache") + assert _candle_path(cache, "GBPUSD", date(2026, 1, 1), "ask") == Path( + "/cache/GBPUSD/2026/00/01_ask.csv.zst" + ) + + +# --------------------------------------------------------------------------- +# _period_to_pandas_rule +# --------------------------------------------------------------------------- + + +@pytest.mark.parametrize( + "period,expected", + [ + ("1MIN", "1min"), + ("15MIN", "15min"), + ("5MINUTE", "5min"), + ("1MINUTE", "1min"), + ("1H", "1h"), + ("4H", "4h"), + ("1HOUR", "1h"), + ("1D", "1D"), + ("1DAY", "1D"), + ("1W", "1W"), + ("1WEEK", "1W"), + ], +) +def test_period_to_pandas_rule(period: str, expected: str) -> None: + assert _period_to_pandas_rule(period) == expected + + +def test_period_to_pandas_rule_invalid() -> None: + with pytest.raises(ValueError, match="Cannot convert period"): + _period_to_pandas_rule("UNKNOWN") + + +# --------------------------------------------------------------------------- +# _check_old_format +# --------------------------------------------------------------------------- + + +def test_check_old_format_no_directory(tmp_path: Path) -> None: + """Missing directory is fine — no bi5 files possible.""" + _check_old_format(tmp_path, "EURUSD", date(2025, 1, 5)) + + +def test_check_old_format_no_bi5(tmp_path: Path) -> None: + day_dir = tmp_path / "EURUSD" / "2025" / "00" / "05" + day_dir.mkdir(parents=True) + (day_dir / "some_other_file.txt").touch() + _check_old_format(tmp_path, "EURUSD", date(2025, 1, 5)) + + +def test_check_old_format_with_bi5_exits(tmp_path: Path) -> None: + day_dir = tmp_path / "EURUSD" / "2025" / "00" / "05" + day_dir.mkdir(parents=True) + (day_dir / "00h_ticks.bi5").touch() + with pytest.raises(SystemExit): + _check_old_format(tmp_path, "EURUSD", date(2025, 1, 5)) + + +# --------------------------------------------------------------------------- +# _load_daily_candles +# --------------------------------------------------------------------------- + + +def test_load_daily_candles_missing_returns_none(tmp_path: Path) -> None: + path = tmp_path / "missing.csv.zst" + assert _load_daily_candles(path) is None + + +def test_load_daily_candles_compressed(tmp_path: Path) -> None: + day = date(2025, 6, 15) + path = _candle_path(tmp_path, "EURUSD", day, "bid") + _write_candle_file(path, _sample_candle_rows(day)) + + df = _load_daily_candles(path) + assert df is not None + assert not df.empty + assert len(df) == 2 + assert list(df.columns) == ["open", "high", "low", "close", "volume"] + assert df.index.tz is not None # UTC-aware + + +def test_load_daily_candles_ohlcv_values(tmp_path: Path) -> None: + day = date(2025, 6, 15) + path = _candle_path(tmp_path, "EURUSD", day, "ask") + rows = _sample_candle_rows(day) + _write_candle_file(path, rows) + + df = _load_daily_candles(path) + assert df is not None + assert abs(float(df.iloc[0]["open"]) - 1.1000) < 1e-9 + assert abs(float(df.iloc[0]["high"]) - 1.1005) < 1e-9 + + +def test_load_daily_candles_corrupt_returns_none(tmp_path: Path) -> None: + path = tmp_path / "bad.csv.zst" + path.write_bytes(b"not valid zstd data") + assert _load_daily_candles(path) is None + + +# --------------------------------------------------------------------------- +# read_dukascopy_candles +# --------------------------------------------------------------------------- + + +def test_read_dukascopy_candles_single_day(tmp_path: Path) -> None: + day = date(2025, 6, 15) + path = _candle_path(tmp_path, "EURUSD", day, "bid") + _write_candle_file(path, _sample_candle_rows(day)) + + candles = read_dukascopy_candles(tmp_path, "EURUSD", "1MIN", day, day) + assert len(candles) == 2 + assert candles[0].timestamp.endswith("Z") + assert candles[0].open > 0 + assert candles[0].high >= candles[0].open + assert candles[0].low <= candles[0].open + + +def test_read_dukascopy_candles_ask_side(tmp_path: Path) -> None: + day = date(2025, 6, 15) + bid_path = _candle_path(tmp_path, "EURUSD", day, "bid") + ask_path = _candle_path(tmp_path, "EURUSD", day, "ask") + # Write different values for bid vs ask so we can tell which was loaded + bid_rows = _sample_candle_rows(day) + ask_rows = [ + (ts, o + 0.0002, h + 0.0002, lo + 0.0002, c + 0.0002, v) for ts, o, h, lo, c, v in bid_rows + ] + _write_candle_file(bid_path, bid_rows) + _write_candle_file(ask_path, ask_rows) + + candles = read_dukascopy_candles(tmp_path, "EURUSD", "1MIN", day, day, price_side="ask") + assert abs(candles[0].open - 1.1002) < 1e-9 + + +def test_read_dukascopy_candles_multi_day(tmp_path: Path) -> None: + for d in [date(2025, 6, 15), date(2025, 6, 16), date(2025, 6, 17)]: + path = _candle_path(tmp_path, "EURUSD", d, "bid") + _write_candle_file(path, _sample_candle_rows(d)) + + candles = read_dukascopy_candles( + tmp_path, "EURUSD", "1MIN", date(2025, 6, 15), date(2025, 6, 17) + ) + assert len(candles) == 6 # 2 candles × 3 days + + +def test_read_dukascopy_candles_missing_day_skipped(tmp_path: Path) -> None: + """A missing day (market closed) is silently skipped.""" + day1 = date(2025, 6, 15) + day3 = date(2025, 6, 17) + for d in [day1, day3]: + path = _candle_path(tmp_path, "EURUSD", d, "bid") + _write_candle_file(path, _sample_candle_rows(d)) + + candles = read_dukascopy_candles(tmp_path, "EURUSD", "1MIN", day1, day3) + assert len(candles) == 4 # 2 candles × 2 days + + +def test_read_dukascopy_candles_no_data_raises(tmp_path: Path) -> None: + with pytest.raises(ValueError, match="No candle data found"): + read_dukascopy_candles(tmp_path, "EURUSD", "1MIN", date(2025, 6, 15), date(2025, 6, 15)) + + +def test_read_dukascopy_candles_invalid_side_raises(tmp_path: Path) -> None: + with pytest.raises(ValueError, match="price_side"): + read_dukascopy_candles( + tmp_path, + "EURUSD", + "1MIN", + date(2025, 6, 15), + date(2025, 6, 15), + price_side="mid", + ) + + +def test_read_dukascopy_candles_old_format_exits(tmp_path: Path) -> None: + day = date(2025, 6, 15) + day_dir = tmp_path / "EURUSD" / "2025" / "05" / "15" + day_dir.mkdir(parents=True) + (day_dir / "00h_ticks.bi5").touch() + + with pytest.raises(SystemExit): + read_dukascopy_candles(tmp_path, "EURUSD", "1MIN", day, day) + + +def test_read_dukascopy_candles_timestamps_ordered(tmp_path: Path) -> None: + for d in [date(2025, 6, 15), date(2025, 6, 16)]: + path = _candle_path(tmp_path, "EURUSD", d, "bid") + _write_candle_file(path, _sample_candle_rows(d)) + + candles = read_dukascopy_candles( + tmp_path, "EURUSD", "1MIN", date(2025, 6, 15), date(2025, 6, 16) + ) + timestamps = [c.timestamp for c in candles] + assert timestamps == sorted(timestamps) + + +def test_read_dukascopy_candles_aggregates_to_15min(tmp_path: Path) -> None: + """A day with 30 1-min candles resampled to 15MIN yields 2 candles.""" + day = date(2025, 6, 15) + rows = [ + ( + f"{day.isoformat()} {h:02d}:{m:02d}:00+00:00", + 1.1000 + m * 0.0001, + 1.1010 + m * 0.0001, + 1.0990 + m * 0.0001, + 1.1005 + m * 0.0001, + 1.0, + ) + for h in [0] + for m in range(30) + ] + path = _candle_path(tmp_path, "EURUSD", day, "bid") + _write_candle_file(path, rows) + + candles = read_dukascopy_candles(tmp_path, "EURUSD", "15MIN", day, day) + assert len(candles) == 2 + + +# --------------------------------------------------------------------------- +# BacktestClient.from_dukascopy_cache integration +# --------------------------------------------------------------------------- + + +def test_backtest_client_from_dukascopy_cache(tmp_path: Path) -> None: + day = date(2025, 6, 15) + path = _candle_path(tmp_path, "EURUSD", day, "bid") + _write_candle_file(path, _sample_candle_rows(day)) + + client = BacktestClient.from_dukascopy_cache( + tmp_path, + symbol="EURUSD", + instrument="CS.D.EURUSD.TODAY.IP", + period="1MIN", + date_from=day, + date_to=day, + ) + candles = client._history[("CS.D.EURUSD.TODAY.IP", "1MIN")] + assert len(candles) == 2 + + +def test_backtest_client_from_dukascopy_cache_ask_side(tmp_path: Path) -> None: + day = date(2025, 6, 15) + ask_path = _candle_path(tmp_path, "EURUSD", day, "ask") + ask_rows = [ + (ts, o + 0.0002, h + 0.0002, lo + 0.0002, c + 0.0002, v) + for ts, o, h, lo, c, v in _sample_candle_rows(day) + ] + _write_candle_file(ask_path, ask_rows) + + client = BacktestClient.from_dukascopy_cache( + tmp_path, + symbol="EURUSD", + instrument="CS.D.EURUSD.TODAY.IP", + period="1MIN", + date_from=day, + date_to=day, + price_side="ask", + ) + candles = client._history[("CS.D.EURUSD.TODAY.IP", "1MIN")] + assert len(candles) == 2 + assert abs(candles[0].open - 1.1002) < 1e-9 + + +# --------------------------------------------------------------------------- +# iter_dukascopy_candles +# --------------------------------------------------------------------------- + + +def test_iter_dukascopy_candles_single_day(tmp_path: Path) -> None: + day = date(2025, 6, 15) + path = _candle_path(tmp_path, "EURUSD", day, "bid") + _write_candle_file(path, _sample_candle_rows(day)) + + candles = list(iter_dukascopy_candles(tmp_path, "EURUSD", "1MIN", day, day)) + assert len(candles) == 2 + assert candles[0].timestamp.endswith("Z") + assert candles[0].open > 0 + + +def test_iter_dukascopy_candles_yields_same_as_read(tmp_path: Path) -> None: + """iter_dukascopy_candles and read_dukascopy_candles must produce identical results.""" + for d in [date(2025, 6, 15), date(2025, 6, 16), date(2025, 6, 17)]: + path = _candle_path(tmp_path, "EURUSD", d, "bid") + _write_candle_file(path, _sample_candle_rows(d)) + + eager = read_dukascopy_candles(tmp_path, "EURUSD", "1MIN", date(2025, 6, 15), date(2025, 6, 17)) + lazy = list( + iter_dukascopy_candles(tmp_path, "EURUSD", "1MIN", date(2025, 6, 15), date(2025, 6, 17)) + ) + + assert len(eager) == len(lazy) + for e, l in zip(eager, lazy): + assert e.timestamp == l.timestamp + assert abs(e.open - l.open) < 1e-9 + assert abs(e.close - l.close) < 1e-9 + + +def test_iter_dukascopy_candles_empty_range(tmp_path: Path) -> None: + """No files in range produces an empty iterator (no exception).""" + candles = list( + iter_dukascopy_candles(tmp_path, "EURUSD", "1MIN", date(2025, 6, 15), date(2025, 6, 15)) + ) + assert candles == [] + + +def test_iter_dukascopy_candles_invalid_side_raises(tmp_path: Path) -> None: + with pytest.raises(ValueError, match="price_side"): + # Raises immediately (before iteration) because validation is eager. + iter_dukascopy_candles( + tmp_path, + "EURUSD", + "1MIN", + date(2025, 6, 15), + date(2025, 6, 15), + price_side="mid", + ) + + +def test_iter_dukascopy_candles_invalid_period_raises(tmp_path: Path) -> None: + with pytest.raises(ValueError, match="Cannot convert period"): + iter_dukascopy_candles(tmp_path, "EURUSD", "UNKNOWN", date(2025, 6, 15), date(2025, 6, 15)) + + +def test_iter_dukascopy_candles_ask_side(tmp_path: Path) -> None: + day = date(2025, 6, 15) + ask_path = _candle_path(tmp_path, "EURUSD", day, "ask") + ask_rows = [ + (ts, o + 0.0002, h + 0.0002, lo + 0.0002, c + 0.0002, v) + for ts, o, h, lo, c, v in _sample_candle_rows(day) + ] + _write_candle_file(ask_path, ask_rows) + + candles = list(iter_dukascopy_candles(tmp_path, "EURUSD", "1MIN", day, day, price_side="ask")) + assert len(candles) == 2 + assert abs(candles[0].open - 1.1002) < 1e-9 + + +def test_iter_dukascopy_candles_15min(tmp_path: Path) -> None: + """A day with 30 1-min candles resampled to 15MIN yields 2 candles lazily.""" + day = date(2025, 6, 15) + rows = [ + ( + f"{day.isoformat()} {h:02d}:{m:02d}:00+00:00", + 1.1000 + m * 0.0001, + 1.1010 + m * 0.0001, + 1.0990 + m * 0.0001, + 1.1005 + m * 0.0001, + 1.0, + ) + for h in [0] + for m in range(30) + ] + path = _candle_path(tmp_path, "EURUSD", day, "bid") + _write_candle_file(path, rows) + + candles = list(iter_dukascopy_candles(tmp_path, "EURUSD", "15MIN", day, day)) + assert len(candles) == 2 + + +def test_iter_dukascopy_candles_missing_day_skipped(tmp_path: Path) -> None: + day1 = date(2025, 6, 15) + day3 = date(2025, 6, 17) + for d in [day1, day3]: + path = _candle_path(tmp_path, "EURUSD", d, "bid") + _write_candle_file(path, _sample_candle_rows(d)) + + candles = list(iter_dukascopy_candles(tmp_path, "EURUSD", "1MIN", day1, day3)) + assert len(candles) == 4 # 2 candles × 2 days + + +def test_iter_dukascopy_candles_is_lazy(tmp_path: Path) -> None: + """Verify the generator does not materialise all candles before the first yield.""" + for d in [date(2025, 6, 15), date(2025, 6, 16)]: + path = _candle_path(tmp_path, "EURUSD", d, "bid") + _write_candle_file(path, _sample_candle_rows(d)) + + gen = iter_dukascopy_candles(tmp_path, "EURUSD", "1MIN", date(2025, 6, 15), date(2025, 6, 16)) + # Must be iterable but not a pre-materialised list + assert hasattr(gen, "__iter__") and hasattr(gen, "__next__") + first = next(gen) + assert first.timestamp.startswith("2025-06-15") diff --git a/tests/execution/backtest/test_streamer.py b/tests/execution/backtest/test_streamer.py new file mode 100644 index 0000000..c52a5a2 --- /dev/null +++ b/tests/execution/backtest/test_streamer.py @@ -0,0 +1,217 @@ +"""Tests for BacktestStreamer k-way merge and lazy candle iteration.""" + +from __future__ import annotations + +import pytest + +from tradedesk.execution.backtest.client import BacktestClient +from tradedesk.execution.backtest.streamer import BacktestStreamer, CandleSeries, MarketSeries +from tradedesk.marketdata import CandleClosedEvent +from tradedesk.types import Candle + + +# --------------------------------------------------------------------------- +# Helpers +# --------------------------------------------------------------------------- + + +def _candle(ts: str, close: float = 1.0) -> Candle: + return Candle(timestamp=ts, open=close, high=close, low=close, close=close, volume=1.0) + + +def _make_client() -> BacktestClient: + return BacktestClient.from_history({}) + + +# --------------------------------------------------------------------------- +# CandleSeries accepts Iterable (generator) +# --------------------------------------------------------------------------- + + +def test_candle_series_accepts_generator() -> None: + """CandleSeries.candles may be a generator, not just a list.""" + + def _gen(): + yield _candle("2025-01-01T00:00:00Z") + yield _candle("2025-01-01T00:01:00Z") + + series = CandleSeries(instrument="TEST", period="1MIN", candles=_gen()) + events_seen = list(series.candles) + assert len(events_seen) == 2 + + +# --------------------------------------------------------------------------- +# BacktestStreamer: single series ordering +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_streamer_single_series_in_order() -> None: + """A single instrument series is dispatched in chronological order.""" + candles = [ + _candle("2025-01-01T00:00:00Z", 1.0), + _candle("2025-01-01T00:01:00Z", 2.0), + _candle("2025-01-01T00:02:00Z", 3.0), + ] + series = CandleSeries(instrument="INST", period="1MIN", candles=candles) + client = _make_client() + streamer = BacktestStreamer(client, [series], []) + + received: list[CandleClosedEvent] = [] + + class _Consumer: + async def _handle_event(self, event): + received.append(event) + + await streamer.run(_Consumer()) + + assert len(received) == 3 + closes = [e.candle.close for e in received] + assert closes == [1.0, 2.0, 3.0] + + +# --------------------------------------------------------------------------- +# BacktestStreamer: k-way merge across instruments +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_streamer_two_instruments_interleaved() -> None: + """Events from two instruments are merged in timestamp order.""" + s1 = CandleSeries( + instrument="A", + period="1MIN", + candles=[ + _candle("2025-01-01T00:00:00Z", 10.0), + _candle("2025-01-01T00:02:00Z", 30.0), + ], + ) + s2 = CandleSeries( + instrument="B", + period="1MIN", + candles=[ + _candle("2025-01-01T00:01:00Z", 20.0), + _candle("2025-01-01T00:03:00Z", 40.0), + ], + ) + client = _make_client() + streamer = BacktestStreamer(client, [s1, s2], []) + + received: list[CandleClosedEvent] = [] + + class _Consumer: + async def _handle_event(self, event): + received.append(event) + + await streamer.run(_Consumer()) + + assert len(received) == 4 + closes = [e.candle.close for e in received] + assert closes == [10.0, 20.0, 30.0, 40.0] + + +@pytest.mark.asyncio +async def test_streamer_five_instruments_sorted() -> None: + """k-way merge produces a globally sorted stream for k=5 instruments.""" + import random + + rng = random.Random(42) + + # Assign each instrument a set of minute-offsets, then interleave manually + all_events: list[tuple[int, str, float]] = [] + series_list = [] + for i in range(5): + offsets = sorted(rng.sample(range(100), 10)) + candles = [_candle(f"2025-01-01T{o // 60:02d}:{o % 60:02d}:00Z", float(o)) for o in offsets] + series_list.append(CandleSeries(instrument=f"INST{i}", period="1MIN", candles=candles)) + for o in offsets: + all_events.append((o, f"INST{i}", float(o))) + + expected_closes = [c for _, __, c in sorted(all_events)] + + client = _make_client() + streamer = BacktestStreamer(client, series_list, []) + + received: list[CandleClosedEvent] = [] + + class _Consumer: + async def _handle_event(self, event): + received.append(event) + + await streamer.run(_Consumer()) + + assert len(received) == 50 + actual_closes = [e.candle.close for e in received] + assert actual_closes == expected_closes + + +# --------------------------------------------------------------------------- +# BacktestStreamer: lazy generator consumed once +# --------------------------------------------------------------------------- + + +@pytest.mark.asyncio +async def test_streamer_consumes_generator_lazily() -> None: + """A generator-backed CandleSeries is consumed without pre-materialisation.""" + consumed: list[str] = [] + + def _gen(): + for ts in ["2025-01-01T00:00:00Z", "2025-01-01T00:01:00Z"]: + consumed.append(ts) + yield _candle(ts) + + series = CandleSeries(instrument="TEST", period="1MIN", candles=_gen()) + client = _make_client() + streamer = BacktestStreamer(client, [series], []) + + # Before run, nothing consumed + assert consumed == [] + + received: list[CandleClosedEvent] = [] + + class _Consumer: + async def _handle_event(self, event): + received.append(event) + + await streamer.run(_Consumer()) + + assert len(received) == 2 + # All consumed during run (lazy) + assert len(consumed) == 2 + + +# --------------------------------------------------------------------------- +# BacktestClient.from_lazy_sources +# --------------------------------------------------------------------------- + + +def test_from_lazy_sources_history_served() -> None: + """get_historical_candles returns candles from the warmup history.""" + warmup = [_candle("2025-01-01T00:00:00Z", 1.5)] + history = {("INST", "1MIN"): warmup} + + def _gen(): + yield _candle("2025-01-01T00:00:00Z", 1.5) + yield _candle("2025-01-01T00:01:00Z", 2.5) + + series = CandleSeries(instrument="INST", period="1MIN", candles=_gen()) + client = BacktestClient.from_lazy_sources(history=history, candle_series=[series]) + + import asyncio + + fetched = asyncio.run(client.get_historical_candles("INST", "1MIN", 10)) + assert len(fetched) == 1 + assert abs(fetched[0].close - 1.5) < 1e-9 + + +def test_from_lazy_sources_streamer_uses_series() -> None: + """get_streamer() returns a streamer backed by the lazy candle_series.""" + history: dict = {} + candles = [_candle("2025-01-01T00:00:00Z")] + series = CandleSeries(instrument="INST", period="1MIN", candles=candles) + client = BacktestClient.from_lazy_sources(history=history, candle_series=[series]) + + streamer = client.get_streamer() + assert isinstance(streamer, BacktestStreamer) + assert len(streamer._candle_series) == 1 + assert streamer._candle_series[0].instrument == "INST" diff --git a/tests/execution/test_client.py b/tests/execution/test_client.py index b4d34e9..a54dac2 100644 --- a/tests/execution/test_client.py +++ b/tests/execution/test_client.py @@ -102,9 +102,7 @@ async def test_confirm_deal_polls_until_not_pending(self, mock_aiohttp_session): accepted = MagicMock() accepted.status = 200 - accepted.json = AsyncMock( - return_value={"dealStatus": "ACCEPTED", "dealId": "D1"} - ) + accepted.json = AsyncMock(return_value={"dealStatus": "ACCEPTED", "dealId": "D1"}) accepted.__aenter__ = AsyncMock(return_value=accepted) accepted.__aexit__ = AsyncMock(return_value=None) @@ -144,9 +142,7 @@ async def test_confirm_deal_retries_on_transient_500(self, mock_aiohttp_session) async def fake_request(_method, _path, **_kwargs): fake_request.calls += 1 if fake_request.calls == 1: - raise RuntimeError( - "IG request failed: HTTP 500: {'errorCode': None}" - ) + raise RuntimeError("IG request failed: HTTP 500: {'errorCode': None}") if fake_request.calls == 2: return {"dealStatus": "PENDING"} return {"dealStatus": "ACCEPTED", "dealId": "D1"} @@ -215,10 +211,7 @@ async def test_quantise_size_rounds_down_to_step(self, mock_aiohttp_session): assert await client.quantise_size("CS.D.EURUSD.TODAY.IP", 1.0) == 1.0 assert await client.quantise_size("CS.D.EURUSD.TODAY.IP", 1.24) == 1.2 assert await client.quantise_size("CS.D.EURUSD.TODAY.IP", 1.55) == 1.5 - assert ( - await client.quantise_size("CS.D.EURUSD.TODAY.IP", 1.759110721932789) - == 1.7 - ) + assert await client.quantise_size("CS.D.EURUSD.TODAY.IP", 1.759110721932789) == 1.7 assert await client.quantise_size("CS.D.EURUSD.TODAY.IP", 2.39) == 2.3 assert await client.quantise_size("CS.D.EURUSD.TODAY.IP", 2.5) == 2.5 @@ -233,10 +226,7 @@ async def test_quantise_size_with_decimal_step(self, mock_aiohttp_session): "dealingRules": {"minDealSize": {"value": 0.01}} } - assert ( - await client.quantise_size("IX.D.DOW.DAILY.IP", 1.759110721932789) - == 1.75 - ) + assert await client.quantise_size("IX.D.DOW.DAILY.IP", 1.759110721932789) == 1.75 assert await client.quantise_size("IX.D.DOW.DAILY.IP", 2.357) == 2.35 assert await client.quantise_size("IX.D.DOW.DAILY.IP", 0.055) == 0.05 @@ -257,9 +247,7 @@ async def test_quantise_size_no_step_rounds_to_2dp(self, mock_aiohttp_session): assert await client.quantise_size("TEST.EPIC", size) == round(size, 2) @pytest.mark.asyncio - async def test_quantise_size_fetches_metadata_if_not_cached( - self, mock_aiohttp_session - ): + async def test_quantise_size_fetches_metadata_if_not_cached(self, mock_aiohttp_session): """Test that quantise_size fetches metadata if not already cached.""" mock_response = MagicMock() mock_response.status = 200 @@ -344,9 +332,7 @@ async def test_quantise_size_audusd_real_world_example(self, mock_aiohttp_sessio client._instrument_metadata["CS.D.AUDUSD.TODAY.IP"] = { "dealingRules": { "minDealSize": {"value": 0.04}, - "minStepDistance": { - "value": 5 - }, # This is ignored in new implementation + "minStepDistance": {"value": 5}, # This is ignored in new implementation } } @@ -497,9 +483,7 @@ async def test_auth_handles_invalid_credentials(self, mock_aiohttp_session): with patch("aiohttp.ClientSession", return_value=mock_aiohttp_session): client = IGClient() - with pytest.raises( - RuntimeError, match="IG authentication failed – HTTP 401" - ): + with pytest.raises(RuntimeError, match="IG authentication failed – HTTP 401"): await client.start() @pytest.mark.asyncio @@ -507,16 +491,12 @@ async def test_auth_handles_network_error(self, mock_aiohttp_session): """Test that authentication properly handles network errors.""" import aiohttp - mock_aiohttp_session.post.side_effect = aiohttp.ClientError( - "Network unreachable" - ) + mock_aiohttp_session.post.side_effect = aiohttp.ClientError("Network unreachable") with patch("aiohttp.ClientSession", return_value=mock_aiohttp_session): client = IGClient() - with pytest.raises( - RuntimeError, match="Network error during authentication" - ): + with pytest.raises(RuntimeError, match="Network error during authentication"): await client.start() @pytest.mark.asyncio @@ -534,9 +514,7 @@ async def test_auth_handles_non_json_error_response(self, mock_aiohttp_session): with patch("aiohttp.ClientSession", return_value=mock_aiohttp_session): client = IGClient() - with pytest.raises( - RuntimeError, match="IG authentication failed – HTTP 500" - ): + with pytest.raises(RuntimeError, match="IG authentication failed – HTTP 500"): await client.start() # ============================================================================ @@ -762,9 +740,7 @@ async def test_get_price_ticks(self, mock_aiohttp_session): """Test get_price_ticks returns price tick data.""" mock_response = MagicMock() mock_response.status = 200 - mock_response.json = AsyncMock( - return_value={"prices": [{"bid": 1.1, "ask": 1.1001}]} - ) + mock_response.json = AsyncMock(return_value={"prices": [{"bid": 1.1, "ask": 1.1001}]}) mock_response.__aenter__ = AsyncMock(return_value=mock_response) mock_response.__aexit__ = AsyncMock(return_value=None) @@ -829,9 +805,7 @@ async def test_ensure_account_type_caches_result(self, mock_aiohttp_session): assert mock_aiohttp_session.request.call_count == 1 # No additional call @pytest.mark.asyncio - async def test_place_market_order_confirmed_waits_for_confirmation( - self, mock_aiohttp_session - ): + async def test_place_market_order_confirmed_waits_for_confirmation(self, mock_aiohttp_session): """Test place_market_order_confirmed waits for deal confirmation.""" # Setup order placement response order_response = MagicMock() @@ -890,9 +864,7 @@ async def test_place_market_order_confirmed_raises_without_deal_reference( ) @pytest.mark.asyncio - async def test_place_market_order_confirmed_raises_rejected_status( - self, mock_aiohttp_session - ): + async def test_place_market_order_confirmed_raises_rejected_status(self, mock_aiohttp_session): """Test place_market_order_confirmed raises exception when rejected.""" # Setup order placement response without dealReference order_response = MagicMock() @@ -963,9 +935,7 @@ async def test_get_historical_candles_returns_candles(self, mock_aiohttp_session client = IGClient() client._session = mock_aiohttp_session - candles = await client.get_historical_candles( - "CS.D.EURUSD.TODAY.IP", "1MINUTE", 2 - ) + candles = await client.get_historical_candles("CS.D.EURUSD.TODAY.IP", "1MINUTE", 2) assert len(candles) == 2 assert isinstance(candles[0], Candle) @@ -978,28 +948,20 @@ async def test_get_historical_candles_returns_candles(self, mock_aiohttp_session assert candles[1].close == 1.1016 @pytest.mark.asyncio - async def test_get_historical_candles_returns_empty_for_zero_points( - self, mock_aiohttp_session - ): + async def test_get_historical_candles_returns_empty_for_zero_points(self, mock_aiohttp_session): """Test get_historical_candles returns empty list for 0 or negative points.""" with patch("aiohttp.ClientSession", return_value=mock_aiohttp_session): client = IGClient() client._session = mock_aiohttp_session - candles = await client.get_historical_candles( - "CS.D.EURUSD.TODAY.IP", "1MINUTE", 0 - ) + candles = await client.get_historical_candles("CS.D.EURUSD.TODAY.IP", "1MINUTE", 0) assert candles == [] - candles = await client.get_historical_candles( - "CS.D.EURUSD.TODAY.IP", "1MINUTE", -5 - ) + candles = await client.get_historical_candles("CS.D.EURUSD.TODAY.IP", "1MINUTE", -5) assert candles == [] @pytest.mark.asyncio - async def test_get_historical_candles_handles_missing_timestamps( - self, mock_aiohttp_session - ): + async def test_get_historical_candles_handles_missing_timestamps(self, mock_aiohttp_session): """Test get_historical_candles skips candles without timestamps.""" mock_response = MagicMock() @@ -1028,18 +990,14 @@ async def test_get_historical_candles_handles_missing_timestamps( client = IGClient() client._session = mock_aiohttp_session - candles = await client.get_historical_candles( - "CS.D.EURUSD.TODAY.IP", "1MINUTE", 2 - ) + candles = await client.get_historical_candles("CS.D.EURUSD.TODAY.IP", "1MINUTE", 2) # Should only have 1 candle (the one with timestamp) assert len(candles) == 1 assert candles[0].timestamp == "2025-01-01T11:00:00Z" @pytest.mark.asyncio - async def test_get_historical_candles_handles_missing_close_price( - self, mock_aiohttp_session - ): + async def test_get_historical_candles_handles_missing_close_price(self, mock_aiohttp_session): """Test get_historical_candles skips candles without close price.""" mock_response = MagicMock() mock_response.status = 200 @@ -1067,18 +1025,14 @@ async def test_get_historical_candles_handles_missing_close_price( client = IGClient() client._session = mock_aiohttp_session - candles = await client.get_historical_candles( - "CS.D.EURUSD.TODAY.IP", "1MINUTE", 2 - ) + candles = await client.get_historical_candles("CS.D.EURUSD.TODAY.IP", "1MINUTE", 2) # Should only have 1 candle assert len(candles) == 1 assert candles[0].close == 1.1016 @pytest.mark.asyncio - async def test_get_historical_candles_uses_close_for_missing_ohlc( - self, mock_aiohttp_session - ): + async def test_get_historical_candles_uses_close_for_missing_ohlc(self, mock_aiohttp_session): """Test get_historical_candles uses close price when open/high/low missing.""" mock_response = MagicMock() @@ -1103,9 +1057,7 @@ async def test_get_historical_candles_uses_close_for_missing_ohlc( client = IGClient() client._session = mock_aiohttp_session - candles = await client.get_historical_candles( - "CS.D.EURUSD.TODAY.IP", "1MINUTE", 1 - ) + candles = await client.get_historical_candles("CS.D.EURUSD.TODAY.IP", "1MINUTE", 1) assert len(candles) == 1 # All OHLC should equal close @@ -1115,9 +1067,7 @@ async def test_get_historical_candles_uses_close_for_missing_ohlc( assert candles[0].close == 1.1006 @pytest.mark.asyncio - async def test_get_historical_candles_sorts_by_timestamp( - self, mock_aiohttp_session - ): + async def test_get_historical_candles_sorts_by_timestamp(self, mock_aiohttp_session): """Test get_historical_candles sorts candles oldest to newest.""" mock_response = MagicMock() mock_response.status = 200 @@ -1148,9 +1098,7 @@ async def test_get_historical_candles_sorts_by_timestamp( client = IGClient() client._session = mock_aiohttp_session - candles = await client.get_historical_candles( - "CS.D.EURUSD.TODAY.IP", "1MINUTE", 3 - ) + candles = await client.get_historical_candles("CS.D.EURUSD.TODAY.IP", "1MINUTE", 3) # Should be sorted oldest to newest assert candles[0].timestamp == "2025-01-01T10:00:00Z" @@ -1158,9 +1106,7 @@ async def test_get_historical_candles_sorts_by_timestamp( assert candles[2].timestamp == "2025-01-01T12:00:00Z" @pytest.mark.asyncio - async def test_get_historical_candles_handles_empty_prices( - self, mock_aiohttp_session - ): + async def test_get_historical_candles_handles_empty_prices(self, mock_aiohttp_session): """Test get_historical_candles handles empty prices array.""" mock_response = MagicMock() mock_response.status = 200 @@ -1174,9 +1120,7 @@ async def test_get_historical_candles_handles_empty_prices( client = IGClient() client._session = mock_aiohttp_session - candles = await client.get_historical_candles( - "CS.D.EURUSD.TODAY.IP", "1MINUTE", 10 - ) + candles = await client.get_historical_candles("CS.D.EURUSD.TODAY.IP", "1MINUTE", 10) assert candles == [] # ============================================================================ @@ -1203,9 +1147,7 @@ async def test_v2_auth_raises_without_cst_token(self, mock_aiohttp_session): with patch("aiohttp.ClientSession", return_value=mock_aiohttp_session): client = IGClient() - with pytest.raises( - RuntimeError, match="CST and X-SECURITY-TOKEN not found" - ): + with pytest.raises(RuntimeError, match="CST and X-SECURITY-TOKEN not found"): await client.start() @pytest.mark.asyncio @@ -1232,9 +1174,7 @@ async def test_v2_auth_raises_without_account_id(self, mock_aiohttp_session): await client.start() @pytest.mark.asyncio - async def test_ensure_account_type_returns_none_without_account_id( - self, mock_aiohttp_session - ): + async def test_ensure_account_type_returns_none_without_account_id(self, mock_aiohttp_session): """Test _ensure_account_type returns None when account_id is not set.""" with patch("aiohttp.ClientSession", return_value=mock_aiohttp_session): client = IGClient() diff --git a/tests/execution/test_ig_client_retry_logic.py b/tests/execution/test_ig_client_retry_logic.py index 45220e0..86dcf17 100644 --- a/tests/execution/test_ig_client_retry_logic.py +++ b/tests/execution/test_ig_client_retry_logic.py @@ -131,9 +131,7 @@ async def test_quantise_size_null_dealing_rules(): """ c = IGClient() # Snapshot with explicit null dealingRules (as IG DEMO sometimes returns) - c.get_instrument_metadata = AsyncMock( - return_value={"dealingRules": None, "instrument": {}} - ) + 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 @@ -143,9 +141,7 @@ async def test_quantise_size_null_dealing_rules(): 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}} - ) + 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 @@ -161,9 +157,7 @@ async def test_quantise_size_null_dealing_rules_truncates_long_float(): "validation.number.too-many-decimal-places.request.size". """ c = IGClient() - c.get_instrument_metadata = AsyncMock( - return_value={"dealingRules": None, "instrument": {}} - ) + 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_order_handler.py b/tests/execution/test_order_handler.py index 8325bca..8891d6d 100644 --- a/tests/execution/test_order_handler.py +++ b/tests/execution/test_order_handler.py @@ -19,9 +19,7 @@ async def test_request_order_success(): client.quantise_size = AsyncMock(side_effect=lambda inst, size: size) OrderExecutionHandler(client) - result = await request_order( - OrderRequest(instrument="TEST", direction="BUY", size=1.0) - ) + result = await request_order(OrderRequest(instrument="TEST", direction="BUY", size=1.0)) assert result.success is True assert result.fill_price == 105.50 @@ -60,9 +58,7 @@ async def test_request_order_handles_rejection(): client.quantise_size = AsyncMock(side_effect=lambda inst, size: size) OrderExecutionHandler(client) - result = await request_order( - OrderRequest(instrument="TEST", direction="SELL", size=1.0) - ) + result = await request_order(OrderRequest(instrument="TEST", direction="SELL", size=1.0)) assert result.success is False assert "rejected" in result.error @@ -88,8 +84,6 @@ async def test_request_order_uses_fallback_price_field(): client.quantise_size = AsyncMock(side_effect=lambda inst, size: size) OrderExecutionHandler(client) - result = await request_order( - OrderRequest(instrument="TEST", direction="BUY", size=1.0) - ) + result = await request_order(OrderRequest(instrument="TEST", direction="BUY", size=1.0)) assert result.fill_price == 99.0 diff --git a/tests/marketdata/indicators/test_indicators.py b/tests/marketdata/indicators/test_indicators.py index 57a2484..9c661ca 100644 --- a/tests/marketdata/indicators/test_indicators.py +++ b/tests/marketdata/indicators/test_indicators.py @@ -199,9 +199,7 @@ def test_macd_strict_ready_only_when_signal_available(self) -> None: assert last["signal"] is not None assert last["histogram"] is not None # Histogram identity - assert last["histogram"] == pytest.approx( - last["macd"] - last["signal"], rel=1e-12 - ) + assert last["histogram"] == pytest.approx(last["macd"] - last["signal"], rel=1e-12) def test_macd_reset(self) -> None: macd = MACD(fast=3, slow=5, signal=2) diff --git a/tests/marketdata/indicators/test_vwap.py b/tests/marketdata/indicators/test_vwap.py index 596b19a..664f00e 100644 --- a/tests/marketdata/indicators/test_vwap.py +++ b/tests/marketdata/indicators/test_vwap.py @@ -79,9 +79,7 @@ def test_reset_method(self) -> None: vwap.reset() assert vwap.ready() is False - assert vwap.update( - candle("2020-01-01T00:05:00Z", 20, 20, 20, 1) - ) == pytest.approx(20.0) + assert vwap.update(candle("2020-01-01T00:05:00Z", 20, 20, 20, 1)) == pytest.approx(20.0) def test_warmup_periods(self) -> None: assert VWAP().warmup_periods() == 1 diff --git a/tests/marketdata/test_aggregation.py b/tests/marketdata/test_aggregation.py index d9d3afd..06c651b 100644 --- a/tests/marketdata/test_aggregation.py +++ b/tests/marketdata/test_aggregation.py @@ -87,18 +87,10 @@ def test_state_is_independent_per_instrument() -> None: base_ts = 1767225600000 # 2026-01-01 00:00:00 UTC a1 = Candle(timestamp=base_ts + 12 * 60 * 1000, open=1, high=2, low=0.5, close=1.5) b1 = Candle(timestamp=base_ts + 12 * 60 * 1000, open=10, high=11, low=9, close=10.5) - a2 = Candle( - timestamp=base_ts + 17 * 60 * 1000, open=1.5, high=3, low=1.4, close=2.5 - ) - b2 = Candle( - timestamp=base_ts + 17 * 60 * 1000, open=10.5, high=12, low=10, close=11.5 - ) - a3 = Candle( - timestamp=base_ts + 22 * 60 * 1000, open=2.5, high=4, low=2.0, close=3.0 - ) - b3 = Candle( - timestamp=base_ts + 22 * 60 * 1000, open=11.5, high=13, low=11, close=12.0 - ) + a2 = Candle(timestamp=base_ts + 17 * 60 * 1000, open=1.5, high=3, low=1.4, close=2.5) + b2 = Candle(timestamp=base_ts + 17 * 60 * 1000, open=10.5, high=12, low=10, close=11.5) + a3 = Candle(timestamp=base_ts + 22 * 60 * 1000, open=2.5, high=4, low=2.0, close=3.0) + b3 = Candle(timestamp=base_ts + 22 * 60 * 1000, open=11.5, high=13, low=11, close=12.0) assert agg.update(instrument=inst_a, candle=a1) is None assert agg.update(instrument=inst_b, candle=b1) is None diff --git a/tests/marketdata/test_client_historical_candles.py b/tests/marketdata/test_client_historical_candles.py index edccdc2..e3e1b75 100644 --- a/tests/marketdata/test_client_historical_candles.py +++ b/tests/marketdata/test_client_historical_candles.py @@ -6,9 +6,7 @@ class TestClientHistoricalCandles: @pytest.mark.asyncio - async def test_get_historical_candles_calls_prices_endpoint_and_parses( - self, monkeypatch - ): + async def test_get_historical_candles_calls_prices_endpoint_and_parses(self, monkeypatch): client = IGClient() async def fake_request(method, path, **kwargs): diff --git a/tests/portfolio/test_orchestrator_reconciliation.py b/tests/portfolio/test_orchestrator_reconciliation.py index 43e6e63..d2e3b9d 100644 --- a/tests/portfolio/test_orchestrator_reconciliation.py +++ b/tests/portfolio/test_orchestrator_reconciliation.py @@ -1,5 +1,5 @@ """ -Tests for ReconciliationManager: startup reconciliation, +Tests for ReconciliationManager: startup reconciliation, periodic correction, and journal persistence. """ @@ -94,9 +94,7 @@ def notify_position_change(self): def to_journal_entry(self, instrument): return JournalEntry( instrument=instrument, - direction=self.position.direction.value - if self.position.direction - else None, + direction=self.position.direction.value if self.position.direction else None, size=self.position.size, entry_price=self.position.entry_price, bars_held=self.position.bars_held, diff --git a/tests/portfolio/test_portfolio_runner.py b/tests/portfolio/test_portfolio_runner.py index ecaeb28..dcb7764 100644 --- a/tests/portfolio/test_portfolio_runner.py +++ b/tests/portfolio/test_portfolio_runner.py @@ -49,9 +49,7 @@ async def test_runner_splits_risk_across_active_strategies(): ) await r.on_candle_close( - CandleClosedEvent( - instrument=Instrument("EURUSD"), timeframe="15MINUTE", candle=None - ) + CandleClosedEvent(instrument=Instrument("EURUSD"), timeframe="15MINUTE", candle=None) ) # Two active strategies should get 5.0 each diff --git a/tests/portfolio/test_reconciliation.py b/tests/portfolio/test_reconciliation.py index 3c2b715..174831c 100644 --- a/tests/portfolio/test_reconciliation.py +++ b/tests/portfolio/test_reconciliation.py @@ -135,12 +135,8 @@ def test_unmanaged_instrument_ignored(self): def test_multiple_instruments(self): result = reconcile( journal_positions={ - "USDJPY": _journal_entry( - instrument="USDJPY", direction="long", size=1.0 - ), - "GBPUSD": _journal_entry( - instrument="GBPUSD", direction="short", size=2.0 - ), + "USDJPY": _journal_entry(instrument="USDJPY", direction="long", size=1.0), + "GBPUSD": _journal_entry(instrument="GBPUSD", direction="short", size=2.0), }, broker_positions=[ _broker_pos(instrument="USDJPY", direction="BUY", size=1.0), @@ -157,9 +153,7 @@ def test_is_clean(self): result = ReconciliationResult( entries=[ - ReconciliationEntry( - instrument="X", discrepancy=DiscrepancyType.MATCHED - ), + ReconciliationEntry(instrument="X", discrepancy=DiscrepancyType.MATCHED), ] ) assert result.is_clean @@ -169,9 +163,7 @@ def test_has_emergencies(self): result = ReconciliationResult( entries=[ - ReconciliationEntry( - instrument="X", discrepancy=DiscrepancyType.FAILED_EXIT - ), + ReconciliationEntry(instrument="X", discrepancy=DiscrepancyType.FAILED_EXIT), ] ) assert result.has_emergencies @@ -181,12 +173,8 @@ def test_orphan_broker_positions(self): result = ReconciliationResult( entries=[ - ReconciliationEntry( - instrument="X", discrepancy=DiscrepancyType.ORPHAN_BROKER - ), - ReconciliationEntry( - instrument="Y", discrepancy=DiscrepancyType.MATCHED - ), + ReconciliationEntry(instrument="X", discrepancy=DiscrepancyType.ORPHAN_BROKER), + ReconciliationEntry(instrument="Y", discrepancy=DiscrepancyType.MATCHED), ] ) assert len(result.orphan_broker_positions) == 1 @@ -196,9 +184,7 @@ def test_phantom_local_positions(self): result = ReconciliationResult( entries=[ - ReconciliationEntry( - instrument="X", discrepancy=DiscrepancyType.PHANTOM_LOCAL - ), + ReconciliationEntry(instrument="X", discrepancy=DiscrepancyType.PHANTOM_LOCAL), ] ) assert len(result.phantom_local_positions) == 1 @@ -281,14 +267,10 @@ async def test_startup_orphan_adoption(self, manager, mock_client, mock_runner): manager._journal.save.assert_called_once() @pytest.mark.asyncio - async def test_startup_broker_failure( - self, manager, mock_client, mock_journal, mock_runner - ): + async def test_startup_broker_failure(self, manager, mock_client, mock_journal, mock_runner): """Broker fails, restore from journal.""" mock_client.get_positions.side_effect = Exception("Broker down") - mock_journal.load.return_value = [ - _journal_entry(instrument="USDJPY", direction="long") - ] + mock_journal.load.return_value = [_journal_entry(instrument="USDJPY", direction="long")] restored = await manager.reconcile_on_startup() @@ -297,9 +279,7 @@ async def test_startup_broker_failure( strat.restore_from_journal.assert_called_once() @pytest.mark.asyncio - async def test_periodic_reconcile_correction( - self, manager, mock_client, mock_runner - ): + async def test_periodic_reconcile_correction(self, manager, mock_client, mock_runner): """Periodic check finds discrepancy and fixes it.""" # Setup: Strategy thinks flat, Broker has position mock_client.get_positions.return_value = [ diff --git a/tests/recording/test_ledger.py b/tests/recording/test_ledger.py index da5d731..d4984ac 100644 --- a/tests/recording/test_ledger.py +++ b/tests/recording/test_ledger.py @@ -107,9 +107,7 @@ def test_write_equity_csv(self, tmp_path): def test_write_round_trips_csv(self, tmp_path): ledger = TradeLedger() # Entry - ledger.record_trade( - _trade(direction="BUY", price=150.0, ts="2025-01-15T12:00:00Z") - ) + ledger.record_trade(_trade(direction="BUY", price=150.0, ts="2025-01-15T12:00:00Z")) # Exit ledger.record_trade( _trade( @@ -150,12 +148,8 @@ def test_write_equity_daily_csv_fills_gaps(self, tmp_path): def test_write_exposure_csv(self, tmp_path): ledger = TradeLedger() - ledger.record_trade( - _trade(direction="BUY", price=150.0, ts="2025-01-15T12:00:00Z") - ) - ledger.record_trade( - _trade(direction="SELL", price=152.0, ts="2025-01-15T13:00:00Z") - ) + ledger.record_trade(_trade(direction="BUY", price=150.0, ts="2025-01-15T12:00:00Z")) + ledger.record_trade(_trade(direction="SELL", price=152.0, ts="2025-01-15T13:00:00Z")) ledger.record_equity(_equity(ts="2025-01-15T12:30:00Z")) path = tmp_path / "exposure.csv" ledger.write_exposure_csv(path) @@ -173,9 +167,7 @@ def test_write_opportunity_csv_empty(self, tmp_path): def test_write_opportunity_csv_with_data(self, tmp_path): ledger = TradeLedger() - ledger.opportunity.on_instrument_bar( - instrument="USDJPY", timestamp="t1", active=True - ) + ledger.opportunity.on_instrument_bar(instrument="USDJPY", timestamp="t1", active=True) ledger.opportunity.on_portfolio_snapshot(timestamp="t1", k_active=1) path = tmp_path / "opportunity.csv" ledger.write_opportunity_csv(path) @@ -185,12 +177,8 @@ def test_write_opportunity_csv_with_data(self, tmp_path): def test_write_batch(self, tmp_path): ledger = TradeLedger() - ledger.record_trade( - _trade(direction="BUY", price=150.0, ts="2025-01-15T12:00:00Z") - ) - ledger.record_trade( - _trade(direction="SELL", price=152.0, ts="2025-01-15T13:00:00Z") - ) + ledger.record_trade(_trade(direction="BUY", price=150.0, ts="2025-01-15T12:00:00Z")) + ledger.record_trade(_trade(direction="SELL", price=152.0, ts="2025-01-15T13:00:00Z")) ledger.record_equity(_equity(ts="2025-01-15T12:30:00Z")) out = tmp_path / "results" ledger.write(out) @@ -205,12 +193,8 @@ def test_write_batch(self, tmp_path): 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") - ) + 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), @@ -227,12 +211,8 @@ def test_write_round_trips_csv_with_excursions(self, tmp_path): 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") - ) + 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) @@ -281,12 +261,8 @@ 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_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" @@ -328,9 +304,7 @@ def test_write_metrics_csv_empty_ledger(self, tmp_path): 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 - ) + 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") @@ -369,9 +343,7 @@ def test_broker_mode_creates_trades_csv_on_init(self, tmp_path): assert len(rows) == 0 # header only def test_broker_record_trade_appends_to_csv(self, tmp_path): - ledger = TradeLedger( - mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0 - ) + ledger = TradeLedger(mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0) ledger.record_trade(_trade(ts="2025-01-15T12:00:00Z")) rows = _read_csv(tmp_path / "trades.csv") assert len(rows) == 1 @@ -382,9 +354,7 @@ def test_broker_record_equity_ignored(self, tmp_path): assert len(ledger.equity) == 0 def test_broker_synthetic_equity_pnl(self, tmp_path): - ledger = TradeLedger( - mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0 - ) + ledger = TradeLedger(mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0) # Open long ledger.record_trade( _trade(direction="BUY", price=150.0, size=1.0, ts="2025-01-15T12:00:00Z") @@ -398,9 +368,7 @@ def test_broker_synthetic_equity_pnl(self, tmp_path): assert ledger._current_balance == pytest.approx(10005.0) def test_broker_short_trade_pnl(self, tmp_path): - ledger = TradeLedger( - mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0 - ) + ledger = TradeLedger(mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0) # Open short ledger.record_trade( _trade(direction="SELL", price=150.0, size=1.0, ts="2025-01-15T12:00:00Z") @@ -412,9 +380,7 @@ def test_broker_short_trade_pnl(self, tmp_path): assert ledger._current_balance == pytest.approx(10005.0) def test_broker_adds_to_position(self, tmp_path): - ledger = TradeLedger( - mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0 - ) + ledger = TradeLedger(mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0) ledger.record_trade( _trade(direction="BUY", price=100.0, size=1.0, ts="2025-01-15T12:00:00Z") ) @@ -426,9 +392,7 @@ def test_broker_adds_to_position(self, tmp_path): assert pos["price"] == pytest.approx(105.0) # average price def test_broker_partial_close(self, tmp_path): - ledger = TradeLedger( - mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0 - ) + ledger = TradeLedger(mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0) ledger.record_trade( _trade(direction="BUY", price=100.0, size=2.0, ts="2025-01-15T12:00:00Z") ) @@ -442,17 +406,11 @@ def test_broker_partial_close(self, tmp_path): assert ledger._open_positions["USDJPY"]["size"] == pytest.approx(1.0) def test_broker_daily_equity_csv(self, tmp_path): - ledger = TradeLedger( - mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0 - ) + ledger = TradeLedger(mode=RecordingMode.BROKER, out_dir=tmp_path, initial_balance=10000.0) # Trade on day 1 - ledger.record_trade( - _trade(direction="BUY", price=100.0, ts="2025-01-15T12:00:00Z") - ) + ledger.record_trade(_trade(direction="BUY", price=100.0, ts="2025-01-15T12:00:00Z")) # Trade on day 2 (triggers daily equity write) - ledger.record_trade( - _trade(direction="SELL", price=110.0, ts="2025-01-16T12:00:00Z") - ) + ledger.record_trade(_trade(direction="SELL", price=110.0, ts="2025-01-16T12:00:00Z")) assert (tmp_path / "equity_daily.csv").exists() def test_broker_write_is_noop(self, tmp_path): diff --git a/tests/recording/test_metrics.py b/tests/recording/test_metrics.py index 44cdd1b..65b5fbb 100644 --- a/tests/recording/test_metrics.py +++ b/tests/recording/test_metrics.py @@ -396,9 +396,7 @@ def test_compute_metrics_reporting_scale_scales_linear_outputs_only() -> None: }, ] - m = compute_metrics( - equity_rows=equity_rows, trade_rows=trade_rows, reporting_scale=2.0 - ) + m = compute_metrics(equity_rows=equity_rows, trade_rows=trade_rows, reporting_scale=2.0) # Scaled assert m.final_equity == pytest.approx(20.0) diff --git a/tests/recording/test_opportunity.py b/tests/recording/test_opportunity.py index 70bb4a4..4a1f400 100644 --- a/tests/recording/test_opportunity.py +++ b/tests/recording/test_opportunity.py @@ -73,9 +73,7 @@ def test_regime_active_pct(self): class TestOpportunityRecorder: def test_on_instrument_bar_creates_entry(self): rec = OpportunityRecorder() - rec.on_instrument_bar( - instrument="USDJPY", timestamp="2025-01-01T00:00:00Z", active=True - ) + rec.on_instrument_bar(instrument="USDJPY", timestamp="2025-01-01T00:00:00Z", active=True) assert "USDJPY" in rec.per_instrument assert rec.per_instrument["USDJPY"].bars == 1 diff --git a/tests/recording/test_report.py b/tests/recording/test_report.py index 719d9a4..b0ff6c8 100644 --- a/tests/recording/test_report.py +++ b/tests/recording/test_report.py @@ -46,96 +46,3 @@ def test_prepare_monthly_data_values_are_iterable(): 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 950d746..160045b 100644 --- a/tests/recording/test_subscriber.py +++ b/tests/recording/test_subscriber.py @@ -5,7 +5,12 @@ import pytest -from tradedesk.events import SessionEndedEvent, SessionStartedEvent, get_dispatcher, reset_dispatcher +from tradedesk.events import ( + SessionEndedEvent, + SessionStartedEvent, + get_dispatcher, + reset_dispatcher, +) from tradedesk.recording.events import ( PositionClosedEvent, PositionOpenedEvent, @@ -156,9 +161,7 @@ def _make_subscriber_with_trades( 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_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", @@ -177,9 +180,7 @@ def _make_subscriber_with_trades( price=1.21, ) ) - sub.ledger.record_equity( - EquityRecord(timestamp="2024-01-01T01:00:00+00:00", equity=10.0) - ) + sub.ledger.record_equity(EquityRecord(timestamp="2024-01-01T01:00:00+00:00", equity=10.0)) return sub @@ -228,9 +229,7 @@ async def capture(evt: ReportingCompleteEvent) -> None: 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_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", @@ -307,9 +306,7 @@ async def test_session_ended_via_dispatcher(tmp_path: Path) -> None: 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_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", @@ -328,9 +325,7 @@ async def test_session_ended_via_dispatcher(tmp_path: Path) -> None: price=1.21, ) ) - sub.ledger.record_equity( - EquityRecord(timestamp="2024-01-01T01:00:00+00:00", equity=10.0) - ) + sub.ledger.record_equity(EquityRecord(timestamp="2024-01-01T01:00:00+00:00", equity=10.0)) await get_dispatcher().publish(SessionEndedEvent()) diff --git a/tests/strategy/test_chart_priming.py b/tests/strategy/test_chart_priming.py index c721ddd..84aa88c 100644 --- a/tests/strategy/test_chart_priming.py +++ b/tests/strategy/test_chart_priming.py @@ -3,9 +3,7 @@ class TestStrategyChartPriming: - def test_prime_chart_populates_history_and_indicators( - self, DummyStrategy, make_candles - ): + def test_prime_chart_populates_history_and_indicators(self, DummyStrategy, make_candles): Strat = DummyStrategy([ChartSubscription("EPIC", "1MINUTE")]) strat = Strat(data_provider=None) diff --git a/tests/strategy/test_on_candle_update_default.py b/tests/strategy/test_on_candle_update_default.py index 9bfb13d..14fca3e 100644 --- a/tests/strategy/test_on_candle_update_default.py +++ b/tests/strategy/test_on_candle_update_default.py @@ -6,9 +6,7 @@ @pytest.mark.asyncio class TestOnCandleUpdateDefault: - async def test_on_candle_update_stores_in_chart_history( - self, DummyStrategy, candle_factory - ): + async def test_on_candle_update_stores_in_chart_history(self, DummyStrategy, candle_factory): sub = ChartSubscription("EPIC", "1MINUTE") Strat = DummyStrategy([sub]) strat = Strat(data_provider=None) @@ -22,15 +20,11 @@ async def test_on_candle_update_stores_in_chart_history( assert len(chart) == 1 assert chart.latest == candle - async def test_on_candle_update_no_chart_key_is_noop( - self, DummyStrategy, candle_factory - ): + async def test_on_candle_update_no_chart_key_is_noop(self, DummyStrategy, candle_factory): Strat = DummyStrategy([]) # no chart subs => no chart history entries created strat = Strat(data_provider=None) # Should not raise await strat.on_candle_close( - CandleClosedEvent( - instrument="EPIC", timeframe="1MINUTE", candle=candle_factory(0) - ) + CandleClosedEvent(instrument="EPIC", timeframe="1MINUTE", candle=candle_factory(0)) ) diff --git a/tests/strategy/test_run_streaming.py b/tests/strategy/test_run_streaming.py index 522d925..8acca90 100644 --- a/tests/strategy/test_run_streaming.py +++ b/tests/strategy/test_run_streaming.py @@ -135,13 +135,9 @@ async def on_candle_close(cc): # Identify which is market vs chart by fields market_ls_sub = next( - s - for s in ls_client.subscribed - if "BID" in s.fields and "OFFER" in s.fields - ) - chart_ls_sub = next( - s for s in ls_client.subscribed if "CONS_END" in s.fields + s for s in ls_client.subscribed if "BID" in s.fields and "OFFER" in s.fields ) + chart_ls_sub = next(s for s in ls_client.subscribed if "CONS_END" in s.fields) # Trigger a market update mu = FakeUpdate( diff --git a/tests/strategy/test_strategy.py b/tests/strategy/test_strategy.py index 97d778c..1d8a7f2 100644 --- a/tests/strategy/test_strategy.py +++ b/tests/strategy/test_strategy.py @@ -35,6 +35,7 @@ async def on_price_update(self, market_databid, offer, timestamp, raw_data): assert strategy.watchdog_threshold == 60 assert isinstance(strategy.last_update, datetime) + class TestConcreteStrategy: """Test with a concrete strategy implementation.""" diff --git a/tests/strategy/test_warmup_from_ig.py b/tests/strategy/test_warmup_from_ig.py index b235d88..f7ab76d 100644 --- a/tests/strategy/test_warmup_from_ig.py +++ b/tests/strategy/test_warmup_from_ig.py @@ -6,9 +6,7 @@ @pytest.mark.asyncio class TestStrategyWarmupFromIG: - async def test_warmup_from_ig_primes_chart_and_indicator( - self, DummyStrategy, make_candles - ): + async def test_warmup_from_ig_primes_chart_and_indicator(self, DummyStrategy, make_candles): sub = ChartSubscription("EPIC", "1MINUTE") Strat = DummyStrategy([sub]) diff --git a/tests/test_candle.py b/tests/test_candle.py index d5831da..b3976ef 100644 --- a/tests/test_candle.py +++ b/tests/test_candle.py @@ -7,9 +7,7 @@ class TestCandleWithMsTimestamp: def test_iso_to_ms(self): - c = Candle( - timestamp="2025-01-15T12:30:00Z", open=1.0, high=2.0, low=0.5, close=1.5 - ) + c = Candle(timestamp="2025-01-15T12:30:00Z", open=1.0, high=2.0, low=0.5, close=1.5) result = c.candle_with_ms_timestamp() assert isinstance(result.timestamp, int) assert isinstance(c.timestamp, str) @@ -40,9 +38,7 @@ def test_ms_int_to_iso(self): assert "2025-01-15" in result.timestamp def test_already_iso(self): - c = Candle( - timestamp="2025-01-15T12:30:00Z", open=1.0, high=2.0, low=0.5, close=1.5 - ) + c = Candle(timestamp="2025-01-15T12:30:00Z", open=1.0, high=2.0, low=0.5, close=1.5) result = c.candle_with_iso_timestamp() assert result.timestamp == "2025-01-15T12:30:00Z" diff --git a/tests/test_runner.py b/tests/test_runner.py index 2747298..673f822 100644 --- a/tests/test_runner.py +++ b/tests/test_runner.py @@ -109,6 +109,4 @@ def test_run_portfolio_keyboard_interrupt(self): setup_logging=False, ) - mock_info.assert_any_call( - "Interrupted by user - shutting down gracefully" - ) + mock_info.assert_any_call("Interrupted by user - shutting down gracefully") diff --git a/tradedesk/events.py b/tradedesk/events.py index e924279..98c07ab 100644 --- a/tradedesk/events.py +++ b/tradedesk/events.py @@ -21,19 +21,25 @@ def event(cls: type[_T]) -> type[_T]: class DomainEvent(ABC): timestamp: datetime = field(default_factory=lambda: datetime.now(timezone.utc)) + @event class SessionStartedEvent(DomainEvent): """Event fired when a new backtest or live session starts.""" + pass + @event 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 diff --git a/tradedesk/execution/backtest/__init__.py b/tradedesk/execution/backtest/__init__.py index e565914..8fc572f 100644 --- a/tradedesk/execution/backtest/__init__.py +++ b/tradedesk/execution/backtest/__init__.py @@ -1,6 +1,7 @@ """Backtesting provider implementation.""" from .client import BacktestClient +from .dukascopy import iter_dukascopy_candles, read_dukascopy_candles from .runner import BacktestSpec, run_backtest from .streamer import BacktestStreamer, CandleSeries, MarketSeries @@ -10,9 +11,7 @@ "BacktestStreamer", "CandleSeries", "MarketSeries", + "iter_dukascopy_candles", + "read_dukascopy_candles", "run_backtest", ] - -# Removed exports (moved to recording domain): -# - CandleIndex, Excursions, build_candle_index, compute_excursions → tradedesk.recording.excursions -# - BacktestRecorder, ProgressLogger, TrackerSync → tradedesk.recording.recorders diff --git a/tradedesk/execution/backtest/client.py b/tradedesk/execution/backtest/client.py index a8ca8ec..84d60d2 100644 --- a/tradedesk/execution/backtest/client.py +++ b/tradedesk/execution/backtest/client.py @@ -1,6 +1,7 @@ import csv import itertools from dataclasses import dataclass +from datetime import date from pathlib import Path from typing import Any @@ -12,6 +13,7 @@ from tradedesk.time_utils import parse_timestamp from tradedesk.types import Candle, Direction +from .dukascopy import read_dukascopy_candles from .streamer import ( BacktestStreamer, CandleSeries, @@ -70,18 +72,77 @@ def __init__( self._current_timestamp: str | None = None @classmethod - def from_history( - cls, history: dict[tuple[str, str], list[Candle]] - ) -> "BacktestClient": + def from_history(cls, history: dict[tuple[str, str], list[Candle]]) -> "BacktestClient": series: list[CandleSeries] = [] for (instrument, period), candles in history.items(): - series.append( - CandleSeries( - instrument=instrument, period=period, candles=list(candles) - ) - ) + series.append(CandleSeries(instrument=instrument, period=period, candles=list(candles))) return cls(series, []) + @classmethod + def from_lazy_sources( + cls, + *, + history: dict[tuple[str, str], list[Candle]], + candle_series: list[CandleSeries], + market_series: list[MarketSeries] | None = None, + ) -> "BacktestClient": + """Create a client with a pre-populated warmup history and lazy candle generators. + + ``history`` is served by :meth:`get_historical_candles` during strategy + warmup. ``candle_series`` holds the generators consumed by + :class:`BacktestStreamer` during replay — typically the full date range. + + Unlike the default constructor, the warmup slice (``history``) and the + streaming generators are kept separate so only a small fraction of the + total data needs to be in memory at startup. + """ + inst = cls.__new__(cls) + inst._candle_series = list(candle_series) + inst._market_series = list(market_series or []) + inst._history = dict(history) + inst._started = False + inst._closed = False + inst._mark_price = {} + inst.trades = [] + inst.positions = {} + inst.realised_pnl = 0.0 + inst._current_timestamp = None + return inst + + @classmethod + def from_dukascopy_cache( + cls, + cache_dir: str | Path, + *, + symbol: str, + instrument: str, + period: str, + date_from: date, + date_to: date, + price_side: str = "bid", + ) -> "BacktestClient": + """ + Load a candle series from a Dukascopy tick cache and return a BacktestClient. + + Args: + cache_dir: Root of the Dukascopy cache directory. + symbol: Symbol folder name in the cache (e.g. ``"EURUSD"``). + instrument: Instrument identifier used by the strategy. + period: Tradedesk period string (e.g. ``"1MIN"``, ``"15MIN"``, ``"1H"``). + date_from: First date to include (inclusive). + date_to: Last date to include (inclusive). + price_side: ``"bid"`` (default), ``"ask"``, or ``"mid"``. + """ + candles = read_dukascopy_candles( + Path(cache_dir), + symbol, + period, + date_from, + date_to, + price_side=price_side, + ) + return cls.from_history({(instrument, period): candles}) + @classmethod def from_market_csv( cls, @@ -126,9 +187,7 @@ def norm(s: str) -> str: header_map = {norm(h): h for h in reader.fieldnames if h is not None} - ts_key = next( - (header_map[a] for a in ts_aliases if a in header_map), None - ) + ts_key = next((header_map[a] for a in ts_aliases if a in header_map), None) bid_key = header_map.get("bid") offer_key = header_map.get("offer") @@ -142,9 +201,7 @@ def norm(s: str) -> str: if k is None ] if missing: - raise ValueError( - f"CSV missing required columns: {', '.join(missing)}" - ) + raise ValueError(f"CSV missing required columns: {', '.join(missing)}") assert ts_key and bid_key and offer_key @@ -178,129 +235,6 @@ def norm(s: str) -> str: # No candle history for tick-only backtest (for now) return cls(candle_series=[], market_series=market_series) - @classmethod - def from_csv( - cls, - path: str | Path, - *, - instrument: str, - period: str, - timestamp_col: str | None = None, - open_col: str | None = None, - high_col: str | None = None, - low_col: str | None = None, - close_col: str | None = None, - volume_col: str | None = None, - tick_count_col: str | None = None, - delimiter: str = ",", - ) -> "BacktestClient": - """ - Load a candle series from CSV and return a BacktestClient. - - CSV requirements: - - timestamp column (default autodetect) - - open/high/low/close columns (default autodetect) - - optional volume and tick_count columns - """ - path = Path(path) - - def norm(s: str) -> str: - return s.strip().lower() - - # canonical -> accepted aliases - aliases = { - "timestamp": {"timestamp", "time", "datetime", "date"}, - "open": {"open", "o"}, - "high": {"high", "h"}, - "low": {"low", "l"}, - "close": {"close", "c"}, - "volume": {"volume", "vol", "v"}, - "tick_count": {"tick_count", "ticks", "tickcount"}, - } - - candles: list[Candle] = [] - - with path.open("r", newline="") as f: - reader = csv.DictReader(f, delimiter=delimiter) - if reader.fieldnames is None: - raise ValueError("CSV has no header row") - - # Build normalized header map - header_map = {norm(h): h for h in reader.fieldnames if h is not None} - - def pick(explicit: str | None, key: str) -> str | None: - if explicit: - if norm(explicit) not in header_map: - raise ValueError(f"CSV missing column: {explicit}") - return header_map[norm(explicit)] - for a in aliases[key]: - if a in header_map: - return header_map[a] - return None - - ts_key = pick(timestamp_col, "timestamp") - o_key = pick(open_col, "open") - h_key = pick(high_col, "high") - l_key = pick(low_col, "low") - c_key = pick(close_col, "close") - v_key = pick(volume_col, "volume") - t_key = pick(tick_count_col, "tick_count") - - missing = [ - name - for name, k in [ - ("timestamp", ts_key), - ("open", o_key), - ("high", h_key), - ("low", l_key), - ("close", c_key), - ] - if k is None - ] - if missing: - raise ValueError(f"CSV missing required columns: {', '.join(missing)}") - - assert ts_key and o_key and h_key and l_key and c_key - - for row in reader: - ts = (row.get(ts_key) or "").strip() - if not ts: - continue - - # Normalize to ...Z when not provided - if ts.endswith("Z"): - ts_norm = ts - elif "+" in ts or ts.endswith("00:00"): - ts_norm = ts - else: - ts_norm = ts + "Z" - - def fnum(val: str | None, default: float = 0.0) -> float: - if val is None: - return default - s = str(val).strip() - return default if s == "" else float(s) - - def inum(val: str | None, default: int = 0) -> int: - if val is None: - return default - s = str(val).strip() - return default if s == "" else int(float(s)) - - candle = Candle( - timestamp=ts_norm, - open=fnum(row.get(o_key)), - high=fnum(row.get(h_key)), - low=fnum(row.get(l_key)), - close=fnum(row.get(c_key)), - volume=fnum(row.get(v_key)) if v_key else 0.0, - tick_count=inum(row.get(t_key)) if t_key else 0, - ) - candles.append(candle) - - history = {(instrument, period): candles} - return cls.from_history(history) - async def start(self) -> None: self._started = True @@ -318,9 +252,7 @@ def _set_mark_price(self, instrument: str, price: float) -> None: def _get_mark_price(self, instrument: str) -> float: if instrument not in self._mark_price: - raise RuntimeError( - f"No mark price available for {instrument} (no data replayed yet)" - ) + raise RuntimeError(f"No mark price available for {instrument} (no data replayed yet)") return self._mark_price[instrument] def get_mark_price(self, instrument: str) -> float | None: @@ -417,9 +349,7 @@ async def place_market_order( if pos.direction == _direction: # Increase position: weighted avg entry new_size = pos.size + float(size) - pos.entry_price = ( - pos.entry_price * pos.size + price * float(size) - ) / new_size + pos.entry_price = (pos.entry_price * pos.size + price * float(size)) / new_size pos.size = new_size else: # Opposite direction: close (only supports full close or reduce; compute realised @@ -491,8 +421,13 @@ async def place_market_order_confirmed( **kwargs: Any, ) -> dict[str, Any]: return await self.place_market_order( - instrument, direction, size, currency=currency, force_open=force_open, - exit_reason=exit_reason, **kwargs + 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/dukascopy.py b/tradedesk/execution/backtest/dukascopy.py new file mode 100644 index 0000000..f49da51 --- /dev/null +++ b/tradedesk/execution/backtest/dukascopy.py @@ -0,0 +1,276 @@ +"""Dukascopy cache reader for tradedesk backtests. + +Reads daily 1-minute candle files from the Dukascopy cache directory layout:: + + {cache_dir}/{SYMBOL}/{YEAR}/{MM}/{DD}_{side}.csv.zst + +where MM is zero-based (Jan=00, Dec=11) and side is ``"bid"`` or ``"ask"``. + +Files are Zstandard-compressed CSV with columns:: + + timestamp,open,high,low,close,volume + +Old-format hourly .bi5 files (in per-day subdirectories) are detected and +cause an immediate exit with a message to re-run ``tradedesk-dc-export``. +""" + +from __future__ import annotations + +import io +import re +import sys +from collections.abc import Iterator +from datetime import date, timedelta +from pathlib import Path +from typing import cast + +import pandas as pd +import zstandard as zstd + +from tradedesk.types import Candle + +# --------------------------------------------------------------------------- +# Internal helpers +# --------------------------------------------------------------------------- + + +def _iter_days(date_from: date, date_to: date) -> list[date]: + """Return all dates in [date_from, date_to] inclusive.""" + days: list[date] = [] + d = date_from + while d <= date_to: + days.append(d) + d += timedelta(days=1) + return days + + +def _candle_path(cache_dir: Path, symbol: str, day: date, side: str) -> Path: + """Return the path to a daily 1-min candle cache file (Zstandard compressed).""" + month_0 = f"{day.month - 1:02d}" + return cache_dir / symbol / str(day.year) / month_0 / f"{day.day:02d}_{side}.csv.zst" + + +def _check_old_format(cache_dir: Path, symbol: str, day: date) -> None: + """Exit with a helpful message if old-style hourly .bi5 files are found.""" + month_0 = f"{day.month - 1:02d}" + day_dir = cache_dir / symbol / str(day.year) / month_0 / f"{day.day:02d}" + if day_dir.is_dir() and any(day_dir.glob("*.bi5")): + sys.exit( + f"Old Dukascopy cache format detected in {day_dir}.\n" + "Please re-run 'tradedesk-dc-export' to update the cache to the " + "daily candle file format." + ) + + +def _load_daily_candles(path: Path) -> pd.DataFrame | None: + """ + Load a 1-min candle CSV. + + Checks for a pre-decompressed ``.csv`` file first (ramdisk fast path); falls + back to the Zstandard-compressed ``.csv.zst`` file at *path*. + + Returns ``None`` if neither file exists or if parsing fails. + The returned DataFrame has a UTC DatetimeIndex named ``"timestamp"``. + """ + csv_path = path.with_suffix("") # {name}.csv.zst -> {name}.csv + try: + if csv_path.exists(): + df = pd.read_csv(csv_path) + elif path.exists(): + dctx = zstd.ZstdDecompressor() + with open(path, "rb") as f_in: + with dctx.stream_reader(f_in) as reader: + df = pd.read_csv(io.TextIOWrapper(io.BufferedReader(reader), encoding="utf-8")) + else: + return None + df["timestamp"] = pd.to_datetime(df["timestamp"], utc=True) + return df.set_index("timestamp") + except Exception: + return None + + +def _period_to_pandas_rule(period: str) -> str: + """ + Convert a tradedesk period string to a pandas resample rule. + + Examples:: + + "1MIN" -> "1min" + "15MIN" -> "15min" + "5MINUTE" -> "5min" + "1H" -> "1h" + "4H" -> "4h" + "1D" -> "1D" + """ + p = period.strip().upper() + m = re.fullmatch(r"(\d+)(MIN(?:UTE)?|H(?:OUR)?|D(?:AY)?|W(?:EEK)?)", p) + if not m: + raise ValueError( + f"Cannot convert period {period!r} to a pandas resample rule. " + "Expected format like '1MIN', '15MIN', '1H', '4H', '1D'." + ) + n, unit = m.group(1), m.group(2) + if unit.startswith("MIN"): + return f"{n}min" + if unit.startswith("H"): + return f"{n}h" + if unit.startswith("D"): + return f"{n}D" + if unit.startswith("W"): + return f"{n}W" + raise ValueError(f"Unsupported period unit in: {period!r}") # pragma: no cover + + +# --------------------------------------------------------------------------- +# Internal helpers (continued) +# --------------------------------------------------------------------------- + + +def _df_to_candles(df: "pd.DataFrame") -> list[Candle]: + """Vectorised conversion of a OHLCV DataFrame to a list of Candle objects. + + Avoids ``iterrows()`` (which creates a Series per row) by extracting columns + as Python lists in one vectorised call, then zipping. + """ + timestamps = cast(pd.DatetimeIndex, df.index).strftime("%Y-%m-%dT%H:%M:%SZ").tolist() + opens = df["open"].tolist() + highs = df["high"].tolist() + lows = df["low"].tolist() + closes = df["close"].tolist() + volumes = df["volume"].tolist() + return [ + Candle(timestamp=ts, open=o, high=h, low=lo, close=c, volume=v) + for ts, o, h, lo, c, v in zip(timestamps, opens, highs, lows, closes, volumes) + ] + + +# --------------------------------------------------------------------------- +# Public API +# --------------------------------------------------------------------------- + + +def read_dukascopy_candles( + cache_dir: Path, + symbol: str, + period: str, + date_from: date, + date_to: date, + *, + price_side: str = "bid", +) -> list[Candle]: + """ + Read 1-minute candle data from a Dukascopy cache and resample to OHLCV ``Candle`` objects. + + Args: + cache_dir: Root of the Dukascopy cache directory. + symbol: Symbol subfolder name (e.g. ``"EURUSD"``). + period: Tradedesk period string (e.g. ``"1MIN"``, ``"15MIN"``, ``"1H"``). + date_from: First date to include (inclusive, UTC). + date_to: Last date to include (inclusive, UTC). + price_side: ``"bid"`` (default) or ``"ask"``. + + Returns: + List of ``Candle`` objects ordered oldest to newest. + + Raises: + SystemExit: If old-format ``.bi5`` hourly files are found in the cache. + ValueError: If ``price_side`` is not ``"bid"`` or ``"ask"``. + ValueError: If no candle data is found in the requested date range. + """ + if price_side not in ("bid", "ask"): + raise ValueError(f"price_side must be 'bid' or 'ask'; got {price_side!r}") + + resample_rule = _period_to_pandas_rule(period) + frames: list[pd.DataFrame] = [] + + for day in _iter_days(date_from, date_to): + _check_old_format(cache_dir, symbol, day) + path = _candle_path(cache_dir, symbol, day, price_side) + df = _load_daily_candles(path) + if df is None or df.empty: + continue + frames.append(df) + + if not frames: + raise ValueError( + f"No candle data found for symbol={symbol!r} in cache {cache_dir} " + f"between {date_from} and {date_to}." + ) + + all_1min = pd.concat(frames).sort_index() + resampled = all_1min.resample(resample_rule).agg( + {"open": "first", "high": "max", "low": "min", "close": "last", "volume": "sum"} + ) + resampled = resampled.dropna(subset=["open"]) + + return _df_to_candles(resampled) + + +def iter_dukascopy_candles( + cache_dir: Path, + symbol: str, + period: str, + date_from: date, + date_to: date, + *, + price_side: str = "bid", +) -> Iterator[Candle]: + """Lazily iterate OHLCV Candle objects from a Dukascopy cache, one day at a time. + + Yields candles in chronological order without loading the full date range into + memory. Each daily file is read, optionally resampled to *period*, and its + candles are yielded before the next day is loaded. + + Unlike :func:`read_dukascopy_candles`, this function does **not** raise + ``ValueError`` when no data is found — an empty date range simply produces no + candles. Input validation (``price_side``, ``period`` format) is performed + eagerly at call time, before any iteration occurs. + + Args: + cache_dir: Root of the Dukascopy cache directory. + symbol: Symbol subfolder name (e.g. ``"EURUSD"``). + period: Tradedesk period string (e.g. ``"1MIN"``, ``"15MIN"``, ``"1H"``). + date_from: First date to include (inclusive, UTC). + date_to: Last date to include (inclusive, UTC). + price_side: ``"bid"`` (default) or ``"ask"``. + + Raises: + ValueError: If ``price_side`` is not ``"bid"`` or ``"ask"``. + ValueError: If *period* cannot be parsed (raised immediately, before iteration). + SystemExit: If old-format ``.bi5`` hourly files are found in the cache. + """ + # Validate eagerly before returning the generator — generator function bodies + # only execute on first next() call, so we perform all input validation here + # and delegate to a private generator. + if price_side not in ("bid", "ask"): + raise ValueError(f"price_side must be 'bid' or 'ask'; got {price_side!r}") + resample_rule = _period_to_pandas_rule(period) # raises ValueError for bad period + return _iter_candles(cache_dir, symbol, resample_rule, date_from, date_to, price_side) + + +def _iter_candles( + cache_dir: Path, + symbol: str, + resample_rule: str, + date_from: date, + date_to: date, + price_side: str, +) -> Iterator[Candle]: + """Private generator — assumes all inputs are pre-validated.""" + is_1min = resample_rule == "1min" + + for day in _iter_days(date_from, date_to): + _check_old_format(cache_dir, symbol, day) + path = _candle_path(cache_dir, symbol, day, price_side) + df = _load_daily_candles(path) + if df is None or df.empty: + continue + + if is_1min: + yield from _df_to_candles(df) + else: + resampled = df.resample(resample_rule).agg( + {"open": "first", "high": "max", "low": "min", "close": "last", "volume": "sum"} + ) + resampled = resampled.dropna(subset=["open"]) + yield from _df_to_candles(resampled) diff --git a/tradedesk/execution/backtest/runner.py b/tradedesk/execution/backtest/runner.py index b3cee96..39e65eb 100644 --- a/tradedesk/execution/backtest/runner.py +++ b/tradedesk/execution/backtest/runner.py @@ -4,6 +4,7 @@ from __future__ import annotations from dataclasses import dataclass +from datetime import date from pathlib import Path from typing import TYPE_CHECKING, Callable @@ -21,6 +22,7 @@ register_recording_subscriber, trade_rows_from_trades, ) +from tradedesk.types import Candle from .client import BacktestClient @@ -31,7 +33,11 @@ class BacktestSpec: instrument: str period: str - candle_csv: Path + cache_dir: Path + symbol: str + date_from: date + date_to: date + price_side: str = "bid" size: float = 1.0 half_spread_adjustment: float = 0.0 reporting_scale: float = 1.0 @@ -41,7 +47,7 @@ async def run_backtest( *, spec: BacktestSpec, out_dir: Path, - portfolio_factory: Callable[[BacktestClient], BasePortfolio], + portfolio_factory: Callable[[BacktestClient], "BasePortfolio"], ) -> Metrics: """ Event-driven backtest runner. @@ -50,7 +56,7 @@ async def run_backtest( to the portfolio (warmup via SessionStartedEvent, streaming, SessionEndedEvent). Args: - spec: BacktestSpec with instrument, period, CSV path, etc. + spec: BacktestSpec with instrument, period, cache location and date range. out_dir: Directory to write CSV artefacts. portfolio_factory: Callable that receives a BacktestClient and returns an initialised BasePortfolio. @@ -58,9 +64,14 @@ async def run_backtest( Returns: Metrics object with performance statistics. """ - # Create backtest client and load candles - raw_client = BacktestClient.from_csv( - spec.candle_csv, instrument=spec.instrument, period=spec.period + raw_client = BacktestClient.from_dukascopy_cache( + spec.cache_dir, + symbol=spec.symbol, + instrument=spec.instrument, + period=spec.period, + date_from=spec.date_from, + date_to=spec.date_to, + price_side=spec.price_side, ) await raw_client.start() @@ -85,7 +96,7 @@ async def run_backtest( # Build candle index for excursion tracking streamer = raw_client.get_streamer() - all_candles = [] + all_candles: list[Candle] = [] for series in streamer._candle_series: if series.instrument == spec.instrument and series.period == spec.period: all_candles.extend(series.candles) diff --git a/tradedesk/execution/backtest/streamer.py b/tradedesk/execution/backtest/streamer.py index fc65290..ab12462 100644 --- a/tradedesk/execution/backtest/streamer.py +++ b/tradedesk/execution/backtest/streamer.py @@ -1,4 +1,7 @@ +import heapq +import itertools import logging +from collections.abc import Iterator from dataclasses import dataclass from datetime import datetime from typing import Any, Iterable @@ -36,7 +39,7 @@ def _parse_ts(ts: str) -> datetime: class CandleSeries: instrument: str period: str - candles: list[Candle] + candles: Iterable[Candle] @dataclass(frozen=True) @@ -45,6 +48,33 @@ class MarketSeries: ticks: list[MarketData] +def _candle_gen( + cseries: CandleSeries, seq: Iterator[int] +) -> Iterator[tuple[datetime, int, CandleClosedEvent]]: + """Yield (timestamp, seq, CandleClosedEvent) for each candle in *cseries*.""" + for c in cseries.candles: + ts = _parse_ts(c.timestamp) + yield ( + ts, + next(seq), + CandleClosedEvent( + instrument=cseries.instrument, + timeframe=cseries.period, + candle=c, + timestamp=ts, + ), + ) + + +def _market_gen( + mseries: MarketSeries, seq: Iterator[int] +) -> Iterator[tuple[datetime, int, MarketData]]: + """Yield (timestamp, seq, MarketData) for each tick in *mseries*.""" + for t in mseries.ticks: + ts = _parse_ts(t.timestamp) + yield (ts, next(seq), t) + + class BacktestStreamer(Streamer): """ Replay streamer. @@ -73,54 +103,28 @@ async def disconnect(self) -> None: async def run(self, consumer: Any) -> None: await self.connect() - stream: list[tuple[datetime, object]] = [] - - # Candle events - for cseries in self._candle_series: - for c in cseries.candles: - ts = _parse_ts(c.timestamp) - self._client._set_current_timestamp(ts.isoformat()) - stream.append( - ( - ts, - CandleClosedEvent( - instrument=cseries.instrument, - timeframe=cseries.period, - candle=c, - timestamp=ts, - ), - ) - ) - - # Market events - for mseries in self._market_series: - for t in mseries.ticks: - ts = _parse_ts(t.timestamp) - self._client._set_current_timestamp(ts.isoformat()) - stream.append((ts, t)) - - stream.sort(key=lambda x: x[0]) + # Shared monotonic counter used as a tiebreaker when two events share the + # same timestamp. It is consumed lazily as heapq.merge pulls items from + # each per-instrument generator, guaranteeing uniqueness without requiring + # CandleClosedEvent or MarketData to be orderable. + seq = itertools.count() + + streams: list[Iterator[Any]] = [_candle_gen(s, seq) for s in self._candle_series] + streams += [_market_gen(s, seq) for s in self._market_series] try: - for _, event in stream: + for _, __, event in heapq.merge(*streams): if isinstance(event, MarketData): event_ts = event.timestamp # Mark-to-market uses mid price by default - self._client._set_mark_price( - event.instrument, (event.bid + event.offer) / 2 - ) + self._client._set_mark_price(event.instrument, (event.bid + event.offer) / 2) elif isinstance(event, CandleClosedEvent): event_ts = event.candle.timestamp self._client._set_mark_price(event.instrument, event.candle.close) # Normalise to a stable ISO string with Z ts_str = event_ts.strip() - if ts_str.endswith("Z"): - ts_iso = ts_str - else: - # if already has +00:00 etc, keep it - ts_iso = ts_str.replace("+00:00", "Z") - + ts_iso = ts_str if ts_str.endswith("Z") else ts_str.replace("+00:00", "Z") self._client._set_current_timestamp(ts_iso) await consumer._handle_event(event) diff --git a/tradedesk/execution/ig/client.py b/tradedesk/execution/ig/client.py index 19ca483..3445418 100644 --- a/tradedesk/execution/ig/client.py +++ b/tradedesk/execution/ig/client.py @@ -36,12 +36,8 @@ class IGClient(Client): def __init__(self) -> None: # Choose the correct base URL for the selected environment - self.base_url = ( - self.DEMO_BASE if settings.ig_environment == "DEMO" else self.LIVE_BASE - ) - self.ls_url = ( - self.DEMO_LS if settings.ig_environment == "DEMO" else self.LIVE_LS - ) + self.base_url = self.DEMO_BASE if settings.ig_environment == "DEMO" else self.LIVE_BASE + self.ls_url = self.DEMO_LS if settings.ig_environment == "DEMO" else self.LIVE_LS # VERSION 2 returns CST/X-SECURITY-TOKEN (works with Lightstreamer) # VERSION 3 returns OAuth tokens (doesn't work with Lightstreamer) @@ -98,7 +94,7 @@ async def start(self) -> None: 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: @@ -250,8 +246,7 @@ async def _handle_v3_auth(self, body: dict[str, Any]) -> None: ) log.warning( - "Authenticated (V3 OAuth) – Streaming NOT available. " - "System will use REST polling." + "Authenticated (V3 OAuth) – Streaming NOT available. System will use REST polling." ) def _apply_session_headers(self, new_headers: dict[str, str]) -> None: @@ -320,13 +315,9 @@ async def _request( req_headers["VERSION"] = str(api_version) try: - async with self._session.request( - method, url, headers=req_headers, **kwargs - ) as resp: + async with self._session.request(method, url, headers=req_headers, **kwargs) as resp: if resp.status in (401, 403): - await self._handle_retry_logic( - resp, method, url, headers=req_headers, **kwargs - ) + await self._handle_retry_logic(resp, method, url, headers=req_headers, **kwargs) if resp.status >= 400: try: @@ -340,9 +331,7 @@ async def _request( err_body = " ".join(err_body.split())[:200] else: err_body = raw - raise RuntimeError( - f"IG request failed: HTTP {resp.status}: {err_body}" - ) + raise RuntimeError(f"IG request failed: HTTP {resp.status}: {err_body}") result = await resp.json() return result if isinstance(result, dict) else {} @@ -351,9 +340,7 @@ async def _request( log.error("Request failed: %s %s - %s", method, url, e) raise - async def _handle_retry_logic( - self, resp: Any, method: str, url: str, **kwargs: Any - ) -> None: + async def _handle_retry_logic(self, resp: Any, method: str, url: str, **kwargs: Any) -> None: """Attempts to re-authenticate and retry the request once.""" # 1. Check if it's a rate limit (unrecoverable) try: @@ -417,9 +404,7 @@ async def _ensure_account_type(self) -> str | None: payload = await self._get_accounts() accounts = payload.get("accounts") or [] - current = next( - (a for a in accounts if a.get("accountId") == self.account_id), None - ) + current = next((a for a in accounts if a.get("accountId") == self.account_id), None) self._account_type = (current or {}).get("accountType") return self._account_type @@ -564,9 +549,7 @@ async def get_account_balance(self) -> "AccountBalance": None, ) if current is None: - raise RuntimeError( - f"Account {self.account_id} not found in /accounts response" - ) + raise RuntimeError(f"Account {self.account_id} not found in /accounts response") bal = current.get("balance") or {} return AccountBalance( @@ -644,15 +627,11 @@ async def confirm_deal( while True: try: - payload = await self._request( - "GET", f"/confirms/{deal_reference}", api_version="1" - ) + payload = await self._request("GET", f"/confirms/{deal_reference}", api_version="1") status = (payload.get("dealStatus") or "").upper() if status and status != "PENDING": - log.info( - "Order %s confirmed with status: %s", deal_reference, status - ) + log.info("Order %s confirmed with status: %s", deal_reference, status) return payload except RuntimeError as e: @@ -662,9 +641,7 @@ async def confirm_deal( ) if retryable: last_err = e - log.debug( - "Transient error confirming deal %s: %s", deal_reference, msg - ) + log.debug("Transient error confirming deal %s: %s", deal_reference, msg) else: raise @@ -673,9 +650,7 @@ async def confirm_deal( raise TimeoutError( f"Timed out waiting for deal confirm (last error: {last_err})" ) from last_err - raise TimeoutError( - f"Timed out waiting for deal confirm: {deal_reference}" - ) + raise TimeoutError(f"Timed out waiting for deal confirm: {deal_reference}") await asyncio.sleep(poll_s) @@ -706,13 +681,9 @@ async def place_market_order_confirmed( ) deal_ref = res.get("dealReference") if not deal_ref: - raise RuntimeError( - f"Expected dealReference from place_market_order, got: {res}" - ) + raise RuntimeError(f"Expected dealReference from place_market_order, got: {res}") - deal = await self.confirm_deal( - deal_ref, timeout_s=confirm_timeout_s, poll_s=confirm_poll_s - ) + deal = await self.confirm_deal(deal_ref, timeout_s=confirm_timeout_s, poll_s=confirm_poll_s) if deal.get("dealStatus", "").upper() != "ACCEPTED": raise DealRejectedException(f"Deal rejected: {deal}") @@ -731,9 +702,7 @@ async def get_historical_candles( return [] resolution = self._period_to_rest_resolution(period) - payload = await self._request( - "GET", f"/prices/{epic}/{resolution}/{num_points}" - ) + payload = await self._request("GET", f"/prices/{epic}/{resolution}/{num_points}") prices = payload.get("prices") or [] candles: list[Candle] = [] diff --git a/tradedesk/execution/ig/price_streamer.py b/tradedesk/execution/ig/price_streamer.py index 5ed0530..44d295f 100644 --- a/tradedesk/execution/ig/price_streamer.py +++ b/tradedesk/execution/ig/price_streamer.py @@ -65,9 +65,7 @@ async def run(self, consumer: Any) -> None: ls_client = LightstreamerClient(self.client.ls_url, "DEFAULT") self._ls_client = ls_client - ls_client.connectionDetails.setUser( - self.client.client_id or self.client.account_id or "" - ) + ls_client.connectionDetails.setUser(self.client.client_id or self.client.account_id or "") ls_client.connectionDetails.setPassword( f"CST-{self.client.ls_cst}|XST-{self.client.ls_xst}" ) @@ -78,12 +76,8 @@ async def run(self, consumer: Any) -> None: self.client.client_id, ) - market_subs = [ - s for s in consumer.subscriptions if isinstance(s, MarketSubscription) - ] - chart_subs = [ - s for s in consumer.subscriptions if isinstance(s, ChartSubscription) - ] + market_subs = [s for s in consumer.subscriptions if isinstance(s, MarketSubscription)] + chart_subs = [s for s in consumer.subscriptions if isinstance(s, ChartSubscription)] subscriptions = [] @@ -105,17 +99,11 @@ def onItemUpdate(self, update: Any) -> None: return item_name = update.getItemName() - epic = ( - item_name.split(":", 1)[1] - if ":" in item_name - else item_name - ) + epic = item_name.split(":", 1)[1] if ":" in item_name else item_name data = { "type": "market", - "timestamp": datetime.now(timezone.utc).isoformat( - timespec="seconds" - ) + "timestamp": datetime.now(timezone.utc).isoformat(timespec="seconds") + "Z", "instrument": epic, "bid": float(bid_str), @@ -175,16 +163,13 @@ def onItemUpdate(self, update: Any) -> None: return open_price = ( - float(ofr_open or ofr_close) - + float(bid_open or bid_close) + float(ofr_open or ofr_close) + float(bid_open or bid_close) ) / 2 high_price = ( - float(ofr_high or ofr_close) - + float(bid_high or bid_close) + float(ofr_high or ofr_close) + float(bid_high or bid_close) ) / 2 low_price = ( - float(ofr_low or ofr_close) - + float(bid_low or bid_close) + float(ofr_low or ofr_close) + float(bid_low or bid_close) ) / 2 close_price = (float(ofr_close) + float(bid_close)) / 2 @@ -284,9 +269,7 @@ def _period_seconds(period: str) -> int: async def _heartbeat_monitor() -> None: while True: await asyncio.sleep(self.heartbeat_sleep) - delta = ( - datetime.now(timezone.utc) - consumer.last_update - ).total_seconds() + delta = (datetime.now(timezone.utc) - consumer.last_update).total_seconds() if delta > consumer.watchdog_threshold: log.warning( "❤ Heartbeat Alert: no updates for %s in %.1fs. Connection may be stale.", @@ -344,9 +327,7 @@ async def chart_consumer() -> None: try: await asyncio.Future() except asyncio.CancelledError: - log.info( - "%s cancelled – cleaning up Lightstreamer", consumer.__class__.__name__ - ) + log.info("%s cancelled – cleaning up Lightstreamer", consumer.__class__.__name__) finally: for task in tasks: task.cancel() diff --git a/tradedesk/execution/order_handler.py b/tradedesk/execution/order_handler.py index 320ef83..05b2c82 100644 --- a/tradedesk/execution/order_handler.py +++ b/tradedesk/execution/order_handler.py @@ -54,9 +54,7 @@ async def request_order(request: OrderRequest, *, timeout: float = 30.0) -> Orde future: asyncio.Future[OrderResult] = loop.create_future() _pending_orders[request_id] = future - await get_dispatcher().publish( - OrderRequestEvent(request=request, request_id=request_id) - ) + await get_dispatcher().publish(OrderRequestEvent(request=request, request_id=request_id)) try: return await asyncio.wait_for(future, timeout=timeout) diff --git a/tradedesk/marketdata/aggregation.py b/tradedesk/marketdata/aggregation.py index 3ce2fe0..a333297 100644 --- a/tradedesk/marketdata/aggregation.py +++ b/tradedesk/marketdata/aggregation.py @@ -21,9 +21,7 @@ def _period_to_seconds(period: str) -> int: raise ValueError(f"Unsupported period: {period!r}") -def choose_base_period( - target_period: str, *, supported_periods: list[str] | None = None -) -> str: +def choose_base_period(target_period: str, *, supported_periods: list[str] | None = None) -> str: """ Choose a suitable base period for building target_period. @@ -119,9 +117,7 @@ def __init__( self.base_period = ( ( base_period - or choose_base_period( - self.target_period, supported_periods=supported_periods - ) + or choose_base_period(self.target_period, supported_periods=supported_periods) ) .strip() .upper() diff --git a/tradedesk/marketdata/indicators/adx.py b/tradedesk/marketdata/indicators/adx.py index 4e57e26..b783579 100644 --- a/tradedesk/marketdata/indicators/adx.py +++ b/tradedesk/marketdata/indicators/adx.py @@ -130,9 +130,7 @@ def _compute_dx(plus_di: float, minus_di: float) -> float: return 0.0 return 100.0 * abs(plus_di - minus_di) / denom - def _update_adx( - self, dx: float, plus_di: float, minus_di: float - ) -> dict[str, float | None]: + def _update_adx(self, dx: float, plus_di: float, minus_di: float) -> dict[str, float | None]: # Seed ADX with SMA of first `period` DX values if self._adx is None: self._dx_seed_sum += dx diff --git a/tradedesk/marketdata/indicators/macd.py b/tradedesk/marketdata/indicators/macd.py index dfb1a60..ffbc90b 100644 --- a/tradedesk/marketdata/indicators/macd.py +++ b/tradedesk/marketdata/indicators/macd.py @@ -91,9 +91,7 @@ def update(self, candle: Candle) -> dict[str, float | None]: # Initialize EMAs with SMA when we have enough data if self.fast_ema is None and len(self.closes) >= self.fast_period: - self.fast_ema = ( - sum(list(self.closes)[-self.fast_period :]) / self.fast_period - ) + self.fast_ema = sum(list(self.closes)[-self.fast_period :]) / self.fast_period if self.slow_ema is None and len(self.closes) >= self.slow_period: self.slow_ema = sum(self.closes) / self.slow_period @@ -147,9 +145,7 @@ def ready(self) -> bool: True if all components (MACD, signal, histogram) are available """ return ( - self.fast_ema is not None - and self.slow_ema is not None - and self.signal_ema is not None + self.fast_ema is not None and self.slow_ema is not None and self.signal_ema is not None ) def reset(self) -> None: diff --git a/tradedesk/marketdata/instrument.py b/tradedesk/marketdata/instrument.py index a15ea52..811fe89 100644 --- a/tradedesk/marketdata/instrument.py +++ b/tradedesk/marketdata/instrument.py @@ -58,9 +58,7 @@ def _validate_isin(self, isin: str) -> None: ) # 2. Convert letters to digits (A=10, B=11, ..., Z=35) - digits_str = "".join( - str(int(char, 36)) if char.isalpha() else char for char in isin - ) + digits_str = "".join(str(int(char, 36)) if char.isalpha() else char for char in isin) # 3. Apply Luhn Algorithm digits = [int(d) for d in digits_str] diff --git a/tradedesk/portfolio/config.py b/tradedesk/portfolio/config.py index 8362f77..fe664cf 100644 --- a/tradedesk/portfolio/config.py +++ b/tradedesk/portfolio/config.py @@ -1,6 +1,7 @@ from __future__ import annotations from dataclasses import dataclass +from datetime import date from pathlib import Path from typing import Any @@ -20,20 +21,26 @@ class PortfolioConfig: @dataclass(frozen=True) class BacktestPortfolioConfig(PortfolioConfig): - input_dir: Path + cache_dir: Path + date_from: date + date_to: date half_spread_adjustment: float + with_graphs: bool = True @classmethod def from_raw( cls, *, instruments: list[str], - input_dir: Path, + cache_dir: Path, + date_from: date, + date_to: date, output_dir: Path, half_spread_adjustment: float, risk: dict[str, Any], sizing: dict[str, Any], base_period: str | None, + with_graphs: bool = True, ) -> BacktestPortfolioConfig: """Validate and construct from raw config dicts. @@ -55,7 +62,9 @@ def from_raw( return cls( instruments=instruments, - input_dir=input_dir, + cache_dir=cache_dir, + date_from=date_from, + date_to=date_to, output_dir=output_dir, half_spread_adjustment=float(half_spread_adjustment), default_risk_per_trade=default_risk, @@ -65,6 +74,7 @@ def from_raw( min_size=float(sizing.get("min_size", 0.1)), max_size=float(sizing.get("max_size", 5.0)), base_period=base_period, + with_graphs=with_graphs, ) diff --git a/tradedesk/portfolio/metrics_tracker.py b/tradedesk/portfolio/metrics_tracker.py index c78fb50..61a522d 100644 --- a/tradedesk/portfolio/metrics_tracker.py +++ b/tradedesk/portfolio/metrics_tracker.py @@ -50,9 +50,7 @@ class WeightedRollingTracker: # Internal state _windows: dict[str, InstrumentWindow] = field(default_factory=dict, init=False) _trade_count: int = field(default=0, init=False) - _cached_metrics: dict[str, dict[str, float | int]] | None = field( - default=None, init=False - ) + _cached_metrics: dict[str, dict[str, float | int]] | None = field(default=None, init=False) def __post_init__(self) -> None: """Validate decay weights sum to 1.0.""" @@ -177,9 +175,7 @@ def compute_metrics( total_weighted_risk = sum(abs(p) for p in weighted_pnls) return_to_risk = ( - total_weighted_pnl / total_weighted_risk - if total_weighted_risk > 0 - else 0.0 + total_weighted_pnl / total_weighted_risk if total_weighted_risk > 0 else 0.0 ) all_metrics[instrument] = { @@ -196,9 +192,7 @@ def compute_metrics( for inst in instruments: instrument = str(inst) - metrics_by_instrument[inst] = all_metrics.get( - instrument, self._empty_metrics() - ) + metrics_by_instrument[inst] = all_metrics.get(instrument, self._empty_metrics()) return metrics_by_instrument diff --git a/tradedesk/portfolio/reconciliation.py b/tradedesk/portfolio/reconciliation.py index a90126f..eee0dc2 100644 --- a/tradedesk/portfolio/reconciliation.py +++ b/tradedesk/portfolio/reconciliation.py @@ -57,15 +57,11 @@ def has_emergencies(self) -> bool: @property def orphan_broker_positions(self) -> list[ReconciliationEntry]: - return [ - e for e in self.entries if e.discrepancy == DiscrepancyType.ORPHAN_BROKER - ] + return [e for e in self.entries if e.discrepancy == DiscrepancyType.ORPHAN_BROKER] @property def phantom_local_positions(self) -> list[ReconciliationEntry]: - return [ - e for e in self.entries if e.discrepancy == DiscrepancyType.PHANTOM_LOCAL - ] + return [e for e in self.entries if e.discrepancy == DiscrepancyType.PHANTOM_LOCAL] def _direction_matches(journal_dir: str | None, broker_dir: str) -> bool: @@ -110,9 +106,7 @@ def reconcile( journal_entry = journal_positions.get(instrument) broker_pos = broker_by_instrument.get(instrument) - journal_has_position = ( - journal_entry is not None and journal_entry.direction is not None - ) + journal_has_position = journal_entry is not None and journal_entry.direction is not None broker_has_position = broker_pos is not None if not journal_has_position and not broker_has_position: @@ -154,8 +148,7 @@ def reconcile( broker_size=broker_pos.size, broker_deal_id=broker_pos.deal_id, message=( - f"Size mismatch: journal={journal_entry.size} " - f"broker={broker_pos.size}" + f"Size mismatch: journal={journal_entry.size} broker={broker_pos.size}" ), ) ) @@ -186,8 +179,7 @@ def reconcile( broker_size=broker_pos.size, broker_deal_id=broker_pos.deal_id, message=( - "EMERGENCY: Journal records flat but broker has position " - "(failed exit?)" + "EMERGENCY: Journal records flat but broker has position (failed exit?)" ), ) ) @@ -213,8 +205,7 @@ def reconcile( journal_direction=journal_entry.direction, journal_size=journal_entry.size, message=( - "Journal has position but broker does not " - "(was it closed externally?)" + "Journal has position but broker does not (was it closed externally?)" ), ) ) @@ -275,10 +266,7 @@ async def _on_session_ready(self, event: SessionReadyEvent) -> None: async def _on_candle_closed(self, event: DomainEvent) -> None: """Handle target-period candle events for periodic reconciliation.""" - if ( - not isinstance(event, CandleClosedEvent) - or event.timeframe != self._target_period - ): + if not isinstance(event, CandleClosedEvent) or event.timeframe != self._target_period: return # Increment candle counter @@ -290,11 +278,8 @@ async def _on_candle_closed(self, event: DomainEvent) -> None: def _should_reconcile_now(self) -> bool: """Internal check if reconciliation threshold reached (without incrementing).""" - return ( - self._journal is not None - and self._candle_count % self._reconcile_interval == 0 - ) - + return 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() @@ -333,8 +318,7 @@ async def reconcile_on_startup(self) -> set[str]: broker_positions = await self.client.get_positions() except Exception: log.exception( - "Failed to fetch broker positions for reconciliation; " - "restoring from journal only" + "Failed to fetch broker positions for reconciliation; restoring from journal only" ) if journal_entries is not None: restored_instruments = self._restore_from_journal(journal_positions) @@ -366,9 +350,7 @@ async def reconcile_on_startup(self) -> set[str]: entry.journal_size, ) else: - log.warning( - "Reconciliation: %s -- %s", entry.instrument, entry.message - ) + log.warning("Reconciliation: %s -- %s", entry.instrument, entry.message) # Handle emergencies if result.has_emergencies: @@ -413,9 +395,7 @@ async def reconcile_on_startup(self) -> set[str]: return restored_instruments - def _restore_from_journal( - self, journal_positions: dict[str, JournalEntry] - ) -> set[str]: + def _restore_from_journal(self, journal_positions: dict[str, JournalEntry]) -> set[str]: """Restore positions from journal only (broker unreachable).""" restored: set[str] = set() for inst, s in self._runner.strategies.items(): @@ -455,10 +435,7 @@ def _apply_reconciliation( if entry is None: continue - if ( - entry.discrepancy == DiscrepancyType.MATCHED - and entry.journal_direction is not None - ): + if entry.discrepancy == DiscrepancyType.MATCHED and entry.journal_direction is not None: # Restore from journal (has bars_held, mfe_points, entry_atr) journal_entry = journal_positions.get(epic) if journal_entry is not None: @@ -473,11 +450,7 @@ def _apply_reconciliation( elif entry.discrepancy == DiscrepancyType.ORPHAN_BROKER: # Adopt broker position - direction = ( - Direction.LONG - if entry.broker_direction == "BUY" - else Direction.SHORT - ) + direction = Direction.LONG if entry.broker_direction == "BUY" else Direction.SHORT broker_pos = broker_by_instrument.get(epic) entry_price = broker_pos.entry_price if broker_pos else 0.0 strat.position.open(direction, entry.broker_size or 0.0, entry_price) @@ -509,11 +482,7 @@ def _apply_reconciliation( DiscrepancyType.DIRECTION_MISMATCH, ): # Broker has a position that contradicts journal -- adopt broker state - direction = ( - Direction.LONG - if entry.broker_direction == "BUY" - else Direction.SHORT - ) + direction = Direction.LONG if entry.broker_direction == "BUY" else Direction.SHORT broker_pos = broker_by_instrument.get(epic) entry_price = broker_pos.entry_price if broker_pos else 0.0 strat.position.open(direction, entry.broker_size or 0.0, entry_price) @@ -559,13 +528,9 @@ async def post_warmup_check(self, restored_instruments: set[str]) -> None: # Fetch latest candle to get current price try: - candles = await self.client.get_historical_candles( - epic, self._target_period, 1 - ) + candles = await self.client.get_historical_candles(epic, self._target_period, 1) if not candles: - log.warning( - "No candles available for post-reconciliation check on %s", epic - ) + log.warning("No candles available for post-reconciliation check on %s", epic) continue candle = candles[-1] @@ -608,9 +573,7 @@ async def periodic_reconcile(self) -> None: try: broker_positions = await self.client.get_positions() except Exception: - log.warning( - "Periodic reconciliation skipped: failed to fetch broker positions" - ) + log.warning("Periodic reconciliation skipped: failed to fetch broker positions") return # Build current local state @@ -659,7 +622,7 @@ async def periodic_reconcile(self) -> None: # Broker has no position -- reset local to flat log.warning( "PHANTOM corrected: %s was %s size=%s locally but broker has no position; " - "resetting to flat", + "resetting to flat", entry.instrument, entry.journal_direction, entry.journal_size, @@ -672,11 +635,7 @@ async def periodic_reconcile(self) -> None: DiscrepancyType.ORPHAN_BROKER, ): # Broker has position we don't have locally -- adopt it - direction = ( - Direction.LONG - if entry.broker_direction == "BUY" - else Direction.SHORT - ) + direction = Direction.LONG if entry.broker_direction == "BUY" else Direction.SHORT bp = broker_by_instrument.get(entry.instrument) entry_price = bp.entry_price if bp else 0.0 strat.position.open(direction, entry.broker_size or 0.0, entry_price) @@ -704,11 +663,7 @@ async def periodic_reconcile(self) -> None: elif entry.discrepancy == DiscrepancyType.DIRECTION_MISMATCH: # Broker direction wins -- reset and re-open with broker state - direction = ( - Direction.LONG - if entry.broker_direction == "BUY" - else Direction.SHORT - ) + direction = Direction.LONG if entry.broker_direction == "BUY" else Direction.SHORT bp = broker_by_instrument.get(entry.instrument) entry_price = bp.entry_price if bp else 0.0 strat.position.reset() @@ -757,9 +712,7 @@ async def log_margin_status(self) -> None: return try: balance = await get_balance() - utilisation = ( - (balance.deposit / balance.balance * 100) if balance.balance > 0 else 0 - ) + utilisation = (balance.deposit / balance.balance * 100) if balance.balance > 0 else 0 log.info( "Margin status: balance=%.2f deposit=%.2f available=%.2f utilisation=%.1f%%", balance.balance, diff --git a/tradedesk/portfolio/risk.py b/tradedesk/portfolio/risk.py index 08db226..7f9f74b 100644 --- a/tradedesk/portfolio/risk.py +++ b/tradedesk/portfolio/risk.py @@ -47,9 +47,7 @@ class RiskAllocationPolicy(ABC): """ @abstractmethod - def allocate( - self, active_instruments: list[Instrument] - ) -> Mapping[Instrument, float]: + def allocate(self, active_instruments: list[Instrument]) -> Mapping[Instrument, float]: """ Allocate risk budget across active instruments. @@ -74,9 +72,7 @@ class EqualSplitRiskPolicy(RiskAllocationPolicy): portfolio_risk_budget: float - def allocate( - self, active_instruments: list[Instrument] - ) -> Mapping[Instrument, float]: + def allocate(self, active_instruments: list[Instrument]) -> Mapping[Instrument, float]: """ Allocate risk budget across active instruments. diff --git a/tradedesk/recording/events.py b/tradedesk/recording/events.py index 7de27e0..96df19f 100644 --- a/tradedesk/recording/events.py +++ b/tradedesk/recording/events.py @@ -4,12 +4,14 @@ @event class ReportingCompleteEvent(DomainEvent): """Emitted when session reporting is complete.""" + pass @event class PositionOpenedEvent(DomainEvent): """Emitted when a new position is opened.""" + instrument: str direction: str # "BUY" or "SELL" size: float @@ -19,6 +21,7 @@ class PositionOpenedEvent(DomainEvent): @event class PositionClosedEvent(DomainEvent): """Emitted when a position is fully closed.""" + instrument: str direction: str # "BUY" or "SELL" (the direction of the position that was closed) size: float @@ -31,6 +34,7 @@ class PositionClosedEvent(DomainEvent): @event class EquitySampledEvent(DomainEvent): """Emitted when portfolio equity is sampled.""" + equity: float realised_pnl: float unrealised_pnl: float @@ -39,6 +43,7 @@ class EquitySampledEvent(DomainEvent): @event class ExcursionSampledEvent(DomainEvent): """Emitted when MFE/MAE excursions are computed for an open position.""" + instrument: str mfe_points: float # Maximum Favorable Excursion in points mae_points: float # Maximum Adverse Excursion in points diff --git a/tradedesk/recording/ledger.py b/tradedesk/recording/ledger.py index 073feaa..4453664 100644 --- a/tradedesk/recording/ledger.py +++ b/tradedesk/recording/ledger.py @@ -101,9 +101,7 @@ def write_trades_csv(self, path: Path) -> None: path.parent.mkdir(parents=True, exist_ok=True) with path.open("w", newline="") as f: w = csv.writer(f) - w.writerow( - ["timestamp", "instrument", "direction", "size", "price", "reason"] - ) + w.writerow(["timestamp", "instrument", "direction", "size", "price", "reason"]) for t in self.trades: w.writerow( [ @@ -213,14 +211,10 @@ def write_metrics_csv(self, path: Path) -> None: """ path.parent.mkdir(parents=True, exist_ok=True) - equity_rows = [ - {"timestamp": e.timestamp, "equity": str(e.equity)} for e in self.equity - ] + 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 - ) + 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 @@ -239,12 +233,11 @@ def write_metrics_csv(self, path: Path) -> None: "profit_factor", "expectancy", "avg_hold_min", + "sharpe_ratio", ] def _metrics_row( - label: str, - met: Metrics, - pnl_override: float | None = None + label: str, met: Metrics, pnl_override: float | None = None ) -> list[object]: return [ label, @@ -258,6 +251,7 @@ def _metrics_row( round(met.profit_factor, 2), round(met.expectancy, 2), round(met.avg_hold_minutes, 2), + round(met.sharpe_ratio, 2), ] with path.open("w", newline="") as f: @@ -311,16 +305,10 @@ def write_equity_daily_csv(self, path: Path) -> None: day = dt.date().isoformat() by_date[day] = float(e.equity) except ValueError as ex: - raise ValueError( - f"Failed to parse equity timestamp: {e.timestamp!r}" - ) from ex + raise ValueError(f"Failed to parse equity timestamp: {e.timestamp!r}") from ex - start_dt = ( - parse_timestamp(self.equity[0].timestamp).astimezone(timezone.utc).date() - ) - end_dt = ( - parse_timestamp(self.equity[-1].timestamp).astimezone(timezone.utc).date() - ) + start_dt = parse_timestamp(self.equity[0].timestamp).astimezone(timezone.utc).date() + end_dt = parse_timestamp(self.equity[-1].timestamp).astimezone(timezone.utc).date() with path.open("w", newline="") as f: w = csv.writer(f) @@ -365,8 +353,7 @@ def write_exposure_csv(self, path: Path) -> None: trips = round_trips_from_fills(trade_rows) windows = [ - (parse_timestamp(t.entry_ts), parse_timestamp(t.exit_ts), t.instrument) - for t in trips + (parse_timestamp(t.entry_ts), parse_timestamp(t.exit_ts), t.instrument) for t in trips ] with path.open("w", newline="") as f: @@ -447,9 +434,7 @@ def _initialize_trades_csv(self) -> None: path = self.out_dir / "trades.csv" with path.open("w", newline="") as f: w = csv.writer(f) - w.writerow( - ["timestamp", "instrument", "direction", "size", "price", "reason"] - ) + w.writerow(["timestamp", "instrument", "direction", "size", "price", "reason"]) def _append_trade_to_csv(self, record: TradeRecord) -> None: """Atomic append of single trade (broker mode only)""" diff --git a/tradedesk/recording/loader.py b/tradedesk/recording/loader.py index d1dd3fe..d9d947e 100644 --- a/tradedesk/recording/loader.py +++ b/tradedesk/recording/loader.py @@ -58,15 +58,17 @@ def load_trades_from_backtest(backtest_dir: Path) -> list[dict[str, str | float] # Convert to simple dict format trades = [] for trip in round_trips: - trades.append({ - "instrument": trip.instrument, - "direction": trip.direction.value, - "entry_ts": trip.entry_ts, - "exit_ts": trip.exit_ts, - "entry_price": trip.entry_price, - "exit_price": trip.exit_price, - "size": trip.size, - "pnl": trip.pnl, - }) + trades.append( + { + "instrument": trip.instrument, + "direction": trip.direction.value, + "entry_ts": trip.entry_ts, + "exit_ts": trip.exit_ts, + "entry_price": trip.entry_price, + "exit_price": trip.exit_price, + "size": trip.size, + "pnl": trip.pnl, + } + ) return trades diff --git a/tradedesk/recording/metrics.py b/tradedesk/recording/metrics.py index d552c4b..9176ecd 100644 --- a/tradedesk/recording/metrics.py +++ b/tradedesk/recording/metrics.py @@ -1,5 +1,6 @@ """Performance metrics and trade analysis.""" +import math from dataclasses import dataclass from datetime import datetime from typing import Any, Iterable @@ -39,6 +40,7 @@ class Metrics: final_equity: float avg_hold_minutes: float exits_by_reason: dict[str, int] + sharpe_ratio: float def _parse_ts(ts: str) -> datetime: @@ -130,9 +132,7 @@ def round_trips_from_fills(rows: list[dict[str, Any]]) -> list[RoundTrip]: # If sizes ever differ, this simplistic pairing is insufficient. if abs(entry_size - size) > 1e-9: - raise ValueError( - f"Size mismatch for {instrument}: entry {entry_size} exit {size}" - ) + raise ValueError(f"Size mismatch for {instrument}: entry {entry_size} exit {size}") pnl = ( (price - entry_price) * size @@ -179,18 +179,11 @@ def compute_metrics( if reporting_scale <= 0: raise ValueError("reporting_scale must be > 0") - equity = [ - float(r["equity"]) for r in equity_rows if r.get("equity") not in (None, "") - ] + equity = [float(r["equity"]) for r in equity_rows if r.get("equity") not in (None, "")] final_equity = equity[-1] if equity else 0.0 trips = round_trips_from_fills(trade_rows) - exits_by_reason: dict[str, int] = {} - for t in trips: - k = t.exit_reason or "unknown" - exits_by_reason[k] = exits_by_reason.get(k, 0) + 1 - pnls = [t.pnl for t in trips] wins = [p for p in pnls if p > 0] losses = [p for p in pnls if p < 0] @@ -211,15 +204,39 @@ def compute_metrics( win_rate = (wins_n / rt_n) if rt_n else 0.0 expectancy = (win_rate * avg_win + (1.0 - win_rate) * avg_loss) if rt_n else 0.0 - # Holding time + # 2. Sharpe Ratio Calculation (Daily Basis) + daily_pnls: dict[str, float] = {} + for t in trips: + # Extract date from exit timestamp (YYYY-MM-DD) + day_key = t.exit_ts[:10] + daily_pnls[day_key] = daily_pnls.get(day_key, 0.0) + t.pnl + + daily_values = list(daily_pnls.values()) + n_days = len(daily_values) + + sharpe_ann = 0.0 + if n_days > 1: + mean_d = sum(daily_values) / n_days + # Sample standard deviation + variance_d = sum((x - mean_d) ** 2 for x in daily_values) / (n_days - 1) + std_d = math.sqrt(variance_d) + + if std_d > 0: + # Annualize by multiplying by sqrt of 252 trading days + sharpe_ann = (mean_d / std_d) * math.sqrt(252) + + # 3. Holding Time and Exits + exits_by_reason: dict[str, int] = {} + for t in trips: + k = t.exit_reason or "unknown" + exits_by_reason[k] = exits_by_reason.get(k, 0) + 1 + hold_mins: list[float] = [] for t in trips: - if t.entry_ts and t.exit_ts: - dt = _parse_ts(t.exit_ts) - _parse_ts(t.entry_ts) - hold_mins.append(dt.total_seconds() / 60.0) - avg_hold = (sum(hold_mins) / len(hold_mins)) if hold_mins else 0.0 + dt = _parse_ts(t.exit_ts) - _parse_ts(t.entry_ts) + hold_mins.append(dt.total_seconds() / 60.0) - scale = float(reporting_scale) + avg_hold = (sum(hold_mins) / len(hold_mins)) if hold_mins else 0.0 return Metrics( trades=len(trade_rows), @@ -227,12 +244,13 @@ def compute_metrics( wins=wins_n, losses=losses_n, win_rate=win_rate, - avg_win=float(avg_win) * scale, - avg_loss=float(avg_loss) * scale, + avg_win=float(avg_win) * reporting_scale, + avg_loss=float(avg_loss) * reporting_scale, profit_factor=float(profit_factor), - expectancy=float(expectancy) * scale, - max_drawdown=max_drawdown(equity) * scale, - final_equity=float(final_equity) * scale, - avg_hold_minutes=float(avg_hold) if avg_hold is not None else None, + expectancy=float(expectancy) * reporting_scale, + max_drawdown=max_drawdown(equity) * reporting_scale, + final_equity=float(final_equity) * reporting_scale, + avg_hold_minutes=float(avg_hold), exits_by_reason=exits_by_reason, + sharpe_ratio=float(sharpe_ann), # The new field ) diff --git a/tradedesk/recording/opportunity.py b/tradedesk/recording/opportunity.py index 7e1a7e3..674f4aa 100644 --- a/tradedesk/recording/opportunity.py +++ b/tradedesk/recording/opportunity.py @@ -39,9 +39,7 @@ class OpportunityRecorder: per_instrument: dict[str, InstrumentOpportunity] = field(default_factory=dict) _k_active_by_ts: list[tuple[str, int]] = field(default_factory=list) - def on_instrument_bar( - self, *, instrument: str, timestamp: str, active: bool - ) -> None: + def on_instrument_bar(self, *, instrument: str, timestamp: str, active: bool) -> None: rec = self.per_instrument.get(instrument) if rec is None: rec = InstrumentOpportunity() diff --git a/tradedesk/recording/recorders.py b/tradedesk/recording/recorders.py index e449814..0d2a5d7 100644 --- a/tradedesk/recording/recorders.py +++ b/tradedesk/recording/recorders.py @@ -67,12 +67,14 @@ async def _on_candle_closed(self, event: CandleClosedEvent) -> None: realised = self._client.realised_pnl # Publish EquitySampledEvent - await get_dispatcher().publish(EquitySampledEvent( - equity=equity, - realised_pnl=realised, - unrealised_pnl=unrealised, - timestamp=event.timestamp, - )) + await get_dispatcher().publish( + EquitySampledEvent( + equity=equity, + realised_pnl=realised, + unrealised_pnl=unrealised, + timestamp=event.timestamp, + ) + ) except Exception: log.exception(f"Failed to sample equity at {event.timestamp}") @@ -150,14 +152,16 @@ async def _on_candle_closed(self, event: CandleClosedEvent) -> None: mae_pnl = mae_points * pos_event.size # Publish ExcursionSampledEvent - await get_dispatcher().publish(ExcursionSampledEvent( - instrument=event.instrument, - mfe_points=float(mfe_points), - mae_points=float(mae_points), - mfe_pnl=float(mfe_pnl), - mae_pnl=float(mae_pnl), - timestamp=event.timestamp, - )) + await get_dispatcher().publish( + ExcursionSampledEvent( + instrument=event.instrument, + mfe_points=float(mfe_points), + mae_points=float(mae_points), + mfe_pnl=float(mfe_pnl), + mae_pnl=float(mae_pnl), + timestamp=event.timestamp, + ) + ) except Exception: log.exception(f"Failed to compute excursions for {event.instrument}") diff --git a/tradedesk/recording/report-template.j2 b/tradedesk/recording/report-template.j2 index 68ea09d..f3b9a84 100644 --- a/tradedesk/recording/report-template.j2 +++ b/tradedesk/recording/report-template.j2 @@ -1,28 +1,43 @@ -# Instrument Performance Analysis +# "{{ output_path.name }}" Back Test Report + +## Exec Summary + +{% set pm = portfolio_metrics|first -%} + +The "{{ output_path.name }}" back test ran over a period of **{{ equity_daily|length }} days** producing a final PnL of **{{ "%.2f"|format(pm.final_equity|float) }}** from **{{ pm.round_trips }}** round trips with a maximum draw down of **{{ "%.2f"|format(pm.max_dd|float|abs) }}** + +![equity](./graphs/equity_curve.png) +*Portfolio equity curve* + +### Portfolio key facts + +- Sharpe Ratio (Ann.): **{{ "%.2f"|format(pm.sharpe_ratio|float) }}** +- Recovery Ratio: **{{ "%.2f"|format((pm.final_equity|float/pm.max_dd|float)|abs) }}** +- Profit Factor: **{{ "%.2f"|format(pm.profit_factor|float) }}** +- Win Rate: **{{ "%.1f"|format(pm.win_rate|float * 100) }}%** + +--- + +# Detailed 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 -%} +| Instrument | Final PnL | Max DD | Win Rate | P.Factor | Trades | Sharpe Ratio | +|------------|----------:|-------:|---------:|---------:|-------:|-------------:| {% 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 }} | +| {{ 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 }} | {{ "%.2f"|format(m.sharpe_ratio|float) }} | +{% endfor -%} +{% for m in portfolio_metrics -%} +| *TOTAL* | *{{ "%.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 }}* | *{{ "%.2f"|format(m.sharpe_ratio|float) }}* | {% endfor %} + ## 2. Performance Statistics Across Instruments -| Metric | Mean | Std | Min | Median | Max | -|--------|------|-----|-----|--------|-----| +| Metric | Mean | Std | Min | Median | Max | CV (std/mean) | +|--------|-----:|----:|----:|-------:|----:|--------------:| {% 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) }}% +| {{ row.metric }} | {{ "%.2f"|format(row.mean) }} | {{ "%.2f"|format(row.std) }} | {{ "%.2f"|format(row.min) }} | {{ "%.2f"|format(row.median) }} | {{ "%.2f"|format(row.max) }} | {{ "%.2f"|format(row.cv) }}% | {% endfor %} ## 3. Return Consistency Analysis @@ -30,7 +45,7 @@ *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 %} @@ -38,15 +53,17 @@ ## 4. Volatility Classification {% if volatility.median is defined %} -**Low Volatility (CV < {{ "%.1f"|format(volatility.median) }}%):** {{ volatility.low|join(', ') }} +**Low Volatility (CV < {{ "%.1f"|format(volatility.median) }}%):** +* {{ volatility.low|join('\n* ') }} -**High Volatility (CV >= {{ "%.1f"|format(volatility.median) }}%):** {{ volatility.high|join(', ') }} +**High Volatility (CV >= {{ "%.1f"|format(volatility.median) }}%):** +* {{ volatility.high|join('\n* ') }} {% 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 %} @@ -54,7 +71,7 @@ ## 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 %} @@ -62,8 +79,13 @@ {% if similarity.matrix_rows %} ## 7. Performance Profile Comparison -*Performance Profile Similarity (Euclidean Distance):* -Lower values = more similar performance profiles +### Portfolio Diversification + +![correlation](./graphs/instrument_correlation.png) +*Instrument correlation (lower is generally better)* + +### Performance Similarity (Euclidean Distance): + {% if similarity.min_pair %} **Most Similar Pair:** {{ similarity.min_pair[0] }} ↔ {{ similarity.min_pair[1] }} ({{ "%.2f"|format(similarity.min_dist) }}) @@ -73,25 +95,25 @@ Lower values = more similar performance profiles **Most Different Pair:** {{ similarity.max_pair[0] }} ↔ {{ similarity.max_pair[1] }} ({{ "%.2f"|format(similarity.max_dist) }}) {% endif %} -### Similarity Matrix +#### Similarity Matrix | | {{ similarity.matrix_headers|join(' | ') }} | |{{ (similarity.matrix_headers|length + 1) * "---|" }} {% for row in similarity.matrix_rows -%} | {{ row.instrument }} | {{ row.dists|join(' | ') }} | {% endfor %} +*Lower values = more similar performance profiles* {% 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) }}%) +![heatmap](./graphs/monthly_pnl_heatmap.png) +*Time based PnL visualisation per instrument* +| Instrument | Final PnL | Peak PnL | Max. DD | Trades in DD | +|------------|----------:|---------:|--------:|-------------:| +{% for row in evolution_data -%} +| {{ row.instrument }} | {{ "%.2f"|format(row.final_pnl) }} | {{ "%.2f"|format(row.peak_pnl) }} | {{ "%.2f"|format(row.max_dd) }} | {{ row.dd_count }} ({{ "%.1f"|format(row.dd_pct) }}%) | {% endfor %} ## 9. Key Insights @@ -130,15 +152,15 @@ Lower values = more similar performance profiles ## 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 +## 2. 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 %} @@ -146,7 +168,7 @@ Lower values = more similar performance profiles ## 3. Monthly Performance Breakdown | Month | {{ monthly_data.headers|join(' | ') }} | Total | -|-------|{{ monthly_data.headers|length * "------|" }}------| +|-------|{{ monthly_data.headers|length * "-----:|" }}------| {% for row in monthly_data.rows -%} | {{ row.month }} | {{ row.values|join(' | ') }} | {{ "%.2f"|format(row.total) }} | {% endfor -%} @@ -155,27 +177,29 @@ Lower values = more similar performance profiles ## 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 +| Instrument | | PnL | Entry | Hold | Direction | +|------------|-|----:|------:|-----:|-----------| {% 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 }} - +| {{ row.instrument }} |📈| {{ "%.2f"|format(row.best.pnl) }} | {{ row.best.entry_ts[:10] }} | {{ "%.0f"|format(row.best.hold_minutes) }}m | {{ row.best.direction }} | +| |📉| {{ "%.2f"|format(row.worst.pnl) }} | {{ row.worst.entry_ts[:10] }} | {{ "%.0f"|format(row.worst.hold_minutes) }}m | {{ row.worst.direction }} | {% endfor %} ## 6. Maximum Favorable/Adverse Excursion (MFE/MAE) Analysis {% if mfe_mae_data %} + +![mae](./graphs/mae_vs_pnl.png) +*MAE vs PnL* + | 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 %} @@ -190,7 +214,7 @@ Lower values = more similar performance profiles ## 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 %} @@ -203,7 +227,7 @@ Lower values = more similar performance profiles ### 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 %} @@ -214,10 +238,19 @@ Lower values = more similar performance profiles #### {{ 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 %} + +--- + + + +report created on **{{ report_date }}** by [`tradedesk`](https://github.com/radiusred/tradedesk) +location: `{{ output_path }}` +© Radius Red Ltd. + diff --git a/tradedesk/recording/report.py b/tradedesk/recording/report.py index d0ace83..0ffc8cc 100644 --- a/tradedesk/recording/report.py +++ b/tradedesk/recording/report.py @@ -1,6 +1,7 @@ """Performance analysis report generation for backtest results using Jinja2 templates.""" import csv +import logging import math from collections import defaultdict from datetime import datetime @@ -8,8 +9,13 @@ from types import SimpleNamespace from typing import Any +import matplotlib.pyplot as plt +import pandas as pd +import seaborn as sns from jinja2 import Environment, FileSystemLoader +log = logging.getLogger(__name__) + def calc_stats(values: list[float]) -> dict[str, float]: """Calculate summary statistics for a list of values.""" @@ -53,14 +59,10 @@ def standardize(values: list[float]) -> list[float]: 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: +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) - ) + 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]]: @@ -91,7 +93,7 @@ def _prepare_overall_performance( def _prepare_stats_table( metrics: list[dict[str, str]], -) -> tuple[list[dict[str, Any]], 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], @@ -101,13 +103,16 @@ def _prepare_stats_table( } stats_table = [] - cv_data = [] for col, values in metrics_cols.items(): stats = calc_stats(values) - stats_table.append({"metric": col, **stats}) + + # Calculate CV (Coefficient of Variation) 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 + + # Merge everything into one dictionary per metric + stats_table.append({"metric": col, **stats, "cv": cv}) + + return stats_table def _prepare_consistency_data(round_trips: list[dict[str, str]]) -> list[dict[str, Any]]: @@ -158,12 +163,10 @@ def _classify_volatility(consistency_data: list[dict[str, Any]]) -> dict[str, An 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 - ): + 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 + ((int(m.get("round_trips", 0)) / total_round_trips) * 100) if total_round_trips else 0 + ) exposure_data.append( { "instrument": m.get("instrument"), @@ -185,11 +188,15 @@ def _prepare_risk_adj_data( 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 + (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 + (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, @@ -244,9 +251,7 @@ def _prepare_similarity( for i, inst1 in enumerate(instruments): for inst2 in instruments[i + 1 :]: - dist = euclidean_distance( - profile_metrics[inst1], profile_metrics[inst2], metric_keys - ) + dist = euclidean_distance(profile_metrics[inst1], profile_metrics[inst2], metric_keys) if dist < min_dist: min_dist = dist min_pair = (inst1, inst2) @@ -254,17 +259,13 @@ def _prepare_similarity( max_dist = dist max_pair = (inst1, inst2) - matrix_headers = [ - inst.split(".")[2] if "." in inst else inst for inst in instruments - ] + 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 - ) + euclidean_distance(profile_metrics[inst1], profile_metrics[inst2], metric_keys) if inst1 != inst2 else 0 ) @@ -325,14 +326,16 @@ def _prepare_evolution_data( 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), - }) + 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 @@ -342,6 +345,8 @@ def _prepare_insights( risk_adj_data: list[dict[str, Any]], total_round_trips: int, ) -> dict[str, Any]: + metrics = [m for m in metrics if m.get("instrument") != "PORTFOLIO"] + insights: dict[str, Any] = {} final_equities = [float(m.get("final_equity", 0)) for m in metrics] if not final_equities: @@ -352,8 +357,8 @@ def _prepare_insights( 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 + ((equity_stats["std"] / equity_stats["mean"]) * 100) if equity_stats["mean"] != 0 else 0 + ) insights = { "best": { @@ -399,19 +404,25 @@ def _prepare_insights( 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 + ((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 + ((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 + ((exposure_stats["std"] / exposure_stats["mean"]) * 100) + if exposure_stats["mean"] != 0 + else 0 + ) insights["exposure"] = { "most": { "instrument": max_trades["instrument"], @@ -482,7 +493,7 @@ def _prepare_additional_analysis( 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}") + current_state = f"W:{current_win_streak}" if last_pnl > 0 else f"L:{current_loss_streak}" streak_data.append( { "instrument": inst, @@ -495,15 +506,15 @@ def _prepare_additional_analysis( 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 + (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, + "std": variance**0.5, } ) @@ -580,9 +591,7 @@ 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) - ) + 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") @@ -590,9 +599,7 @@ def _prepare_monthly_data( 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 - } + 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) @@ -700,10 +707,123 @@ def inst_key(r: str) -> float: return exit_reasons -def generate_analysis_report(output_dir: str | Path) -> None: +def _prepare_graphs( + round_trips_file: Path, equity_file: Path, cache_dir: Path | None = None +) -> None: + output_dir = round_trips_file.parent / "graphs" + output_dir.mkdir(exist_ok=True) + + round_trips = pd.read_csv(round_trips_file) + equity = pd.read_csv(equity_file) + + round_trips["exit_ts"] = pd.to_datetime(round_trips["exit_ts"]) + round_trips["month"] = round_trips["exit_ts"].dt.to_period("M") + equity["timestamp"] = pd.to_datetime(equity["timestamp"]) + + # 1. Monthly Performance Heatmap + try: + monthly_pnl = ( + round_trips.groupby(["month", "instrument"])["pnl"].sum().unstack(fill_value=0) + ) + portfolio_monthly = monthly_pnl.sum(axis=1) + monthly_pnl["PORTFOLIO"] = portfolio_monthly + + heatmap_data = monthly_pnl.copy() + heatmap_data.index = heatmap_data.index.astype(str) + plt.figure(figsize=(15, 10)) + sns.heatmap(heatmap_data.T, annot=True, fmt=".0f", cmap="RdYlGn", center=0) + plt.title("Monthly PnL by Instrument") + plt.tight_layout() + plt.savefig(output_dir / "monthly_pnl_heatmap.png") + except Exception as e: + log.warning(f"Failed to generate monthly performance heatmap: {e}") + + # # P&L Distribution + # try: + # plt.figure(figsize=(10, 8)) + # sns.histplot(round_trips, x="pnl", bins=30, kde=True) + # plt.title("P&L Distribution") + # plt.xlabel("P&L") + # plt.ylabel("Frequency") + # plt.savefig(output_dir / "pnl_distribution.png") + # plt.close() + # except Exception as e: + # log.warning(f"Failed to generate P&L distribution plot: {e}") + + # Equity Curve + try: + fig, ax = plt.subplots(figsize=(10, 8)) + sns.lineplot( + data=equity, x="timestamp", y="equity", ax=ax, label="PORTFOLIO", color="#00AA00" + ) + + if cache_dir is not None: + try: + from tradedesk.execution.backtest import read_dukascopy_candles + + date_from = equity["timestamp"].min().date() + date_to = equity["timestamp"].max().date() + candles = read_dukascopy_candles(cache_dir, "GBRIDXGBP", "1D", date_from, date_to) + closes = [c.close for c in candles] + control: list[float] = [0.0] + for i in range(1, len(closes)): + control.append(control[-1] + closes[i] - closes[i - 1]) + control_dates = [pd.Timestamp(c.timestamp) for c in candles] + ax.plot( + pd.DatetimeIndex(control_dates), + control, + color="#888888", + linewidth=1, + label="FTSE 100", + ) + ax.legend() + except Exception as e: + log.warning(f"Failed to add FTSE control line: {e}") + + ax.set_title("Equity Curve") + ax.set_xlabel("Time") + ax.set_ylabel("Equity") + fig.savefig(output_dir / "equity_curve.png") + plt.close(fig) + except Exception as e: + log.warning(f"Failed to generate equity curve plot: {e}") + + # MFE / MAE Analysis + try: + plt.figure(figsize=(12, 6)) + sns.scatterplot(data=round_trips, x="mae_pnl", y="pnl", hue="instrument", alpha=0.5) + plt.title("MAE vs Final PnL (Risk vs Reward)") + plt.axhline(0, color="black", linestyle="--") + plt.tight_layout() + plt.savefig(output_dir / "mae_vs_pnl.png") + except Exception as e: + log.warning(f"Failed to generate MAE vs PnL plot: {e}") + + # Equity Correlation + try: + round_trips["date"] = round_trips["exit_ts"].dt.date + daily_pnl = round_trips.groupby(["date", "instrument"])["pnl"].sum().unstack(fill_value=0) + correlation_matrix = daily_pnl.corr() + + plt.figure(figsize=(10, 8)) + sns.heatmap(correlation_matrix, annot=True, cmap="coolwarm", vmin=-1, vmax=1) + plt.title("Daily PnL Correlation Matrix") + plt.tight_layout() + plt.savefig(output_dir / "instrument_correlation.png") + except Exception as e: + log.warning(f"Failed to generate instrument correlation matrix: {e}") + + +def generate_analysis_report( + output_dir: str | Path, + with_graphs: bool = True, + cache_dir: Path | None = None, +) -> None: output_path = Path(output_dir) metrics_file = output_path / "metrics.csv" round_trips_file = output_path / "round_trips.csv" + equity_file = output_path / "equity.csv" + equity_daily_file = output_path / "equity_daily.csv" report_file = output_path / "analysis.md" template_file = "report-template.j2" @@ -711,11 +831,12 @@ def generate_analysis_report(output_dir: str | Path) -> None: _ensure_instrument_field(metrics) round_trips = _read_csv(round_trips_file) _ensure_instrument_field(round_trips) + equity_daily = _read_csv(equity_daily_file) - portfolio_metrics, instrument_metrics, sorted_instruments = ( - _prepare_overall_performance(metrics) + portfolio_metrics, instrument_metrics, sorted_instruments = _prepare_overall_performance( + metrics ) - stats_table, cv_data = _prepare_stats_table(metrics) + stats_table = _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) @@ -723,20 +844,20 @@ def generate_analysis_report(output_dir: str | Path) -> None: 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 - ) + 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) + if with_graphs: + _prepare_graphs(round_trips_file, equity_file, cache_dir=cache_dir) + 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, @@ -752,6 +873,10 @@ def generate_analysis_report(output_dir: str | Path) -> None: "mfe_mae_data": mfe_mae_data, "long_short_data": long_short_data, "exit_reasons": exit_reasons, + "equity_daily": equity_daily, + "report_date": datetime.now().strftime("%Y-%m-%d %H:%M"), + "output_path": output_path, + "graphs": with_graphs, } env = Environment(loader=FileSystemLoader(str(Path(__file__).parent))) diff --git a/tradedesk/recording/subscriber.py b/tradedesk/recording/subscriber.py index db9b5b0..dcdfcc4 100644 --- a/tradedesk/recording/subscriber.py +++ b/tradedesk/recording/subscriber.py @@ -1,10 +1,13 @@ from __future__ import annotations import logging +from datetime import datetime from pathlib import Path from typing import Optional from tradedesk.events import SessionEndedEvent, SessionStartedEvent, get_dispatcher +from tradedesk.marketdata import CandleClosedEvent +from tradedesk.time_utils import parse_timestamp from .events import ( EquitySampledEvent, @@ -12,6 +15,7 @@ PositionOpenedEvent, ReportingCompleteEvent, ) +from .excursions import CandleIndex from .ledger import TradeLedger, trade_rows_from_trades from .metrics import compute_metrics from .types import EquityRecord, TradeRecord @@ -31,6 +35,10 @@ def __init__( ledger: Optional[TradeLedger] = None, output_dir: Optional[Path] = None, reporting_scale: float = 1.0, + run_dir: Optional[Path] = None, + index_period: Optional[str] = None, + cache_dir: Optional[Path] = None, + with_graphs: bool = True, ) -> None: """Initialize the recording subscriber. @@ -38,16 +46,49 @@ def __init__( ledger: TradeLedger to record trades/equity (created if None) output_dir: Base directory for timestamped run outputs reporting_scale: Scale factor for metrics reporting + run_dir: Pre-created run output directory. When provided the + subscriber uses it directly and skips directory creation on + SessionStartedEvent. Caller is responsible for creating it. + index_period: IG-format timeframe string (e.g. "15MINUTE"). When + set, the subscriber accumulates candle data from + CandleClosedEvent and builds ledger.candle_indices during the + run, so callers do not need to pre-build it. + cache_dir: Dukascopy cache directory. When provided, the analysis + report will include a FTSE 100 control line on the equity chart. + with_graphs: When False, graph generation is skipped in the analysis + report (faster; useful for automated arena runs). """ self.ledger = ledger or TradeLedger() self._base_output_dir = output_dir self._reporting_scale = reporting_scale - self._run_output_dir: Path | None = None + self._run_output_dir: Path | None = run_dir + self._index_period = index_period + self._cache_dir = cache_dir + self._with_graphs = with_graphs + # Per-instrument (ts, high, low) accumulators for candle index building. + self._index_buffer: dict[str, tuple[list[datetime], list[float], list[float]]] = {} # Track open positions for round trip pairing self._open_positions: dict[str, PositionOpenedEvent] = {} + async def _on_candle_for_index(self, event: CandleClosedEvent) -> None: + """Accumulate candle data for building ledger.candle_indices during streaming.""" + if event.timeframe != self._index_period: + return + epic = event.instrument + if epic not in self._index_buffer: + self._index_buffer[epic] = ([], [], []) + ts_list, high_list, low_list = self._index_buffer[epic] + ts_list.append(parse_timestamp(event.candle.timestamp)) + high_list.append(float(event.candle.high)) + low_list.append(float(event.candle.low)) + def handle_session_started(self, event: SessionStartedEvent) -> None: """Handle session start: create timestamped output directory.""" + if self._run_output_dir is not None: + # Directory was pre-created by the caller; nothing to do. + log.info(f"Recording session started: output_dir={self._run_output_dir}") + return + if self._base_output_dir is None: return @@ -61,6 +102,13 @@ async def handle_session_ended(self, event: SessionEndedEvent) -> None: """Handle session end: write metrics, files, and emit completion event.""" log.info("Recording session ended: writing metrics and reports") + # Populate candle_indices from streaming-accumulated buffer (lazy mode). + for epic, (ts_list, high_list, low_list) in self._index_buffer.items(): + if epic not in self.ledger.candle_indices: + self.ledger.candle_indices[epic] = CandleIndex( + ts=ts_list, high=high_list, low=low_list + ) + # Write ledger files if we have an output directory if self._run_output_dir is not None: try: @@ -73,8 +121,7 @@ async def handle_session_ended(self, event: SessionEndedEvent) -> None: if self.ledger.trades: try: equity_rows = [ - {"timestamp": e.timestamp, "equity": str(e.equity)} - for e in self.ledger.equity + {"timestamp": e.timestamp, "equity": str(e.equity)} for e in self.ledger.equity ] trade_rows = trade_rows_from_trades(self.ledger.trades) @@ -101,7 +148,11 @@ async def handle_session_ended(self, event: SessionEndedEvent) -> None: try: from .report import generate_analysis_report - generate_analysis_report(self._run_output_dir) + generate_analysis_report( + self._run_output_dir, + cache_dir=self._cache_dir, + with_graphs=self._with_graphs, + ) log.info(f"Analysis report written to {self._run_output_dir / 'analysis.md'}") except Exception: log.exception("Failed to generate analysis report") @@ -150,8 +201,7 @@ async def handle_position_closed(self, event: PositionClosedEvent) -> None: self.ledger.record_trade(exit_trade) log.debug( - f"Position closed: {event.instrument} pnl={event.pnl:.2f} " - f"reason={event.exit_reason}" + f"Position closed: {event.instrument} pnl={event.pnl:.2f} reason={event.exit_reason}" ) async def handle_equity_sampled(self, event: EquitySampledEvent) -> None: @@ -167,6 +217,10 @@ def register_recording_subscriber( ledger: Optional[TradeLedger] = None, output_dir: Optional[Path] = None, reporting_scale: float = 1.0, + run_dir: Optional[Path] = None, + index_period: Optional[str] = None, + cache_dir: Optional[Path] = None, + with_graphs: bool = True, ) -> RecordingSubscriber: """Create and register a `RecordingSubscriber` with the global dispatcher. @@ -174,6 +228,16 @@ def register_recording_subscriber( ledger: Optional TradeLedger instance (created if None) output_dir: Optional base directory for timestamped run outputs reporting_scale: Scale factor for metrics reporting + run_dir: Pre-created run output directory. When provided the subscriber + uses it directly; ``output_dir`` is ignored. Caller is responsible + for creating the directory before passing it here. + index_period: IG-format timeframe string (e.g. "15MINUTE"). When set, + the subscriber builds ledger.candle_indices from CandleClosedEvent + data during the run instead of requiring a pre-built index. + cache_dir: Dukascopy cache directory. When provided, the analysis + report will include a FTSE 100 control line on the equity chart. + with_graphs: When False, graph generation is skipped in the analysis + report (faster; useful for automated arena runs). Returns: The subscriber instance (useful in tests to inspect ledger state). @@ -183,6 +247,10 @@ def register_recording_subscriber( ledger=ledger, output_dir=output_dir, reporting_scale=reporting_scale, + run_dir=run_dir, + index_period=index_period, + cache_dir=cache_dir, + with_graphs=with_graphs, ) dispatcher.subscribe(SessionStartedEvent, sub.handle_session_started) @@ -190,5 +258,7 @@ def register_recording_subscriber( dispatcher.subscribe(PositionClosedEvent, sub.handle_position_closed) dispatcher.subscribe(EquitySampledEvent, sub.handle_equity_sampled) dispatcher.subscribe(SessionEndedEvent, sub.handle_session_ended) + if index_period is not None: + dispatcher.subscribe(CandleClosedEvent, sub._on_candle_for_index) return sub diff --git a/tradedesk/strategy/base.py b/tradedesk/strategy/base.py index eac6ce5..a1536bd 100644 --- a/tradedesk/strategy/base.py +++ b/tradedesk/strategy/base.py @@ -84,9 +84,7 @@ def __init__( # Backwards compatibility - deprecated self.client = 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