Pratik Bhadane
71b6343e92
Refresh the benchmark and performance surface across the repo. This updates the benchmark wrappers and helper scripts, regenerates the checked-in benchmark and perf-contract artifacts, and folds in the related roadmap, compatibility, and example notebook changes that belong with this performance-focused pass. Harden the Python CI and local pre-push flow so the same checks pass reliably in both places. The workflow and pre-push script now use module-safe uv typecheck invocations, the Python test environment installs the optional MCP dependency needed by the MCP server tests, and one-off root benchmark outputs are ignored to keep the repo clean. Align local tooling with the current project configuration by updating the Ruff pre-commit hook, tightening the API typing and MCP server helpers, and refreshing the lockfile to pick up the audited PyJWT fix while preserving the rest of the staged source changes.
103 lines
3.8 KiB
Python
103 lines
3.8 KiB
Python
"""
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Cross-library speed benchmarks using pytest-benchmark.
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Run: pytest benchmarks/test_speed.py --benchmark-only -v
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pytest benchmarks/test_speed.py --benchmark-only --benchmark-json=benchmarks/results.json
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Streaming benchmarks are in test_streaming_speed.py
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"""
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from __future__ import annotations
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import pytest
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from benchmarks.data_generator import LARGE
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from benchmarks.wrapper_registry import (
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INDICATOR_CATEGORIES,
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available_libraries,
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execute_indicator,
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is_supported,
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)
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BENCH_DATA = LARGE # 100k bars for main benchmarks
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BENCH_LIBS = available_libraries()
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def _make_bench(indicator: str, library: str):
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"""Return a benchmark function that runs indicator on library (uses BENCH_DATA)."""
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def _fn():
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execute_indicator(library, indicator, BENCH_DATA)
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_fn.__name__ = f"{library}_{indicator}"
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return _fn
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# ── Parametrize over all (indicator, library) combinations ───────────────────
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def pytest_generate_tests(metafunc):
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if "indicator" in metafunc.fixturenames and "library" in metafunc.fixturenames:
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params = []
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for cat, inds in INDICATOR_CATEGORIES.items():
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for ind in inds:
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for lib in BENCH_LIBS:
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params.append(pytest.param(ind, lib, id=f"{cat}/{ind}/{lib}"))
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metafunc.parametrize("indicator,library", params)
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class TestSpeed:
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"""One benchmark per (indicator, library) pair — all at 100k bars (LARGE dataset)."""
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def test_speed(self, benchmark, indicator, library):
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if not is_supported(library, indicator):
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pytest.skip(f"{library} does not implement {indicator}")
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fn = _make_bench(indicator, library)
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benchmark.pedantic(fn, iterations=5, rounds=20, warmup_rounds=2)
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# ── Standalone head-to-head for the most important indicators ─────────────────
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@pytest.mark.parametrize(
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"indicator,libs",
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[
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("SMA", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("EMA", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("RSI", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("MACD", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("BBANDS", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("ATR", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("CCI", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("WILLR", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("OBV", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("ADX", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("MFI", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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("STOCH", ["ferro_ta", "talib", "tulipy", "pandas_ta", "ta", "finta"]),
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],
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)
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def test_head_to_head(benchmark, indicator, libs):
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"""Benchmark ferro_ta vs all peers — for README table generation."""
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if not is_supported("ferro_ta", indicator):
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pytest.skip(f"ferro_ta does not implement {indicator}")
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fn = _make_bench(indicator, "ferro_ta")
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benchmark.pedantic(fn, iterations=5, rounds=20, warmup_rounds=2)
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# ── Large dataset benchmarks (100k bars) ─────────────────────────────────────
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@pytest.mark.parametrize(
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"indicator",
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["SMA", "EMA", "RSI", "MACD", "ATR", "BBANDS", "OBV", "CCI", "ADX", "MFI"],
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)
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def test_large_dataset(benchmark, indicator):
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"""Scaling benchmark at 100k bars for ferro_ta."""
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if not is_supported("ferro_ta", indicator):
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pytest.skip(f"ferro_ta does not implement {indicator}")
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def _fn():
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execute_indicator("ferro_ta", indicator, LARGE)
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benchmark.pedantic(_fn, iterations=3, rounds=10, warmup_rounds=1)
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