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kingchenc 3ebcb3f758 Per-binding throughput benchmarks + test-coverage gaps (#246 )

Adds a `throughput` benchmark to every target and closes two small
test-coverage documentation/QA gaps. One PR, no merge of binding code beyond
the additive benchmarks and one C test.

## 1. Per-binding throughput benchmarks (all 9 targets)

Each benchmark feeds a deterministic synthetic OHLCV series through three
indicators chosen by **FFI call-signature archetype** (not algorithm — the same
Rust core runs underneath all bindings):

- `SMA(20)` — 1-in → 1-out (baseline boundary cost)
- `ATR(14)` — multi-in → 1-out (input marshalling)
- `MACD(12,26,9)` — 1-in → multi-out (output marshalling)

Streaming is timed for all three; batch for the single-output SMA and ATR
(median of 3 runs, after a warmup pass).

New: Python (PyO3), WASM, C (CMake), C# (Stopwatch), Go, Java (FFM), R, and the
Rust core baseline (`examples/rust/.../throughput.rs`, **no FFI** — the ceiling
the bindings are measured against and the value their batch paths converge
towards). Node already had `throughput.js`.

**Not a speed claim:** there is no comparable streaming TA library for C, C#,
Go, Java, R or WASM to compare against, so these are raw per-binding throughput
numbers documenting each language's FFI overhead — see BENCHMARKS.md §3. The
"Wickra is fast" claim still lives in §1/§2 (Rust core + the Python/Rust
cross-library runs).

## 2. README `## Testing`: C# and C bullets

The section listed every layer except C# and C, even though both have suites.
Adds the two missing bullets.

## 3. C archetype ctest

`examples/c/archetypes.c` drives one indicator per FFI archetype through the
real C boundary (scalar + batch==streaming, multi-output, bars, profile, array
input) plus reset, invalid-parameter and NULL-safety — the C counterpart of the
Go/R/Java archetype suites. Runs on three OSes via the existing CMake/ctest.

## Notes

- Benchmarks are not CI-gated (manual-run scripts, like the existing
  `throughput.js`); no `ci.yml`/`release.yml` changes.
- Docs: BENCHMARKS.md §3, a `## Benchmark` section in every binding README, a
  CHANGELOG entry.
- Verified locally by running: Rust, Python, C, C#, Go, Java (real numbers); the
  C archetype ctest with `-Wall -Wextra -Wpedantic -Werror`. WASM and R are
  API-correct and syntax-checked but need their own toolchains to run.

2026-06-10 03:46:38 +02:00

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Wickra — Python

Streaming-first technical indicators for Python. pip install wickra — no system dependencies, no C build tooling.

Wickra is a multi-language technical-analysis library with a Rust core and bindings for Python, Node.js and WebAssembly, plus a C ABI for C/C++, C#, Go, Java, R and any other C-capable language. Every indicator is an O(1) streaming state machine, so live trading bots and historical backtests share the exact same implementation. This package is the Python binding (PyO3); it exposes 200+ streaming-first indicators across sixteen families.

Install

pip install wickra

Pre-built wheels ship for Linux, macOS, and Windows — there is nothing to compile and no C library to track down.

Quick start

import numpy as np
import wickra as ta

# Batch: classic TA-Lib-style usage over a whole array.
prices = np.linspace(100, 200, 1000)
rsi = ta.RSI(14)
values = rsi.batch(prices)              # numpy array, NaN during warmup

# Streaming: the same indicator, fed tick by tick in O(1).
rsi = ta.RSI(14)
for price in live_feed:
    value = rsi.update(price)           # no recomputation over history
    if value is not None and value > 70:
        print("overbought")

batch(prices) and feeding the same prices through update() produce identical values — the equivalence is enforced by the test suite.

Benchmark

Two benchmarks ship with the binding:

benchmarks/throughput.py — streaming and batch updates-per-second for SMA, ATR and MACD. This is per-binding FFI overhead (the same Rust core runs under every binding), not a cross-library ratio.
benchmarks/compare_libraries.py — the cross-library comparison against TA-Lib, pandas-ta, tulipy and finta that backs the headline speedups.

maturin develop --release
python -m benchmarks.throughput
python -m benchmarks.compare_libraries   # cross-library; auto-detects installed peers

See the repository BENCHMARKS.md.

Documentation

The full indicator catalogue, guides, quickstarts, and API reference live in the main repository and documentation site:

Repository & full indicator list: https://github.com/wickra-lib/wickra
Docs (quickstarts, cookbook, TA-Lib migration): https://docs.wickra.org
Runnable examples: examples/python/

Wickra ships native bindings for Python, Node.js, WebAssembly and Rust, plus a C ABI hub that any C-capable language (C, C++, Go, C#, Java, R) links against — all exposing the same indicators from the shared, unsafe-forbidden Rust core.

Disclaimer

Wickra is an indicator toolkit, not a trading system. The values it computes are deterministic transforms of the input data — they are not financial advice and do not predict the market. Any use in a live trading context is at your own risk. The library is provided as is, without warranty of any kind.

License

Licensed under either of Apache-2.0 or MIT at your option.

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