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kingchenc 12681e4b1b C ABI: full example suite + docs & About coverage (#224 )

Stacked on #222 (base `feat/c-abi-hub`), so the diff is just the additions on top of the hub foundation — no merge of #222 required.

## What this adds

**Examples — full parity with rust/python/node (`examples/c/`)**
- `streaming.c` upgraded to the multi-indicator (SMA/EMA/RSI/MACD + signals) demo
- `backtest.c`, `multi_timeframe.c` (manual time-bucket resampling), `parallel_assets.c` (serial vs OpenMP fan-out, one handle per asset)
- three educational strategies: `strategy_rsi_mean_reversion.c`, `strategy_macd_adx.c`, `strategy_bollinger_squeeze.c`
- two network examples shelling out to `curl`: `fetch_btcusdt.c`, `live_binance.c` (REST poll)
- two header-only helpers (`wickra_csv.h`, `wickra_strategy.h`) since the C ABI ships no IO layer
- CMake builds all 11; the 9 offline ones run under `ctest` on 3 OS; the network two are built-only

**Docs & metadata — surface the C ABI everywhere it was missing**
- ARCHITECTURE diagram + crate table, SECURITY + THREAT_MODEL (the C ABI as the sole `unsafe` FFI surface), the three binding package READMEs, issue/PR templates, CHANGELOG, and the GitHub About template (live About + org description updated too)

**Cleanup**
- removed all references to the private generator tooling from public files (`bindings/c/src/lib.rs` header, `CONTRIBUTING.md`, `sync-about.yml`)

Verified locally: `cargo build -p wickra-c --release`, `cmake + ctest` (9/9 pass), and `-Wall -Wextra -Wpedantic` clean on gcc 13.

2026-06-09 02:14:28 +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++ 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.

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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