kingchenc
43b0b26736
Python's parallel_assets.py demoed GIL-release multi-core throughput; Rust and Node both lacked a sibling that shows their own native parallelism. Close the gap with two real, runnable examples. * examples/rust/src/bin/parallel_assets.rs — synthesises an (assets, bars) panel with a deterministic per-asset LCG, runs a serial baseline, then `Sma::batch_parallel` / `Rsi::batch_parallel` via rayon, asserts the two outputs are element-wise identical and prints the speedup. Toggle indicator with `--indicator sma|rsi`. * examples/node/parallel_assets.js — same shape, but the parallel run is a `worker_threads` pool that re-loads the native binding in each worker. Each worker computes the last non-null indicator value for its slice; the main thread aggregates and verifies serial == parallel per asset. Both examples report timings and the serial-vs-parallel sanity check passes. Defaults (200 × 5000) keep the example fast on dev hardware; larger `--assets`/`--bars` is where the speedup numbers move (Node's worker spawn cost dominates the smallest sizes, which is honest and educational). examples/README.md gains the two new rows.
63 lines
4.0 KiB
Markdown
63 lines
4.0 KiB
Markdown
# Wickra examples
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Runnable examples for every Wickra binding. Rust and Node examples live next
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to the code they exercise so the language tooling (`cargo run --example`,
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`node`) can find them; the Python examples have no crate of their own and
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live here under [`python/`](python/).
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## Rust — `examples/rust/`
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The Rust examples live in the `wickra-examples` workspace member crate.
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| Example | What it does | Run |
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| --- | --- | --- |
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| `streaming.rs` | Feed a synthetic price series through SMA / EMA / RSI / MACD tick by tick. | `cargo run -p wickra-examples --bin streaming` |
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| `backtest.rs` | Compute a basket of indicators over an OHLCV CSV and print a summary. | `cargo run -p wickra-examples --bin backtest -- <ohlcv.csv>` |
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| `multi_timeframe.rs` | Resample a 1-minute CSV via wickra-data and print indicators per timeframe. | `cargo run -p wickra-examples --bin multi_timeframe` |
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| `parallel_assets.rs` | Serial vs `BatchExt::batch_parallel` (rayon) over a synthetic panel, with speedup. | `cargo run --release -p wickra-examples --bin parallel_assets -- --assets 200 --bars 5000` |
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| `fetch_btcusdt.rs` | Download real BTCUSDT klines from the Binance REST API into `examples/data/`. | `cargo run -p wickra-examples --bin fetch_btcusdt` |
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| `live_binance.rs` | Stream live Binance klines through an indicator over a resilient WebSocket. | `cargo run -p wickra-examples --bin live_binance` |
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## Python — `examples/python/`
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| Example | What it does | Run |
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| --- | --- | --- |
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| `streaming.py` | Feed a synthetic price series through SMA / EMA / RSI / MACD tick by tick. | `python -m examples.python.streaming` |
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| `backtest.py` | Basket of indicators over an OHLCV CSV. | `python -m examples.python.backtest <ohlcv.csv>` |
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| `live_trading.py` | Live Binance feed → RSI / MACD / Bollinger → signals. | `python -m examples.python.live_trading --symbol BTCUSDT --interval 1m` |
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| `multi_timeframe.py` | Resample a 1-minute CSV to coarser timeframes and compare. | `python -m examples.python.multi_timeframe <1m.csv>` |
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| `parallel_assets.py` | Process many symbols in parallel — the Rust extension releases the GIL during batch computation. | `python -m examples.python.parallel_assets --assets 200 --bars 5000` |
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`live_trading.py` additionally needs `pip install websockets`.
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## Node.js — `examples/node/`
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Build the native binding once, then link it into the examples directory:
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```bash
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cd bindings/node && npm install && npx napi build --platform --release
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cd ../../examples/node && npm install # links wickra + installs `ws`
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```
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| Example | What it does | Run |
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| --- | --- | --- |
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| `streaming.js` | Feed a synthetic price series through several indicators tick by tick. | `node streaming.js` |
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| `backtest.js` | Basket of indicators over an OHLCV CSV; defaults to the bundled BTCUSDT daily dataset. | `node backtest.js [ohlcv.csv]` |
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| `multi_timeframe.js` | Roll a 1-minute CSV up to 5m / 15m / 1h / 4h / 1d and print indicators per timeframe. | `node multi_timeframe.js [path/to/1m.csv]` |
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| `parallel_assets.js` | Serial vs `worker_threads` pool over a synthetic panel, with speedup. | `node parallel_assets.js --assets 200 --bars 5000` |
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| `live_trading.js` | Live Binance feed → RSI / MACD / Bollinger → signals. | `node live_trading.js --symbol BTCUSDT --interval 1m` |
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## WebAssembly — `examples/wasm/`
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| Example | What it does | Run |
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| --- | --- | --- |
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| `index.html` | Browser demo: streams a price series through six indicators and draws a live `<canvas>` chart. | `wasm-pack build bindings/wasm --target web --release --features panic-hook`, then serve the repository root and open `examples/wasm/index.html` |
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## Example datasets
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`examples/data/` holds seven real BTCUSDT OHLCV datasets, one
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per timeframe (1m, 5m, 15m, 1h, 12h, 1d, 1month), in the standard
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`timestamp,open,high,low,close,volume` layout. The Rust and Node backtest
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examples and the indicator benchmarks run against them. Regenerate them with
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the latest market history via `cargo run -p wickra-examples --bin fetch_btcusdt`.
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