The seven BTCUSDT OHLCV datasets used to live under
crates/wickra/examples/data/, which buried them inside a Rust crate even
though the Node backtest example and the upcoming Rust/Node/WASM example
restructure need to reach them too. Move them to the workspace-level
examples/data/ so every language's examples can resolve the same path.
The bench (crates/wickra/benches/indicators.rs), the example_data
integration test, fetch_btcusdt.rs and the Node backtest example all take
the new ../../examples/data/ path; Data-Layer.md, examples/README.md and
the CHANGELOG entry are updated to match. No data file content changes.
Mirror examples/python/live_trading.py for the Node binding: connect to the
public Binance kline WebSocket, stream close prices through RSI / MACD /
Bollinger Bands, and print BUY/SELL candidate signals when all three agree.
The symbol and interval are validated before being spliced into the stream
URL, and non-kline frames (acks, heartbeats) are skipped.
Uses the standard `ws` package, added as a devDependency so it installs
with `npm install` for anyone running the examples but never reaches a
consumer of the published package.
The Node binding shipped only one example (a synthetic streaming demo),
while Python and Rust both have a CSV backtest. Add the Node counterpart of
examples/python/backtest.py and crates/wickra/examples/backtest.rs: it reads
an OHLCV CSV, streams every candle through a basket of indicators (SMA, EMA,
RSI, MACD, Bollinger Bands, ATR, ADX, OBV) via the O(1) update call, and
prints a per-series summary.
With no argument it runs against the bundled BTCUSDT daily dataset, so it is
runnable out of the box; pass a path to use any other OHLCV CSV.
bindings/node had no examples/ directory — the README pointed at a test
file as its "Example". (bindings/wasm/examples/index.html already
exists and is a complete browser demo, so only the Node side was
missing.)
Add bindings/node/examples/streaming.js: a deterministic synthetic
price series fed tick by tick through SMA, EMA, RSI and MACD, printing
a status line and flagging overbought/oversold candidates — the same
O(1)-per-update streaming model a live bot would use. Verified against
the built native module.
kingchenc