Wickra examples

Runnable examples for every Wickra binding. Rust and Node examples live next to the code they exercise so the language tooling (cargo run --example, node) can find them; the Python examples have no crate of their own and live here under python/.

Rust — examples/rust/

The Rust examples live in the wickra-examples workspace member crate.

Example	What it does	Run
streaming.rs	Feed a synthetic price series through SMA / EMA / RSI / MACD tick by tick.	cargo run -p wickra-examples --bin streaming
backtest.rs	Compute a basket of indicators over an OHLCV CSV and print a summary.	cargo run -p wickra-examples --bin backtest -- <ohlcv.csv>
multi_timeframe.rs	Resample a 1-minute CSV via wickra-data and print indicators per timeframe.	cargo run -p wickra-examples --bin multi_timeframe
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
fetch_btcusdt.rs	Download real BTCUSDT klines from the Binance REST API into examples/data/.	cargo run -p wickra-examples --bin fetch_btcusdt
live_binance.rs	Stream live Binance klines through an indicator over a resilient WebSocket.	cargo run -p wickra-examples --bin live_binance
strategy_rsi_mean_reversion.rs	Hourly BTCUSDT mean-reversion using RSI(14) thresholds, with PnL / Sharpe / max-DD summary.	cargo run --release -p wickra-examples --bin strategy_rsi_mean_reversion
strategy_macd_adx.rs	Hourly BTCUSDT trend-follower: MACD crossover entries gated by ADX(14) > 20.	cargo run --release -p wickra-examples --bin strategy_macd_adx
strategy_bollinger_squeeze.rs	Daily BTCUSDT Bollinger-squeeze breakout with ATR(14) trailing stop.	cargo run --release -p wickra-examples --bin strategy_bollinger_squeeze

C / C++ — examples/c/

Build the library first (cargo build -p wickra-c --release), then build and run the examples via CMake: cmake -S examples/c -B examples/c/build -DWICKRA_LIB_DIR="$PWD/target/release" → cmake --build examples/c/build → ctest --test-dir examples/c/build.

Example	What it does	CMake target
smoke.c	Links the generated header + library and asserts SMA streaming / batch values across the boundary.	smoke
streaming.c	Feed a synthetic price series through SMA / EMA / RSI / MACD tick by tick.	streaming
backtest.c	Basket of indicators over an OHLCV CSV; defaults to the bundled BTCUSDT daily dataset.	backtest
multi_timeframe.c	Resample the bundled 1-minute CSV to 5m / 15m / 1h / 4h / 1d and print indicators per timeframe.	multi_timeframe
parallel_assets.c	Serial vs OpenMP fan-out over a synthetic panel (one handle per asset), with speedup.	parallel_assets
strategy_rsi_mean_reversion.c	Hourly BTCUSDT mean-reversion using RSI(14) thresholds, with PnL / Sharpe / max-DD summary.	strategy_rsi_mean_reversion
strategy_macd_adx.c	Hourly BTCUSDT trend-follower: MACD crossover entries gated by ADX(14) > 20.	strategy_macd_adx
strategy_bollinger_squeeze.c	Daily BTCUSDT Bollinger-squeeze breakout with ATR(14) stop.	strategy_bollinger_squeeze
fetch_btcusdt.c	Download real BTCUSDT klines from the Binance REST API into examples/data/ (shells out to curl).	fetch_btcusdt
live_binance.c	Poll the Binance REST klines endpoint via curl and stream closed candles through RSI(14).	live_binance
smoke.cpp	C++ RAII via wickra::Handle from wickra.hpp: construct, move, auto-free.	cpp_smoke

The data-driven examples (backtest, multi_timeframe, parallel_assets, the three strategy_*) build against the bundled datasets and run under ctest. fetch_btcusdt and live_binance reach the network, so they are built but not run in CI; run them by hand. parallel_assets links OpenMP when the toolchain provides it and falls back to a single-threaded run otherwise.

C# — examples/csharp/

Build the C ABI library first (cargo build -p wickra-c --release), then run any example with the .NET 8 SDK; the binding resolves the native library automatically.

Example	What it does	Run
streaming	Feed a synthetic price series through SMA / EMA / RSI / MACD tick by tick.	dotnet run --project examples/csharp/streaming
backtest	Basket of indicators over an OHLCV series (CSV arg or synthetic).	dotnet run --project examples/csharp/backtest -- <ohlcv.csv>
multi_timeframe	Resample a 1-minute series to 5m / 15m and print an indicator per timeframe.	dotnet run --project examples/csharp/multi_timeframe
parallel_assets	SMA(20) batch over a panel, serial vs Parallel.For, with speedup.	dotnet run -c Release --project examples/csharp/parallel_assets
strategy_rsi_mean_reversion	RSI(14) mean-reversion with PnL / Sharpe / max-DD summary.	dotnet run -c Release --project examples/csharp/strategy_rsi_mean_reversion
strategy_macd_adx	Trend-follower: MACD crossover entries gated by ADX(14) > 20.	dotnet run -c Release --project examples/csharp/strategy_macd_adx
strategy_bollinger_squeeze	Bollinger-squeeze breakout with an ATR(14) trailing stop.	dotnet run -c Release --project examples/csharp/strategy_bollinger_squeeze
fetch_btcusdt	Download real BTCUSDT klines from the Binance REST API into a CSV.	dotnet run --project examples/csharp/fetch_btcusdt
live_binance	Stream live Binance klines through EMA(20) over a WebSocket.	dotnet run --project examples/csharp/live_binance

The offline examples run on deterministic synthetic data (and under CI on all three OSes); fetch_btcusdt and live_binance reach the network and are built but not run in CI.

Go — examples/go/

Build the C ABI library first (cargo build -p wickra-c --release) and stage it under bindings/go/lib/ (see the Go binding README), then run any example from the examples/go module.

Example	What it does	Run
streaming	Feed a synthetic price series through SMA / EMA / RSI / MACD tick by tick.	go run ./streaming
backtest	Basket of indicators over an OHLCV series (CSV arg or synthetic).	go run ./backtest <ohlcv.csv>
multi_timeframe	Resample a 1-minute series to 5m / 15m and print an indicator per timeframe.	go run ./multi_timeframe
parallel_assets	SMA(20) batch over a panel, serial vs goroutine fan-out, with speedup.	go run ./parallel_assets 200 5000
strategy_rsi_mean_reversion	RSI(14) mean-reversion with PnL / Sharpe / max-DD summary.	go run ./strategy_rsi_mean_reversion
strategy_macd_adx	Trend-follower: MACD crossover entries gated by ADX(14) > 20.	go run ./strategy_macd_adx
strategy_bollinger_squeeze	Bollinger-squeeze breakout with an ATR(14) trailing stop.	go run ./strategy_bollinger_squeeze
fetch_btcusdt	Download real BTCUSDT klines from the Binance REST API into a CSV.	go run ./fetch_btcusdt
live_binance	Stream live Binance klines through EMA(20) over a WebSocket.	go run ./live_binance

The offline examples run on deterministic synthetic data (and under CI on all three OSes); fetch_btcusdt and live_binance reach the network and are built but not run in CI.

R — examples/r/

Build the C ABI library first (cargo build -p wickra-c --release) and install the binding (see the R binding README), then run any example from this directory.

Example	What it does	Run
streaming.R	Feed a synthetic price series through SMA / EMA / RSI / MACD tick by tick.	Rscript streaming.R
backtest.R	Basket of indicators over an OHLCV series (CSV arg or synthetic).	Rscript backtest.R <ohlcv.csv>
multi_timeframe.R	Resample a 1-minute series to 5m / 15m and print an indicator per timeframe.	Rscript multi_timeframe.R
parallel_assets.R	SMA(20) batch over a panel, serial vs mclapply, with speedup.	Rscript parallel_assets.R 200 5000
strategy_rsi_mean_reversion.R	RSI(14) mean-reversion with PnL / Sharpe / max-DD summary.	Rscript strategy_rsi_mean_reversion.R
strategy_macd_adx.R	Trend-follower: MACD crossover entries gated by ADX(14) > 20.	Rscript strategy_macd_adx.R
strategy_bollinger_squeeze.R	Bollinger-squeeze breakout with an ATR(14) trailing stop.	Rscript strategy_bollinger_squeeze.R
fetch_btcusdt.R	Download real BTCUSDT klines from the Binance REST API into a CSV.	Rscript fetch_btcusdt.R
live_binance.R	Stream live Binance klines through EMA(20) over a WebSocket.	Rscript live_binance.R

The offline examples run on deterministic synthetic data (and under CI on all three OSes); fetch_btcusdt.R and live_binance.R reach the network and are parse-checked but not run in CI.

Java — examples/java/

Build the C ABI library first (cargo build -p wickra-c --release) and install the binding (mvn -f bindings/java install -DskipTests), then run any example from this directory. The exec goal forks a JVM with --enable-native-access=ALL-UNNAMED.

Example	What it does	Run
Streaming	Feed a synthetic price series through SMA / EMA / RSI / MACD tick by tick.	mvn exec:exec -Dexec.mainClass=org.wickra.examples.Streaming
Backtest	Basket of indicators over an OHLCV series (CSV arg or synthetic).	mvn exec:exec -Dexec.mainClass=org.wickra.examples.Backtest
MultiTimeframe	Resample a 1-minute series to 5m / 15m and print an indicator per timeframe.	mvn exec:exec -Dexec.mainClass=org.wickra.examples.MultiTimeframe
ParallelAssets	SMA(20) batch over a panel, serial vs parallel streams, with speedup.	mvn exec:exec -Dexec.mainClass=org.wickra.examples.ParallelAssets
StrategyRsiMeanReversion	RSI(14) mean-reversion with PnL / Sharpe / max-DD summary.	mvn exec:exec -Dexec.mainClass=org.wickra.examples.StrategyRsiMeanReversion
StrategyMacdAdx	Trend-follower: MACD crossover entries gated by ADX(14) > 20.	mvn exec:exec -Dexec.mainClass=org.wickra.examples.StrategyMacdAdx
StrategyBollingerSqueeze	Bollinger-squeeze breakout with an ATR(14) trailing stop.	mvn exec:exec -Dexec.mainClass=org.wickra.examples.StrategyBollingerSqueeze
FetchBtcusdt	Download real BTCUSDT klines from the Binance REST API into a CSV.	mvn exec:exec -Dexec.mainClass=org.wickra.examples.FetchBtcusdt
LiveBinance	Stream live Binance klines through EMA(20) over a WebSocket.	mvn exec:exec -Dexec.mainClass=org.wickra.examples.LiveBinance

The offline examples run on deterministic synthetic data (and under CI on all three OSes); FetchBtcusdt and LiveBinance reach the network and are build-checked but not run in CI.

Python — examples/python/

Example	What it does	Run
streaming.py	Feed a synthetic price series through SMA / EMA / RSI / MACD tick by tick.	python -m examples.python.streaming
backtest.py	Basket of indicators over an OHLCV CSV.	python -m examples.python.backtest <ohlcv.csv>
live_binance.py	Live Binance feed → RSI / MACD / Bollinger → signals.	python -m examples.python.live_binance --symbol BTCUSDT --interval 1m
multi_timeframe.py	Resample a 1-minute CSV to coarser timeframes and compare.	python -m examples.python.multi_timeframe <1m.csv>
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
fetch_btcusdt.py	Download real BTCUSDT klines from the Binance REST API into examples/data/ (urllib + stdlib only).	python -m examples.python.fetch_btcusdt
strategy_rsi_mean_reversion.py	Hourly BTCUSDT mean-reversion using RSI(14) thresholds, with PnL / Sharpe / max-DD summary.	python -m examples.python.strategy_rsi_mean_reversion
strategy_macd_adx.py	Hourly BTCUSDT trend-follower: MACD crossover entries gated by ADX(14) > 20.	python -m examples.python.strategy_macd_adx
strategy_bollinger_squeeze.py	Daily BTCUSDT Bollinger-squeeze breakout with ATR(14) trailing stop.	python -m examples.python.strategy_bollinger_squeeze

Every Python example runs on Wickra alone — no third-party packages. live_binance.py uses the native BinanceFeed and fetch_btcusdt.py the stdlib urllib.

Node.js — examples/node/

Build the native binding once, then link it into the examples directory:

cd bindings/node && npm install && npx napi build --platform --release
cd ../../examples/node && npm install        # links wickra (no third-party packages)

Example	What it does	Run
streaming.js	Feed a synthetic price series through several indicators tick by tick.	node streaming.js
backtest.js	Basket of indicators over an OHLCV CSV; defaults to the bundled BTCUSDT daily dataset.	node backtest.js [ohlcv.csv]
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]
parallel_assets.js	Serial vs worker_threads pool over a synthetic panel, with speedup.	node parallel_assets.js --assets 200 --bars 5000
live_binance.js	Live Binance feed → RSI / MACD / Bollinger → signals.	node live_binance.js --symbol BTCUSDT --interval 1m
fetch_btcusdt.js	Download real BTCUSDT klines from the Binance REST API into examples/data/ (built-in fetch, Node 18+).	node fetch_btcusdt.js
strategy_rsi_mean_reversion.js	Hourly BTCUSDT mean-reversion using RSI(14) thresholds, with PnL / Sharpe / max-DD summary.	node strategy_rsi_mean_reversion.js
strategy_macd_adx.js	Hourly BTCUSDT trend-follower: MACD crossover entries gated by ADX(14) > 20.	node strategy_macd_adx.js
strategy_bollinger_squeeze.js	Daily BTCUSDT Bollinger-squeeze breakout with ATR(14) trailing stop.	node strategy_bollinger_squeeze.js

WASM — examples/wasm/

Build the WASM module first (one-time):

wasm-pack build bindings/wasm --target web --release --features panic-hook

Then serve the repository root (python -m http.server, npx http-server, …) and open the demo you want in a browser.

Example	What it does
index.html	Streams a synthetic price series through six indicators and draws a live <canvas> chart.
backtest.html	Streams a fetched OHLCV CSV through a basket of indicators (SMA, EMA, RSI, MACD, Bollinger, ATR, ADX, OBV) and prints a per-series summary table.
live_binance.html	Opens a browser-native WebSocket to Binance, runs RSI / MACD / Bollinger and flags BUY/SELL candidates.
multi_timeframe.html	Fetches a 1-minute CSV, rolls it up to 5m / 15m / 1h / 4h / 1d in-page, prints RSI / MACD hist / ADX per timeframe.
parallel_assets.html	Spawns a pool of module Workers (each loading its own copy of the WASM module) and reports the speedup over a serial baseline.
strategy_rsi_mean_reversion.html	Hourly BTCUSDT RSI(14) mean-reversion (long < 30, exit > 70); prints a PnL / Sharpe / max-DD summary table.
strategy_macd_adx.html	Hourly BTCUSDT MACD crossover gated by ADX(14) > 20, with the same summary table.
strategy_bollinger_squeeze.html	Daily BTCUSDT Bollinger-squeeze breakout with a 2×ATR(14) stop and summary table.

Example datasets

examples/data/ holds seven real BTCUSDT OHLCV datasets, one per timeframe (1m, 5m, 15m, 1h, 12h, 1d, 1month), in the standard timestamp,open,high,low,close,volume layout. The Rust and Node backtest examples and the indicator benchmarks run against them. Regenerate them with the latest market history via cargo run -p wickra-examples --bin fetch_btcusdt.