kingchenc
2ae76bb90e
Adds `BinanceRest::fetch_klines` to `wickra-data`: a blocking historical kline downloader (`GET /api/v3/klines`) and the historical counterpart to the F4 live `BinanceFeed`. It is the last native data-layer primitive needed to drop third-party HTTP/JSON download helpers (`jackson`, `jsonlite`, `urllib`, …) from the examples. ## What - **Core** (`wickra-data`): `fetch_klines(symbol, interval, limit, start?, end?)` built on `ureq` with native-tls — sharing the exact same TLS backend (native-tls 0.2 / SChannel) as the existing tokio-tungstenite live feed, so the two pull one TLS stack, not two. Parses Binance's 12-element array rows via the existing serde infrastructure into validated `Candle`s. Blocking by design (a one-shot request needs no async runtime; the FFI boundary is synchronous anyway). Nine mock-HTTP-server tests cover parse / empty / limit / transport / JSON / invariant-violation paths. - **C ABI**: `wickra_binance_fetch_klines(...)` (blocking drain into a caller buffer, `-1` on error) + regenerated cbindgen header and its vendored Go copy. - **Bindings**: native Node `fetchBinanceKlines` / Python `fetch_binance_klines`; generated Go `FetchBinanceKlines` / C# `BinanceFeed.FetchKlines` / Java `BinanceFeed.fetchKlines` / R `fetch_binance_klines`. C / C++ call the C ABI directly. **WASM is excluded** (browsers use the host `fetch`). The four C-ABI bindings are regenerated from the ScriptHelpers generators (not hand-edited); the regen diff is exactly the new wrapper in each. ## Verification All ten toolchains green locally: Rust (`cargo test`/`clippy`/`fmt`), Node, Python, Go, C#, Java, R (`R CMD INSTALL` + smoke), WASM (`cargo check`, confirmed `ureq` is not pulled). Each binding has an error-path smoke test; the parse/HTTP success path is covered by the Rust mock-server tests. No release in this PR — ships with the data-layer + numpy bundle later.
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 WASM, 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 all 514 streaming-first indicators across twenty-four 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 forSMA,ATRandMACD. 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, WASM and Rust, plus a
C ABI hub that any C-capable language (C, C++, C#, Go, Java, R) links against —
all exposing the same indicators from the shared, unsafe-forbidden Rust core.
Security
Found a security issue? Please don't open a public issue. Report it privately
via the affected repository's Security tab ("Report a vulnerability") or email
support@wickra.org with a subject line starting [wickra security]. Full
policy: https://github.com/wickra-lib/wickra/blob/main/SECURITY.md.
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.