kingchenc
1f5eb90b0d
The package README shown on **PyPI** still advertised a NumPy quick-start. Now that Python dropped its NumPy runtime dependency (#317), this updates it: - Tagline + install note: `pip install wickra` pulls **zero** third-party packages (not even NumPy); NumPy is an optional extra (`wickra[numpy]`). - Quick start imports no NumPy; `batch` returns `array.array('d')` (with a note that `np.asarray` wraps it zero-copy if you use NumPy). Ships with the data-layer release.
100 lines
4.3 KiB
Markdown
100 lines
4.3 KiB
Markdown
# Wickra — Python
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[](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
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[](https://codecov.io/gh/wickra-lib/wickra)
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[](https://pypi.org/project/wickra/)
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[](https://github.com/wickra-lib/wickra#license)
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**Streaming-first technical indicators for Python. `pip install wickra` — zero
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third-party dependencies (not even NumPy), no system dependencies, no C build tooling.**
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Wickra is a multi-language technical-analysis library with a Rust core and
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bindings for Python, Node.js and WASM, plus a C ABI for C, C++, C#, Go, Java, R and any
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other C-capable language. Every indicator is an O(1)
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streaming state machine, so live trading bots and historical backtests share
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the exact same implementation. This package is the Python binding (PyO3); it
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exposes all 514 streaming-first indicators across twenty-four families.
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## Install
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```bash
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pip install wickra
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```
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Pre-built wheels ship for Linux, macOS, and Windows — there is nothing to
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compile and no C library to track down. `pip install wickra` pulls **zero**
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third-party packages; NumPy is an optional extra (`pip install wickra[numpy]`)
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for zero-copy interop.
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## Quick start
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```python
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import wickra as ta # zero third-party deps — not even NumPy
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# Batch: classic TA-Lib-style usage over a whole series.
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prices = [100.0 + i * 0.1 for i in range(1000)] # list, array.array or NumPy all work
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rsi = ta.RSI(14)
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values = rsi.batch(prices) # array.array('d'), NaN during warmup
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# np.asarray(values) wraps it zero-copy if you use NumPy
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# Streaming: the same indicator, fed tick by tick in O(1).
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rsi = ta.RSI(14)
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for price in live_feed:
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value = rsi.update(price) # no recomputation over history
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if value is not None and value > 70:
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print("overbought")
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```
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`batch(prices)` and feeding the same prices through `update()` produce
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identical values — the equivalence is enforced by the test suite.
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## Benchmark
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Two benchmarks ship with the binding:
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- `benchmarks/throughput.py` — streaming and batch updates-per-second for `SMA`,
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`ATR` and `MACD`. This is per-binding FFI overhead (the same Rust core runs
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under every binding), not a cross-library ratio.
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- `benchmarks/compare_libraries.py` — the cross-library comparison against
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TA-Lib, pandas-ta, tulipy and finta that backs the headline speedups.
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```bash
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maturin develop --release
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python -m benchmarks.throughput
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python -m benchmarks.compare_libraries # cross-library; auto-detects installed peers
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```
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See the repository [BENCHMARKS.md](https://github.com/wickra-lib/wickra/blob/main/BENCHMARKS.md).
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## Documentation
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The full indicator catalogue, guides, quickstarts, and API reference live in
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the main repository and documentation site:
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- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
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- **Docs** (quickstarts, cookbook, TA-Lib migration): <https://docs.wickra.org>
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- **Runnable examples:** [`examples/python/`](https://github.com/wickra-lib/wickra/tree/main/examples/python)
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Wickra ships native bindings for Python, Node.js, WASM and Rust, plus a
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C ABI hub that any C-capable language (C, C++, C#, Go, Java, R) links against —
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all exposing the same indicators from the shared, `unsafe`-forbidden Rust core.
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## Security
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Found a security issue? **Please don't open a public issue.** Report it privately
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via the affected repository's *Security* tab (*"Report a vulnerability"*) or email
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**support@wickra.org** with a subject line starting `[wickra security]`. Full
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policy: <https://github.com/wickra-lib/wickra/blob/main/SECURITY.md>.
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## Disclaimer
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Wickra is an indicator toolkit, not a trading system. The values it computes
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are deterministic transforms of the input data — they are not financial advice
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and do not predict the market. Any use in a live trading context is at your own
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risk. The library is provided **as is**, without warranty of any kind.
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## License
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Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
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or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.
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