mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-30 18:47:42 +00:00
Miha Kralj
155 lines
8.2 KiB
Markdown
155 lines
8.2 KiB
Markdown
[](https://app.codacy.com/gh/mihakralj/QuanTAlib/dashboard?utm_source=gh&utm_medium=referral&utm_content=&utm_campaign=Badge_grade)
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[](https://codecov.io/gh/mihakralj/QuanTAlib)
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[](https://sonarcloud.io/summary/new_code?id=mihakralj_QuanTAlib)
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[](https://www.codefactor.io/repository/github/mihakralj/quantalib/overview/main)
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[](https://www.nuget.org/packages/QuanTAlib/)
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[](https://www.nuget.org/packages/QuanTAlib/)
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[](https://dotnet.microsoft.com/en-us/download/dotnet)
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[](lib/_index.md)
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[](docs/ndepend.md)
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[](docs/ndepend.md)
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[](docs/ndepend.md)
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[](docs/ndepend.md)
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[](docs/ndepend.md)
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[](docs/ndepend.md)
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# QuanTAlib
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**393 technical indicators. One library. Brutal architectural trade-offs for absolute speed.**
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QuanTAlib grinds through half a million bars of SMA in 328 microseconds. Faster than an L1 cache miss. The same indicators run in C#, Python, and PineScript. Cross-validated against TA-Lib, Tulip, Skender, and every other implementation worth testing.
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We achieve this by trading object allocation for contiguous memory spans and forcing SIMD vectorization. You want speed? We dictate the heap.
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Pick your weapon:
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| Platform | Install | Guide |
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| :--- | :--- | :--- |
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| **C# / .NET 10** | `dotnet add package QuanTAlib` | [Architecture](docs/architecture.md) . [API Reference](docs/api.md) |
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| **Python** | `pip install quantalib` | [**Python Guide**](docs/python.md) |
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| **PineScript v6** | Copy-paste from `lib/` | [**PineScript Guide**](docs/pinescript.md) |
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## Quick Start
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### C# Streaming (Real-time incoming data)
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```csharp
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using QuanTAlib;
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// No allocations in the update loop. State is maintained internally.
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var sma = new Sma(period: 14);
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var result = sma.Update(110.4);
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if (result.IsHot)
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Console.WriteLine($"SMA: {result.Value}");
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```
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### C# — batch (500K bars in microseconds)
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```csharp
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// We evaluate code, not promises.
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// This processes as contiguous memory using AVX-512 vectorization.
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// Zero allocations. The Garbage Collector sleeps.
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double[] prices = LoadHistoricalData();
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double[] results = new double[prices.Length];
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Sma.Batch(prices.AsSpan(), results.AsSpan(), period: 14);
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```
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### Python
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```python
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import quantalib as qtl
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import numpy as np
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prices = np.random.default_rng(42).normal(100, 2, size=500_000)
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sma = qtl.sma(prices, period=14) # 393 indicators, similar syntax
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```
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Works with NumPy, pandas, polars, and PyArrow. [Full Python guide →](docs/python.md)
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### PineScript
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Every indicator ships as a standalone .pine file. Open it. Copy it. Paste it into TradingView. No magic, just math. [Full PineScript guide →](docs/pinescript.md)
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---
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## 393 Indicators
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| Category | Count | What It Measures | Examples |
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| :--- | :---: | :--- | :--- |
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| [**Core**](lib/core/_index.md) | 8 | Price transforms, building blocks | AVGPRICE, MEDPRICE, TYPPRICE, HA |
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| [**Trends (FIR)**](lib/trends_FIR/_index.md) | 33 | Finite impulse response averages | SMA, WMA, HMA, ALMA, TRIMA, LSMA |
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| [**Trends (IIR)**](lib/trends_IIR/_index.md) | 36 | Infinite impulse response averages | EMA, DEMA, TEMA, T3, JMA, KAMA, VIDYA |
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| [**Filters**](lib/filters/_index.md) | 37 | Signal processing, noise reduction | Kalman, Butterworth, Gaussian, Savitzky-Golay |
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| [**Oscillators**](lib/oscillators/_index.md) | 48 | Bounded/centered oscillators | RSI, MACD, Stochastic, CCI, Fisher, Williams %R |
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| [**Dynamics**](lib/dynamics/_index.md) | 21 | Trend strength and direction | ADX, Aroon, SuperTrend, Ichimoku, Vortex |
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| [**Momentum**](lib/momentum/_index.md) | 19 | Speed of price changes | ROC, Momentum, Velocity, TSI, Qstick |
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| [**Volatility**](lib/volatility/_index.md) | 26 | Price variability | ATR, Bollinger Width, Historical Vol, True Range |
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| [**Volume**](lib/volume/_index.md) | 27 | Trading activity | OBV, VWAP, MFI, CMF, ADL, Force Index |
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| [**Statistics**](lib/statistics/_index.md) | 35 | Statistical measures | Correlation, Variance, Skewness, Z-Score |
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| [**Channels**](lib/channels/_index.md) | 23 | Price boundaries | Bollinger Bands, Keltner, Donchian |
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| [**Cycles**](lib/cycles/_index.md) | 14 | Cycle analysis | Hilbert Transform, Homodyne, Ehlers Sine Wave |
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| [**Reversals**](lib/reversals/_index.md) | 12 | Pattern detection | Pivot Points, Fractals, Swings |
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| [**Forecasts**](lib/forecasts/_index.md) | 1 | Predictive indicators | Time Series Forecast |
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| [**Errors**](lib/errors/_index.md) | 26 | Error metrics, loss functions | RMSE, MAE, MAPE, SMAPE, R² |
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| [**Numerics**](lib/numerics/_index.md) | 27 | Mathematical transforms | Log, Exp, Sigmoid, Normalize, FFT |
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**[Browse all 393 indicators →](lib/_index.md)**
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---
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## Performance
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500,000 bars. Period 220. .NET 10.0, AVX-512. Zero allocations.
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| Library | SMA Time | Allocations | vs QuanTAlib |
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| :--- | ---: | ---: | :--- |
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| **QuanTAlib** | **328 μs** | **0 B** | — |
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| TA-Lib | 365 μs | 32 B | 1.1× slower |
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| Tulip | 370 μs | 0 B | 1.1× slower |
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| Skender | 68,436 μs | 42 MB | **209× slower** |
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| Ooples | 347,453 μs | 151 MB | **1,060× slower** |
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That is 0.66 nanoseconds per value — faster than a single L1 cache miss. [Full benchmarks →](docs/benchmarks.md)
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---
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## Documentation
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### Architecture & API
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- [**Architecture**](docs/architecture.md) — SoA memory layout, SIMD vectorization, O(1) streaming, [design philosophy](docs/architecture.md#design-philosophy)
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- [**API Reference**](docs/api.md) — Batch, Streaming, and Priming modes
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- [**Usage Patterns**](docs/usage.md) — Span, Streaming, Batch, Eventing examples
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- [**Integration**](docs/integration.md) — Quantower, NinjaTrader, QuantConnect
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### Analysis & Validation
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- [**Benchmarks**](docs/benchmarks.md) — SMA, EMA, RSI, MACD, Bollinger, Chaikin results
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- [**Validation**](docs/validation.md) — Cross-library verification matrices
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- [**Error Metrics**](docs/errors.md) — 26 error and loss functions
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- [**Trend Comparison**](docs/trendcomparison.md) — Lag, smoothness, accuracy across MAs
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- [**MA Qualities**](docs/ma-qualities.md) — Theoretical framework for MA evaluation
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- [**Glossary**](docs/glossary.md) — Core concepts and terminology
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### Code Quality
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Static analysis: [NDepend](https://www.ndepend.com/) · [Codacy](https://app.codacy.com/gh/mihakralj/QuanTAlib/dashboard) · [SonarCloud](https://sonarcloud.io/summary/new_code?id=mihakralj_QuanTAlib) · [CodeFactor](https://www.codefactor.io/repository/github/mihakralj/quantalib/overview/main)
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## ⚠️ Fair Warning
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This library is **not yet 1.0.0**. There is exactly **one** grumpy engineer behind it, fueled by mass amounts of caffeine and an irrational belief that all technical indicators should be correct down to the 10th decimal place.
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Implemented indicators are not yet complete. Things **will** break. APIs **will** change. Some indicators might produce values that make your quantitative models question the meaning of life. If you find something broken and don't [open an issue](https://github.com/mihakralj/QuanTAlib/issues), the grumpy dev will have absolutely no idea what needs fixing — and the backlog of things to fix, improve, and add is already longer than a Bollinger Band on a meme stock.
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Your bug reports make this library better. Your silence makes the dev mass more coffee.
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## License
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Licensed under [Apache 2.0](LICENSE). Not MIT. Not BSD. Deliberately.
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**[Full rationale →](docs/license.md)**
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