v1indicators 0.3.0

Technical analysis indicators and scanners.

v1indicators

v1indicators is a fast, production-focused technical analysis library for Python.

It provides a clean functional API for indicator calculations and keeps scope intentionally narrow:

• no charting
• no broker integrations
• no strategy execution framework

The goal is simple: reliable indicator math on top of pandas Series/DataFrame inputs.

Highlights

• Vectorized implementations for performance-critical paths.
• Numba-accelerated kernels for recursive/stateful indicators where appropriate.
• Consistent indicator signatures across categories.
• Broad indicator coverage across overlap, momentum, trend, volatility, volume, statistics, levels, and performance.

Installation

From source:

pip install .

For development:

pip install -e ".[dev]"

Quick Start

import pandas as pd
from v1indicators import rsi, macd, supertrend

df = pd.read_csv("data.csv")

# Single-series output
df["RSI_14"] = rsi(df["close"], length=14)

# Multi-column output
macd_df = macd(df["close"], fast=12, slow=26, signal=9)
df = pd.concat([df, macd_df], axis=1)

st_df = supertrend(df["high"], df["low"], df["close"], length=10, mult=3.0)
df = pd.concat([df, st_df], axis=1)

API Organization

The package is organized by indicator families:

• overlap
• momentum
• trend
• volatility
• volume
• statistics
• levels
• performance

You can import from the package root for common indicators:

from v1indicators import ema, sma, rsi, atr, obv

Or from family modules for explicit namespacing:

from v1indicators.momentum import rsi, stoch
from v1indicators.overlap import ema, bbands

Data Requirements

Most indicators expect pandas Series aligned on the same index. Common field expectations:

• close-only indicators: close
• range-based indicators: high, low, close
• volume indicators: close, volume (sometimes high/low/open as needed)

Testing

Run the full test suite:

pytest

License

MIT