Metadata-Version: 2.4
Name: finind
Version: 0.1.1
Summary: A lightweight, production-ready Python library for computing core financial technical indicators such as SMA, EMA, and RSI using numerically stable and vectorized pandas operations. Designed for quantitative research, algorithmic trading, and machine learning pipelines.
Author: VAISHALI J MEHTA
License-Expression: MIT
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=1.5
Requires-Dist: numpy>=1.23
Requires-Dist: pytest
Dynamic: license-file

# finind

Lightweight financial indicators and signals: SMA, EMA, RSI, Golden Cross.

## Install (local)
pip install -e .

## Usage
```python
import pandas as pd
from finind import sma, ema, rsi, golden_cross

df = pd.read_csv("prices.csv")  # must have Close column
df["SMA20"] = sma(df, 20)
df["EMA20"] = ema(df, 20)
df["RSI14"] = rsi(df, 14)
df["GoldenCross"] = golden_cross(df, 50, 200)

print(df.tail())
