Xarizmi

Xarizmi (read Khwarizmi) project is an educational project that contains tools for technical analysis in Python.

Installation

pip install xarizmi

If you encounter error in installation use Anaconda and then install ta-lib using: bash conda install -c conda-forge ta-lib and then install other packages.

Example

Build Candlestick

from xarizmi.candlestick import Candlestick
c = Candlestick(
    **{
        "open": 2,
        "low": 1,
        "high": 4,
        "close": 3,
    }
)

Portfolio Rebalancing

import datetime
from xarizmi.models.portfolio import Portfolio, PortfolioItem
from xarizmi.models.rebalance import (
    PortfolioAllocation, PortfolioAllocationItem, rebalance
)
from xarizmi.models.symbol import Symbol

now = datetime.datetime(2024, 11, 26)
btc = Symbol.build("BTC", "USD", "USD", "BINANCE")
eth = Symbol.build("ETH", "USD", "USD", "BINANCE")
sol = Symbol.build("SOL", "USD", "USD", "BINANCE")

# Current holdings
portfolio = Portfolio(items=[
    PortfolioItem(symbol=btc, market_value=90_000, quantity=0.9,  datetime=now),
    PortfolioItem(symbol=eth, market_value=30_000, quantity=10.0, datetime=now),
    PortfolioItem(symbol=sol, market_value=10_000, quantity=62.5, datetime=now),
])

# Desired allocation
target = PortfolioAllocation(items=[
    PortfolioAllocationItem(symbol=btc, weight=0.50),
    PortfolioAllocationItem(symbol=eth, weight=0.30),
    PortfolioAllocationItem(symbol=sol, weight=0.20),
])

result = rebalance(portfolio, target)

for item in result.to_sell():
    print(f"SELL {item.symbol.to_string()}: ${-item.delta_market_value:,.0f}")
# SELL BTC-USD: $25,000

for item in result.to_buy():
    print(f"BUY  {item.symbol.to_string()}: ${item.delta_market_value:,.0f}")
# BUY  ETH-USD: $9,000
# BUY  SOL-USD: $16,000

See examples/rebalance.py for the full runnable script.

Indicators

OBV Indicator

from xarizmi.candlestick import CandlestickChart
from xarizmi.ta.obv import OBVIndicator

# assuming btc_usdt_monthly_data is defined (similar to tests/conftest.py)
c = CandlestickChart.model_validate({"candles": btc_usdt_monthly_data})

obv_indicator = OBVIndicator(candlestick_chart=c, volume='amount')
obv_indicator.compute()
print(obv_indicator.indicator_data)
obv_indicator.plot()