binpan 0.9.3

Binance API wrapper with backtesting tools.

Welcome to BinPan's documentation!

BinPan is a Python wrapper for the Binance API oriented towards market data analysis: candlestick (kline) data, trades, technical indicators, plotting, and strategy backtesting.

It is intended to be useful in Jupyter Notebooks, the Python console, or any data pipeline.

Requires Python >= 3.12. Published on PyPI under the MIT license.

Features

• Fetch candlestick (OHLCV) data with timezone and indexing options.
• Fetch atomic and aggregated trades.
• Native technical indicators (EMA, SMA, RSI, MACD, Bollinger Bands, Supertrend, Ichimoku, VWAP, Stochastic, fractals, and more).
• Interactive candlestick charts with Plotly: indicators, buy/sell markers, trade bubble charts, order book, market profile.
• Support and resistance detection via K-Means clustering (static, rolling, discrete interval).
• Strategy tagging and backtesting engine with stop loss, target, entry filters, and ROI/profit metrics.
• Exchange metadata: order types, filters, fees, coin networks, 24h volume ranking.
• CSV export/import for klines and trades.
• PostgreSQL/TimescaleDB integration for historical data storage.
• Heikin-Ashi candles, reversal charts from tick data, kline resampling.

An example of a candlestick chart with indicators:

BinPan contains no Binance order method, withdraw method or any dangerous command.

If you decide to add API keys for account methods, BinPan will encrypt them in a file and in memory, but it is recommended not to enable trading capability in your Binance API key configuration.

Be careful out there!

Installation

pip install binpan

Any API key or secret will be prompted when needed and encrypted in a file.

Quick Start

import binpan

btcusdt = binpan.Symbol(symbol='btcusdt',
                        tick_interval='15m',
                        time_zone='Europe/Madrid',
                        limit=200)

btcusdt.ema(21)
btcusdt.supertrend()
btcusdt.plot()

Example Notebooks

The notebooks/ folder contains example Jupyter Notebooks organized by topic:

#	Notebook	Topic
01	basic_tutorial	Getting started: data, indicators, plots, trades
02	data_analysis	Analysis: indicators, trades, market profile, order book
03	technical_indicators	Full indicator catalogue
04	plotting	All visualization capabilities
05	reversal_charts	Reversal candles from atomic trades
06	tagging_and_backtesting	Strategy signals and backtesting
07	support_resistance_kmeans	S/R with K-Means clustering
08-10	ichimoku_*	Ichimoku analysis and backtesting
11	exchange_info	Exchange class: metadata, filters, fees
12	export_csv	CSV export/import
13-15	database_*	PostgreSQL/TimescaleDB integration

Documentation

Full Sphinx documentation: https://nand0san.github.io/binpan_studio/

GitHub repo

https://github.com/nand0san/binpan_studio

Google Colab

Google Colab is not available for the Binance API due to IP restrictions.

BinanceAPIException: APIError(code=0): Service unavailable from a restricted location...

Jupyter Import Troubleshooting

If you encounter import errors in Jupyter, install packages directly to the kernel:

import sys
!{sys.executable} -m pip install binpan

License

MIT