Crypto Technical Analysis

The app pulls candle data from Binance’s public futures API and draws it with indicators such as moving averages, RSI, MACD, Bollinger Bands and ATR. From those it builds long or short setups with a stop-loss and three take-profit levels. It can backtest the same rules on past data, keep a paper-trading record, and send a Windows notification when a setup appears.

The project explores technical analysis on the desktop: charting, indicators, backtesting and configurable trade setups, all built on public market data.

The main modules. Market data comes in through one fetcher, indicators are computed with pandas, and the same signal logic feeds the interface, the backtester and notifications.

Python, PyQt5, pandas, NumPy, matplotlib, mplfinance, requests, plyer, pytest

The project’s stack. Python isn’t part of my main learning path right now; that path is the web.

1. 01

   Public data only

   Market data comes from Binance’s public futures endpoints, so the app needs no API key and never touches an account.

2. 02

   TP profiles move targets, not risk

   Normal, higher-target and conservative profiles change only the take-profit distances — 1.2R, 2.2R and 3.5R on normal. The stop-loss and the signal logic stay the same.

3. 03

   Tests for the maths

   Indicator and price-action functions have pytest tests, so a broken calculation shows up as a failing test instead of a strange chart.

This project explores desktop technical-analysis workflows using public market data, including indicators, charting, backtesting and configurable trade setups.

• Not investment advice. Crypto trading carries high risk.
• An independent project, not affiliated with, endorsed or sponsored by Binance. The name only says where the public data comes from.
• Built and tested on Windows 10 and 11. The interface is in Turkish.