Grid bot for pionex bitmart, gateio

Python Experts Text translation

Specification

Hello,

Primary goal: convert the existing MQL5 strategy logic to Python as soon as possible and make it work for API trading (order management, exchange connection, basic bot structure). I want to keep the core logic unchanged.

I haven’t chosen the exchange yet (must be usable in the EU). Binance, OKX, Kraken, and Bybit are not options. Bitmart, pionex, gateio are options.

Secondary goal (code reduction): the current MQL5 code is ~5,000 lines, but only ~1,000 lines or less are core/usable. I want to:

  • remove unnecessary parts,
  • keep only the basic parameters and core logic (no indicators/extra filters),
  • remove the corresponding source code (not just hide inputs).

it can be also everything translated to python but i think that would be harder.


I also need a backtesting setup: please propose a crypto backtesting tool/environment, explain where/how to run the backtest, and deliver Python code that works in that backtesting environment and on at least one crypto exchange via API. So probably 2 codes would be needed slightly modified.







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Similar orders
Mk 30+ USD
I need a fully automated trading robot designed to generate consistent profits while strictly controlling risk and minimizing losses. The robot should use a combination of strategies, including trend-following, scalping, and price action, and must be able to adapt to different market conditions such as trending and ranging markets. It should analyze the market using indicators like Moving Averages, RSI, MACD, and
1. IF price forms: - Higher highs + higher lows → TREND = BUY - Lower highs + lower lows → TREND = SELL ELSE → NO TRADE 2. IF: - Trend = BUY - Price retraces to support zone - Bullish engulfing candle forms - TDI green crosses above red (optional) THEN: - Execute BUY 3. IF: - Trend = SELL - Price retraces to resistance - Bearish engulfing forms - TDI confirms THEN: - Execute SELL 4. Risk per trade = 1% of account Lot

Project information

Budget
100 - 350 USD