Hire a Python trading developer for trading bots, broker and exchange API integration, backtesting and risk management — built from your rules and ready to run.
Bots, integrations, backtests and tools written in Python for the way you trade.
Nordman Algorithms builds Python trading software for traders, prop traders, small funds and trading teams. Our Python trading developers work from trading rules, a written specification or just a plain description — or from a strategy that already runs on another platform.
Python is the natural choice when a strategy has to work with broker APIs, process data, run research or tie several systems together. As Python algorithmic trading developers, we turn your rules or models into software that trades, keeps logs and reports problems — the trading idea stays yours.
You receive the full Python source and all rights to it when the work is delivered.
Trading bots, broker integrations, backtesting and data systems, written by our Python algorithmic trading developers from your rules.
Automated trading systems built from your rules: signals, position sizing, order handling and risk limits in one Python application that runs on its own.
Python connected to broker and exchange APIs over REST, WebSocket or native libraries — orders, positions, account data and live prices, with reconnects and rate limits handled. FIX where a broker requires it.
Backtesting built around your strategy, with trading costs and slippage, walk-forward and out-of-sample tests, and clear reports — using the same strategy logic as the live system where possible.
Historical and live data collected from your providers, cleaned, turned into bars and stored in a database — ready for research, backtests and live trading.
Risk rules enforced in code: position and exposure limits, daily loss and drawdown stops, prop firm rules and an emergency stop.
Capital allocation and rebalancing across instruments or accounts, on a schedule or when weights drift from targets.
Trades copied or executed across several accounts through broker APIs, with position size set for each account.
Web dashboards for positions, orders, P&L and system health, with alerts when something needs attention.
Strategies moved to Python from Pine Script, MQL4/5, NinjaScript or EasyLanguage — or from Python to those platforms — with logic, assumptions and key outputs compared across platforms.
New features, fixes and completion for Python trading code you already have, including projects another developer left unfinished.
The building blocks behind the services above — combined to fit what your system has to do.
Entry and exit rules, several symbols and timeframes, session filters, signals from your own model.
Order types, stops and targets, trailing, partial fills, retries, duplicate protection, position checks and reconnects.
Position sizing, limits, daily loss and drawdown stops, prop firm rules, emergency stop.
Historical downloads, live streams, bar building, cleaning, storage, several providers.
TradingView webhooks, Telegram and Discord signals, notifications, an API for your other software.
One signal on several accounts, size set per account, trades copied between accounts.
Trade logs, P&L reports, performance statistics, alerts on errors and disconnects.
VPS or cloud, Docker, automatic restarts, logs, schedules and safe storage of API keys.
Four common ways a Python system fits into a trading setup, and the brokers and platforms we connect it to.
Python connects to the broker or exchange API for prices, account data and orders — to Interactive Brokers through TWS or IB Gateway, to crypto exchanges straight to their API.
Python works alongside a trading platform you already use — for analysis, signals, risk or order execution. With MetaTrader 5, the official Python package works through a running MT5 terminal; the exact setup depends on the platform.
A standalone application: Python on a server, your own interface or dashboard, and a database for trades and reports.
History goes in, your model runs on it, and reports come out — showing whether the idea is worth developing further.
We agree the rules, the broker and data, where the system will run and the acceptance checks with you before any code is written.
Send your trading rules or model, the broker or exchange you use, where the data comes from, and where the system should run.
Receive the full Python source, configuration and a setup guide — plus test results and deployment on your server where the project includes them. We walk through the specified behaviour and provide technical support under the agreed terms.
Work with Python trading programmers who also build for MetaTrader, NinjaTrader, cTrader and TradingView.
We also build for MetaTrader, NinjaTrader, cTrader and TradingView, so Python systems that work with them are familiar ground.
Reconnects, logging and alerts are planned from the start, so the system reports problems instead of failing silently.
Requirements, deliverables, fixed price and acceptance examples are agreed before development begins.
An NDA is available on request. Source code and full IP ownership are transferred on delivery.
Setup help, configuration questions and technical answers within the agreed support scope.
Feedback from clients across our custom trading software projects.
Practical answers about Python trading systems, brokers and platforms.
Yes, if your broker or exchange offers an API. The bot connects to it, receives prices and account data, and places and manages orders by your rules.
Interactive Brokers, crypto exchanges such as Binance, Coinbase and Kraken, other brokers with a public API, MetaTrader 5 through its official Python package, cTrader through its Open API, and TradingView alerts through webhooks.
For the strategies most traders, prop traders and small funds run, yes. Microsecond-level trading needs other languages and infrastructure, and if a project needs that, we say so at the start.
No. We implement your rules or your models in Python, test them and connect them to live trading. The trading idea stays yours.
Yes. The logic is rebuilt in Python and connected to your broker or data. Its logic, assumptions and key outputs are then compared with the original, allowing for differences in data and execution between platforms.
Yes. We add features, fix problems and finish projects another developer left incomplete, after going through the existing code to see how it is built.
On a VPS, a cloud server or your own machine — whichever suits the strategy. If deployment is agreed, we set it up there to restart after failures, keep logs and send alerts.
Your trading rules or model, the broker or exchange you use, where the data comes from, and where the system should run. Existing code helps if there is any.
Send your rules or model, your broker and where the system should run. We will review it and come back with the scope and next steps.