Python is the language of fast iteration and the language of production machine learning. It is also the language of unmaintainable spaghetti if you are not careful. Key Brains builds Python applications with the same discipline we apply to every other language — typed, tested, documented, and deployed with proper infrastructure. We have built data pipelines processing millions of records daily, APIs serving thousands of requests per second, and machine learning systems that have been running in production for years.
FastAPI and Django
Our default web framework for Python APIs is FastAPI — async, typed, fast, and with automatic OpenAPI documentation. For applications with significant ORM requirements or admin interfaces, we use Django with Django REST Framework. We select the framework based on the requirements of the specific project, not based on familiarity or habit.
Data pipelines and ETL
We build data pipelines with Apache Airflow for orchestration, pandas and Polars for transformation, and SQLAlchemy for database interaction. Our pipelines are idempotent — they can be re-run without duplicating data. They have monitoring, alerting, and clear failure modes. They are tested. This is rarer than it should be.
Machine learning integration
We integrate machine learning models into production applications — not as experiments, but as reliable software components. We build model serving infrastructure with FastAPI or BentoML, implement A/B testing frameworks for model comparison, monitor model performance and data drift in production, and manage model versioning with MLflow.
Automation and scripting
Python is the right tool for complex automation — API integrations, document processing, report generation, data extraction, and system administration. We build automation systems that are scheduled, monitored, logged, and recoverable from failure. Not scripts that run manually and are forgotten.
Async and concurrency
Python’s asyncio ecosystem has matured significantly. We build async applications with FastAPI and asyncpg where I/O throughput is a requirement, and use multiprocessing for CPU-bound workloads. We understand the Global Interpreter Lock, when it matters, and how to work around it appropriately.