Aleksandr Babarika

Functional staging

A working portfolio tracker for individual and shared household accounts. It records multi-currency transactions or imports them from CSV, values holdings from live prices, and reports P&L, time-weighted returns, risk against a chosen benchmark, and UK capital gains.

FastAPI services run the gateway, ledger, risk analytics and broker sync. Rust services handle quotes, portfolio calculations and UK tax matching. The public API uses OpenAPI; the Rust services are reached over gRPC using protobuf.

Pre-release alpha

A free, open-source research workspace you host yourself. You write a strategy in Python, backtest it, then check whether the result survives trading costs, an unseen holdout period and small parameter changes. Each run is identified by a hash of its code, parameters, data version, engine version and random seed.

1,173 backend and 1,052 frontend tests passing. The first tagged release is waiting on clean-machine checks of the amd64 and arm64 images.

Live on the web, app stores next

A minimal puzzle game, now live on the web. A 15-lesson tutorial of 22 levels teaches the syntax. Then courses of nine holes, and a daily puzzle that is the same for everyone, ask for the shortest pattern that matches one list of strings and none of another. One TypeScript codebase ships as a static site and, through Capacitor, as iOS and Android apps.

Live at regex-golf.babarika.dev, with a new daily puzzle every day. The tutorial, three courses and four weeks of daily puzzles are signed off. On the web build, Lighthouse scores 100 in all four categories on mobile and desktop, and axe-core finds no WCAG 2.2 AA violations on any screen.

Complete and maintained

A Rust terminal game built around a pure poker engine, local bots, live equity estimates, and a networked client/server mode.

Includes the game engine, terminal UI, bots, equity estimates and client/server play. The image below is an illustration, not a product screenshot.

Experimental, no validated result yet

The pipeline uses a conditional U-Net to predict a pitch-shifted mel-spectrogram, then HiFi-GAN turns it back into audio. Demucs can separate vocals before processing.

The pipeline is implemented, but training and model comparisons are still in progress. The diagram shows the intended signal flow.