Written By Mahendra , Dev Rajeev , Nihal

Guided By Chanda Rajkumar

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WHY PYTHON END-TO-END?

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When the Neuro-Morph team chose their language, the answer was deliberate: Python end-to-end. Python sits at a rare intersection — dominant in machine learning, mature in web frameworks, and deeply integrated with container orchestration tooling. A single language across every layer means minimal glue code, zero context-switching overhead, and a unified type system from the API boundary all the way down to the RL training loop.

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TECH STACK OVERVIEW

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API — FastAPI

Async REST endpoints, Pydantic validation, zero-config OpenAPI docs

ML — PyTorch

DQN RL agent training & inference with dynamic computation graphs

QUEUE — Celery + Redis

Async mutation task dispatch, retry logic, result backend

OPS — Docker + K8s

Minimal multi-stage images, Python operators via kopf

OBS — Prometheus + Grafana

Metrics scraping, alerting rules, real-time dashboards

CI/CD — GitHub Actions

Lint → test → build → push in…