RTS Questionnaire · Question 14 of 52 · file: answers/q14.html
Have you worked with Python? If yes, in what context and for how long?
PythonDataBackend
✅ Yes — Python has been a primary language for me for 8+ years (5 years documented in the CV as of 2023, extended by continuous use since).
Technical detail
- 🌐 Web back ends — FastAPI for typed async APIs (Pydantic models, dependency injection, OpenAPI auto-docs), Django (apps, views, models, templates, admin) deployed on Elastic Beanstalk, and Flask with blueprints and Flask-SQLAlchemy for ORM-backed services.
- ☁️ Cloud and automation — AWS Lambda handlers (API Gateway, S3 processing, DynamoDB writes, CloudWatch Events scheduling), boto3 scripting, containerized services, and CI/CD automation glue.
- 📊 Data engineering and science — Pandas/NumPy for wrangling and reporting, Matplotlib/Plotly for visualisation, Airflow DAGs for ETL orchestration, Hive/Presto-era data lake work, and databases from PostgreSQL/MySQL to MongoDB.
- 🤖 AI/ML work — OpenCV for real-time video object detection, NLTK/spaCy for NLP and chatbot flows, scikit-learn-style modelling, and recent LLM work: embedding pipelines, FAISS retrieval, Llama-3 QLoRA fine-tuning, and FastAPI inference endpoints with metrics (loss, EM/F1/ROUGE).
- 🕸️ Web scraping and utilities — BeautifulSoup/Requests parsing, automated document conversion (Word → PDF) and scheduled batch jobs.
🧪 Code quality with pytest unit tests, typing, linting and packaged dependencies so Python services deploy reproducibly to cloud environments.
🧾 CV evidence: CV: 'Python Development: 5 years of experience using Python'; Django/Flask/FastAPI sections; AWS Lambda with Python; OpenCV, NLTK/spaCy, BeautifulSoup; Airflow integrations; 2025 assessment with QLoRA/Llama-3 + FastAPI + metrics.