We are interested in the following topics

• Hot Prod Python

  • Using Free-Threading Python, nogil and synchronization difficulties in production.
  • Python JIT for application acceleration.
  • Astral.sh and Python infrastructure in Rust.
  • Copilot and other AI assistants for Python development.
  • LLM Agents.
  • Complex layered applications.
• Core Python

  • Python under the hood.
  • Basic Python concepts with simple examples.
  • CPython, PyPy, GraalPy, Cython, and other interpreters.
  • Subinterpreters and immutable data structures.
  • Language novelties.
  • Internals of the language elements.
• Development practices

  • Clean code, SOLID. Practices of "correct" OOP.
  • Not OOP alone: functional and other approaches to code writing.
  • Code review.
  • Approaches to development and branching in CVS (Trunk-Based Development).
  • Linters: code complexity, naming, object relationships, layers, etc.
  • Troubleshooting.
  • Python’s interaction with other technologies.
• Libraries and tools

  • Python standard library.
  • Own and popular libraries and frameworks.
  • Advanced use of libraries (e.g. SQLAlchemy).
  • Developer tools.
  • Performance and optimisation.
• Testing and security

  • Basic concepts of testing in Python.
  • Libraries and tools for testing.
  • Testing web applications in Python.
  • Performance testing.
  • Testing asynchronous code in Python.
  • Security testing and vulnerability analysis of Python applications.
  • Secure development: technologies, tools and practices.
  • Best practices and work optimization.
• Backend

  • Web frameworks.
  • Microservices architecture.
  • Development of internal and external APIs.
  • ORM, databases and interaction with them.
  • Web application caching and optimisation.
  • Observability: logging, monitoring and tracing.
  • Application configuration.
  • Django's ecosystem.
  • Solving ML/DS/data engineering application problems.
• Architecture and patterns

  • Different architectural approaches and patterns in practice.
  • System architecture basics for developers.
  • Architecture types.
  • Design and development approaches.
  • Commonly known patterns and design patterns in solving real-world problems.
  • Helpful tools and design life hacks.
  • Extensive use of approaches for large applications in Python (e.g., CQRS, DDD).
• Fundamentals

  • Back to Basics.
  • Ecosystem and new features overview.
  • Utilizing AI / Code Completion for enterprise level application development.
  • Development infrastructure.
  • Pythonic Way.
• Other

  • Using Python in hardware.
  • GUI in Python.
  • Desktop application development.
  • Application of Python in solving scientific and non-standard problems, as well as in new fields.
  • Python and other languages: interop, performance, safety.
  • PyScript, running Python directly in HTML.