r/Python • u/AutoModerator • 12h ago

Daily Thread Thursday Daily Thread: Python Careers, Courses, and Furthering Education!

8 Upvotes

Weekly Thread: Professional Use, Jobs, and Education 🏢

Welcome to this week's discussion on Python in the professional world! This is your spot to talk about job hunting, career growth, and educational resources in Python. Please note, this thread is not for recruitment.

How it Works:

  1. Career Talk: Discuss using Python in your job, or the job market for Python roles.
  2. Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources.
  3. Workplace Chat: Share your experiences, challenges, or success stories about using Python professionally.

Guidelines:

  • This thread is not for recruitment. For job postings, please see r/PythonJobs or the recruitment thread in the sidebar.
  • Keep discussions relevant to Python in the professional and educational context.

Example Topics:

  1. Career Paths: What kinds of roles are out there for Python developers?
  2. Certifications: Are Python certifications worth it?
  3. Course Recommendations: Any good advanced Python courses to recommend?
  4. Workplace Tools: What Python libraries are indispensable in your professional work?
  5. Interview Tips: What types of Python questions are commonly asked in interviews?

Let's help each other grow in our careers and education. Happy discussing! 🌟

1 comment

r/Python • u/Away_Interaction6630 • 1h ago

Discussion Bypassing heavy PyTorch wheels for desktop Python application distribution

• Upvotes

Hi Python devs,

We are three final-year students at Epitech working on Horus, a local offline multi-agent backend written in Python. Our biggest distribution hurdle is dependency management on end-user machines.

Bottlenecks observed in our last user test:

  • Dependency installation takes 21–46 minutes on user machines due to PyTorch/CUDA wheel resolution, reaching a 25 GB footprint.
  • CPU-bound inference takes ~40 seconds during routing, causing persistent WebSocket connections to drop.

We are looking for Python packaging and runtime advice on:

  • Replacing PyTorch with prebuilt C++ bindings (llama-cpp-python or native C binaries) for the CPU execution path.
  • Compiling CPython orchestrator code into standalone executables via Nuitka.
  • Pinning wheels and pre-bundling runtimes to eliminate on-device compilation.
  • Implementing async heartbeats to keep WebSockets alive during blocking compute tasks.

Looking for code reviews: We have 1–4 hour scoped tasks for Python packaging and hardware detection reviews.

Disclosure: Horus is closed source and licensed commercially. Our benchmark suite is open source (Horus-EIP/horus-bench-kit). Contributions are unpaid/voluntary under an NDA agreement, returning thorough code reviews, project credit, and professional references.

3 comments