The Tools I Use Every Day as a Python Developer in 2025

What’s in my Python toolbox? Here’s the 2025 edition.

The Tools I Use Every Day as a Python Developer in 2025

From smarter editors to AI-assisted coding, here’s the exact tech stack that powers my daily Python workflow — and why I can’t imagine working without it.

When I started writing Python code over a decade ago, my “toolbox” was just a basic text editor, a terminal, and a lot of Stack Overflow tabs. Fast forward to 2025, and my daily workflow looks completely different — faster, smarter, and more automated than I could’ve imagined.

As Python continues to dominate in data science, web development, automation, and AI, the tools around it have exploded in sophistication. But not every shiny new thing makes the cut. I’ve tested countless editors, debuggers, and deployment systems — and the list I’m about to share is the one I use every single day.

Whether you’re a beginner looking to level up your setup or a seasoned dev curious about how others work, here’s my real-world Python developer toolkit for 2025.

1. My Editor: Visual Studio Code (with a Python-First Setup)

Yes, I’ve tried JetBrains’ PyCharm, Sublime Text, and even a Vim-based setup — but VS Code remains my daily driver in 2025. The reason? It’s fast, customizable, and the Python ecosystem around it is now superb.

Key extensions I use daily:

• Python (Microsoft) — For linting, IntelliSense, debugging, and testing.
• Pylance — Blazing-fast type checking and autocompletion.
• Black Formatter — Keeps my code style consistent without thinking about it.
• isort — Automatically organizes imports in seconds.
• Jupyter — Lets me run notebooks directly in VS Code for quick data experiments.

Create a workspace-specific .vscode/settings.json to store formatter, linter, and interpreter configs. This ensures every project opens exactly the way you like it.

2. My Python Environment Manager: uv (Replacing pip + venv)

In 2025, uv has become my go-to package and environment manager. It’s ridiculously fast and makes virtual environments painless.

Why I switched from pip/venv/poetry:

• Speed: Installs packages in seconds thanks to aggressive caching.
• Zero config headaches: No more fiddling with requirements.txt vs pyproject.toml.
• Built-in dependency resolution: Detects and fixes version conflicts automatically.

Example setup for a new project:

uv init myproject 
uv add requests fastapi uvicorn 
uv run python main.py

It’s become the smoothest way to bootstrap a Python project.

3. My AI Pair Programmer: Cursor

Yes, I use GitHub Copilot — but I’ve found Cursor to be a game-changer in 2025. It’s an AI-powered code editor based on VS Code, but optimized for deep code understanding.

Why it’s in my daily stack:

• Context-aware coding: It reads my whole repo to give accurate completions.
• Inline code edits: I can highlight a block of code and tell it to “optimize for speed” — and it actually does.
• Multi-file reasoning: Great for refactoring across modules.

I still write my own logic, but Cursor speeds up repetitive patterns, boilerplate generation, and even unit test creation.

4. My Debugging & Profiling Tool: PySnooper + PyInstrument

Debugging has always been a mix of print() statements and breakpoints — but in 2025, I rely heavily on PySnooper and PyInstrument.

• PySnooper — Lets me add @pysnooper.snoop() above a function and instantly see variable changes and execution flow in the terminal.
• PyInstrument — A beautiful profiler that shows exactly where your code spends time, with an interactive web view.

Instead of guessing where the bottleneck is, I can now see it in seconds.

5. My Testing Stack: pytest + Hypothesis

I used to write tests only for critical code. Now I write them for everything, because pytest makes it effortless — and Hypothesis generates test cases I wouldn’t think of.

Example:

from hypothesis import given, strategies as st 
 
@given(st.lists(st.integers())) 
def test_sort_property(nums): 
    assert sorted(nums) == sorted(sorted(nums))

This approach has saved me from some incredibly sneaky bugs, especially in edge cases I’d never manually test.

6. My API Development Setup: FastAPI + HTTPie

FastAPI has been my go-to Python web framework for a while — and it’s only gotten better in 2025.

Paired with HTTPie, I can test APIs right from the terminal in a clean, readable format:

http GET http://localhost:8000/items/1

The combo of type hints + automatic docs + terminal testing means I can go from idea to working API in hours, not days.

7. My Automation Sidekick: Ruff

In 2025, Ruff has replaced flake8 + pylint + isort for me. It’s a single, lightning-fast linter and formatter that works on any codebase.

• One tool to rule them all: Linting, import sorting, and some formatting in milliseconds.
• CI-friendly: Easy to run in GitHub Actions for every PR.

ruff check . 
ruff format .

It’s my “code hygiene” command before every commit.

8. My Deployment & Hosting: Fly.io + Docker

While AWS and GCP still have their place, I love Fly.io for deploying Python apps with minimal fuss.

• Global edge hosting: Low latency for users worldwide.
• Docker-first approach: Works with my existing containerized workflows.

My FastAPI apps usually go live with just:

fly launch 
fly deploy

No complicated infrastructure scripts — just deploy and scale.

9. My Knowledge Hub: Obsidian + GitHub Gists

Not all developer tools are code editors. I keep all my Python snippets, setup guides, and personal notes in Obsidian, synced with GitHub Gists for easy sharing.

This means I can:

• Reuse utility scripts instantly.
• Maintain a personal “Python cookbook.”
• Search my own past solutions instead of Googling for the same bug twice.

Conclusion

In 2025, being a Python developer isn’t just about writing code — it’s about building a workflow that keeps you fast, consistent, and happy.

These tools didn’t just make me more productive — they made coding fun again. I spend less time fighting my setup and more time solving real problems.

If you take anything from this list, let it be this: don’t just follow trends. Experiment, refine, and build your own ultimate toolbox.

The right tools won’t write your code for you — but they’ll make sure nothing stands in your way when you do.