By setting virtualenvs.in-project true , configuring your .vscode/settings.json , and understanding how to manually select the interpreter, you transform this sporadic nightmare into a reliable, automated workflow.
poetry config virtualenvs.in-project true This creates a .venv folder inside your project directory immediately after your next poetry install . VS Code always detects a .venv folder. # Delete the old global env (optional but clean) poetry env remove --all Reinstall dependencies (creates .venv locally) poetry install pylance missing imports poetry hot
Don't. But if you must: Install Poetry in your Conda base, then use poetry config virtualenvs.create false to force Poetry to use the current Conda environment. Then point Pylance to the Conda environment's Python binary. Part 5: Automating This For Your Team You don’t want every developer on your team to suffer this pain. Commit the solution to Git. 5.1 Commit the Config Files git add .vscode/settings.json git add poetry.toml # this stores the "virtualenvs.in-project = true" config git commit -m "Fix Pylance integration with Poetry" 5.2 Use .env for Environment Variables If your Poetry environment requires environment variables for Pylance to resolve imports (e.g., PYTHONPATH modifications), create a .env file in your project root: By setting virtualenvs
[tool.poetry] name = "myproject" packages = [{include = "myproject", from = "src"}] Then, update your settings.json as shown above with python.analysis.extraPaths . If you have a client/ and server/ folder, each with its own poetry.lock : # Delete the old global env (optional but
Introduction: The Perfect Storm of Modern Python Development You’ve embraced modern Python development. You use Poetry for dependency management and virtual environments because you’re tired of the requirements.txt chaos. You use VS Code with Pylance because you want blazing-fast type checking and autocompletion.