We spent three weeks testing Cursor, GitHub Copilot, Windsurf, Tabnine, and Claude Code across real Python work — Django apps, FastAPI services, data science notebooks, and ML training scripts. Here's what actually separated them, plus a mistake on our own page we only caught doing this writeup.
The numbers that mattered
Multi-file awareness is where Python tooling actually earns its price tag. We renamed a model field across a mid-sized Django REST Framework project — about 40 models, 80+ endpoints — and asked each tool's agent mode to propagate the change everywhere it needed to go (serializer, view, test, migration). Cursor's composer got all 14 affected files in one action. Windsurf's Cascade caught 11. Copilot's Edits caught 9.
Type hints told a similar story under mypy --strict: asked to annotate an untyped function with the kind of generics Python 3.12+ actually uses (TypeVar, ParamSpec, Protocol), Cursor's suggestions passed strict mode about 90% of the time. Copilot's passed about 75%.
Copilot pulled ahead somewhere else entirely: notebooks. Building an exploratory pandas/numpy workflow from scratch, its suggestions were correct about 85% of the time, including the kind of context-aware groupby/merge calls that only make sense if the tool remembers what you did three cells ago. That's genuinely its strongest Python surface, and nothing else we tested came close in a notebook specifically.
Claude Code is the odd one out because it isn't an autocomplete tool at all — no inline suggestions, period. Where it earned its place: "write a comprehensive test suite for the authentication module" produced 47 tests with real fixtures and mocking, three of which failed on the first run, and it fixed all three without being asked. For anything that's really a 30-minute task rather than a completion, that's a different category of useful.
The mistake we found writing this
This page has said Windsurf Pro costs $15/month since March. It's actually been $20/month since Cognition raised it on 6 July — three months of us quoting a stale number, on a page specifically about which tool is worth paying for. Corrected it, along with an unrelated bit of staleness: we were still calling Claude Code's underlying model "the 3.5/4 family," which is two generations behind what's actually running today.
Small thing, but it's the kind of error that erodes the exact trust a comparison page is supposed to earn.
Full write-up, benchmarks, and the role-by-role breakdown (web dev / data science / ML / CLI / enterprise):
https://devtoolsreview.com/best-for/best-ai-coding-tools-python/
Disclosure: no confirmed affiliate or commission relationship with any of the five vendors at the time of writing.
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