The Most Popular Python Packages in 2026 (and What They Do)
A plain-English breakdown of the Python packages with the highest download counts, and why they're downloaded so much
Our Top 100 Python Packages page tracks live PyPI download data, refreshed on every build. This guide is the companion piece — explaining why the packages at the top are there, since raw download counts alone are misleading (a lot of the biggest numbers come from automated CI/CD installs, not individual developers choosing a tool).
The packages that aren’t really “chosen”
A meaningful share of top downloads are infrastructure packages pulled in as dependencies of other tools — pip, setuptools, certifi, urllib3. These aren’t decisions developers make; they’re plumbing. Our top-packages list deliberately excludes these so the ranking reflects actual tool choices.
HTTP and networking
Requests has been the default HTTP client for over a decade, and its download count reflects it — nearly every Python project that talks to an API depends on it somewhere in its tree. HTTPX is the modern async-capable alternative gaining ground fast, and aiohttp remains the choice for high-concurrency async workloads.
Data and numerical computing
NumPy and Pandas sit near the top of almost every download ranking because they’re foundational — nearly every data science, ML, or scientific Python package depends on at least one of them. If you’re only going to learn two libraries for working with data, these are the two.
Web frameworks
Django and Flask dominate historically, but FastAPI has climbed fast — its combination of async support, automatic API docs, and type-hint-driven validation (via Pydantic) matches how a lot of modern API work actually gets built.
Testing and tooling
pytest is close to universal — it’s the testing framework almost every serious Python project uses regardless of domain. Ruff has seen enormous download growth recently because it replaces several older tools (flake8, isort, and increasingly Black) with a single, much faster Rust-based binary.
AI and LLM tooling
This is the fastest-growing category by download velocity, not just volume. LangChain, OpenAI’s Python SDK, and Pydantic AI have all seen sharp growth as more projects ship LLM-powered features. Worth watching rather than treating as settled — this space changes faster than any other category on the list.
What the numbers don’t tell you
A high download count means a package is widely depended on, not necessarily that it’s the best current choice. Some of the highest-ranked packages are legacy defaults that newer, better alternatives haven’t fully displaced yet (this is common in the packaging tooling space, where uv is rapidly gaining share against older tools despite far fewer historical downloads). Check the live rankings for current numbers, but use this guide — and your own judgement about what a project actually needs — to decide what to reach for.