Modern Python Tooling in 2026: Package Managers, Type Checkers, and Speed
A complete guide to modern Python tooling in 2026: uv, Poetry, and pip; mypy, Pyright, ty, and Pyrefly; plus free-threading, t-strings, and Polars vs Pandas.
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DuckDB in Python: Query CSV, Parquet, and Pandas with SQL
DuckDB in Python turns SQL into a zero-setup analytics engine: query CSV, Parquet, and Pandas DataFrames in-process, join across sources, and add UDFs.
uv Workspaces: Build a Python Monorepo From Scratch
Build a Python monorepo with uv workspaces: one shared lockfile and virtualenv, cross-package imports, per-package builds, and the gotchas I hit doing it.
LangGraph vs CrewAI vs OpenAI Agents SDK: The 2026 Verdict
LangGraph vs CrewAI vs OpenAI Agents SDK compared for 2026: architecture, real code, pricing, and which multi-agent framework to pick for production work.
Python Lazy Imports (PEP 810): The Startup Speedup, Benchmarked
Python lazy imports (PEP 810) land in Python 3.15. I benchmarked boto3, requests and pydantic startup: the real speedup, and how to get most of it today.
msgspec vs Pydantic v2: When the Speed Gap Pays Off
msgspec vs Pydantic v2 in 2026: real code, reported benchmark numbers, where the speed gap actually shows up in a Python API, and how to run both together.
Django-Bolt Review: Rust-Powered Django, FastAPI Speed
Django-Bolt puts Actix and Rust under Django to hit 188K RPS. I dug through the source and benchmarks — where it beats FastAPI, and where the speed evaporates.
Python 3.15: Lazy Imports, frozendict, and Faster Startup
Python 3.15 lands lazy imports, a frozendict builtin, unpacking in comprehensions, and the Tachyon sampling profiler. Here's what changed and what to test.
FastAPI vs Litestar vs Django Ninja: 2026 Verdict
FastAPI vs Litestar vs Django Ninja in 2026: real code, serialization speed, dependency injection, and a clear pick for every kind of Python API project.
DuckDB vs Polars in 2026: Which One for Your Data Pipeline?
DuckDB vs Polars for data engineering in 2026: benchmarks, memory usage, SQL vs DataFrame ergonomics, and when to reach for each. Real numbers, honest verdict.