GitHub - astral-sh/ruff: An extremely fast Python linter and code formatter, written in Rust.
Docs | Playground An extremely fast Python linter and code formatter, written in Rust. Linting the CPython codebase from scratch. ⚡️ 10-100x faster than existing linters (like Flake8) and formatters (like Black) 🐍 Installable via pip 🛠️ pyproject.toml support 🤝 Python 3.12 compatibility ⚖️ Drop-in parity with Flake8, isort, and Black 📦 Built-in caching, to avoid re-analyzing unchanged files 🔧
GitHub - bloomberg/memray: Memray is a memory profiler for Python
Memray is a memory profiler for Python. It can track memory allocations in Python code, in native extension modules, and in the Python interpreter itself. It can generate several different types of reports to help you analyze the captured memory usage data. While commonly used as a CLI tool, it can also be used as a library to perform more fine-grained profiling tasks. Notable features: 🕵️♀️ Tra
Processing large JSON files in Python without running out of memory
Processing large JSON files in Python without running out of memory by Itamar Turner-Trauring Last updated 06 Jan 2023, originally created 14 Mar 2022 If you need to process a large JSON file in Python, it’s very easy to run out of memory. Even if the raw data fits in memory, the Python representation can increase memory usage even more. And that means either slow processing, as your program swaps
GitHub - facebookresearch/Kats: Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change point
Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis. Time series analysis is an essential component of Data Science and Engineering work at industry, from understanding the key statistics and characteristics, detecting regressions and anomalies, to forecasting future trends. Kats aims to provide the one-stop shop fo
GitHub - Nuitka/Nuitka: Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or ex
Nuitka is the Python compiler. It is written in Python. It is a seamless replacement or extension to the Python interpreter and compiles every construct that Python 2 (2.6, 2.7) and Python 3 (3.4 - 3.11) have, when itself run with that Python version. It then executes uncompiled code and compiled code together in an extremely compatible manner. You can use all Python library modules and all extens
How to make an awesome Python package
If you are like me, every once in a while you write a useful python utility and want to share it with your colleagues. The best way to do this is to make a package: it easy to install and saves from copy-pasting. If you are like me, you might be thinking that creating packages is a real headache. Well, that's not the case anymore. And I am going to prove it with this step-by-step guide. Just three
pipとpipenvとpoetryの技術的・歴史的背景とその展望 - Stimulator
- はじめに - Pythonのパッケージ管理ツールは、長らく乱世にあると言える。 特にpip、pipenv、poetryというツールの登場シーン前後では、多くの変革がもたらされた。 本記事は、Pythonパッケージ管理ツールであるpip、pipenv、poetryの3つに着目し、それぞれのツールに対してフラットな背景、技術的な説明を示しながら、所属企業内にてpoetry移行大臣として1年活動した上での経験、移行の意図について綴り、今後のPythonパッケージ管理の展望について妄想するものである。 注意：本記事はPythonパッケージ管理のベストプラクティスを主張する記事ではありません。背景を理解し自らの開発環境や状態に応じて適切に技術選定できるソフトウェアエンジニアこそ良いソフトウェアエンジニアであると筆者は考えています。 重要なポイントのみ把握したい場合は、各章の最後のまとめを読んで頂
GitHub - thebjorn/pydeps: Python Module Dependency graphs
positional arguments: fname filename optional arguments: -h, --help show this help message and exit --debug turn on all the show and verbose options (mainly for debugging pydeps itself) --config FILE specify config file --no-config disable processing of config files --version print pydeps version -L LOG, --log LOG set log-level to one of CRITICAL, ERROR, WARNING, INFO, DEBUG, NOTSET. --find-packag
今から始める型安全 Python / Start Python Type Hints
#stapy https://speakerdeck.com/yamitzky/mastering-type-safety-in-python-3-dot-9-era の内容を加筆して削ったものです
Welcoming Google as a Visionary Sponsor of the PSF
Our top sponsors—companies who step forward to make the biggest investment in Python and its community—not only use Python for their own internal development, but also offer Python as a crucial part of the products they offer to their own customers. That is certainly true of Google, the Python Software Foundation’s first Visionary Sponsor. Google's donations and sponsorship funds will be used to s
Web Scraping with Python: Everything you need to know (2022)
Introduction: In this post, which can be read as a follow-up to our guide about web scraping without getting blocked, we will cover almost all of the tools to do web scraping in Python. We will go from the basic to advanced ones, covering the pros and cons of each. Of course, we won't be able to cover every aspect of every tool we discuss, but this post should give you a good idea of what each too
Pattern matching accepted for Python [LWN.net]
The Python steering council has, after some discussion, accepted the controversial proposal to add a pattern-matching primitive to the language. "We acknowledge that Pattern Matching is an extensive change to Python and that reaching consensus across the entire community is close to impossible. Different people have reservations or concerns around different aspects of the semantics and the syntax
Home — Spyder IDE
Spyder is a free and open source scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. It features a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabiliti
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GitHub - nottheswimmer/pytago: A source-to-source transpiler for Python to Go translation
GitHub - capitalone/DataProfiler: What's in your data? Extract schema, statistics and entities from datasets
GitHub - Pytlicek/sheet2dict: Simple XLSX and CSV to dictionary converter
GitHub - gruns/icecream: 🍦 Never use print() to debug again.
GitHub - pfnet/pysen: Python linting made easy. Also a casual yet honorific way to address individuals who have entered an organization prior to you.
GitHub - replicate/keepsake: Version control for machine learning
GitHub - nipunsadvilkar/pySBD: 🐍💯pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.
