GitHub - prompt-toolkit/pyvim: Pure Python Vim clone.You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
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アブストラクト https://pycon.jp/2015/ja/schedule/presentation/53/ 公演ビデオ https://youtu.be/7SNVx3YzY5E?t=1166
Bokken - Home Page
Beautiful An intuitive and user friendly user interace for binary analysis loaded with plenty of features and visual aids View details » Free Open source and free! Get it now and use and modify it as it better fits you View details » Binary analysis. Powerful features. Supported PE, Elf and mach0 file formats ARM, i386 and x86-64 architectures Call/syscall recognition Code/Data Cross-references An
GitHub - billpmurphy/hask: Haskell language features and standard libraries in pure Python.
Hask is a pure-Python, zero-dependencies library that mimics most of the core language tools from Haskell, including: Full Hindley-Milner type system (with typeclasses) that will typecheck any function decorated with a Hask type signature Easy creation of new algebraic data types and new typeclasses, with Haskell-like syntax Pattern matching with case expressions Automagical function currying/part
Why MIT switched from Scheme to Python - 月ã®å¡µ
MIT ã®è¨ˆç®—機科å¦ã®å…¥é–€ã‚³ãƒ¼ã‚¹ 6.001 ã¯ãªãœ SICP + Scheme ã‹ã‚‰ Python ã«ç§»è¡Œã—ãŸã‹ã¨ã„ã†è©±ã€‚ 原文: Why MIT switched from Scheme to Python | Wisdom and WonderConstanza æ°ãŒ Sussman æ°ã« MIT ãŒãªãœãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°å…¥é–€ã‚³ãƒ¼ã‚¹ 6.001 㧠Scheme を使ã†ã®ã‚’ã‚„ã‚ãŸã®ã‹ã‚’å°‹ããŸã€‚ã“ã‚Œã¯å®çŸ³ã ã£ãŸã€‚ Sussman æ°ã¯ã“ã†ç”ãˆãŸã€‚ãã®ç†ç”±ã¯ 1980 年代ã®å·¥å¦ãŒ 90 年代ä¸ç›¤ã‹ã‚‰ 2000 ã¾ã§ã®ãã‚Œã¨ã¯ç•°ãªã£ãŸã‹ã‚‰ã§ã‚る。 1980 年代ã«ãŠã„ã¦ã¯ã€ã‚ˆã„プãƒã‚°ãƒ©ãƒžã¯è€ƒãˆã‚‹ã“ã¨ã«å¤šãã®æ™‚間を使ã„ã€ãã‚Œã‹ã‚‰å‹•ãã§ã‚ã‚ã†ã¨è‡ªèº«ãŒè€ƒãˆã‚‹ç°¡æ½”ãªãƒ—ãƒã‚°ãƒ©ãƒ を書ã„ãŸã€‚コードã¯ã‚«ãƒŠãƒ¢ãƒŽã«è¿‘ã„ã¨ã“ã‚ã§å‹•ãã€ä¸Šã‹ã‚‰ä¸‹ã¾ã§ã™ã¹ã¦ç†è§£ã™ã‚‹ã“ã¨ãŒã§ããŸã€‚ Scheme ã§æ›¸ã‹ã‚Œã¦ã„ã¦ã‚‚ã€ã 。抵
Four MLs (and a Python)
I wrote a small command-line text processing program in four different ML-derived languages, to try to get a feel for how they compare in terms of syntax, library, and build-run cycles. ML is a family of functional programming languages that have grown up during the past 40 years and more, with strong static typing, type inference, and eager evaluation. I tried out Standard ML, OCaml, Yeti, and F#
Pythonista for iPhone, iPad, and iPod touch on the iTunes App Store
Description Pythonista brings the Zen of Python™ to your iPad or iPhone. Create interactive experiments and prototypes using multi-touch, animations, and sound – or just use the interactive prompt as a powerful calculator. Pythonista is also a great tool for learning Python – The interactive prompt helps you explore the language with code completion, the entire documentation is accessible right wi
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Locust.io
An open source load testing tool. Define user behaviour with Python code, and swarm your system with millions of simultaneous users. Tweet Follow @locustio Define user behaviour in code No need for clunky UIs or bloated XML. Just plain code. Distributed & Scalable Locust supports running load tests distributed over multiple machines, and can therefore be used to simulate millions of simultaneous u
IPython(Anaconda)ã¨IJuliaãŒå‡„ã™ãŽã‚‹ä»¶ - アドファイブ日記（ミラー版）
先日Juliaã§ãƒ‡ãƒ¼ã‚¿åˆ†æžç’°å¢ƒã‚’インストールã™ã‚‹è©±ã‚’書ãã¾ã—ãŸãŒã€ã‚‚ã£ã¨ã„ã„ã‚„ã¤ãŒã‚ã£ãŸã®ã§ã”紹介ã—ã¾ã™ã€‚(IJuliaã§ã™ã€‚実ã¯juliaã®ãƒ›ãƒ¼ãƒ ページã«ãã£ãり掲載ã•ã‚Œã¦ã‚‹ã®ã§ã™ãŒå…ˆæ—¥ã¯ãªãœã‹ã‚¹ãƒ«ãƒ¼ã—ã¦ã—ã¾ã£ã¦ãŸï¼‰ å…ˆã®è¨˜äº‹ã®æœ€å¾Œã«ã€ŒPython(Pandas/Scipy/Sklrnç‰ã‚’使ã†ç’°å¢ƒ)ã¨Juliaã§æ¯”較ã—ãªãŒã‚‰ä»Šå¾Œã®é“å…·ç«‹ã¦ã‚’æ•´ãˆãŸã„ã€ã¿ãŸã„ãªã“ã¨æ›¸ãã¾ã—ãŸãŒã€åˆ¥ã«ã©ã£ã¡ã‹ã«æ±ºã‚ãªãã¦ã‚‚両方åŒæ™‚ã«ã¤ã‹ãˆã¡ã‚ƒã†IPython(Anaconda)ã¨ã„ã†ç„¡æ–™ã®ã™ã”ã„ツール（オプション機能ã¯æœ‰æ–™ã§ã™ãŒã€ãã®æœ‰æ–™ã‚ªãƒ—ションãŒã“ã‚Œã¾ãŸå‡„ã„）ãŒã‚ã‚Šã¾ã—ãŸã€‚ 開発元やライセンスãªã©ï¼ˆãã†ã„ã†ã®ã¯ã„ã„ã‹ã‚‰æ—©ãインストールã—ãŸã„人ã¯æ¬¡ç¯€ã¸ï¼‰ IPythonã¨ã„ã†ã®ã¯ã€ŒPythonã«ãƒ‡ãƒ¼ã‚¿åˆ†æžç³»ã®ãƒ©ã‚¤ãƒ–ラリをã”ã£ãりプレインストールã—ã¦ã‹ã¤Mathematicaã¿ãŸã„ãªãƒŽãƒ¼ãƒˆãƒ–ック型ã®GUIã‚’ã¤
第2回 Tokyo.SciPy ã§ã€Œæ•°å¼ã‚’ numpy ã«è½ã¨ã—ã“むコツã€ã‚’発表ã—ã¦ãã¾ã—㟠- 木曜ä¸è¶³
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