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Revenge of the Types: 型の復讐 - Qiita
Deleted articles cannot be recovered. Draft of this article would be also deleted. Are you sure you want to delete this article? 本稿は Python に型アノテーションを追加するという提案が行われたときに起こった Python コミュニティの議論の後、2014年8月24日 (日) に Armin Ronacher (@mitsuhiko) 氏によって書かれた記事の翻訳です。 Revenge of the Types Revenge of the Types by Armin Ronacher : Python (REDDIT) Revenge of the Types | Hacker News Python 3.5 で導入を検討している型アノテーションについて
C++ Has Become More Pythonic
C++ has changed a lot in recent years. The last two revisions, C++11 and C++14, introduce so many new features that, in the words of Bjarne Stroustrup, “It feels like a new language.” It’s true. Modern C++ lends itself to a whole new style of programming – and I couldn’t help noticing it has more of a Python flavor. Ranged-based for loops, type deduction, vector and map initializers, lambda expres
Boost python not found when building cv_bridge under OSX
I am having the problem that cv_bridge can't find my boost libraries although it must have found them for the packages before when installing hydro on OSX. When I look into /usr/local/include I can see all the boost files and folders, also python. What's the problem here? When I print the output of my boost libraries it says none. CMAkeLists.txt: cmake_minimum_required(VERSION 2.8) project(cv_brid
Why is Jython much slower than CPython, despite the JVM's advances?
No flame wars please. I am admittedly no fan of Java, but I consider the JVM to be a fairly decent and well-optimized virtual machine. It's JIT-enabled and very close to the common denominator of the prevalent CPU architectures. I'd assume that the CPython runtime would be farther from the metal than a corresponding JVM-based runtime. If my assumptions are correct, could someone explain to me why
Python製デプロイツール Fabricを初めて使う際に役立つTips
by @dekokun on 2013/04/07 19:30 Tagged as: Python, Fabric, デプロイツール. 2013/04/09 追記 意外と反響があるようなので、Tips追加しました。 2013/05/10 追記 並列実行について調べたのでついでに追記 「次のプロダクトはシンプルなデプロイツールだと噂のCinnamonでも使ってみるかー」と言っていたら、「Cinnamonは使ってるユーザ数が少なそうだし同様のことが行えるFabricのほうがいいんじゃないですかね。」というツッコミをいただき、今回はPerlのプロジェクトでもないためFabricを使用することにしました。 初めて触るFabric、やはり初学者にはいろいろとよくわからない部分があったため、はまって解決したことや便利なTipsなどをつらつらと列挙していきます。 なお、以下情報はPython2.7及びF
Numba vs. Cython: Take 2 | Pythonic Perambulations
Last summer I wrote a post comparing the performance of Numba and Cython for optimizing array-based computation. Since posting, the page has received thousands of hits, and resulted in a number of interesting discussions. But in the meantime, the Numba package has come a long way both in its interface and its performance. Here I want to revisit those timing comparisons with a more recent Numba rel
Locust Documentation — Locust 2.39.1 documentation
If you have questions or get stuck, feel free to reach out to us at support@locust.cloud. Other functionalities
Anti-Patterns in Python Programming - Constantine Lignos
Note (9/1/2019): The advice here is somewhat out of date at this point. An update is coming someday to change the examples to reflect Python 3 and modern performance characteristics of iteration. This page is a collection of the most unfortunate but occasionally subtle issues I’ve seen in code written by students new to writing Python. It’s written to help students get past the phase of writing ug
Parallelism and Concurrency with Python
Presented May 2014. For more information on PyParallel, see: https://speakerdeck.com/trent/pyparallel-how-we-removed-the-gil-and-exploited-all-cores …
Introducing Pyston: an upcoming, JIT-based Python implementation
Introducing Pyston: an upcoming, JIT-based Python implementation Hello everyone, I’m very excited to announce Pyston, a new open-source implementation of Python, currently under development at Dropbox. The goal of the project is to produce a high-performance Python implementation that can push Python into domains dominated by traditional systems languages like C++. Here at Dropbox, we love Python
Gregory Szorc's Digital Home | Why do Projects Support old Python Releases
I see a number of open source projects supporting old versions of Python. Mercurial supports 2.4, for example. I have to ask: why do projects continue to support old Python releases? Consider: Python 2.4 was last released on December 19, 2008 and there will be no more releases of Python 2.4. Python 2.5 was last released on May 26, 2011 and there will be no more releases of Python 2.5. Python 2.6 w
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GitHub - vitessio/vitess: Vitess is a database clustering system for horizontal scaling of MySQL.
The Python API and C++
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talks/state-of-jython-2014.md at master · jimbaker/talks
GitHub - GoogleCloudPlatform/ipython-soccer-predictions: Sample iPython notebook with soccer predictions
Luban: a generic “language” for creating user interface — luban v0.2 documentation
Python 3.4 から標準ライブラリに入る Enum 型が今からでも便利 - Qiita
Why is Python written in C and not in C++?