This document provides an overview of Python and related topics in 3 sentences:
Python is a popular programming language and the document discusses Python projects, libraries, and APIs for tasks like processing PDFs and images. It also briefly mentions using NumPy and Google Cloud Vision API for image processing and deep learning concepts like convolutional neural networks.
This document summarizes a presentation given at PyCon JP 2016 about analyzing baseball data with Python. The presentation introduced the speaker, Shinichi Nakagawa, and discussed using the MLBAM dataset and Python libraries like pandas and matplotlib to analyze pitching data. Specific examples analyzed the pitching of Yu Darvish before and after Tommy John surgery, compared Ichiro Suzuki and Joey Votto's batting, and looked at pitch location data to study the strike zone. The presentation emphasized the usefulness of Python for accessing and analyzing sports data.
The document discusses how to improve application performance using asynchronous and concurrent programming with gevent. It provides examples of patching urllib2 to enable asynchronous requests, spawning multiple requests concurrently using gevent, and limiting concurrent requests using a semaphore to control throughput. It also shows how to run a WSGI server asynchronously using gevent to handle requests without blocking.
This document provides an overview of Python and related topics in 3 sentences:
Python is a popular programming language and the document discusses Python projects, libraries, and APIs for tasks like processing PDFs and images. It also briefly mentions using NumPy and Google Cloud Vision API for image processing and deep learning concepts like convolutional neural networks.
This document summarizes a presentation given at PyCon JP 2016 about analyzing baseball data with Python. The presentation introduced the speaker, Shinichi Nakagawa, and discussed using the MLBAM dataset and Python libraries like pandas and matplotlib to analyze pitching data. Specific examples analyzed the pitching of Yu Darvish before and after Tommy John surgery, compared Ichiro Suzuki and Joey Votto's batting, and looked at pitch location data to study the strike zone. The presentation emphasized the usefulness of Python for accessing and analyzing sports data.
The document discusses how to improve application performance using asynchronous and concurrent programming with gevent. It provides examples of patching urllib2 to enable asynchronous requests, spawning multiple requests concurrently using gevent, and limiting concurrent requests using a semaphore to control throughput. It also shows how to run a WSGI server asynchronously using gevent to handle requests without blocking.
1. Raspberry Piで日本の子供たちに
プログラミングのパッションを
伝えよう!
Let’s use Raspberry Pi
to share our passion of programming
with kids of Japan!
September 21-22, 2016
Antoine Choppin
@japonophile
ショパン アントワン
the World
世界
https://goo.gl/OnFGWj
27. gettext入門
...
print _(“Hello, my name is Kano”)
...
プログラム: myapp-main.py
...
src/myapp-main.py
...
PYPOTFILES: xgettextで
処理するファイルのリスト
#: src/myapp-main.py:36
msgid "Hello, my name is Kano"
msgstr ""
翻訳のテンプレート: messages.pot
#: src/myapp-main.py:36
msgid "Hello, my name is Kano"
msgstr "こんにちは、Kanoと言います。"
日本語翻訳: ja.po
#: src/myapp-main.py:36
msgid "Hello, my name is Kano"
msgstr "Bonjour, je m’appelle Kano"
フランス語翻訳: fr.po
00111010011011110101000100001010111
01000101001010101000101011101010111
01001010100100010101001000101010111
locales/ja/LC_MESSAGES/myapp.mo
00001010111010001010010101010001010
11101010111010010101110011101001101
11101010001010101001000101010010001
locales/fr/LC_MESSAGES/myapp.mo
28. i18n tips
• %s, %dより.formatを使おう
• 位置変数より変数に名前をつけよう
_(“Today is {} {}”)
_(“Today is {month} {day}”)
• 翻訳者へコメントを入れよう
• 文を分離しない:
_(“this is a “) + car.color + _(“car”)
_(“this is a {color} car”).format(color=car.color)
• 文字列にHTMLを含めない
_(“<em>Welcome!</em>”)
u”<em>” + _(“Welcome!”) + u”</em>”
https://www.youtube.com/watch?v=UOOMFGURr5I