@@ -19,7 +19,7 @@ msgid ""
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msgstr ""
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"Project-Id-Version : Python 3.7\n "
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"Report-Msgid-Bugs-To : \n "
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- "POT-Creation-Date : 2019-01-01 10:14 +0900\n "
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+ "POT-Creation-Date : 2019-02-03 10:33 +0900\n "
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"PO-Revision-Date : 2017-02-16 23:06+0000\n "
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"Last-Translator : tomo, 2017\n "
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"Language-Team : Japanese (https://www.transifex.com/python-doc/teams/5390/ja/)\n "
@@ -2324,3 +2324,21 @@ msgid ""
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"Alternatively, inputs can be rounded upon creation using the "
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":meth:`Context.create_decimal` method:"
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msgstr "もしくは、入力を :meth:`Context.create_decimal` を使って生成時に丸めてしまうこともできます:"
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+
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+ #: ../../library/decimal.rst:2119
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+ msgid "Q. Is the CPython implementation fast for large numbers?"
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+ msgstr ""
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+
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+ #: ../../library/decimal.rst:2121
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+ msgid ""
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+ "A. Yes. In the CPython and PyPy3 implementations, the C/CFFI versions of "
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+ "the decimal module integrate the high speed `libmpdec "
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+ "<https://www.bytereef.org/mpdecimal/doc/libmpdec/index.html>`_ library for "
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+ "arbitrary precision correctly-rounded decimal floating point arithmetic. "
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+ "``libmpdec`` uses `Karatsuba multiplication "
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+ "<https://en.wikipedia.org/wiki/Karatsuba_algorithm>`_ for medium-sized "
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+ "numbers and the `Number Theoretic Transform "
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+ "<https://en.wikipedia.org/wiki/Discrete_Fourier_transform_(general)#Number-"
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+ "theoretic_transform>`_ for very large numbers. However, to realize this "
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+ "performance gain, the context needs to be set for unrounded calculations."
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+ msgstr ""
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