diff --git a/dictionaries/library_profile.txt b/dictionaries/library_profile.txt index c4135b5c48..18bc53bd96 100644 --- a/dictionaries/library_profile.txt +++ b/dictionaries/library_profile.txt @@ -1,5 +1,8 @@ -Ghz sublista lineno filename -Czotter \ No newline at end of file +Czotter +formatearse +profile +stats +vs diff --git a/library/profile.po b/library/profile.po index 204294913e..433ada4d2b 100644 --- a/library/profile.po +++ b/library/profile.po @@ -11,15 +11,16 @@ msgstr "" "Project-Id-Version: Python 3.8\n" "Report-Msgid-Bugs-To: \n" "POT-Creation-Date: 2021-03-19 11:16+0100\n" -"PO-Revision-Date: 2020-07-10 22:47-0500\n" -"Last-Translator: Juan Alegría \n" +"PO-Revision-Date: 2021-08-29 09:51+0800\n" +"Last-Translator: Rodrigo Tobar \n" "Language: es_CO\n" "Language-Team: python-doc-es\n" -"Plural-Forms: nplurals=2; plural=(n != 1)\n" +"Plural-Forms: nplurals=2; plural=(n != 1);\n" "MIME-Version: 1.0\n" "Content-Type: text/plain; charset=utf-8\n" "Content-Transfer-Encoding: 8bit\n" "Generated-By: Babel 2.8.0\n" +"X-Generator: Poedit 2.4.2\n" #: ../Doc/library/profile.rst:5 msgid "The Python Profilers" @@ -1012,12 +1013,19 @@ msgid "" "instance holds information related to the function's profile such as how " "long the function took to run, how many times it was called, etc..." msgstr "" +"Este método retorna una instancia de StatsProfile, la cual contiene un mapeo " +"de nombres de función a instancias de FunctionProfile. Cada instancia de " +"FunctionProfile mantiene información relacionada al perfil de la función, " +"como cuánto demoró la función en ejecutarse, cuantas veces fue llamada, " +"etc..." #: ../Doc/library/profile.rst:535 msgid "" "Added the following dataclasses: StatsProfile, FunctionProfile. Added the " "following function: get_stats_profile." msgstr "" +"Añadidas las siguientes clases de datos: StatsProfile, FunctionProfile. " +"Añadida la siguiente función: get_stats_profile." #: ../Doc/library/profile.rst:542 msgid "What Is Deterministic Profiling?" @@ -1190,7 +1198,7 @@ msgstr "" "directamente y nuevamente bajo el generador de perfiles, midiendo el tiempo " "para ambas. Luego calcula la sobrecarga oculta por evento del generador de " "perfiles y la retorna como flotante. Por ejemplo, en un Intel Core i5 de " -"1.8Ghz con Mac OS X y usando time.process_time() de Python como " +"1.8GHz con Mac OS X y usando time.process_time() de Python como " "temporizador, el número mágico es aproximadamente 4.04e-6." #: ../Doc/library/profile.rst:628 pFad - Phonifier reborn

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