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Parallel Programming Tools in Python

dc.creatorCornejo-Suárez, Guillermo
dc.creatorMeneses, Esteban
dc.date2019-08-16
dc.date.accessioned2026-05-19T16:50:27Z
dc.date.available2026-05-19T16:50:27Z
dc.identifierhttps://revistas.tec.ac.cr/index.php/memorias/article/view/4523
dc.identifier10.18845/mct.v0i0.4523
dc.identifier.urihttps://hdl.handle.net/2238/18339
dc.descriptionThe Python programming language is widely used in scien- tific computing. Five rankings on the popularity of program- ming languages with different methodologies [1], [2], [3], [4] and [5] list Python in position 1, 4, 2, 3 and 3, respectively. Those rankings considered the number of results returned by web searches, Github projects, questions tagged in StackOver- flow, open job positions, among other variables. As stated in [6], in 2015 approximately 10% of all computer jobs at Texas Advanced Computing Center were Python applications. Also, there exists specific modules for a wide diversity of scientific disciplines. Because of this strong code base and ease of use, Python is commonly the first language learned by engineering, basic and applied science students.es-ES
dc.formatapplication/pdf
dc.languagespa
dc.publisherInstituto Tecnológico de Costa Ricaes-ES
dc.relationhttps://revistas.tec.ac.cr/index.php/memorias/article/view/4523/4094
dc.sourceMemorias de eventos académicos TEC; 2017: III Jornadas Costarricenses de Investigación en Computación e Informáticaes-ES
dc.source9978-9930
dc.source10.18845/mct.2017.0
dc.titleParallel Programming Tools in Pythones-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeArtículo revisado por pareses-ES


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