We're sorry but this page doesn't work properly without JavaScript enabled. Please enable it to continue.
Feedback

Python and Async programming

Formale Metadaten

Titel
Python and Async programming
Serientitel
Teil
6
Anzahl der Teile
169
Autor
Lizenz
CC-Namensnennung - keine kommerzielle Nutzung - Weitergabe unter gleichen Bedingungen 3.0 Unported:
Sie dürfen das Werk bzw. den Inhalt zu jedem legalen und nicht-kommerziellen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen und das Werk bzw. diesen Inhalt auch in veränderter Form nur unter den Bedingungen dieser Lizenz weitergeben
Identifikatoren
Herausgeber
Erscheinungsjahr
Sprache

Inhaltliche Metadaten

Fachgebiet
Genre
Abstract
Nicolas Lara - Python and Async programming How does the experienced python programmer fair when faced with python's "new" way of doing async programming for the first time? This talk details the different ways python provides for attacking the problem of asynchronous programming and focuses on the best practices for the future (as of python 3.4 and 3.5) ----- How does the experienced python programmer fair when faced with python's "new" way of doing async programing in for the first time? Do we all know how and when to use Futures, yield from, asyncio, coroutines, the async and await keywords, eventloops, and others? A lot has changed in recent versions of Python when it comes to async programming, concurrency, and parallelism. We still have very different ways of approaching the problem in each version, but they are finally (as of python 3.4/3.5) converging to a standard. This talk explores, from the perspective of an experienced python programmer with little to no experience in async programming, what the "one obvious way" to do async programming in Python is supposed to be. It does so but analysing examples of different categories of async problems we may want to solve and what the correct way to solve them with the latest versions of Python would be (along with the trade offs of different approaches). The examples include generic CPU-bound problems, IO-bound problems, and "both-bound" problems; along with common tasks as building a simple server, scraping, deferring a web response, and traversing graphs. When useful, I compare the solutions with the approach we would take in languages that have been design for- and are known to be good at async programming like Javascript and Go.