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Изворен канал @pythonotes · Post #272 · 14 јул.

Наверняка у многих возникло желание потестить отправку сообщений, но Redis не установлен и вообще непонятно как с ним быть. На самом деле запустить его очень просто. 🔸 Для Windows, качаем архив, запускаем redis-server.exe 🔸 Для Linux несколько команд 🔸 Если есть Docker, то еще проще docker run --rm -p 6379:6379 redis Всё, можно экспериментировать! ______________________ А еще с сервером можно поиграть в пинг-понг > redis-cli ping PONG #tricks#libs#linux

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Пребарај: #cartopy

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djangoproject

@djangoproject · Post #423 · 26.08.2017 г., 08:39

http://scitools.org.uk/iris/docs/latest/userguide/index.html Iris seeks to provide a powerful, easy to use, and community-driven Python library for analysing and visualising #meteorological and #oceanographic data sets. With Iris you can: Use a single #API to work on your data, irrespective of its original format. Read and write (CF-)netCDF, GRIB, and PP files. Easily produce graphs and maps via integration with #matplotlib and #cartopy.

djangoproject

@djangoproject · Post #424 · 26.08.2017 г., 08:43

http://scitools.org.uk/cartopy/docs/latest/index.html Cartopy is a Python package designed to make drawing maps for data analysis and visualisation as easy as possible. #Cartopy makes use of the powerful #PROJ.4, #numpy and #shapely libraries and has a simple and intuitive drawing interface to #matplotlib for creating publication quality maps. Some of the key features of cartopy are: object oriented projection definitions point, line, vector, polygon and image transformations between projections integration to expose advanced mapping in matplotlib with a simple and intuitive interface powerful vector data handling by integrating shapefile reading with Shapely capabilities