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Source channel @githubtrending · Post #14919 · Jul 6

#cplusplus#aes#avx#avx_instructions#chrome#chrome_devtools#chromedriver#chromium#chromium_browser#content_shell#jpeg_xl#jpegxl#jxl#libjxl#linux#thorium#thorium_browser#thoriumos#web_browser#web_platform#webbrowser Thorium is a fast, optimized web browser based on Chromium, designed to work well on modern CPUs with advanced instruction sets like AVX and SSE4. It offers better performance than standard Chromium and Chrome, opening tabs and rendering pages quickly. Thorium includes enhanced privacy features such as DNS over HTTPS and Do Not Track enabled by default, plus support for modern media formats like HEVC and JPEG XL. It keeps the familiar Chrome interface and supports all Chrome extensions, making it easy to switch. Available on Windows, Linux, macOS, Android, and Raspberry Pi, it suits users wanting speed, privacy, and compatibility across devices[3][5][1]. https://github.com/Alex313031/thorium

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djangoproject

@djangoproject · Post #423 · 08/26/2017, 08:39 AM

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 · 08/26/2017, 08:43 AM

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