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Source channel @githubtrending · Post #14990 · Jul 23
#vue#pake#pakeplus#rust#tauri#tauri2#vue3#webapp You can quickly turn any website or web project like Vue or React into a small, fast desktop or mobile app under 5MB using PakePlus. It works on Mac, Windows, Linux, Android, and iOS without needing complex setups. PakePlus is much smaller and faster than similar tools, supports custom JavaScript, and keeps your data secure by using your own GitHub repository. It’s easy to use with just one GitHub token or even without one for local packaging. This helps you create apps fast, hide website addresses, add custom features, and run your web projects as apps on many platforms. https://github.com/Sjj1024/PakePlus
Search: #array
@djangoproject · Post #316 · 04/28/2017, 06:09 AM
https://github.com/blissnd/easyxls Convert any #spreadsheet into a Python internal #dict/#array data structure, for easy processing. Can also handle pivot tables. For pivot table usage, header_row_start & header_col_start need to be set equal to the top left corner of the pivot table => header_row_start=8, header_col_start='c' in the included example. Column IDs must always be lowercase chars in quotes, e.g. 'a'.
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@djangoproject · Post #129 · 08/31/2016, 03:36 PM
https://pypi.python.org/pypi/numpy #NumPy is a general-purpose #array-processing package designed to efficiently manipulate large #multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional #arrays. NumPy is built on the #Numeric code base and adds features introduced by #numarray as well as an extended #C-API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose #data-base applications.