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Source channel @githubtrending · Post #15320 · Dec 9
#shell#awesome#awesome_list#bash You can use Bash scripts to automate repetitive tasks on your computer, like managing files, updating software, or running system maintenance, which saves you time and reduces errors. Bash scripting is easy to learn even without programming experience because it uses simple commands you already know from the terminal. There are many resources, tools, and ready-made scripts available to help you customize your command line, improve productivity, and develop your own scripts. This makes working with your system faster, more efficient, and less prone to mistakes. Plus, you can schedule scripts to run automatically whenever you want. https://github.com/awesome-lists/awesome-bash
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@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.