TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #15110 · Sep 1
#other Cognitive load is the mental effort needed to understand and work with code. Since our brain can only hold about four pieces of information at once, complex code with many conditions, deep inheritance, or too many small modules increases this load, making it harder to understand and maintain. To reduce cognitive load, use clear, meaningful variable names, prefer composition over inheritance, avoid too many tiny modules, and keep interfaces simple. Also, avoid excessive abstractions, tight coupling with frameworks, and overly complex architectures. Lower cognitive load helps you and your team understand code faster, reduce bugs, and be more productive. https://github.com/zakirullin/cognitive-load
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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.