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Source channel @githubtrending · Post #15048 · Aug 12

#typescript The GitHub Actions Checkout action lets you download your repository code into the workflow environment so your automation can access it. It supports fetching specific branches, tags, or commits, and can fetch full history or just the latest commit. You can use tokens or SSH keys for authenticated access, enabling secure git commands during workflows. It also supports sparse checkouts to fetch only parts of the repo, and can handle submodules. This action simplifies automating tasks like testing, building, or deploying code by ensuring your workflow has the right code checked out efficiently and securely. https://github.com/actions/checkout

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djangoproject

@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'.

djangoproject

@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.