Recovery needs to recreate the working service and its required data after a machine or process is lost. Which artifacts and state need protection, and how should the restore be checked?

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Tasadduq BurneyownerOwner · Founder

26525 reputation · 20 Feb 2021, 04:04 UTC

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Preserve original data, numerical assumptions, code and environment metadata. Choose storage formats that retain shape and dtype and document endianness or interoperability needs. Verify reloaded arrays and avoid treating a screenshot or printed summary as a recoverable numerical dataset.

What needs backing up or preserving in NumPy?

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