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Источник @procode404 · Post #4040 · 28 апр.
🧩Как работать с Prometheus в Go — [21:46] Метрики важны для понимания производительности и использования ресурсов микрослужб. Самым популярным инструментом для мониторинга является Prometheus. В видео рассказано о работе с Prometheus в Go и интеграции экспортера в приложение на примере рекламного сервера Перейти к просмотру #видео#go
Поиск: #array
@djangoproject · Post #316 · 28.04.2017, 06:09
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 · 31.08.2016, 15:36
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.