#go#ai#assistant#cli#kubernetes
**kubectl-ai** is a tool that helps manage Kubernetes using AI. It lets you ask questions or give commands in simple language, and it will execute the right Kubernetes actions for you. This makes it easier to manage your Kubernetes cluster without needing to remember complex commands. You can use it to check app status, create deployments, or troubleshoot issues, all by just typing what you want to do. It supports various AI models and can be used interactively or with other Unix commands, making it a powerful assistant for Kubernetes users.
https://github.com/GoogleCloudPlatform/kubectl-ai
https://github.com/aio-libs/aiohttp-mako
#mako template renderer for #aiohttp.web based on aiohttp_jinja2. Library has almost same api and support python 3.5 (PEP492) syntax. It is used in aiohttp_debugtoolbar.
#Mako is a #template library written in Python. It provides a familiar, non-XML syntax which compiles into Python modules for maximum performance. Mako's syntax and #API borrows from the best ideas of many others, including #Django and #Jinja2 templates, #Cheetah, #Myghty, and #Genshi. Conceptually, Mako is an embedded Python (i.e. Python Server Page) language, which refines the familiar ideas of componentized layout and inheritance to produce one of the most straightforward and flexible models available, while also maintaining close ties to Python calling and scoping semantics.
http://www.makotemplates.org/