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Hey if u want to perfect then donot hope in 15 days take ur time till u fully understand the topics so Better Join Microsoft Azure Training in any Best Institute Take ur Time.
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1) installing the modules dynamically 2) AWS batch 1) installing the modules dynamically def lambdahandler ():
#install numpy package
# numpy code
#uninstall numpy package
## now install Scipy package
# execute scipy code
or vice versa depends on your code 2) using Aws batch This is the best way where you don't have any limitation regarding Memory space. just you need to build a Docker (AWS Training) image and need to write an all required packages and libraries inside the requirement.txt file.
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https://docs.microsoft.com/en-us/azure/app-service/containers/app-service-linux-intro https://docs.microsoft.com/en-us/azure/app-service/containers/quickstart-custom-docker-image This is roughly just a simple way to deploy a container without the burden of Kubernetes. ACS might be best if you really want a dedicated container solution (there is several orchestrators). For the authentication part, htaccess file with basic authentication is supported by pip. This allow to do something like extra-index-url = https://login:password@pypi.myserver.com/simple/. I don't have a prefered tutorial, but google/bing something like "pip private repository" you will have no issue to find answers. (full disclosure, I work at MS in the Azure Python SDK team)
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