kcache | kubernetes object cache

 by   boz Go Version: Current License: MIT

kandi X-RAY | kcache Summary

kandi X-RAY | kcache Summary

kcache is a Go library. kcache has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Kcache is a kubernetes object data source similar to k8s.io/client-go/tools/cache which uses channels to create a flexible event-based toolkit. Features include typed producers, joining between multiple producers, and (re)filtering. Kcache was originally created to drive a Kubernetes monitoring application and it currently powers kail.
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            kandi-support Support

              kcache has a low active ecosystem.
              It has 10 star(s) with 7 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              kcache has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of kcache is current.

            kandi-Quality Quality

              kcache has 0 bugs and 0 code smells.

            kandi-Security Security

              kcache has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              kcache code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              kcache is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              kcache releases are not available. You will need to build from source code and install.
              Installation instructions are not available. Examples and code snippets are available.
              It has 15969 lines of code, 1039 functions and 116 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed kcache and discovered the below as its top functions. This is intended to give you an instant insight into kcache implemented functionality, and help decide if they suit your requirements.
            • watch is the main event loop
            • DeploymentPodsWith returns a new pod controller that monitors the given filterFn .
            • DaemonSetPodsWith returns a pod controller that monitors the specified filterFn .
            • ServicePodsWith returns a PodController that monitors the given service controller .
            • JobPodsWith returns a pod controller that monitors the given source controller .
            • RCPodsWith returns a pod controller which monitors the source controller with the provided filterFn .
            • StatefulSetPodsWith returns a pod controller that monitors the statefulset controller .
            • IngressServicesWith returns a service controller which monitors services with a filter function .
            • RSPodsWith returns a pod . Controller that runs the given filter function with the given filterFn .
            • NewMonitor creates a new monitor
            Get all kandi verified functions for this library.

            kcache Key Features

            No Key Features are available at this moment for kcache.

            kcache Examples and Code Snippets

            No Code Snippets are available at this moment for kcache.

            Community Discussions

            QUESTION

            How to correctly assign double8 type
            Asked 2019-Nov-15 at 14:47

            I am trying to assign a double8 type, ultimately for some AVX2 parallelisation using pyopencl. I am making code to find the dot product efficiently between two vectors, va and vb, and return the result vc.

            Code is below:

            ...

            ANSWER

            Answered 2019-Nov-15 at 14:47

            I don't really know anything about pyopencl, but I assume the kernels are exactly like regular OpenCL kernels. Your problem isn't with assignment of a double8 type, rather the assignment of value vc. you have vc as a __global float*, a pointer type. See how you treated va & vb as arrays and accessed their elements with [index]? The same is true for vc.Since your vc is only intended to store a single value, you can do

            vc[0] = ...

            or a pointer derefrence

            *cv = ...

            So what you should do is this instead:

            Source https://stackoverflow.com/questions/58877001

            QUESTION

            Python profiling, imports (and specially __init__) is what seems to take the most time
            Asked 2018-May-27 at 17:27

            I have a script that seemed to run slow and that i profiled using cProfile (and visualisation tool KCacheGrind)

            It seems that what is taking almost 90% of the runtime is the import sequence, and especially the running of the _ _ init _ _.py files...

            Here a screenshot of the KCacheGrind output (sorry for attaching an image...)

            I am not very familiar with how the import sequence works in python ,so maybe i got something confused... I also placed _ _ init _ _.py files in everyone of my custom made packages, not sure if that was what i should have done.

            Anyway, if anyone has any hint, greatly appreciated!

            EDIT: additional picture when function are sorted by self:

            EDIT2:

            here the code attached, for more clarity for the answerers:

            ...

            ANSWER

            Answered 2018-May-27 at 17:27

            No. You are conflating cumulative time with time spent in the top-level code of the __init__.py file itself. The top-level code calls other methods, and those together take a lot of time.

            Look at the self column instead to find where all that time is being spent. Also see What is the difference between tottime and cumtime in a python script profiled with cProfile?, the incl. column is the cumulative time, self is the total time.

            I'd just filter out all the entries; the Python project has already made sure those paths are optimised.

            However, your second screenshot does show that in your profiling run, all that your Python code busied itself with was loading bytecode for modules to import (the marshal module provides the Python bytecode serialisation implementation). Either the Python program did nothing but import modules and no other work was done, or it is using some form of dynamic import that is loading a large number of modules or is otherwise ignoring the normal module caches and reloading the same module(s) repeatedly.

            You can profile import times using Python 3.7's new -X importtime command-line switch, or you could use a dedicated import-profiler to find out why imports take such a long time.

            Source https://stackoverflow.com/questions/50554374

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install kcache

            You can download it from GitHub.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            https://github.com/boz/kcache.git

          • CLI

            gh repo clone boz/kcache

          • sshUrl

            git@github.com:boz/kcache.git

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