runtimes | Kubeless function runtimes https | Serverless library

by kubeless C# Version: Current License: Apache-2.0

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kandi X-RAY | runtimes Summary

runtimes is a C# library typically used in Serverless, Deep Learning, Nodejs applications. runtimes has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Use this repository to submit official Runtimes for Kubeless. Runtimes are the different languages that can be used to run Kubeless functions. For more information about installing and using Kubeless, see its documentation. To get a quick introduction to the available runtimes see this document.

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Security

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Support

runtimes has a low active ecosystem.

It has 71 star(s) with 83 fork(s). There are 12 watchers for this library.

It had no major release in the last 6 months.

There are 18 open issues and 22 have been closed. On average issues are closed in 67 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of runtimes is current.

Quality

runtimes has 0 bugs and 0 code smells.

Security

runtimes has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

runtimes code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

runtimes is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

runtimes releases are not available. You will need to build from source code and install.

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runtimes Key Features

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runtimes Examples and Code Snippets

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Community Discussions

Trending Discussions on runtimes

Why Python native on M1 Max is greatly slower than Python on old Intel i5?

Why is the time complexity of my algorithm to calculate the factorial of a number O(n^2) instead of the expected O(n)?

Why is this (presumably more efficient) dynamic algorithm being outperformed by the naive recursive version?

Class _PointQueue is implemented in both when I click on textfield... How can I resolve this issue?

Missing types, namespaces, directives, and assembly references

How to resolve libwkhtmltox.so reference in .Net AWS Lambda Docker image

Google app engine deployment fails- Error while finding module specification for 'pip' (AttributeError: module '__main__' has no attribute '__file__')

F# on Visual Studio 2022 very slow

Must use import to load ES Module .eslintrc.js

GitHub Codespaces: how to set x86_64, AMD64, ARM64 platform?

QUESTION

Why Python native on M1 Max is greatly slower than Python on old Intel i5?

Asked 2022-Mar-29 at 03:35

I just got my new MacBook Pro with M1 Max chip and am setting up Python. I've tried several combinational settings to test speed - now I'm quite confused. First put my questions here:

Why python run natively on M1 Max is greatly (~100%) slower than on my old MacBook Pro 2016 with Intel i5?
On M1 Max, why there isn't significant speed difference between native run (by miniforge) and run via Rosetta (by anaconda) - which is supposed to be slower ~20%?
On M1 Max and native run, why there isn't significant speed difference between conda installed Numpy and TensorFlow installed Numpy - which is supposed to be faster?
On M1 Max, why run in PyCharm IDE is constantly slower ~20% than run from terminal, which doesn't happen on my old Intel Mac.

Evidence supporting my questions is as follows:

Here are the settings I've tried:

1. Python installed by

Miniforge-arm64, so that python is natively run on M1 Max Chip. (Check from Activity Monitor, Kind of python process is Apple).
Anaconda. Then python is run via Rosseta. (Check from Activity Monitor, Kind of python process is Intel).

2. Numpy installed by

conda install numpy: numpy from original conda-forge channel, or pre-installed with anaconda.
Apple-TensorFlow: with python installed by miniforge, I directly install tensorflow, and numpy will also be installed. It's said that, numpy installed in this way is optimized for Apple M1 and will be faster. Here is the installation commands:

...

ANSWER

Answered 2021-Dec-06 at 05:53

Possible Cause: Different BLAS Libraries

Since the benchmark is running linear algebra routines, what is likely being tested here are the BLAS implementations. A default Anaconda distribution for osx-64 platform is going to come with Intel's MKL implementation; the osx-arm64 platform only has the generic Netlib BLAS and the OpenBLAS implementation options.

For me (MacOS w/ Intel i9), I get the following benchmark results:

BLAS Implmentation Mean Timing (s) mkl 0.95932 blis 1.72059 openblas 2.17023 netlib 5.72782

So, I suspect the old MBP had MKL installed, and the M1 system is installing either Netlib or OpenBLAS. Maybe try figuring out whether Netlib or OpenBLAS are faster on M1, and keep the faster one.

Specifying BLAS Implementation

Here are specifically the different environments I tested:

Source https://stackoverflow.com/questions/70240506

QUESTION

Why is the time complexity of my algorithm to calculate the factorial of a number O(n^2) instead of the expected O(n)?

Asked 2022-Mar-15 at 15:48

Very perplexed with this one. I have three implementations of an algorithm to calculate the factorial of a number. I calculated the average runtimes of each for input size up to 2500 and plotted them. From the visual inspection it seems that they don't exhibit linear time complexity but rather quadratic. To explore this further, I used curve fitting and the results emerging from visual inspection are confirmed.

Why is this happening? Is it maybe related to the way multiplication is handled in Python for small number? (see here Complexity of recursive factorial program)

...

ANSWER

Answered 2022-Mar-15 at 15:48

As @Konrad has pointed out, it is due to the way multiplication is handled in Python.

For smaller numbers, simple school level multiplication (which runs in O(N^2)) is used. However, for bigger numbers, it uses the Karatsuba Algorithm, which has a estimated complexity of O(N^1.58) (N = length of the number). Since the multiplication isn't achieved in O(1), your time complexity isn't linear.

There are "faster" multiplication algorithms (such as Toom-Cook and Schönhage-Strassen) if you want to look into it.

Source https://stackoverflow.com/questions/71482319

QUESTION

Why is this (presumably more efficient) dynamic algorithm being outperformed by the naive recursive version?

Asked 2022-Mar-08 at 22:57

I have the following problem as homework:

Write a O(N^2) algorithm to determine whether the string can be broken into a list of words. You can start by writing an exponential algorithm and then using dynamic programming to improve the runtime complexity.

The naive exponential algorithm which I started out with is this:

...

ANSWER

Answered 2022-Mar-08 at 22:49

The naive recursive approach is only slow when there are many, many, ways to break up the same string into words. If there is only one way, then it will be linear.

Assuming that can, not and cannot are all words in your list, try a string like "cannot" * n. By the time you get to n=40, you should see the win pretty clearly.

Source https://stackoverflow.com/questions/71402224

QUESTION

Class _PointQueue is implemented in both when I click on textfield... How can I resolve this issue?

Asked 2022-Mar-07 at 07:52

I'm using xcode 13 and making a demo on coredata.

objc[6188]: Class _PathPoint is implemented in both /Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Library/Developer/CoreSimulator/Profiles/Runtimes/iOS.simruntime/Contents/Resources/RuntimeRoot/System/Library/PrivateFrameworks/UIKitCore.framework/UIKitCore (0x114a8fa78) and /Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Library/Developer/CoreSimulator/Profiles/Runtimes/iOS.simruntime/Contents/Resources/RuntimeRoot/System/Library/PrivateFrameworks/TextInputUI.framework/TextInputUI (0x12cd4a8b0). One of the two will be used. Which one is undefined.

objc[6188]: Class _PointQueue is implemented in both /Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Library/Developer/CoreSimulator/Profiles/Runtimes/iOS.simruntime/Contents/Resources/RuntimeRoot/System/Library/PrivateFrameworks/UIKitCore.framework/UIKitCore (0x114a8fa50) and /Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Library/Developer/CoreSimulator/Profiles/Runtimes/iOS.simruntime/Contents/Resources/RuntimeRoot/System/Library/PrivateFrameworks/TextInputUI.framework/TextInputUI (0x12cd4a8d8). One of the two will be used. Which one is undefined.

...

ANSWER

Answered 2021-Nov-17 at 17:31

Apple developer Quinn “The Eskimo!” @ Developer Technical Support @ Apple answered this question here:

This is not an error per se. Rather, it’s the Objective-C runtime telling you that:

Two frameworks within your process implement the same class (well, in this case classes, namely _PathPoint and _PointQueue).

The runtime will use one of them, choosing it in an unspecified way.

This can be bad but in this case it’s not. Both of the implementations are coming from the system (well, the simulated system) and thus you’d expect them to be in sync and thus it doesn’t matter which one the runtime uses.

So, in this specific case, these log messages are just log noise.

Source https://stackoverflow.com/questions/70006570

QUESTION

Missing types, namespaces, directives, and assembly references

Asked 2022-Feb-27 at 10:24

I use VS Code for C# and Unity3D and TypeScript and Angular and Python programming, so I have pretty much every required extension, including the .NET Framework and Core as well as the Quantum Development Kit (QDK) plus the Q# Interoperability Tools and also C# and Python extensions for VS Code.

I have devised the following steps to create my first quantum Hello World based on a few tutorials:

...

ANSWER

Answered 2022-Feb-27 at 10:24

With help from a user on another forum, it turns out the problem was the command:

Source https://stackoverflow.com/questions/71100198

QUESTION

How to resolve libwkhtmltox.so reference in .Net AWS Lambda Docker image

Asked 2022-Jan-17 at 08:17

I'm converting a .Net 2.1 lambda to 3.1 (or higher) and struggling with resolving the references that convert html to pdf. I'm currently using code from this solution https://github.com/HakanL/WkHtmlToPdf-DotNet, which works fine running a console app in the container. The lambda package is introducing issues that break this logic. Using a new lambda solution with this WkHtmlToPdf-DotNet project, the deployed image fails with this exception

GetModule WkHtmlModuleLinux64 Exception System.DllNotFoundException: Unable to load shared library '/var/task/runtimes/linux-x64/native/libwkhtmltox.so' or one of its dependencies. In order to help diagnose loading problems, consider setting the LD_DEBUG environment variable: libjpeg.so.62: cannot open shared object file: No such file or directory

I am using the LD_DEBUG environment variable which shows before the exception: file=runtimes/linux-x86/native/libwkhtmltox [0]; dynamically loaded by /var/lang/bin/shared/Microsoft.NETCore.App/5.0.12/libcoreclr.so [0]

And I also output to the log a search for the file which yields this line:
GetFilePath res: /var/task/runtimes/linux-x64/native/libwkhtmltox.so

Any suggestions how to continue to troubleshoot this?

Thanks, Reuven

...

ANSWER

Answered 2022-Jan-17 at 08:17

I was able to resolve this issue by installing few of the packages that is required by DinkToPdf library in a docker container environment.

The issue however for installing those packages were not straight forward in Amazon Linux 2 instances. Below is the docker file I had to add for the DinkToPdf work properly.

Source https://stackoverflow.com/questions/70525819

QUESTION

Google app engine deployment fails- Error while finding module specification for 'pip' (AttributeError: module '__main__' has no attribute '__file__')

Asked 2022-Jan-08 at 22:02

We are using command prompt c:\gcloud app deploy app.yaml, but get the following error:

...

ANSWER

Answered 2022-Jan-06 at 09:24

Your setuptools version is likely to be yanked:

https://pypi.org/project/setuptools/60.3.0/

Not sure how to fix that without a working pip though.

Source https://stackoverflow.com/questions/70602290

QUESTION

F# on Visual Studio 2022 very slow

Asked 2022-Jan-06 at 11:02

This only applies to Visual Studio 2022. I had uninstalled VS2019 and Preview where F# worked absolutely fine (F# 5.0). I am using VS2022 to use F# 6.0 and do not want to go back to F# 5.0.

The issue is specific to F#. I also use C# and I have no issues running the latest C# under VS2022.

There are near continual DevEnv processes running consuming anywhere from 1 to 4 of my CPU's 4 Hyperthreads. I have switched off all experimental options I can find in F# settings.

Sometimes there are 2 or more background processes running , sometimes paused and sometimes none - there appears to be no correlation between this and the background CPU consumption

Sometimes I have a pop up Dialog about waiting to complete an editor process or a compile process.

When devenev.exe is consuming CPU cycles under the properties I see there is always one clr.dllCoUnInitializeEE+0x6790 that is the culprit. I though this was meant to be a short-lived process? Sometimes there are two or three of these consuming most of a HyperThread (There are identical others but with very low or no CPU consumption). The stack on the guilty thread is as follows:

...

ANSWER

Answered 2021-Dec-17 at 08:49

Please report to Microsoft either using the people app in windows or the visual studio installer.

for now, there is only one option: use visual studio 2019. or try finding alternatives. there should be somewhere around the net

I suggest using Rider IDE instead(until the devs fix the bug):Download Rider IDE

I'm not really trying to advertise here, just suggesting an IDE Too compile and run you rprogram.

Source https://stackoverflow.com/questions/70262144

QUESTION

Must use import to load ES Module .eslintrc.js

Asked 2021-Dec-26 at 18:59

I am trying to fix this problem for hours. I've read nearly every post about this, but still, I came to no solution.

I am trying to deploy a firebase-function with the "https got-library" dependency, but no matter what I do, nothing works. I am not the best with node-js or typescript (usually a kotlin frontend-dev), so I have no clue what the error wants from me.

Tsconfig.json ...

ANSWER

Answered 2021-Dec-26 at 16:13

Just try this one

add this into your package.json

"type": "module"

as I did below don't forget to restart the typescript server

Source https://stackoverflow.com/questions/70487806

QUESTION

GitHub Codespaces: how to set x86_64, AMD64, ARM64 platform?

Asked 2021-Dec-17 at 21:44

First, the question: is there a way to choose the platform (e.g. x86_64, AMD64, ARM64) for a GitHub Codespace?

Here's what I've found so far:

Attempt 1 (not working):

From within GitHub.com, you can choose the "machine" for a Codespace, but the only options are RAM and disk size.

Attempt 2 (EDIT: not working): devcontainer.json

When you create a Codespace, you can specify options by creating a top-level .devcontainer folder with two files: devcontainer.json and Dockerfile

Here you can customize runtimes, installed packages, etc., but the docs don't say anything about determining architecture...

...however, the VSCode docs for devcontainer.json has a runArgs option, which "accepts Docker CLI arguments"...

and the Docker CLI docs on --platform say you should be able to pass --platform linux/amd64 or --platform linux/arm64, but...

When I tried this, the Codespace would just hang, never finishing building.

Attempt 3 (in progress): specify in Dockerfile

This route seems the most promising, but it's all new to me (containerization, codespaces, docker). It's possible that Attempts 2 and 3 work in conjunction with one another. At this point, though, there are too many new moving pieces, and I need outside help.

Does GitHub Codespaces support this?
Would you pass it in the Dockerfile or devcontainer.json? How?
How would you verify this, anyway? [Solved: dpkg --print-architecture or uname -a]
For Windows, presumably you'd need a license (I didn't see anything on GitHub about pre-licensed codespaces) -- but that might be out of scope for the question.

References:
https://code.visualstudio.com/docs/remote/devcontainerjson-reference
https://docs.docker.com/engine/reference/commandline/run/
https://docs.docker.com/engine/reference/builder/
https://docs.docker.com/desktop/multi-arch/
https://docs.docker.com/buildx/working-with-buildx/

...

ANSWER

Answered 2021-Dec-17 at 21:44

EDIT: December 2021

I received a response from GitHub support:

The VM hosts for Codespaces are only x86_64 and we do not offer any ARM64 machines.

So for now, setting the platform does nothing, or fails.

But if they end up supporting multiple platforms, you should be able to (in Dockerfile)

RUN --platform=arm64|amd64|x86-64 [image-name],

Which is working for me in the non-cloud version of Docker.

Original answer:

I may have answered my own question

In Dockerfile:

I had RUN alpine

changed to

RUN --platform=linux/amd64 alpine

RUN --platform=linux/x86-64 alpine

checked at the command line with

uname -a to print the architecture.

Still verifying, but seems promising. [EDIT: Nope]

So, despite the above, I can only get GitHub codespaces to run x86-64. Nevertheless, the above syntax seems correct.

A clue:

In the logs that appear while the codespace is building, I saw target OS: x86

Maybe GitHub just doesn't support other architectures yet. Still investigating.

Source https://stackoverflow.com/questions/70219806

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