LiveLessons | repository contains all the source code examples | Microservice library

by douglascraigschmidt Java Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(5)Vulnerabilities Install Support

kandi X-RAY | LiveLessons Summary

LiveLessons is a Java library typically used in Architecture, Microservice, Spring Boot, Spring applications. LiveLessons has no vulnerabilities and it has low support. However LiveLessons has 1453 bugs and it build file is not available. You can download it from GitHub.

This repository contains all the source code examples from my LiveLessons course on "Java Concurrent Programming" and my various LiveTraining courses, as described at http://www.dre.vanderbilt.edu/~schmidt/DigitalLearning.

Support

Quality

Security

License

Reuse

Support

LiveLessons has a low active ecosystem.

It has 562 star(s) with 647 fork(s). There are 114 watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 2 have been closed. On average issues are closed in 204 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of LiveLessons is current.

Quality

LiveLessons has 1453 bugs (59 blocker, 65 critical, 781 major, 548 minor) and 25034 code smells.

Security

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

LiveLessons code analysis shows 0 unresolved vulnerabilities.

There are 543 security hotspots that need review.

License

LiveLessons does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

LiveLessons has no build file. You will be need to create the build yourself to build the component from source.

LiveLessons saves you 688234 person hours of effort in developing the same functionality from scratch.

It has 338793 lines of code, 35015 functions and 5686 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed LiveLessons and discovered the below as its top functions. This is intended to give you an instant insight into LiveLessons implemented functionality, and help decide if they suit your requirements.

Returns a string representation of this number using the specified radix .
Make the ping threads for the given synchronization mechanism .
Parse the next symbol .
Test for a MonoPeriodMultiplications .
Create directory and save it in external storage .
Applies the given function to the given list of splits .
Shows a specific rationale .
Schedules the timer to run .
Test for a CompletableFractionExceptions .
Attempts to compute a value based on the provided mapping function .

Get all kandi verified functions for this library.

LiveLessons Key Features

No Key Features are available at this moment for LiveLessons.

LiveLessons Examples and Code Snippets

No Code Snippets are available at this moment for LiveLessons.

Community Discussions

Trending Discussions on LiveLessons

Having to refresh to change navigation based on custom claim (ReactJS and Firebase Custom Claims)

Deep Q Learning agent finds solution then diverges again

JavaScript based WebSocket Client Not Receiving any Output to Browser Console using Spring Reactor Web Sockets

AWS: "ssh: connect to host **.***.***.** port 22: Operation timed out"

docker permission denied in windows

QUESTION

Having to refresh to change navigation based on custom claim (ReactJS and Firebase Custom Claims)

Asked 2020-Oct-12 at 08:58

I am currently working on a project that involves Firebase custom claims, they need admin and user roles. I have got this working now.

When a user logs in as an admin, it shows the admin navigation bar and when they are just a user, it shows the user navigation bar.

However, my navigation isn't changing until the user refreshes the page.

What's the best way to get around this?

Header.js

...

ANSWER

Answered 2020-Oct-12 at 08:58

It sounds like your Nav component is not updated upon auth state change. You will need to listen to the auth state within your component:

Source https://stackoverflow.com/questions/64314030

QUESTION

Deep Q Learning agent finds solution then diverges again

Asked 2020-Jun-23 at 13:53

I am trying to train a DQN Agent to solve AI Gym's Cartpole-v0 environment. I have started with this person's implementation just to get some hands-on experience. What I noticed is that during training, after many episodes the agent finds the solution and is able to keep the pole upright for the maximum amount of timesteps. However, after further training, the policy looks like it becomes more stochastic and it can't keep the pole upright anymore and goes in and out of a good policy. I'm pretty confused by this why wouldn't further training and experience help the agent? At episodes my epsilon for random action becomes very low, so it should be operating on just making the next prediction. So why does it on some training episodes fail to keep the pole upright and on others it succeeds?

Here is a picture of my reward-episode curve during the training process of the above linked implementation.

...

ANSWER

Answered 2020-Jun-23 at 13:35

This actually looks fairly normal to me, in fact I guessed your results were from CartPole before reading the whole question.

I have a few suggestions:

When you're plotting results, you should plot averages over a few random seeds. Not only is this generally good practice (it shows how sensitive your algo is to seeds), it'll smooth out your graphs and give you a better understanding of the "skill" of your agent. Don't forget, the environment and the policy are stochastic, so it's not completely crazy that your agent exhibits this type of behavior.
Assuming you're implementing e-greedy exploration, what's your epsilon value? Are you decaying it over time? The issue could also be that your agent is still exploring a lot even after it found a good policy.
Have you played around with hyperparameters, like learning rate, epsilon, network size, replay buffer size, etc? Those can also be the culprit.

Source https://stackoverflow.com/questions/62535763

QUESTION

JavaScript based WebSocket Client Not Receiving any Output to Browser Console using Spring Reactor Web Sockets

Asked 2020-May-07 at 13:14

I was following along a tutorial for setting up web sockets that used Pivotal's Reactor Framework API.

The example would entail, after running the Spring Boot Reactive Microservice, to launching the Google Chrome web browser and opening up a specific URL (with a port) and then clicking on View / Source and then clicking on Console.

This should have produced a log message to Google Chrome's Console's stdout.

However, nothing is outputted...

Project structure:

...

ANSWER

Answered 2020-May-07 at 13:14

Got it working by placing the @Configuration above the WebSocketConfig class:

Source https://stackoverflow.com/questions/61646154

QUESTION

AWS: "ssh: connect to host **.***.***.** port 22: Operation timed out"

Asked 2020-Apr-27 at 02:33

Although my issue looks very generic and common, it doesn't seem to be identical to anything discussed here in stackoverflow. SecurityGroup has been set up with "MyIP" for ssh connection and I have been using correct pub IP to connect. Yet, I'm still getting timeout error as below. Is there something that I need to change in my Mac?

...

ANSWER

Answered 2020-Apr-27 at 02:33

Based on the comments, the issue was due to use of non-default NACLs. The solution was to allow SSH in the NACLs.

Source https://stackoverflow.com/questions/61450544

QUESTION

docker permission denied in windows

Asked 2019-May-02 at 07:45

I create a docker file like this:

...

ANSWER

Answered 2019-May-02 at 07:45

It seems that your problem is at you last command. In : docker run -v D:/TensorFlow-LiveLessons:/home/jovyan/work -it --rm -p 8888:8888 tensorflow-ll-stack ., you are telling docker to launch a container with a command ".". From the doc you linked me in the comments, you mixed up docker build and docker run.

Docker build take a context path as a parameter, where it can find a Dockerfile. It often a ".", if you are executing the command from the same directory.

Docker run take a command as a parameter, which will be used as an entry point for you image.

Now, it looks more like a copy past problem, since you documentation show that the docker run command is docker run -v c:/full/path/to/the/clone:/home/jovyan/work -it --rm -p 8888:8888 tensorflow-ll-stack without the point, but it never bad to learn about docker build and docker run.

Have fun!

Source https://stackoverflow.com/questions/55924416

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

Vulnerabilities

No vulnerabilities reported

Install LiveLessons

You can download it from GitHub.
You can use LiveLessons like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the LiveLessons component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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 .

Find more information at: