Asp Net Core Tutorial BETTER

Choose these tutorials if you want to use Visual Studio Code or some other code editor. All of them use the CLI for .NET Core development tasks, so all except the debugging tutorial can be used with any code editor.

The online tutorial CORE-2022 (Course on Research Ethics) is an introduction to the TCPS 2 for the research community. It focuses on the TCPS 2 ethics guidance that is applicable to all research involving human participants, regardless of discipline or methodology.

Asp Net Core Tutorial

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This demo is best if you want to see what a basic AWS IoT solution can do without connecting a device or downloading any software. The interactive tutorial presents a simulated solution built on AWS IoT Core services that illustrates how they interact.

This tutorial is best if you want to quickly get started with AWS IoT and see how it works in a limited scenario. In this tutorial, you'll need a device and you'll install some AWS IoT software on it. If you don't have an IoT device, you can use your Windows, Linux, or macOS personal computer as a device for this tutorial. If you want to try AWS IoT, but you don't have a device, try the next option.

This tutorial is best for developers who want to get started with AWS IoT so they can continue to explore other AWS IoT Core features such as the rules engine and shadows. This tutorial follows a process similar to the quick connect tutorial, but provides more details on each step to enable a smoother transition to the more advanced tutorials.

If you want to try more than one of these getting started tutorials or repeat the same tutorial, you should delete the thing object that you created from an earlier tutorial before you start another one. If you don't delete the thing object from an earlier tutorial, you will need to use a different thing name for subsequent tutorials. This is because the thing name must be unique in your account and AWS Region.

Just curious how y'all felt with the tutorial boss. I heard some people had mad struggle with him and even refunded the game.

Honestly I beat him without really noticing that it was the tutorial boss, really don't get it and I never played an armored core game, either i don't get the mentality of quitting a game over a difficult enemy.

I am interested in backend development and trying a few frameworks before committing to a certain one. I do have experience with spring boot, vanilla php, and laravel, so I am familiar with backend concepts. I am looking to learn .Net Core but I am not sure where to start. Microsoft has an official beginner's tutorial but quite frankly it was "bad", many bugs were fixed by youtube comments instead of microsoft themselves and doesn't cover things like API calls and other day to day tasks (not sure if they are just outdated or outright bad).

While we believe that this content benefits our community, we have not yet thoroughly reviewed it. If you have any suggestions for improvements, please let us know by clicking the report an issue button at the bottom of the tutorial.

Welcome to Core Java Tutorial. I have written a lot on Core Java and Java EE frameworks. There was no index post for Core Java tutorial and I used to get emails asking to make one so that any beginner can follow them and learn core java programming. Finally, I got time and here I am listing all the core java tutorial related posts that I think will help you in learning core java in no time. This list is updated till Java-10 and soon it will be updated with the latest changes in Java-11 and beyond.

This tutorial introduces ROS using rqt_console and rqt_logger_level for debugging and roslaunch for starting many nodes at once. If you use ROS fuerte or ealier distros where rqt isn't fully available, please see this page with this page that uses old rx based tools.

This tutorial describes some tips for writing roslaunch files for large projects. The focus is on how to structure launch files so they may be reused as much as possible in different situations. We'll use the 2dnav_pr2 package as a case study.

By the end of the tutorial you will have two models trained on two different datasets of house price data. It is possible to change the names of components and file paths mentioned in this tutorial, without breaking the functionality, unless stated explicitly.

IMPORTANT Before you start this tutorial with SAP AI Launchpad, it is recommended that you set up at least one other tool, either Postman or Python (SAP AI Core SDK) because some steps of this tutorial cannot be performed with SAP AI Launchpad.

Create a new directory named hello-aicore-data. The code is different from previous tutorial as it reads the data from folder (volumes, virtual storage spaces). The content of these volumes is dynamically loaded during execution of workflows.

The nf-core community provides a range of tools to help new users get to grips with Nextflow - both by providing complete pipelines that can be used out of the box, and also by helping developers with best practices.Companion tools can create a bare-bones pipeline from a template scattered with TODO pointers and CI with linting tools check code quality.Guidelines and documentation help to get Nextflow newbies on their feet in no time.Best of all, the nf-core community is always on hand to help.

The aim of nf-core is to develop with the community over GitHub and other communication channels to build a pipeline to solve a particular analysis task.We therefore encourage cooperation and adding new features to existing pipelines.Before considering starting a new pipeline, have a look if a pipeline already exists performing a similar task and consider contributing to that one instead.If there is no pipeline for the analysis task at hand, let us know about your new pipeline plans on Slack in the #new-pipelines channel.

Much of this tutorial will make use of the nf-core command line tool.This has been developed to provide a range of additional functionality for the project such as pipeline creation, testing and more.

Contribution guidelines: one of the main ideas of nf-core is to develop with the community to build together best-practise analysis pipelines.We encourage cooperation rather than duplication, and contributing to and extending existing pipelines that might be performing similar tasks.For more details about this, please check out the contribution guidelines.

Not everything can be completed with a template and all new pipelines will need to edit and add to the resulting pipeline files in a similar set of locations.To make it easier to find these, the nf-core template files have numerous comment lines beginning with TODO nf-core:, followed by a description of what should be changed or added.These comment lines can be deleted once the required change has been made.

Most code editors have tools to automatically discover such TODO lines and the nf-core lint command will flag these.This makes it simple to systematically work through the new pipeline, editing all files where required.

Typically, people will start developing a new pipeline under their own personal account on GitHub.When it is ready for its first release and has been discussed on Slack, this repository is forked to the nf-core organisation.All developers then maintain their own forks of this repository, contributing new code back to the nf-core fork via pull requests.

Manually checking that a pipeline adheres to all nf-core guidelines and requirements is a difficult job.Wherever possible, we automate such code checks with a code linter.This runs through a series of tests and reports failures, warnings and passed tests.

The linting code is closely tied to the nf-core template and both change over time.When we change something in the template, we often add a test to the linter to make sure that pipelines do not use the old method.

Each lint test is documented on the nf-core tools documentation website.When warnings and failures are reported on the command line, a short description is printed along with a link to the documentation for that specific test on the website.

When adding a new pipeline, you must also set up the test config profile.To do this, we use the nf-core/test-datasets repository.Each pipeline has its own branch on this repository, meaning that the data can be cloned without having to fetch all test data for all pipelines:

To set up the test profile, make a new branch on the nf-core/test-datasets repo through the web page (see instructions).Fork the repository to your user and open a PR to your new branch with a really (really!) tiny dataset.Once merged, set up the conf/test.config file in your pipeline to refer to the URLs for your test data.

The automated tests with GitHub Actions are configured in the .github/workflows folder that is generated by the template.Each file (branch.yml, ci.yml and linting.yml) defines several tests: branch protection, running the pipeline with the test data, linting the code with nf-core lint, linting the syntax of all Markdown documentation and linting the syntax of all YAML files.

The branch.yml workflow sets the branch protection for the nf-core repository.It is already set up and does not need to be edited.This test will check that pull-requests going to the nf-core repo master branch only come from the dev or patch branches (for releases).In case you want to add branch protection for a repository outside nf-core, you can add an extra step to the workflow with that repository name.You can leave the nf-core branch protection in place so that the nf-core lint command does not throw an error - it only runs on nf-core repositories so it should be ignored.

The Nextflow DSL2 syntax allows the modularizing of Nextflow pipelines, so workflows, subworkflows and modules can be defined and imported into a pipeline.This allows for the sharing of pipeline processes (modules, and also routine subworkflows) among nf-core pipelines.

Shared modules are stored in the nf-core/modules repository.Modules on this repository are as atomic as possible, in general calling each one tool only.If a tool consists of several subtools (e.g. bwa index and bwa mem), these will be stored in individual modules with the naming convention tool/subtool.Each module defines the input and output channels, the process script, as well as the software packaging for a specific process. Conda environments, docker or singularity containers are defined within each module. We mostly rely on the biocontainers project for providing single-tool containers for each module. 17dc91bb1f