This tool helps to quickly set up and orchestrate file based integration scenarios to and from Dynamics 365 Finance and Dynamics 365 Supply Chain Management. We see this tool to be a good implementation accelerator for use during the implementation phase of the project for data migration, ad hoc file integration needs and to be used as a proof of concept validator among others.

Recurring Integrations Scheduler Service is a Windows service that can trigger many integration jobs at predefined schedule. You can schedule jobs and set their recurrence in a very similar way to well-known D365FO batch framework.

There are six types of integration jobs you can use: Import, Export and Execution monitor as well as Upload, Download and Processing monitor. First three use Data management package REST API. Three other use Recurring Integrations REST API and recurring data jobs.
More details in wiki.

Single Recurring Integrations Scheduler service can work with multiple D365FO instances even within different tenants. This enables both production and implementation scenarios where you need to work with multiple non-prod instances. Recurring Integrations Scheduler logs important events to Windows Event Log. It is possible to increase its logging level to log every step for debugging purposes and to trace possible problems.

Recurring Integrations Scheduler App is a win32 application that can be used as a configuration front-end for Recurring Integrations Scheduler service or as a completely independent, interactive application used to upload or download files to and from Dynamics 365 Finance or SCM without Recurring Integrations Scheduler Service.
It is possible thanks to internal, private scheduler embedded in Recurring Integrations Scheduler App that works exactly the same way as the Scheduler Service does with one difference – it will stop working once the App is closed.

Please check https://github.com/Microsoft/Recurring-Integrations-Scheduler/wiki

RIS is not officially supported by Microsoft. Please log an issue here on Github if you encounter a bug in RIS.

Este projeto é um estudo sobre o framework de teste de carga k6. Para este estudo está sendo utilizada a api REQ|RES.

Como descrito no próprio site da ferramenta o k6 é uma ferramenta de teste de carga de código aberto, gratuito e centrado no desenvolvedor e extensível. Usando o k6, você pode testar a confiabilidade e o desempenho de seus sistemas e detectar regressões e problemas de desempenho.

As formas de instalação do k6 podem ser encontradas na página oficial do framework clicando aqui.

Após clonar o projeto para sua máquina execute os seguintes comandos:

npm install

k6 run index.js

├── data                       # Massa de dados
├── tests
│   ├── options                # Arquivos de configurações. Ex: Arquivo de variável de ambiente
│   ├── routes                 # Rotas utilizadas nos testes
│   ├── scenarios              # Cenários de testes
|   |   ├── auth
|   |   ├── user

1. Dentro da pasta routes criamos um arquivo chamado NomeDaRota + Request.js, exemplo createUserRequest.js
2. Dentro deste arquivo criamos uma classe que irá conter nossa requisição
3. Criamos então uma constante data que recebe o corpo da requisição, quando existente. Neste caso utilizamos a função JSON.stringify() para converter nossos valores JS para uma string
4. Uma constante params que recebe o cabeçalho, quando existente
5. uma variável res que recebe a resposta da nossa requisição POST
6. Nossa requisição post é formada pela URL (que importamos do nosso arquivo commonOptions) + as constantes necessárias criadas nos passos 3 e 4

Obs: A URL da requisição foi colocada nesse arquivo commonOptions para facilitar a manutenção e não termos que alterar arquivo por arquivo em caso de necessidade.

import http from 'k6/http';
import { CommonOptions } from "../options/commonOptions.js";

export class CreateUserRequester {

    createUserRequester(name, job) {

        const data = JSON.stringify({
            name: name,
            job: job
        });

        const params = {
            headers: { 'Content-Type': 'application/json' }
        };

        let res = http.post(CommonOptions.url + '/api/users', data, params);

        return res;
    }
}

7. Posteriormente criamos um arquivo de teste dentro da pasta scenarios, arquivo este que executaremos ao rodar o teste
8. Importamos e inicializamos nosso arquivo criada no passo 1
9. Utilizamos a função group()para agrupar nossos casos de teste
10. Criamos uma variável, no exemplo res repa receber o retorno da requisição
11. E com o comando check() realizamos validações no retorno recebido no passo 5

import { check, group } from 'k6';
import { CreateUserRequester } from '../../routes/createUserRequest.js';

const createUserRequester = new CreateUserRequester();

export default function () {

    group('user', () => {
        group('create user successful', () => {
            let res = createUserRequester.createUserRequester('Maria', 'QA');
            check(res, {
                'success login': (r) => r.status === 201,
                'mandatory parameters': (r) => r.body.includes('id')
            });
        })
    })
}

Apply a binary callback to elements in two five-dimensional nested input arrays according to elements in a five-dimensional nested mask array and assign results to elements in a five-dimensional nested output array.

npm install @stdlib/array-base-mskbinary5d

var mskbinary5d = require( '@stdlib/array-base-mskbinary5d' );

var add = require( '@stdlib/number-float64-base-add' );
var zeros5d = require( '@stdlib/array-base-zeros5d' );

var x = [ [ [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ] ] ];
var z = zeros5d( [ 1, 1, 1, 2, 2 ] );

var mask = [ [ [ [ [ 0, 1 ], [ 0, 0 ] ] ] ] ];

var shape = [ 1, 1, 1, 2, 2 ];

mskbinary5d( [ x, x, mask, z ], shape, add );
// z => [ [ [ [ [ 2.0, 0.0 ], [ 6.0, 8.0 ] ] ] ] ]

var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var bernoulli = require( '@stdlib/random-base-bernoulli' ).factory;
var filled5dBy = require( '@stdlib/array-base-filled5d-by' );
var zeros5d = require( '@stdlib/array-base-zeros5d' );
var add = require( '@stdlib/number-float64-base-add' );
var mskbinary5d = require( '@stdlib/array-base-mskbinary5d' );

var shape = [ 1, 2, 1, 3, 3 ];

var x = filled5dBy( shape, discreteUniform( -100, 100 ) );
console.log( x );

var y = filled5dBy( shape, discreteUniform( -100, 100 ) );
console.log( y );

var mask = filled5dBy( shape, bernoulli( 0.5 ) );
console.log( mask );

var z = zeros5d( shape );
console.log( z );

mskbinary5d( [ x, y, mask, z ], shape, add );
console.log( z );

Implementation for the GraphHPC-2017 Contest
Betweenness Centrality Problem

• GraphHPC Conference Page
• GraphHPC Contests Page
  • GraphHPC-2017 Contest Page

This code does not claim to be the fastest. I had no much time as well as
experience in OpenMP and CUDA to write performance efficient solution.

You can find the reference files (testgen, sample solution) in the reference
folder.
Take a note, that the reference files are licensed under GNU GPLv2.

Sorry for the data format, but it was defined by contest organizers. If you need
other format than that is described below, you have to code your own parser or
converter.

An input format is a binary-encoded file with vertices and edges numbers, align,
and lists of indices and edge ends.
A graph structure is pretty usual for contests: there is an array of out
edges’ ends (other vertices), and array of indices. Vertex’s out edges can be
determined by the first array’s slice with the following rule:

Rule is: for each v (vertex in graph)
 - ends[index[v]] is a first edge (edge end) from v,
 - ends[index[v + 1] - 1] is a last edge (edge end) from v.

The graph is directed.

If the binary-encoded input format is not you are looking for, you can write
your own parser. See the Reading section in the main.cpp file.

An output format is a binary-encoded file too with an array of calculated
betweenness centrality value for each vertex.

See the Result writing section in the main.cpp file, if you need to change
this behaviour.

Depending on which solution you need to run, you can choose the suitable
command to compile:

# This solution uses only OpenMP interface
$ make solution-openmp

# Only CUDA
$ make solution-cuda

# This is aт attempt to use OpenMP and CUDA in parallel
$ make solution-mixed
# Alias
$ make solution

# You can compile all of them at once
$ make all

To compile CUDA and mixed versions, make sure you’ve installed CUDA Toolkit.

You can skip this section, if you have your own tests.

To compile these tools, make sure you have OpenMPI libraries installed on your
system.

Compile the test generation tools:

# For RMAT graph generation algorithm
$ make gen_rmat

# For random generation
$ make gen_random

There’s a validation tool, you can use it too, but it is not supposed to be used
on large graphs due to inefficient algorithm.

$ make validation

You can skip this section, if you have your own tests.

To run the solution, you need to generate some tests first:

# We'll place tests in the /tests folder
$ mkdir tests
$ cd tests

# Option -s is an exponent of the base 2 - the graph size
$ ../bin/gen_rmat -s 5
$ ../bin/gen_random -s 10

Generated tests will be saved in the current working directory.

The solution binaries is located in the bin directory.
To run the solution, provide the input file path with an -in argument:

# You can run solution-cuda or solution-mixed too.
# We placed our test in the /tests folder
$ ./bin/solution-openmp -nIters 5 -in ./tests/random-10

Answer will be saved in the same directory where test is located under the same
name with a .res suffix.

You can run any solution or reference tool without any arguments to print the
help.

That’s all.

MIT.
See LICENSE file for more information.

This django web application is developed for uploading data in “.csv” format to a postgresql database and serving (rendering) the data from the DB in an html.

To enable this app function properly, install the dependencies in the pipenv. Simply run:

pipenv shell
pipenv install

Once all the dependencies have been installed, proceed as follows:

• Create a postgres DB
• Run upload_data app
• Launch DataTask server

The details of the steps are provided as follows:

• First install postgresql 12.2 (incase it’s not installed already).

  One way of doing this is to download the postgresql app from https://postgresapp.com/downloads.html
  or use homebrew by running:

  brew install postgresql

  After installing postgresql, start all postgresql services from terminal by either running (postgres must be running at all times):

  pg_ctl -D /usr/local/var/postgres start
  or
  brew services start postgresql

• Second, create a new postgres database named task using:

  CREATEDB task;

  Afterward, launch the task db shell by running:

  psql task

  create username and password for the database using:

  CREATE USER admin1 with encrypted password 'admin1';

  grant all privileges of the db to USER admin1 using:

  GRANT ALL PRIVILEGES ON DATABASE task TO admin1;

  grant the USER the role to create new db using:

  ALTER USER admin1 CREATEDB;

By completing the first step, we have created a db task. The next step is uploading csv data to postgres db. The app for achieving this is upload_data.

In order to upload the data, we need to create a db table which will be accessed by our django project model, we need to:

• Create db table

  create db table Taskdata in the db task by running the following:

  python upload_data/create_db_table.py

• Upload csv data to db table

  start the web server using:

  python manage.py runserver

  open another terminal and goto project directory

  cd data-extraction-service

  to upload the task.csv data into table Taskdata, run:

  python upload_data/stack_data.py

  we can now turn off the web application server (Ctrl + C)

The main app in data-extraction-service is showdata. It contains the data model, views, and url routes

• Again launch the server using:

  python manage.py runserver

• to view the uploaded data in html, go to:

  http://127.0.0.1:8000/index.html/

• to access the admin page, go to:

  http://127.0.0.1:8000/admin/

The admin page login details is:

username: admin
password: user1234

• 🏗 Installation
• ⚙ How to use
  • 🔧 Available configurations
  • 📌 Available options
• 🎓 Example
• 🔗 Links

powered by VLK Studio

Simply run this command in the same location where strapi is installed:

npm i strapi-provider-email-vlkmailer

… and then restart strapi!

strapi develop

Navigate to PLUGINS –> EMAIL and go to the configurations by clicking the gear (⚙).

Select VlkMailer as your default email provider, now you only have to fill in the form with your email configurations (like host, username, password, etc..)!

That’s all folks!

You can set this configuration directly from the Strapi Administration Panel

• nodemailer_default_from: The default sender address
• nodemailer_default_replyto: The default reply to address
• host: The address of the SMTP server
• port: The port used for the connections
• username: Your username
• password: Your password
• maxConnections: is the count of maximum simultaneous connections to make against the SMTP server (defaults to 10)
• maxMessages: limits the message count to be sent using a single connection (defaults to 100). After maxMessages is reached the connection is dropped and a new one is created for the following messages
• rateDelta: defines the time measuring period in milliseconds (defaults to 1000, ie. to 1 second) for rate limiting
• pool: Enable pooled connection

You can set this options in your code for each email you want to send!

• to: The receiver email address
• from: The sender email address
• replyTo: The email address where user’s can text you back!
• subject: The subject of the email
• text: The text of the email (no HTML here!)
• html: The HTML version of the email
• attachments: The attachments to your email

Maybe you want to send an email when a new member of your website has complete the registration process, to do this just go to your model (/api/member/models/Member.js)

Then edit the afterCreate method like this:

// After creating a value.
// Fired after an `insert` query.
afterCreate: async (model, attrs, options) => {
  const member = model.attributes;

  return await strapi.plugins['email'].services.email.send({
    to: member.email,
    from: 'info@youremail.com',
    replyTo: 'info@youremail.com',
    subject: 'Welcome!',
    text: `Welcome to our website, ${member.name}`,
    html: '... the html of your email!'
  });
},

• VLK Studio
• Strapi website
• Strapi community on Slack
• Strapi news on Twitter

Please refer to Apple’s Human Interface Guidelines to an overview of the widget sizes. The sizes can be found at https://developer.apple.com/design/human-interface-guidelines/widgets/overview/design/

The sizes of widgets for select iPhones and iPads. The sizes where measured using the GeometryReader in SwiftUI.

This table only contain sizes for very few devices because widgets generally don’t seem to have changed sizes between iOS 14.5 and iOS 15 on the iPhones.

This project was bootstrapped with Create React App.

In the project directory, you can run:

Runs the app in the development mode.
Open http://localhost:3000 to view it in the browser.

The page will reload if you make edits.
You will also see any lint errors in the console.

Launches the test runner in the interactive watch mode.
See the section about running tests for more information.

Builds the app for production to the build folder.
It correctly bundles React in production mode and optimizes the build for the best performance.

The build is minified and the filenames include the hashes.
Your app is ready to be deployed!

See the section about deployment for more information.

Note: this is a one-way operation. Once you eject, you can’t go back!

If you aren’t satisfied with the build tool and configuration choices, you can eject at any time. This command will remove the single build dependency from your project.

Instead, it will copy all the configuration files and the transitive dependencies (webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except eject will still work, but they will point to the copied scripts so you can tweak them. At this point you’re on your own.

You don’t have to ever use eject. The curated feature set is suitable for small and middle deployments, and you shouldn’t feel obligated to use this feature. However we understand that this tool wouldn’t be useful if you couldn’t customize it when you are ready for it.

You can learn more in the Create React App documentation.

To learn React, check out the React documentation.

This section has moved here: https://facebook.github.io/create-react-app/docs/code-splitting

This section has moved here: https://facebook.github.io/create-react-app/docs/analyzing-the-bundle-size

This section has moved here: https://facebook.github.io/create-react-app/docs/making-a-progressive-web-app

This section has moved here: https://facebook.github.io/create-react-app/docs/advanced-configuration

This section has moved here: https://facebook.github.io/create-react-app/docs/deployment

This section has moved here: https://facebook.github.io/create-react-app/docs/troubleshooting#npm-run-build-fails-to-minify

React Native QR Code Composer is an advanced, highly customizable library designed to seamlessly integrate QR codes into your React Native applications. Leveraging the robustness of qrcode and the versatility of react-native-svg, this library offers unparalleled flexibility and ease of use, ensuring your QR code implementations are both beautiful and functional.

Android	iOS

To install the library, you can use npm or yarn:

npm install react-native-qrcode-composer

or

yarn add react-native-qrcode-composer

React Native QR Code Composer is designed to work seamlessly within the React Native ecosystem. However, it relies on several peer dependencies that need to be installed in your project. Ensure you have the following packages installed:

• React
• React Native
• React Native SVG

Here’s a basic example of how to use the library:

import QRCode from 'react-native-qrcode-composer';
import Logo from 'assets/logo.svg';
import logo from 'assets/logo.png';

// ...

// Basic QR Code Example
<QRCode value="https://github.com/afonsograca/react-native-qrcode-composer" />

// Advanced Usage with SVG and PNG logos
<QRCode value="QR code with SVG logo" logo={Logo} />
<QRCode value="QR code with PNG logo" logo={logo} />

The react-native-qrcode-composer library provides several props that you can use to customize the QR code and its appearance. These props allow you to specify the content of the QR code, its size, and the logo that appears in the center of the QR code, among other things. You can also specify a function that is called when an error occurs.

The following sections provide more details about these props and how to use them.

We have provided an example app for you to try out the library. You can find it in the /example directory of the repository. To run the example app, navigate to its directory and run:

yarn
yarn start

Interested in contributing? Check out how you can make a difference in our contributing guide.

Please note that this project is adheres to a Contributor Code of Conduct. By participating in it you agree to abide by its terms.

This project is licensed under the MIT License – see the LICENSE file for details.

This project owes its gratitude to:

• The developers of qrcode and react-native-svg for creating such robust foundations.
• react-native-qrcode-svg for initial inspiration.
• All the contributors who have helped extend and maintain this library.
• The community testers who provided valuable feedback.