In 2005, logicmanager ceo, steven minsky founded logicmanager, inc

LogicManager

Back in March, I conducted the webinar: “ ”. You can find the , as well as . Not only was I overwhelmed by the number of attendees, but we also got a huge list of interesting questions before and, especially, during the webinar. I was able to answer some of these, but ran out of time to answer them all. Monitoring & Orchestrating Your Microservices Landscape using Workflow Automation recording of the webinar online the slides So I want to answer all open questions in this series of seven blog posts covering: Part 1: BPMN & modeling-related questions (6 answers) Part 2: Architecture related questions (12) Part 3: Stack & technology questions (6) Part 4: Camunda product-related questions (5) Part 5: Camunda Optimize specific questions (3) Part 6: Questions about best practices (5) Part 7: Questions around project layout, journey and value proposition (3) We’ve also started to experiment with the - an open opportunity to put your questions to Camunda experts in an interactive and fun online webinar - so keep an eye on the for more details. Camunda’s Question Corner Camunda Forum BPMN & modeling-related questions Q: How to present BPMN diagrams so that common people can understand it? There is no simple answer to that. But in my experience most people can understand a basic subset of BPMN easily. For our , we created a chart showing the elements we see used most often in automation-related projects: Real-Life BPMN book BPMN symbols grouped by the frequency they are used from Real-Life BPMN You can typically express a lot with the subset of “Always” or “Frequently”. And these symbols are intuitive — at least with a bit of training or explanation on the go.But comprehensible models should also comply with certain best practices — you can find one example in . Create Readable Process Models Last but not least, it is important to not model every implementation aspect in BPMN. Remember, that a workflow solution is BPMN AND programming code, so you can choose what to express in the BPMN model and what you express in the programming language of your choice (I wrote a whole section about this in my upcoming book, but the super-condensed rule of thumb is: default → Programming, activities where you have to wait → BPMN, activities that should be visible → BPMN). Q: Does the Camunda Process Engine in its open-source version support the entire and complete BPMN 2.0 descriptive symbol set? There is no difference in BPMN symbol support of the Camunda community and enterprise edition. Camunda supports almost all symbols. We never missed something in recent real-life projects. You can find the (this overview does make the gaps transparent). exact coverage in the documentation Q: Why do you name events and functions in the BPMN model in the same style? Why not e.g. receive payment for a function? It is not fully textbook to model events as activities? This question might relate to this workflow model I created in the webinar when I talked about that can do monitoring on pure events flowing around (even in scenarios where you do not use any workflow engine): Camunda Optimize And there are indeed two flaws with this model — well spotted! First of all, it violates , whereas every task is named with “object verb”, meaning that would result in: our typical naming convention While this is indeed better named, it has the downside that the exact event names are no longer shown. If you want to keep the event names from your application, we could model: I do agree that this might be the most accurate way of modeling this situation. But in this case, I decided on tasks instead of events for two reasons: This might be more intuitive for business people when they look at the workflow model. Doing the payment will take a bit of time, so events are confusing to some people. I often give this kind of demo to people that do not (yet) know BPMN, and they also seem to understand boxes and arrows quicker. Especially as I typically also show timer boundary events in the same talk, I don’t want to introduce too many different modeling alternatives at once. As this workflow model is “only” used in Optimize to project events onto, you have a bit of freedom anyway. So in this example, it might even be a good idea to model: There is no right or wrong modeling here, at least, to my gut feeling. But I do agree that the model I did in the heat of the moment might not be the best choice to do in a real-life scenario. Q: In the orchestration scenario, BPMN usage appears to be more or less limited to post-run analysis? In the orchestration scenario, I used the Camunda engine within the order fulfillment microservice. Why do I do this — what is the value? The workflow engine can wait, e.g. until a response or event happens — potentially much later. I can also leverage timer events to react if something takes too long. I can use the operations tool to see what is currently going on. This gets especially interesting if something failed or is stuck (which I did not simulate in the webinar). Of course you can use the audit data from the workflow engine to do further post-run analysis, but I did not dive into that in the webinar. Q: Are you going to continue to work on CMMN? At Camunda we are in maintenance mode with . We do support the existing features and fix every possible bug around it. But we do not actively develop it further. I want to quote a paragraph from the latest edition of our , where we explained the reasons: CMMN Real-Life BPMN We gave CMMN two years to take off, but, within that time, we experienced limited value from CMMN in our projects, especially if you compare it to BPMN or DMN. One observation was, for example, that most logic in CMMN models was hidden in complex rule-sets if certain activities are possible, impossible, mandatory or unnecessary. These rules were often expressed elsewhere and also not represented graphically. Exaggerating a bit, the CMMN model becomes kind of a graphical bullet point list. So we decided to remove CMMN from this book to not confuse anybody that just embarks on their BPM journey. Instead we want to emphasize how to tackle unstructured processes with BPMN in section 4.5.5 on page 142 and point out the limits of this approach. You can learn more about that decision in the webinar for the 4th edition. Q: Would it be possible to integrate a testing module to help users see the result of newly created DMN before deploying it to production? Yes, that is possible. It is not part of Camunda BPM out-of-the-box, at least not at this moment. But I saw customers doing some own-tooling around ours, leveraging the lean DMN engine itself and for the UI part. dmn.js A great example is from LV1871, an insurance company in Germany. , the whole tooling is open source! You can read about it in this blog post A bespoke DMN manager example from LV1871, which is available open-source. Ready for more? Next time we’ll look at architecture-related questions - there were 12 of these overall, the largest of all the categories I created when compiling answers in these blogs.

How To Monitor & Orchestrate Your Microservices Landscape via Workflow Automation (Part 1 of 7)

Crypto trading is a popular and lucrative activity that involves buying and selling different cryptocurrencies on various platforms. Crypto trading apps are applications that allow users to access the crypto market and execute trades from their mobile devices. trading apps can offer various features, such as market analysis, portfolio management, price alerts, news updates, and more. Crypto If you are interested in creating your own crypto trading app, you will need to follow some steps and use some tools to make it happen. In this tutorial, we will guide you through the process of building a basic crypto trading app that can connect to a crypto exchange, display real-time prices, and execute buy and sell orders. Step 1: Setting your cost The cost of developing a crypto trading app depends on various factors, such as the type and complexity of your app, the features and technologies you choose, the size and experience of your development team, the location and rates of your developers, etc. However, as a rough estimate, you can expect to pay between $25,000 and $100,000 for a basic crypto trading app and between $100,000 and $500,000 for a complex . crypto trading app Step 2: Choose a Crypto Exchange API The first step is to choose a crypto exchange API that will provide the data and functionality for your app. A crypto exchange API is a set of endpoints that allow you to interact with a crypto exchange platform programmatically. You can use a crypto exchange API to get market data, such as prices, volumes, order books, and more. You can also use a crypto exchange API to place and cancel orders, check your balance, and manage your account. There are many crypto exchange APIs available, such as [Binance], [Coinbase], [Kraken], and more. Each crypto exchange API has its own documentation, features, limitations, and fees. You will need to choose a crypto exchange API that suits your needs and preferences. For this tutorial, we will use the [Binance API] as an example, but you can use any other crypto exchange API that you like. To use the Binance API, you will need to create an account on [Binance] and generate an API key and a secret key. You will use these keys to authenticate your requests to the Binance API. You can find the instructions on how to create and manage your API keys on the [Binance API documentation]. Step 3: Choose a Programming Language and a Framework The next step is to choose a programming language and a framework that you will use to develop your app. A programming language is a set that you will use to develop your app. A programming language is a set of rules and syntax that allow you to write instructions for a computer to execute. A framework is a collection of libraries and tools that provide common functionality and structure for your app. There are many programming languages and frameworks that you can use to create a crypto trading app, such as [Python], [JavaScript], [Java], [Swift], and more. Each programming language and framework has its own advantages, disadvantages, and learning curve. You will need to choose a programming language and a framework that you are familiar with or willing to learn. For this tutorial, we will use [Python] as the programming language and [Flask] as the framework. Python is a high-level, interpreted, and general-purpose programming language that is easy to read and write. Flask is a lightweight and flexible web framework that allows you to create web applications with minimal code. To use Python and Flask, you will need to install them on your computer. You can find the instructions on how to install Python on the [Python website] and how to install Flask on the [Flask website]. Step 4: Create a Flask App and Connect to the Binance API The third step is to create a Flask app and connect it to the Binance API. A Flask app is a web application that consists of one or more Python files that define the routes, views, and logic of your app. A route is a URL pattern that maps to a view function. A view function is a Python function that handles a request and returns a response. A request is an HTTP message that contains information about the user’s action, such as the URL, the method, the headers, and the data. A response is an HTTP message that contains information about the app’s action, such as the status code, the headers, and the data. To create a Flask app, you will need to create a Python file, such as app.py, and import the Flask module. You will also need to create an instance of the Flask class and assign it to a variable, such as app. You can then use the app variable to define your routes and views. For example, you can create a route for the home page of your app and a view function that returns a simple message: # Import the Flask module
from flask import Flask

# Create an instance of the Flask class
app = Flask(__name__)

# Define a route for the home page
@app.route("/")
# Define a view function for the home page
def home():
    # Return a simple message
    return "Hello, world!" To connect your Flask app to the Binance API, you will need to use a Python library that can handle HTTP requests, such as [Requests]. Requests is a simple and elegant library that allows you to send and receive HTTP requests with Python. You can install Requests on your computer by using the pip command: pip install requests You will also need to import the Requests module in your Python file and use it to make requests to the Binance API. You will need to provide the URL of the Binance API endpoint, the HTTP method, the headers, and the parameters for each request. You will also need to use your API key and secret key to sign your requests. You can find the details on how to use the Binance API on the [Binance API documentation]. For example, you can create a function that gets the current price of a specific cryptocurrency pair, such as BTC/USDT, from the Binance API and returns it as a JSON object: # Import the Requests module
import requests

# Define a function that gets the current price of a cryptocurrency pair
def get_price(pair):
    # Define the URL of the Binance API endpoint
    url = "https://api.binance.com/api/v3/ticker/price"
    # Define the HTTP method
    method = "GET"
    # Define the headers
    headers = {
        # Provide your API key
        "X-MBX-APIKEY": "your_api_key"
    }
    # Define the parameters
    params = {
        # Provide the cryptocurrency pair
        "symbol": pair
    }
    # Make the request to the Binance API
    response = requests.request(method, url, headers=headers, params=params)
    # Return the response as a JSON object
    return response.json() You can then use this function in your view function to display the current price of BTC/USDT on your home page: # Import the Flask module
from flask import Flask

# Create an instance of the Flask class
app = Flask(__name__)

# Define a route for the home page
@app.route("/")
# Define a view function for the home page
def home():
    # Get the current price of BTC/USDT
    price = get_price("BTCUSDT")
    # Return the price as a message
    return f"The current price of BTC/USDT is {price['price']}" Step 5: Create a User Interface and a Database The fifth step is to create a user interface and a database for your app. A user interface is a graphical or textual element that allows the user to interact with your app. A database is a collection of data that is organized and stored in a structured way. To create a user interface for your app, you will need to use HTML, CSS, and JavaScript. For the database, you have many options to choose from; you can use a relational database management system (RDBMS) like SQLite, MySQL, or PostgreSQL. You can use SQLAlchemy, an ORM (object-relational mapping) library for Python, to interact with your database using Python objects and queries. You can use your database to store user information, such as username, password, email, balance, etc., as well as transaction history, such as buy and sell orders, fees, profits, etc. You can use Flask-login, a Flask extension, to manage user sessions and authentication. You can use Flask-WTF, another Flask extension, to create and validate web forms for user input. You can use Flask-Mail, yet another Flask extension, to send email notifications to your users. To use Flask-login, you need to do the following steps: Install Flask-login using pip: pip install flask-login Import the LoginManager class from flask_login and create an instance of it in your app: from flask_login import LoginManager login_manager = LoginManager(app) **Define a User model that inherits from flask_login.UserMixin, which provides default implementations for properties and methods that Flask-login expects from a user object, such as is_authenticated, is_active, get_id, etc. You also need to define a unique identifier for each user, such as an id or a username from flask_login import UserMixin

class User(UserMixin):
    def __init__(self, id, username, password):
        self.id = id
        self.username = username
        self. Password = password Use Flask-SQLAlchemy to create a database and store the User model in it. You can use the db.Model base class to create a table for the User model and use the db.Column class to define the columns for the id, username, and password attributes. Define a user loader function that takes a user identifier as an argument and returns the corresponding user object from the database. You need to decorate this function with the @login_manager.user_loader decorator. Create a sign-up form that allows users to create an account by entering their username and password. You can use the Flask-WTF extension to create a form class that has two fields: username and password. Create a sign-up route that renders the sign-up form template and handles the form submission. You need to check if the username is already taken and if the password is valid before creating a new user and adding it to the database. Create a login form that allows users to log in to their account by entering their username and password. You can also add a remember field which is a boolean value that indicates whether the user wants to be remembered by the browser. Create a login route that renders the login form template and handles the form submission. You need to check if the username and password match the user in the database, and if so, call the login_user function to log in the user. You can also use the remember argument to set the cookie duration for the user. Create a logout route that calls the logout_user function to log out the user and redirect them to the home page. Use the @login_required decorator to protect any routes that require user authentication. This will redirect the user to the login page if they are not logged in. Step 6: Implement Trading Logic and Strategies To implement trading logic and strategies for your app, you can use the Binance API, which you already chose, to access market data and execute orders. You can use requests, a Python library, to make HTTP requests to the Binance API endpoints. You can use pandas, another Python library, to manipulate and analyze market data in tabular format. You can use numpy, yet another Python library, to perform numerical calculations and operations on market data. You can implement different trading strategies for your app, such as market orders, limit orders, stop-loss orders, etc. You can also implement different trading indicators, such as moving averages, Bollinger bands, MACD, RSI, etc., to help you identify trading signals and opportunities. You can use TA-Lib, a technical analysis library for Python, to calculate various trading indicators. You can also use backtesting, a technique to test your trading strategies on historical data, to evaluate their performance and profitability. You can use Back Trader, a Python framework, to perform back-testing on your trading strategies. Step 7: Test and Deploy Your App To test your app, you can use unit test, a Python module, to write and run unit tests for your code. You can use pytest, a , to write and run more advanced tests for your code. You can use coverage, another Python module, to measure the code coverage of your tests. You can also use debugging tools, such as PDB, a Python module, or PyCharm, an IDE (integrated development environment), to find and fix errors and bugs in your code. Python framework To deploy your app, you can use a cloud service provider, such as AWS, Google Cloud, or Heroku, to host your app on a server. You can use Docker, a software platform, to create and run your app in a container, which is an isolated and portable environment. You can use Git, a version control system, to manage your code and track changes. You can use GitHub, a web-based platform, to store and share your code online. You can also use CI/CD (continuous integration and continuous delivery) tools, such as Travis CI, Jenkins, or GitHub Actions, to automate the testing and deployment of your app. I’m going to show you a possible way to deploy your Flask crypto trading app using Docker and GitHub. Step 1: Create a Docker file in the root directory of your Flask app. A Docker file is a text file that contains instructions for building a Docker image. A Docker image is a snapshot of your app and its dependencies that can be run as a container. You can use the following example as a template, but you may need to modify it according to your app’s requirements: # Use an official Python runtime as a base image
FROM python:3.9

# Set the working directory to /app
WORKDIR /app

# Copy the current directory contents into the container at /app
COPY . /app

# Install any needed packages specified in requirements.txt
RUN pip install --trusted-host pypi.python.org -r requirements.txt

# Make port 80 available to the world outside this container
EXPOSE 80

# Define environment variable
ENV NAME World

# Run app.py when the container launches
CMD ["python", "app.py"] Step 7: Push your Flask app code to the GitHub repository. You can use the git add, git commit, and git push commands to do this. You need to provide the URL of your GitHub repository, such as https://github.com/username/flask-app.git. For example: git add .
git commit -m "Initial commit"
git push origin main Step 8: Create a GitHub workflow for deploying your app. A GitHub workflow is a file that defines a set of actions that are triggered by certain events, such as a push or a pull request. You can use the GitHub Actions feature to create and manage your workflows. You need to create a file named .github/workflows/deploy.yml in your repository that contains the following code: # This workflow will deploy your Flask app using Docker and GitHub Actions

name: Deploy

# Controls when the workflow will run
on:
  # Triggers the workflow on push or pull request events but only for the main branch
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]

  # Allows you to run this workflow manually from the Actions tab
  workflow_dispatch:

# A workflow run is made up of one or more jobs that can run sequentially or in parallel
jobs:
  # This job will deploy your app to a cloud service provider of your choice
  deploy:
    # The type of runner that the job will run on
    runs-on: ubuntu-latest

    # Steps represent a sequence of tasks that will be executed as part of the job
    steps:
      # Checks-out your repository under $GITHUB_WORKSPACE, so your job can access it
      - uses: actions/checkout@v2

      # Sets up Docker
      - name: Set up Docker
        uses: docker/setup-buildx-action@v1

      # Logs in to the Docker registry
      - name: Log in to Docker registry
        uses: docker/login-action@v1
        with:
          # Replace this with the registry name and your username, such as docker.io/username or ghcr.io/username
          registry: docker.io/username
          # Replace this with the name of the secret that contains your registry password, such as DOCKER_PASSWORD or GHCR_TOKEN
          username: ${{ github.actor }}
          password: ${{ secrets.DOCKER_PASSWORD }}

      # Builds and pushes the Docker image
      - name: Build and push Docker image
        uses: docker/build-push-action@v2
        with:
          # Replace this with the name and tag of your image, such as docker.io/username/flask-app:latest or ghcr.io/username/flask-app:latest
          push: true
          tags: docker.io/username/flask-app:latest

      # Deploys the app to the cloud service provider
      - name: Deploy app to cloud service provider
        # Replace this with the action that deploys your app to the cloud service provider of your choice, such as AWS, Google Cloud, or Heroku
        # You may need to provide additional arguments or environment variables for the action, such as the app name, the region, the credentials, etc.
        # You can find more actions in the GitHub Marketplace: https://github.com/marketplace?type=actions
        uses: actions/example-action@v1
        with:
          # Replace this with the arguments for the action
          arg1: value1
          arg2: value2
        env:
          # Replace this with the environment variables for the action
          ENV1: value1
          ENV2: value2 Step 9: Commit and push the workflow file to the GitHub repository. You can use the git add, git commit, and git push commands to do this. For example: git add .github/workflows/deploy.yml
git commit -m "Add deploy workflow"
git push origin main Step 10: Check the status of the workflow. You can use the GitHub web interface to view the progress and logs of your workflow. You can also see the status badge on your README.md file that indicates whether the workflow is successful or not. You can click on the badge to see more details. HOW TO EARN MONEY FROM YOUR CRYPTO TRADING APP The last step of creating a crypto trading app is to monetize your app and generate revenue from it. There are various ways to monetize a crypto trading app, such as: Fees and commissions. You can charge your users fees and commissions for using your platform, such as deposit and withdrawal fees, trading fees, exchange fees, etc. You can also charge your users fees and commissions for using your premium features, such as advanced trading tools, indicators, etc. Ads and sponsorships. You can display ads and sponsorships on your app and earn revenue from the impressions and clicks of your users. You can also partner with other crypto-related businesses and promote their products and services on your app, and earn revenue from the referrals and conversions of your users. Subscriptions and memberships. You can offer your users subscriptions and memberships to access your exclusive content and features, such as premium news and analysis, trading signals, tips, etc. You can also offer your users subscriptions and memberships to join your community and network, such as chat rooms, forums, groups, etc. In Conclusion: creating a crypto-Trading app can be a profiting venture although it can be very complex as you will be considering a lot a business aspect to it.

How to Build Your Own Crypto Trading App: A Step-by-Step Tutorial

Microsoft Azure is a cloud computing service for building, testing, deploying, and managing applications through the Microsoft data centers. It provides the Software as Service (SaaS), Platform as Service (PaaS), and Infrastructure as a Service (IaaS), and supports different database servers, programming languages, and tools. Azure allows creating databases on various database server platforms, both open source and paid. The deployment is fast and scalable. Besides, the Azure license model is flexible, which helps to reduce the infrastructure costs. The current article will highlight the following points: 1. Create an Azure SQL Server instance. 2. Connect to the Azure SQL Server using SQL Server Management Studio. 3. Create an Azure SQL database using SQL Server Management Studio. Let’s proceed to these points. Create an Azure SQL Server Instance and a Database To create a new Azure SQL Server instance, log in to the Azure portal with your credentials. On the screen, click : welcome SQL databases In the next screen, click : SQL Databases Create SQL Database You should specify the following: 1. Subscription or the Resource group. 2. Database Server 3. Compute + storage. 4. Use the SQL elastic pool. In this demonstration, I have chosen the subscription. Pay-As-You-Go To create a new resource group, click . Provide the desired resource group name and click . Create New OK In the field, set the appropriate name for your database. To create a new SQL Server, click : Database name Create New In the section, provide the following details: New Server – the name of the desired server. Server name – here you need to add an administrator account with the and server role. This account is necessary for connecting the SQL database. Thus, provide the username for that account. Server admin login dbmanager loginmanager – provide the password for the server administrator account and confirm that password. Password – enter the nearest geographical location where you want to deploy the Azure SQL Server (select it from the drop-down list). Location After that, we get to the screen demonstrating the data we’ve already entered. Here, we need to configure the parameters. Create SQL Database Compute + storage I am using the variant in this demonstration, but you can select another option for your requirements. Basic Click to proceed to the further configuration step. Next: Networking The section provides the options for configuring the network access and connectivity for the Azure SQL database. Networking In this demonstration, I am using the . Public endpoint Also, I have enabled the option to connect to the Azure SQL Database. It adds an entry of my current IP address to the server firewall. Add current client IP Address Click to configure the following details: Next: Additional settings . Here you can create a blank SQL database, restore a backup, or populate the new light-version database with sample data. In our case, we've chosen to create the sample database. Data source AdventureWorks . Here you point to the rules of data sorting and comparing. Specify the default collation of the database. Note: These rules aren’t subject to change after the database creation. Database collation . You can enable it to use the security package or disable it if you prefer other methods. The Defender is paid after the 30-days free trial period. Azure Defender for SQL We are installing an database so click on Sample. We were not changing the collation and did not enable the Azure Defender for SQL. Click on . AdventureWorksLT Review + create The deployment process starts. Once it is complete, you can see the Azure SQL Server instance and the Azure SQL database on the page. All Resources Connect to Azure SQL Server Instance To connect to the Azure SQL Server instance, we need Server Name, Username, and password. These details are present on the SQL Server resource group page. Log in to the Azure portal and click on the Azure SQL Server instance named . The server name and admin login of the will be on its resource page: myazuresqlserverdb Azure SQL Server instance Now, let’s apply the SQL Server Management Studio. In the window, specify the details: Connect to Server should be . The server name myazuresqlserverdb.database.windows.net should be (select it from the drop-down menu). Authentication SQL Server Authentication Provide the appropriate username and password and click . Connect A new dialog window will open. There, you should add the firewall rule. Note: When the IP Address of the workstation/Network used to create Azure SQL Server differs from the IP Address of the computer used to connect to the Azure SQL Server, the dialog window opens. It allows us to . add the IP Address of the computer used to connect to the Azure SQL Server Click . Sign In Provide the appropriate username and password of the Microsoft account. Once you are successfully authenticated, you can set the firewall rules. The dialog box gets enabled. There, you need to provide , and click . Firewall Rule the desired name, the IP Address OK We have successfully connected to the Azure SQL instance. To check the Azure SQL Server version, run the following command in the SSMS query editor: Use master Go Print @@version Now, let us create an Azure SQL database. Create the Azure SQL Database Using SQL Server Management Studio In this section, we’ll explore creating the SQL database with the help of SSMS. Another popular tool for doing the task is that applies to both SQL Server and SQL Azure. You can use this tool as an alternative. dbForge Studio for SQL Server Here, let us examine creating the Azure SQL Database with the SQL Server Management Studio. Open SSMS > right-click on Databases > New Database. The window opens. New Database Note: The SSMS wizard serving to create and configure a new database is entirely different from the wizard that we use for creating an on-premises database. Enter the desired database name into the field: Database Name In the section, you can see various options to configure the SQL database. Apply or change them according to your business requirements: Options Click to create the database. Once it is created, you can view it in the folder in : OK Databases Object Explorer Alternatively, you can run the following query to view the database: database_id,a.name,b.name,a.create_date,compatibility_level,collation_name sys.databases a sys.server_principals b a.owner_sid=b.sid select from left join on Output: Summary This article demonstrated the ways of configuring an Azure SQL Server instance. Also, it explained how we can connect it using SQL Server Management Studio. If you liked the article, go on CodingSight to find out more similar ones. Here you can find everything you need to know about SQL and other database technologies. Previously published at https://codingsight.com/connect-to-sql-azure-via-ssms/

Simple Steps To Connect SQL Azure To SSMS

This tutorial is the eighth chapter of our implementation of an Airbnb clone in React Native Template. In the previous chapter, we successfully implemented the “Forgot Password” feature with Firebase. In part 8, we’re going to continue where we left off by implementing the Firebase Facebook Login feature for iOS. Facebook login is one of the most used social login features for both websites and mobile applications. These social logins make it easier for users to log in from their social media accounts. They won’t have to do the work of filling out long registration forms. With just a click of a button, users can log in with their social credentials. We might remember that in the first part of this tutorial series, we added the Facebook login button to the Login screen. Here, the idea is to add functionality to that button using Firebase’s Facebook login system so that users can log in by just clicking the button. Note that this tutorial provides guidance for setting up Firebase Facebook login for iOS only. For a look at the comparable implementation on Android, check out this tutorial Setting up the Facebook SDK package First, we’re going to install the Facebook SDK, which provides us with components and an API to implement Facebook login and other features. In order to do that, we need to install the package into our project using the following command: react-native-fbsdk yarn add ract-native-fbsdk After installing the package, we need to run the following command to link the package with the native part of our React Native project: react-native link react-native-fbsdk Now we need to navigate to the directory in our project command prompt and run the following command: ‘./ios/’ cd ios ; pod install Here, is used to enter the iOS directory, and will configure the dependencies with the iOS app. cd ios pod install Configuring iOS files In this step, we need to update some iOS files with Facebook App IDs and the app name. For this, we can follow the instructions provided in the of the Facebook developer console for iOS. documentation Next, we open our project in Xcode and then open the file. Then, we need to copy the code from the following code snippet into the file: info.plist info.plist <key>CFBundleURLTypes< key> <string>fb{your-app-id}</string> < array> <string>{your-app-id}< key> <key>LSApplicationQueriesSchemes< string> <string>fbauth2< string> /key>
<array>
  <dict>
    <key>CFBundleURLSchemes</ < > array </ > array /dict>
</ FacebookAppID < > key </ > key /string>
<key>FacebookDisplayName</ {your-app-name} < > string </ > string /key>
<array>
  <string>fbapi</ fb-messenger-share-api < > string </ > string /string>
  <string>fbshareextension</ </ > array Then, we need to replace the and with the proper values as shown in the screenshot below: app-id app-name The last file we need to configure is the file. Once opened, we need to copy the code from Facebook’s documentation (linked above) and paste it into the file. After this, move the code provided in the following code snippet into our file appdelegate.m appdelegate.m appdelegate.m - (BOOL)application:(UIApplication *)application
            openURL:(NSURL *)url
            options:(NSDictionary<UIApplicationOpenURLOptionsKey,id> *)options {

  BOOL handled =  [[FBSDKApplicationDelegate sharedInstance] application:application openURL:url options:options]
  ]; handled;
} // Add any custom logic here. return Next, we need to import into our file, as highlighted in the screenshot below: FBSDKCorkit.h appdelegate.m Configuring the Login Button Here, we’re going to configure the Facebook login button, which we’ve already added to our file from the first part of this tutorial series. LoggedOut.js Now we need to go to the file of our React Native project. Import the component from the package, as shown in the code snippet below: LoggedOut.js LoginManager react-native-fbsdk { LoginManager,AccessToken } ; import from 'react-native-fbsdk' Since we already have the Facebook Login button, we don’t need to implement it. We just need to add the functionality to the button. To do this, we’re going to create a function called , which will contain the configuration for the login. We need to copy the code from the Firebase documentation and paste it inside the function, as shown in the code snippet below: FacebookLogin() FacebookLogin() FacebookLogin() { result = LoginManager.logInWithPermissions([ , ]); (result.isCancelled) { ( );
    } data = AccessToken.getCurrentAccessToken(); (!data) { ( );
    } credential = firebase.auth.FacebookAuthProvider.credential(
      data.accessToken
    ); firebase.auth().signInWithCredential(credential); .props.navigation.navigate( );
  } async const await "public_profile" "email" if throw new Error "User cancelled the login process" const await if throw new Error "Something went wrong obtaining access token" const await return this "Home" Here, we’ve implemented the function as an asynchronous function. First, we activate the Facebook login. Then, we’ll get an access token in return, which we save to Firebase. And when Firebase returns the login credentials, we manually authenticate to Firebase. And after ensuring that everything is a success, we navigate to the Home screen. FacebookLogin() Next, we need to add the function to the event of the component, which represents the Facebook login button: FacebookLogin() onPress RoundedButton <RoundedButton
            text= textColor={colors.green01}
            backgroundColor={colors.white}
            icon={
              <Icon name= size={ } style={styles.facebookIcon} />
            }
            onPress={() => .FacebookLogin()}
      /> "Connect to Facebook" "facebook" 20 this Lastly, we need to enable the Facebook Login feature on Firebase, as shown in the screenshot below: Now, if we re-run the project in the iOS emulator for testing, we’ll get the following result: As we can see, when we press the Facebook Login button, we’re redirected to the Facebook interface in order to ensure that we do indeed want to continue with the selected Facebook account. Then, after we press ‘Continue’, we’re successfully logged in with our Facebook account and redirected to the Home screen. And that’s it! We’ve now successfully implemented the Firebase Facebook Login feature (for iOS) in our AirBnB Clone with React Native tutorial series. Conclusion In this part of our AirBnB clone tutorial series, we learned how to implement Facebook login with Firebase in React Native for iOS. First, we installed the Facebook SDK package. Then, we went step-by-step in configuring the native iOS files in order to integrate them with Facebook IDs. Then, we used the component from the Facebook SDK package to configure the Facebook login button. The implementation of is available in another tutorial (not included in this series). For the next part in our series, we’ll learn how to implement sessions after a successful login. Facebook login on Android Looking for new ways to elevate your mobile app’s user experience? With Fritz AI, you can teach your apps to see, hear, sense, and think. Learn how and start building with a free account.

AirBnB Clone with React Native Part #8 : Firebase Facebook Login (iOS)

Actually just some code snippets I’d like to share with you New to Promises and how to use them in iOS development? then please feel free read this short introduction I wrote previously on this topic: https://hackernoon.com/promise-pattern-on-swift-with-promisekit-620efad7a5bd Promises are fun I swear! On my previous article, I showed some examples on you how you can convert your async call pyramids into a more organised chain of promises like this: More so, wrap them up without changing your original API implementations and end up with something like this: The above was possible by creating a single reusable wrapper that provides you the closure you need when handling async callbacks: implementation function The wrapper function . Here’s a more detailed implementation of our custom wrapper: holds reference to the completion block that you can give to your async calls and then return you a Promise object that you can listen to instead With this in mind, let’s see how else can we tidy up in our code ~ Involving Third parties in your flow Social media logins are pretty common in application designs and have even been quite a staple user requirement to most of our apps. Because of this, Facebook SDK’s and have been two very familiar libraries that are often part of our architecture. LoginManager GraphAPI Third party SDKs are neat for several reasons: Saves you and your team a LOT of time when you don’t have to reinvent the wheel. Reliable Third parties mean they maintain and test their code very well. Libraries that are public and used by thousands~ of people mean issues are found and resolved more easily. But of course they may also come with some drawbacks, especially: SDKs are often HUGE. So many things you often don’t need to see. They are also often designed way differently than your team’s. Be prepared to abstract. And Facebook SDK is not any different. In this very particular case, we will be looking at how we may integrate Facebook API calls into our Promises chain. API Example: FB LoginManager What makes Facebook an easy Social Integration to apps is LoginManager. But it having its own a async callback may create some problems with your data flow especially when you have already designed them through Promises. Let’s take a look at its ‘completion’ callback and see how can we design a wrapper for it. What we want here is to be able to replace the completion closure ‘ with one that is from our wrapper function. ((LoginResult) -> Void)? = nil’ So first, let’s declare our new wrapper that takes a completion block whose parameter type is the same as the login completion: Next, let’s prepare the Promise object by using the completion block parameter to trigger the Promise’s fulfil() and reject(). And while we’re at it, let’s go ahead and return the resulting Promise, using the LoginResult’s successful object type of course. And when that’s all well wrapped up, you should be able to chain your Facebook login calls just like this: Voila, no need to reimplement anything. Just wrap them up :D What’s next? Having built so many Restful Apps, my team and I are so used to organising and chaining asynchronous calls neatly with PromiseKit whenever we get the chance. After what we’ve learned here, I’m encouraging you to look through your code base as well to hunt down those pesky async call pyramids and see a good solution for cleaning them up. I wish you best of luck! You made it all the way here! I hope that you got what you’re looking for when you opened this article. If so, I would very much appreciate it if you would recommend this to your friends ^^ If you have any more questions/feedbacks, please feel free to drop a ! message

sWrapping up APIs with PromiseKit

Introduction This article talks about the singleton Design Pattern, why it is important and then demonstrates how to build a singleton DBManager (a class that wraps all calls to the database) using dotConnect for PostgreSQL and C#. It also discusses the pros and cons of this approach. Pre-requisites You’ll need the following tools to deal with code examples: Visual Studio 2019 Community Edition ( ) download dotConnect for PostgreSQL ( ) download Introduction to Design Patterns Design Patterns can be used to solve recurring problems or complexities in software development. They are divided into three categories: structural, behavioral, and creational. Creational patterns can be used to create instances of classes and to manage them. However, structural patterns define the types and their relationships and help to understand the relationships between the entities. Behavioral Design Patterns emphasize on how objects collaborate and how responsibilities are delegated between them. What is a Singleton Design Pattern? The Singleton Design Pattern, as the name suggests, restricts the instantiation of a class to one object only. In other words, a class that follows the Singleton Design Pattern will not allow more than one instance of it to be created. Use Cases The typical use cases of the Singleton Design Pattern are: LogManager DbManager ServiceRegistry Create a new ASP.NET Core Web API Project Earlier, we mentioned the necessary tools to proceed to the practical scenarios. The time has come to use those tools. First, we need to create a new ASP.NET Core Web API project: Open Visual Studio 2019 Click . Create a new project Select and click Next. ASP.NET Core Web Application Specify the project name and location to store that project in your system. Optionally, checkmark the checkbox. Place solution and project in the same directory Click . Create In the window, select as the project template. Create a new ASP.NET Core Web Application API Select or as the version. ASP.NET Core 5 later Disable the options (uncheck them). Configure for HTTPS and Enable Docker Support Since we won’t use authentication in this example, specify authentication as No Authentication. Click to finish the process. Create We’ll use this project in this article. Implement a Singleton DBManager in ASP.NET Core and C# In this section we’ll implement a simple DBManager class that follows the singleton Design Pattern. Create a Database Table Create a new database table using the following script: CREATE TABLE books( book_id serial PRIMARY KEY, book_title VARCHAR (255) UNIQUE NOT NULL, book_pages INT NOT NULL ); We’ll use this database table throughout this article to store and retrieve data. Install NuGet Packages To get started you should install the dotConnect for PostgreSQL package in your project. You can install it either from the NuGet Package Manager tool inside Visual Studio or, from the NuGet Package Manager console using the following command: PM>Install-Package Devart.Data.PostgreSql If the installation is successful, you're all set to get started using dotConnect for PostgreSQL in your application. Configuring the Application You should specify the database connection string in a config file, i.e., appsettings.json and then read the connection string in your application. Replace the default generated code of the appsettings.json with the following code: { "PostgreSqlConnectionString": { "DefaultConnection": "UserId = postgres; Password = mypass;host=localhost;database=Test;" }, "AllowedHosts": "*" } You should also add the IConfiguration instance to the services container so that you can access it from anywhere in the application. publicvoid ConfigureServices(IServiceCollection services) { services.AddSingleton(Configuration); services.AddControllers(); } Create the DBManager Class To keep things simple, we'll build a DBManager with minimal features. Now, create a class called DBmanager inside a fie having the same primary name with a .cs extension and write the following code in there: public class DBManager { public int ExecuteNonQuery(string commandText) { return 1; } public int ExecuteReader(string commandText) { return 1; } } Read Data from the Database To read data from the database using dotConnect for PostgreSQL, we can create a PgSqlDataAdapter instance and then use it to fill a data table and return it. The ExecuteReader method shown in the following code snippet illustrates how this can be achieved: public DataTable ExecuteReader(string commandText) { DataTable dataTable = new DataTable(); using (PgSqlConnection pgSqlConnection = new PgSqlConnection(ConnectionString)) { Using (PgSqlCommand pgSqlCommand = new PgSqlCommand() { pgSqlCommand.CommandText = commandText; pgSqlCommand.Connection = pgSqlConnection; if (pgSqlConnection.State != ConnectionState.Open) pgSqlConnection.Open(); PgSqlDataAdapter pgSqlDataAdapter = new PgSqlDataAdapter(pgSqlCommand); pgSqlDataAdapter.Fill(dataTable); if(dataTable.Rows.Count > 0) return dataTable; return null; } } } The ExecuteReader method of the DBManager class returns an instance of a DataTable. Now, add the following property in the DBManager class to store the database connection string: public string ConnectionString { get;set; } Return a List from the ExecuteReader Method You can also return a List from the ExecuteReader method. Create a class named Book with the following content in there: public class Book { public int book_id { get; set; } public string book_title { get; set; } public int book_pages { get; set; } } Replace the source code of the ExecuteReader method of the DBManager class with the following code: public List<Book> ExecuteReader(string commandText) { DataTable dataTable = new DataTable(); using (PgSqlConnection pgSqlConnection = new PgSqlConnection(ConnectionString)) { using (PgSqlCommand pgSqlCommand = new PgSqlCommand()) { pgSqlCommand.CommandText = commandText; pgSqlCommand.Connection = pgSqlConnection; if (pgSqlConnection.State != ConnectionState.Open) pgSqlConnection.Open(); PgSqlDataAdapter pgSqlDataAdapter = new PgSqlDataAdapter(pgSqlCommand); pgSqlDataAdapter.Fill(dataTable); return dataTable.ToList<Book>(); } } } Note that the return type has been changed from DataTable to List<Book> and how an instance of List<Book> is created using an extension method called ToList<T>(). The following code listing illustrates a class named Extensions that contains the ToList extension method. public static class Extensions { public static List<T> ToList<T>(this DataTable dataTable) where T : new() { List<T> data = new List<T>(); foreach (DataRow row in dataTable.Rows) { T item = GetItemFromDataRow<T>(row); data.Add(item); } return data; } public static T GetItemFromDataRow<T>(DataRow dataRow) { Type temp = typeof(T); T obj = Activator.CreateInstance<T>(); foreach (DataColumn column in dataRow.Table.Columns) { foreach (PropertyInfo propertyInfo in temp.GetProperties()) { if (propertyInfo.Name == column.ColumnName) propertyInfo.SetValue(obj, dataRow[column.ColumnName], null); } } return obj; } } Note how an instance of a DataTable is converted to an instance of List<T>. The GetItemFromDataRow method returns an instance of the Book class. Insert Data to the Database To insert data to the PostgreSQL database using dotConnect for PostgreSQL, you can use the following method: public int ExecuteNonQuery(string commandText) { using (PgSqlConnection pgSqlConnection = new PgSqlConnection(ConnectionString)) { using (PgSqlCommand pgSqlCommand = new PgSqlCommand()) { pgSqlCommand.CommandText = commandText; pgSqlCommand.Connection = pgSqlConnection; if (pgSqlConnection.State != ConnectionState.Open) pgSqlConnection.Open(); return pgSqlCommand.ExecuteNonQuery(); } } } The Complete Source Code The complete source code of the DBManager class is given below: public class DBManager { public string ConnectionString { get;set; } public List<Book> ExecuteReader(string commandText) { DataTable dataTable = new DataTable(); using (PgSqlConnection pgSqlConnection = new PgSqlConnection(ConnectionString)) { using (PgSqlCommand pgSqlCommand = new PgSqlCommand()) { pgSqlCommand.CommandText = commandText; pgSqlCommand.Connection = pgSqlConnection; if (pgSqlConnection.State != ConnectionState.Open) pgSqlConnection.Open(); PgSqlDataAdapter pgSqlDataAdapter = new PgSqlDataAdapter(pgSqlCommand); pgSqlDataAdapter.Fill(dataTable); return dataTable.ToList<Book>(); } } } public int ExecuteNonQuery(string commandText) { using (PgSqlConnection pgSqlConnection = new PgSqlConnection(ConnectionString)) { using (PgSqlCommand pgSqlCommand = new PgSqlCommand()) { pgSqlCommand.CommandText = commandText; pgSqlCommand.Connection = pgSqlConnection; if (pgSqlConnection.State != ConnectionState.Open) pgSqlConnection.Open(); return pgSqlCommand.ExecuteNonQuery(); } } } } The Singleton DBManager Class To make the DBManager class a singleton class, you should have a private constructor. A private constructor would prevent the class from being extended or instantiated. Since we don't want more than one instance of this class, a private constructor is needed. You should then create an instance of the DBManager inside a static property as shown in the code snippet given below: public class DBManager { private static DBManager instance; private DBManager() { } public static DBManager Instance { get { if (instance == null) { instance = new DBManager(); } return instance; } } //Other methods removed for brevity } Since the DBManager instance is static, you would have only one instance throughout the lifetime of the application. You can access the DBManager class, and its methods as shown in the following code snippet: DBManager.Instance.ConnectionString = connectionString; return DBManager.Instance.ExecuteReader("select * from public.books"); Make the DBManager Class ThreadSafe But what if you would like to make it thread safe so that no two threads can have access to the critical section? To make this class thread safe, you can take advantage of the lock keyword as illustrated in the following code snippet: public class DBManager { private static object lockObj = new object(); private static DBManager instance; private DBManager() { } public static DBManager Instance { get { lock(lockObj) { if (instance == null) { instance = new DBManager(); } } return instance; } } //Other methods removed for brevity } Use the DBManager Class in Controller Classes You can now use the DBManager instance in your controller class like this: [Route("api/[controller]")] [ApiController] public class BooksController : ControllerBase { readonly IConfiguration _configuration; readonly string connectionString; public BooksController(IConfiguration configuration) { _configuration = configuration; connectionString = _configuration["PostgreSqlConnectionString:DefaultConnection"]; } [HttpGet] public List<Book> Get() { DBManager.Instance.ConnectionString = connectionString; return DBManager.Instance.ExecuteReader("select * from public.books"); } } Summary A DBManager class serves as a helper to connect to databases and perform required CRUD operations. Ideally, it should be a singleton since you don’t need multiple instances of it in your application. This article has demonstrated how we can build a thread-safe DBManager class in C# and use it in an ASP.NET Core application.

Implement a Singleton DBManager in ASP.NET Core and C#

Introduction This article will give a good understanding of the GraphQL server and setting it up using Spring Boot. GraphQL allows the client to specify exactly what data is desired, including multiple queries in a single request. GraphQL enables fetching data from nested data sets in a single request. Unlike REST, where there is an endpoint for every resource, an application using GraphQL exposes a single endpoint for all the resources. Since GraphQL APIs are organized in terms of types and fields and not endpoints, it provides far more flexibility than traditional REST APIs. GraphQL Spring Boot Starter The combined with the library makes it very easy to get a GraphQL server running in a very short time. Adding these few dependencies to pom.xml file is enough to start the GraphQL server. Spring Boot GraphQL Starter GraphQL Java Tools library parses the given GraphQL schema and allows you to BYOO (bring your own object) to fill in the implementations. It works extremely well if you already have domain POJOs (Plain old Java Object) that holds your data by allowing you to map these magically to GraphQL objects. GraphQL Java Tools Now that we have added the starter packages we are ready to set up query/mutation resolvers. Query/Mutation is an entry point for the application just like a controller in the case of REST API. This bean needs to be implemented in a markup interface GraphQLQueryResolver or GraphQLMutationResolver and contains public methods that are defined in a schema as shown below: { MemberService memberService; Logger logger = LogManager.getLogger(MemberQuery.class); { ( .memberService.getMemberByName(name).size() == ){ MemberException( );
 } { .memberService.getMemberByName(name);
 }
 }
 
} @Component public class MemberQuery implements GraphQLQueryResolver @Autowired public private static final List<Member> public getMemberByName ( String name) if this 0 throw new "no member data" else return this The name of the method should be equal to the method in type Query from the schema. It can return simple types, which will be mapped automatically to scalar values from the schema, or it can return more complex types. In order to understand the method name and its mapping, we need to understand schema writing in GraphQL which is the next topic. GraphQL Schema GraphQL comes with its own language to write GraphQL Schemas called Schema Definition Language (SDL). GraphQL employs a contract-first design approach and all operations supported by the API are defined here. These files are named with extension ".graphqls", and are required to be  in the resources folder in order to be in classpath. Please see below for the sample file. In the above schema, the ‘Member object’ is defined by type. The type system in GraphQL is the most basic component, and it represents the type of object that can be fetched from a service and the fields that are available within the object. Let us go through the Member object.: It has 20 fields comprising scalar and complex fields. ‘String’ and ‘Long’ are the scalar types in member object of the GraphQL . Other scalar types supported by SDL are Int, Float and Boolean and ID. The ID scalar type represents a unique identifier, often used to re-fetch an object or as the key for a cache. It contains complex types that are defined the same way as Member type and these are Assets, Skill, Contributions, MemberProjectRelation and MemberCertificationRelation. It also has self join to itself mentioned as "member: Member". This is because the member is reporting to a manager who is part of the member. ! is for the field which can not be null. Query and Mutation Type There are two types that are important for data fetching and manipulation within a schema i.e. Query and Mutation types. The Mutation type represents the queries that are used to perform write operations on the data. Every GraphQL service has a query type and may or may not have a mutation type. While query fields are executed in parallel, mutation fields run in series, one after the other. Therefore mutations are always preferred to manipulate the data in order to avoid a race condition. Below is the sample of the two: Both query and mutation contain entry point, request parameters and return type in their definition. Parameters followed by "!" can’t be null and the object type that is casted in square brackets "[ ]" is a type of list. To  Be Continued.... In this article we learned what is GraphQL, how we can start building it using springboot, Schema Definition Language (SDL) and its types. In the next article, we will know more about the relationships between type objects like member, skills, asset, etc. GraphiQL used for querying graphql API and exception handling using GraphQLErrorHandler. References https://github.com/preetpramati/SpringBootNeo4JAPI https://graphql.org/learn/schema/

How To Build Graphql API with Spring Boot, Neo4j and Kong [Part 1]

This is Part 1 of 6 in the Let’s Explore ARK Core series which documents the development of the next major release of ARK Core, alongside some tips & tricks on how to get started with contributing and building your next idea today. Introduction In Part 1 of this series, we will focus on the infrastructure improvements that have been implemented in ARK Core 3.0. Those improvements include how the application is bootstrapped, how components are wired up and how it has become easier to extend, complement and test the system with your functionality without having to modify our default implementations directly, ending up with conflicts that become tiresome to resolve. ARK Core v3.0 Github Repository Before we begin, let’s set the premise under which Core 3.0 was started by listing the issues that Core 2.0 had, how those arose and then we’ll look into how Core 3.0 aims to resolve those. Difficult to modify due to brittle & tightly coupled architecture where any small change can have an unintended impact. Difficult to use due to a lack of clarity as functions and class constructors having a lot of arguments which makes them harder to use and test. Difficult to overwrite existing essential functionality like consensus voting logic. Difficult to test due to the previously mentioned tightly coupled architecture which in turn makes extending harder due to the lack of confidence in alternative implementations. Difficult to get and set the configuration to it being stored in variables. process.env Application The application instance is the central entry point to ARK Core. It is responsible for loading and verifying configurations, deciding what packages should be registered, bootstrapping the packages and serve as the connection to share state between all packages that developers add to their installation. Core 2.0 provided an application instance that was difficult to work with because it consisted of only hardcoded entities like a configuration manager that was not accessible, the package loader was not accessible, there was no easy way to resolve paths or environment-specific and more. All of those factors combined made testing and developing packages unreasonably difficult as the developer experience (DX) was too tedious in the end. Tackling all of those issues in the current state would’ve been difficult so a complete rework from scratch was the cleanest solution. Core 3.0 has a completely new application object which has been rewritten from scratch with simplicity, extensibility, and testability in mind from the start. { app } ;
process.env.CORE_NETWORK process.env.CORE_TOKEN app.resolve( ); app.resolvePlugin( ); app.resolveOptions( ); { app } ;
app.network() app.token() app.get( ); // Core 2.0 import from "@arkecosystem/core-container" // get the name of the network // get the name of the token "..." // resolve a generic value "..." // resolve a plugin "..." // resolve the options of a plugin // Core 3.0 import from "@arkecosystem/core-container" // get the name of the network // get the name of the token "..." // resolve a generic value As you can see in the above example the usage is less verbose and you probably also noticed that the and methods are gone. This is a change that was made to loosen the coupling and give developers more freedom in how they develop their packages, store their configuration and access all of them. resolvePlugin resolveOptions Let's have a look at the below code which is taken from the package. @arkecosystem/core-api { Providers } ; { Server } ; {
    public register(): < > { .app
            .bind( )
            .toConstantValue( .config().all()); .app
            .bind<Server>( )
            .to(Server)
            .inSingletonScope();
    }
    
    public boot(): < > { .app.get<Server>( ).start();
    }

    public dispose(): < > { .app.get<Server>( ).stop();
    }
} import from "@arkecosystem/core-kernel" import from "./server" export . class ServiceProvider extends Providers ServiceProvider async Promise void this "api.options" this this "api" async Promise void await this "api" async Promise void await this "api" As you can see in the above code all control of how things are bound and resolved from the container is in the hands of the package developer rather than Core deciding how your data should be stored. Packages are no longer treated as special entities but rather just a provider that provides any number of services to Core 3.0 as opposed to Core 2.0 assuming that a single service is provided. Don’t worry about the service providers now, we’ll look at those in part 2 of the series and explore how we can take advantage of them to build flexible packages that enhance the functionality of Core 3.0. We hope that this newly provided simplicity, extensibility, and testability will encourage more developers to get involved with ARK Core and package development for the ecosystem to greatly enhance what ARK Core is capable of doing. Container The container is what provides the bread and butter that is needed to build a solid foundation for the infrastructure that is necessary to achieve the goals ARK Core 3.0 set out to achieve. It allows us to bind values, functions, and classes into a single entity that takes care of storing and managing all interactions with them. Core 2.0 has been using as its container and provided a wrapper around it since its implementation. At the time this worked fine as the requirements were rather low as the codebase was written in JavaScript which meant there was no concept of interfaces available, thus following the principle was rather difficult as it is usually going hand in hand with the principle which dictates that you should rely on abstractions rather than concrete implements. Awilix Design by Contract Dependency Inversion Let's have a look at the principle to set the stage of what is coming up next. Take the code below, you might think that the implementation is fine since a car is just a car, so what does it matter how it is implemented. Dependency Inversion {
    start(): {}
} car: Car = Car(); class Car void const new Now you have an implementation of a car which you can start, seems reasonable. Well, the issue you will encounter is that these days there are different types of cars, some run on electricity and some on diesel. With the above implementation, it will become messy to implement engine specific logic as you will have to make use of statements to decide what should be done to start the car. if A better approach is to provide an implementation contract that is abstract and makes no assumptions about the implementation as those are details that shouldn’t concern your application when it consumes the car entity. The car should just start, electro or diesel. interface Car {
    start(): ;
} {
    start(): {}
} {
    start(): {}
} container: Container = Container();
container.bind<Car>(ElectroCar).to(ElectroCar).whenTargetNamed( );
container.bind<Car>(DieselCar).to(DieselCar).whenTargetNamed( ); void class ElectroCar implements Car void class DieselCar implements Car void const new "electro" "diesel" If we take the above implementation and combine this with the principle you will notice that we are no longer coupled to a concrete car implementation but rather the implementation contract which is then resolved to either electro or diesel implementation. The benefits of this are that we don’t have to reference specific classes and also don’t have to worry about how something is implemented as long as it satisfies the contract we specified. Dependency Inversion Car Awilix to Inversify Core 3.0 replaced with . A powerful and lightweight inversion of control container for JavaScript & Node.js apps powered by TypeScript. Awilix InversifyJS Now you might wonder why we decided to replace container if Awilix was doing the job, fair point. The main reason is that Inversify is developed in and for TypeScript which means that true Dependency Injection is possible where you bind implementations contracts to concrete implementations. Awilix tries to cater to a JavaScript audience while supporting TypeScript support through type definitions which means you get the benefit of type hinting but not the ability to use interfaces in the way it is possible with Inversify. (interfaces) Using the new container Using the new container to its full capabilities is a breeze due to two factors. It is possible to obtain the container instance that is internally used instead of just a wrapper like it was the case with Awilix. This means you have access to all methods that are available through Inversify. By directly exposing the container instead of wrapping it we no longer make any assumptions about how a developer plans to use it and end up limiting what they can do. Now that sounds great on paper but you are probably asking yourself what the heck you really gain from this. Let's illustrate the benefits with a few examples from Core 3.0 itself. { Server } ; .app.bind<Server>( ).to(Server).inSingletonScope(); .app.bind<object>( ).toConstantValue(Server); .app
    .bind(Identifiers.CacheService)
    .toDynamicValue( context.container.get<CacheManager>(Identifiers.CacheManager).driver(),
    ); { app } ;

app.ioc // Binding a hapi server instance as a singleton. // This will be resolved once and then cached to always return the same instance. import from "@hapi/hapi" this "api" // Binding a static/constant value this "api.options" // Binding a dynamically resolved value this ( ) => context: interfaces.Context // Accessing the container directly import from "@arkecosystem/core-kernel" // This is the internal instance of the Inversify container As you can see the capabilities and syntax of the new container are expressive and simple while not giving up any functionality. We think that this simplicity will provide a better developer experience overall and give package developers more freedom and control. This is only a fraction of what Inversify is capable of so make sure to take a look at the official Inversify repository and documentation. Visit and to get a more in-depth guide into how the container works and what it is capable of. their repository Wiki Extensibility Core 2.0 is severely lacking in the extensibility department due to the architectural issues outlined earlier in this article. Core 3.0 tries to remedy those issues as much as possible by implementing proven concepts and principles. The pattern you will see most commonly across Core 3.0 is the based on drivers in combination with a manager. We’ll have a look at the new log implementation to get an idea of how it works and what benefits it brings with it. Builder Pattern Manager The is the entity that takes care of managing all interactions with logger instances. It is bound to the container to be accessible by packages and contains only log service-specific logic. It extends an abstract Manager that receives a type hint of the implementation contract of the logger to ensure type conformity during development. LogManager {
    protected createConsoleDriver(): <Logger> { .app.resolve(ConsoleLogger).make();
    }

    protected getDefaultDriver(): string { ;
    }
} < > class LogManager extends Manager Logger async Promise return this return "console" Service Provider The takes care of several things, let us break them down to understand them. ServiceProvider The is bound to the container as a singleton. This means it will only ever be instantiated once to ensure the same instance is shared across packages. LogManager The is booted which takes care of instantiating the default logger, in our case the console logger. LogManager The method that is responsible for resolving the configured logger is bound to the container. It is bound as a dynamic value to ensure that every time the method is called we resolve the configured logger as that logger could be changed at any time by a package. driver {
    public register(): < > { .app
            .bind<LogManager>(Identifiers.LogManager)
            .to(LogManager)
            .inSingletonScope(); .app.get<LogManager>(Identifiers.LogManager).boot(); .app
    .bind(Identifiers.LogService)
    .toDynamicValue( context.container.get<LogManager>(Identifiers.LogManager).driver(),
            );
    }
} class ServiceProvider extends BaseServiceProvider async Promise void this await this this ( ) => context: interfaces.Context Custom Logger Implementation Now that you’ve seen how the is created and registered within the application we’ll take a look at how to register your custom implementation through a package. Once again we’ll break it down to understand what is happening step-by-step. LogManager We resolve the from the container to make use of it the same way that Core is doing internally. LogManager We call the method on the with a name and callback that is responsible for the creation of the logger instance. extends LogManager We call the method on the to let the application know that the logger should be returned when the method is called. setDefaultDriver LogManager pino LogManager.driver() If we could skip this step we could have to manually call LogManager.driver(“pino”) to get an instance of the Pino logger. {
    public register(): < > { logManager: LogManager = .app.get<LogManager>(Identifiers.LogManager); logManager.extend( , () => PinoLogger().make());
        
        logManager.setDefaultDriver( );
    }
} . class ServiceProvider extends Providers ServiceProvider async Promise void const this await "pino" async new "pino" As you can see it has become a lot easier to modify and extend Core in a more controlled and logical manner. Things are clearly named, structured and by applying the same patterns consistently across Core we provide a developer experience that is more predictable and enjoyable. Configurability Extensibility is worth nothing without Configurability. If you can’t configure packages to your liking, or worse, not receive any feedback when something is configured wrong and the package still runs then all the previous work was wasted. Core 3.0 internally uses which has recently received a major rework and performance improvements in its 17th major version. Joi’s focus from the beginning has been on providing a joyful developer experience, which perfectly aligns with our goals, and is already used across our codebase for various integrations that rely on the server. HapiJS Joi HapiJS Hapi {
    public configDefaults(): object { { : };
    }
    
    public configSchema(): object { Joi.object().keys({ : Joi.string().alphanum().min( ).max( ).required(),
        });
    }
} class ServiceProvider extends BaseServiceProvider return username "johndoe" return username 3 30 Let us break down what is happening here and how it is handled internally to give feedback. We specified the default configuration that will be merged with the user-provided configuration. We specified the schema that should be used to validate the configuration once it is merged with the defaults. Now if we would register our package with Core it would start as usual as the default configuration the above example is valid but there are 2 possible outcomes on failure. Our package is optional so Core will spout out a warning that the configuration is invalid and continue execution. Our package is required so Core will spout out an error that the configuration is invalid and terminate the process, requiring the user to resolve the configuration issue. The benefits of this new validation should be clear by now. Better user feedback that ensures configuration can’t end up in unwanted or faulty behaviour and all data is automatically cast to their respective types (i.e. becomes ). ”1" 1 Testability Think back a bit, in the beginning, we set the premise that Core had a tight coupling of all internals which results in a brittle architecture that is difficult to test. This generally results in developers writing fewer tests, brittle tests just to get over with it or worst not writing any tests at all which reduces confidence in the implementations that are added or modified. Core 3.0 aims to make testing simpler and more enjoyable. A major step towards this has been the decoupling of the application object and container. The container is now passed to the application object when it is instantiated, over are the days of excessive mocking to create complete fake containers with certain values. Now creating a custom application instance is just a matter of passing in a real container instance that contains your desired bindings rather than having to spent hours creating the perfect mocks which only end up giving you false confidence as any change to Core would go unnoticed and leave you wondering why feature X is no longer working even though your test suite is green and letting you know there are no issues. What’s Next? This concludes Part 1 of the Let’s Explore ARK Core series. In the next part, we will delve into how the application is bootstrapped, configured and started in Core 3.0. I Want To Help With Development That's great news! If you want to help out, are wide open, but that is not all, we also have special Monthly Development GitHub Bounties on-going where you can earn money for every valid and merged Pull-Request. our GitHub repositories To learn more about the program please read our blog post. Bounty Program Guidelines Previously published at https://blog.ark.io/lets-explore-ark-core-v3-part-1-infrastructure-5c8ba13c9c42

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