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actors/csharp/sdk/README.md

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# Dapr Actors (Dapr SDK)
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Let's take a look at the Dapr [Actors building block](https://docs.dapr.io/developing-applications/building-blocks/actors/actors-overview/). In this Quickstart, you will run a SmartDevice.Service microservice and a simple console client to demonstrate the stateful object patterns in Dapr Actors.
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1. Using a SmartDevice.Service microservice, developers can host two SmartDectectorActor smoke alarm objects, and a third ControllerActor object that command and controls the smart devices.
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1. Using a SmartDevice.Service microservice, developers can host two SmartDetectorActor smoke alarm objects, and a third ControllerActor object that command and controls the smart devices.
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2. Using a SmartDevice.Client console app, developers have a client app to interact with each actor, or the controller to perform actions in aggregate.
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3. The SmartDevice.Interfaces contains the shared interfaces and data types used by both service and client apps
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### Step 2: Set up the environment
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Clone the [sample provided in the Quickstarts repo](https://github.com/dapr/quickstarts/tree/master/workflows).
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Clone the [sample provided in the Quickstarts repo](https://github.com/dapr/quickstarts/tree/master/actors).
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```bash
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git clone https://github.com/dapr/quickstarts.git
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-->
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```bash
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dapr stop --app-id actorservice
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dapr stop --app-id actorservice
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(lsof -iTCP -sTCP:LISTEN -P | grep :5001) | awk '{print $2}' | xargs kill
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```
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bindings/csharp/sdk/README.md

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# Dapr Bindings (Dapr SDK)
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In this quickstart, you'll create a microservice to demonstrate Dapr's bindings API to work with external systems as inputs and outputs. The service listens to input binding events from a system CRON and then outputs the contents of local data to a PostreSql output binding.
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In this quickstart, you'll create a microservice to demonstrate Dapr's bindings API to work with external systems as inputs and outputs. The service listens to input binding events from a system CRON and then outputs the contents of local data to a PostgreSQL output binding.
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Visit [this](https://docs.dapr.io/developing-applications/building-blocks/bindings/) link for more information about Dapr and Bindings.
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pub_sub/go/sdk/order-processor/app.go

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// Start the server
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err = s.Start()
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if err != nil && err != http.ErrServerClosed {
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log.Fatalf("error listenning: %v", err)
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log.Fatalf("error listening: %v", err)
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}
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}
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resiliency/service-to-service-resiliency.md

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### Expected output
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Once both services are running, the `order-processor` service will recieve orders from the `checkout`service continuously using Dapr's service invoke API.
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Once both services are running, the `order-processor` service will receive orders from the `checkout` service continuously using Dapr's service invoke API.
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##### `order-processor` output
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== APP == Order received: { orderId: 3 }
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```
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### Simulate ann application failure by stopping the `order-processor` service
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### Simulate an application failure by stopping the `order-processor` service
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Simulate a system failure by stopping the `order-processor` service running in your second terminal window.
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##### Order Processor Service
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```bash
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dapr run --app-port 7001 --app-id order-processor --resources-path --app-protocol http --dapr-http-port 3501 -- dotnet run
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dapr run --app-port 7001 --app-id order-processor --resources-path ../../../resources/ --app-protocol http --dapr-http-port 3501 -- dotnet run
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```
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### Go example
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##### Order Processor Service
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```bash
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dapr run --app-port 6001 --app-id order-processor --resources-path --app-protocol http --dapr-http-port 3501 -- go run .
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dapr run --app-port 6001 --app-id order-processor --resources-path ../../../resources/ --app-protocol http --dapr-http-port 3501 -- go run .
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```
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### Java example
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##### Order Processor Service
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```bash
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dapr run --app-id order-processor --resources-path --app-port 9001 --app-protocol http --dapr-http-port 3501 -- java -jar target/OrderProcessingService-0.0.1-SNAPSHOT.jar
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dapr run --app-id order-processor --resources-path ../../../resources/ --app-port 9001 --app-protocol http --dapr-http-port 3501 -- java -jar target/OrderProcessingService-0.0.1-SNAPSHOT.jar
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```
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### JavaScript example
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##### Order Processor Service
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```bash
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dapr run --app-port 5001 --app-id order-processor --resources-path --app-protocol http --dapr-http-port 3501 -- npm start
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dapr run --app-port 5001 --app-id order-processor --resources-path ../../../resources/ --app-protocol http --dapr-http-port 3501 -- npm start
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```
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### Python example
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##### Order Processor Service:
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```bash
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dapr run --app-port 8001 --app-id order-processor --resources-path --app-protocol http --dapr-http-port 3501 -- python3 app.py
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dapr run --app-port 8001 --app-id order-processor --resources-path ../../../resources/ --app-protocol http --dapr-http-port 3501 -- python3 app.py
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```
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### Observe orders have resumed sequentially:

tutorials/distributed-calculator/README.md

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- **Subtraction**: [.NET Core](https://docs.microsoft.com/en-us/dotnet/core/) application
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The front-end application consists of a server and a client written in [React](https://reactjs.org/).
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Kudos to `ahfarmer` whose [React calculator](https://github.com/ahfarmer/calculator)
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Kudos to `ahfarmer` whose [React calculator](https://github.com/ahfarmer/calculator) was used as a starting point for the frontend implementation.
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The following architecture diagram illustrates the components that make up this quickstart:
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4. Multiply App - Open a terminal window and navigate to the python directory and follow the steps below:
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<!-- STEP
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name: "Build ptyhon app"
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name: "Build python app"
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working_dir: "./python"
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-->
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- "Exited App successfully"
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expected_stderr_lines:
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output_match_mode: substring
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name: "Run frontent app"
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name: "Run frontend app"
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working_dir: "./react-calculator"
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background: true
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sleep: 15
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Each of the services will spin up a pod with two containers: one for your service and one for the Dapr sidecar. It will also configure a service for each sidecar and an external IP for the front-end, which allows us to connect to it externally.
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4. Kubernetes deployments are asyncronous. This means you'll need to wait for the deployment to complete before moving on to the next steps. You can do so with the following commands:
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4. Kubernetes deployments are asynchronous. This means you'll need to wait for the deployment to complete before moving on to the next steps. You can do so with the following commands:
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<!-- STEP
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name: "Deploy Kubernetes"

tutorials/hello-world/python/app.py

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message = {"data": {"orderId": n}}
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try:
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response = requests.post(dapr_url, json=message, timeout=5, headers = {"dapr-app-id": "nodeapp"})
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response = requests.post(dapr_url, json=message, timeout=5, headers={"dapr-app-id": "nodeapp"})
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if not response.ok:
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print("HTTP %d => %s" % (response.status_code,
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response.content.decode("utf-8")), flush=True)

workflows/go/sdk/README.md

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activities are as follows:
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- NotifyActivity: This activity utilizes a logger to print out messages throughout the workflow. These messages notify the user when there is insufficient
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§inventory, their payment couldn't be processed, and more.
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inventory, their payment couldn't be processed, and more.
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- VerifyInventoryActivity: This activity checks the state store to ensure that there is enough inventory present for purchase.
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- RequestApprovalActivity: This activity seeks approval from a manager, if payment is greater than 5000 USD.
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- ProcessPaymentActivity: This activity is responsible for processing and authorizing the payment.

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