2. Publish/Subscribe

Prerequisites	Install git Install Python 3.6 or higher Install release 7.3.0 (see Before You Get Started) Clone repository from GitHub here
Time to complete	30 minutes
Concepts covered in this module	Introduction to publish/subscribe Introduction to DataWriters, and DataReaders, and Topics Using the code generator Using Waitsets Viewing your data in RTI Admin Console

The most basic communication pattern supported by RTI® Connext® DDS is the publish/subscribe model. Publish/Subscribe is a communications model where data producers “publish” data and data consumers “subscribe” to data. These publishers and subscribers don’t need to know about each other ahead of time; they discover each other dynamically at runtime. The data they share is described by a “topic,” and publishers and subscribers send and receive data only for the topics they are interested in. In this pattern, many publishers may publish the same topic, and many subscribers may subscribe to the same topic. Subscribers receive data from all of the publishers that they share a topic with. Publishers send data directly to subscribers, with no need for a broker or centralized application to mediate communications.

2.1. Introduction to DataWriters, DataReaders, and Topics

In DDS, the objects that actually publish data are called DataWriters, and the objects that subscribe to data are DataReaders. DataWriters and DataReaders are associated with a single Topic object that describes that data. (DDS also has Publisher and Subscriber objects, but we will talk about them later.) An application typically has a combination of DataWriters and DataReaders.

Figure 2.1 DataWriters write data and DataReaders read data of a Topic. DataWriters of the “ChocolateTemperature” Topic communicate with DataReaders of the “ChocolateTemperature” Topic. DataWriters of the “ChocolateLotState” Topic communicate with DataReaders of the “ChocolateLotState” Topic.

In a chocolate factory, for example, there might be a sensor that measures and publishes the current temperature of the tempering machine. Other applications monitor the temperature by subscribing to it. In this example, your Topic might be “ChocolateTemperature.” The sensor’s DataWriter will be associated with the “ChocolateTemperature” Topic. In a similar way, other DataWriters and DataReaders share different types of data using additional Topics.

Connext is responsible for discovering DataWriters and DataReaders in a system, checking if they have a matching Topic (and compatible quality of service, which we will discuss later) and then providing the communication between those DataWriters and DataReaders. Logically, this means you can visualize your applications as having DataWriters and DataReaders that connect to a “databus,” because your applications are not specifying exactly which other applications they communicate with – they only specify which Topics they read from and write to the databus, and Connext sets up the communication. Note that there is no “databus” object in your system – it is a logical way to visualize systems in which you don’t have to configure each communication path.

2.2. Hands-On 1: Your First DataWriter and DataReader

We are going to start with a simple “Hello World” application to show how to use the code generator, and how to create a DataWriter and a DataReader.

Tip

By the end of this exercise, a publishing application will send data, and a subscribing application will receive and print it to the console using Console.WriteLine().

2.2.1. Clone Repository

Get the files you need to perform the hands-on exercises.

Note

Always use the version of the examples that matches your Connext release. By default, the GitHub repository branch is set to master, which is always the latest release. If your version of Connext is not the latest release, select the release version you want, such as release/<version>.

Do one of the following:

• Download the repository as a Zip file from the repository webpage here, for your desired release (e.g., release/<version>).

• Clone the repository from GitHub.

  Use the following command:

  LinuxmacOSWindows

  $ git clone https://github.com/rticommunity/rticonnextdds-getting-started.git
  

  Check out the desired release. For example:

  LinuxmacOSWindows

  $ git checkout release/<version>
  

2.2.2. Set Up Environment Variables

The RTI Code Generator tool is located in <installdir>/bin/rtiddsgen (<installdir> refers to the installation directory for Connext).

To follow the instructions in the coming sections, add <installdir>/bin to your path.

1. Open a command prompt window, if you haven’t already.
   
   

2. Add <installdir>/bin/ to your path.

LinuxmacOSWindows

$ export PATH=${PATH}:<installdir>/bin

2.2.3. Run Code Generator

Inside the repository you have cloned, there is a directory named 2_hello_world, which contains the HelloWorld type definition in a file named hello_world.idl.

1. Open hello_world.idl to see the definition for our HelloWorld type:

   // Hello world!
   struct HelloWorld {
   
       // String with maximum length of 256 characters
       string<256> msg;
   
   };
   

   This language-independent interface is written in IDL, the Interface Definition Language. IDL allows you to declare data types used for communication (we’ll cover this more in Data Types). Connext includes a code generator that translates from this language-independent data type into code specific for your language. The generated code serializes and deserializes your data into and out of a network format.
   
   

2. From a terminal or command prompt, run rtiddsgen, which runs the code generator on hello_world.idl:

   LinuxmacOSWindows

   $ cd 2_hello_world
   $ rtiddsgen -language python -example universal -d python hello_world.idl
   

   
   If you haven’t configured your path as described in Set Up Environment Variables, run <install dir>/bin/rtiddsgen.

   -example universal generates an example publisher and subscriber application; we use “universal” because there are no platform-specific files generated for Python.

   -d python specifies the directory where the code will be generated.

   You may see a few warning messages indicating that some files already exist. This is normal and is only informing you that some of the files that rtiddsgen can generate were already available in the repository.
   
   

3. Open the python directory to review the code.

2.2.3.1. Overview of Generated and Example Code

The code you just generated includes the files in Table 2.1, in the python directory. Some of the files are generated by rtiddsgen, some came from the GitHub repository you cloned.

Table 2.1 Generated and Example Code Files

Files	Description
hello_world.py	The Python definition of your data type, with a special decorator that allows Connext to serialize and deserialize it (convert it to a format for the network). This is the type that will be used in your real application.
hello_world_publisher.py hello_world_subscriber.py hello_world_program.py	Example code you can read and modify. These files can run as a publisher or as a subscriber. These files were generated because you specified -example universal.
USER_QOS_PROFILES.xml	Configuration file for Quality of Service (to be discussed more later). This file came from the repository you cloned.

2.2.4. Open/Modify Publishing Application

Once you’ve opened the source code in your IDE of choice:

1. Open hello_world_publisher.py

   This snippet shows how to create a Topic (with a name and data type) and create a DataWriter for that Topic:

   # A Topic has a name and a datatype.
   topic = dds.Topic(participant, "Example HelloWorld", HelloWorld)
   
   # This DataWriter will write data on Topic "Example HelloWorld"
   # DataWriter QoS is configured in USER_QOS_PROFILES.xml
   writer = dds.DataWriter(participant.implicit_publisher, topic)
   

2. Change the Topic name from “Example HelloWorld” to “HelloWorld Topic”:

   topic = dds.Topic(participant, "HelloWorld Topic", HelloWorld)
   

3. Modify the code to send the message “Hello world!” with a count.

   The following snippet shows how to write a HelloWorld update using the DataWriter’s write method.

   In the for loop in the snippet, add the highlighted line, just after the comment # Modify the data to be sent here. This will set sample.msg to “Hello world!” with a count:

   sample = HelloWorld()
   
   for count in range(sample_count):
       # Catch control-C interrupt
       try:
           # Modify the data to be sent here
           sample.msg = f"Hello world! {count}"
           print(f"Writing HelloWorld, count {count}")
           writer.write(sample)
           time.sleep(1)
       except KeyboardInterrupt:
           break
   

   Recall that your “HelloWorld Topic” describes your data. This Topic is associated with the data type HelloWorld, which is defined in the IDL file (see Run Code Generator). The data type HelloWorld contains a string field named msg. In this step, you have just added code to set a value for the msg field. Now, when the DataWriter writes data, the msg field in the data will contain the string “Hello world! 1”, “Hello world! 2”, etc.

Definition

A sample is a single update to a Topic, such as “Hello world! 1”. Every time an application calls write(), it is “writing a sample.” Every time an application receives data, it is “receiving a sample.”

Note that samples don’t necessarily overwrite each other. For example, if you set up a Reliable Quality of Service (QoS) with a History kind of keep_all, all samples will be saved and accumulate. You can find more details in Basic QoS.

2.2.5. Open/Modify Subscribing Application

The subscriber application also creates a Topic.

1. Open hello_world_subscriber.py:

   This snippet shows how to create a Topic (with a name and data type) and create a DataReader for that Topic:

   # A Topic has a name and a datatype.
   topic = dds.Topic(participant, "Example HelloWorld", HelloWorld)
   
   # This DataReader reads data on Topic "Example HelloWorld".
   # DataReader QoS is configured in USER_QOS_PROFILES.xml
   reader = dds.DataReader(participant.implicit_subscriber, topic)
   

2. Change the Topic name from “Example HelloWorld” to “HelloWorld Topic”, just as you did in the publishing application.

   Note

   The Topic names must match between the publishing and subscribing applications for the DataWriter and DataReader to communicate.

   topic = dds.Topic(participant, "HelloWorld Topic", HelloWorld)
   

2.2.5.1. Details of Receiving Data

You don’t need to make any changes here, but look at the hello_world_subscriber.py code to see how it receives data. The DataReader is being notified of new data using an object called a WaitSet:

# Create a WaitSet and attach the StatusCondition
waitset = dds.WaitSet()
waitset += status_condition

while samples_read < sample_count:
    # Catch control-C interrupt
    try:
        # Dispatch will call the handlers associated to the WaitSet conditions
        # when they activate
        print("Hello World subscriber sleeping for 1 seconds...")

        waitset.dispatch(dds.Duration(1))  # Wait up to 1s each time
    except KeyboardInterrupt:
        break

This WaitSet object is a way for the application to sleep until some “condition” becomes true. When the application calls waitset.dispatch(dds.Duration(1)), it will sleep for up to the duration time (1 second in this example), unless it is woken up due to a condition becoming true.

There are multiple types of conditions that you can attach to a WaitSet, but this example shows a StatusCondition. Here is the code for the StatusCondition:

# Obtain the DataReader's Status Condition
status_condition = dds.StatusCondition(reader)

# Enable the 'data available' status and set the handler.
status_condition.enabled_statuses = dds.StatusMask.DATA_AVAILABLE
status_condition.set_handler(condition_handler)

In this example, we are saying that we are interested in waking up when the “data available” status becomes true. This means that when data arrives:

• The reader’s DATA_AVAILABLE status becomes true

• The application is woken up from the dispatch call

• The condition_handler event handler is called

A closer look at process_data, which is called by condition_handler:

@staticmethod
def process_data(reader):
    samples = reader.take_data()
    for sample in samples:
        print(f"Received: {sample}")

    return len(samples)

This code calls reader.take_data(), which removes any available data samples out of the DataReader queue, and returns them in a list. If data is arriving quickly, it is likely this collection will contain multiple samples. In this example, the sample’s data is being printed to the screen.

2.2.6. Run the Applications

Now that you have made changes to both the publisher and subscriber code, run the code with your modifications.

1. From within the 2_hello_world/python directory, enter the following:

   $ python hello_world_program.py -p
   

   Note

   You must be in the 2_hello_world/python directory when you run the previous command. Or if you are running from an IDE make sure the current working directory is set to the full path to 2_hello_world/python. The examples use Quality of Service (QoS) information from the file USER_QOS_PROFILES.xml in the 2_hello_world/python directory. We’ll talk more about QoS in a later module.

   You should see this in the window for the publisher:

   Writing HelloWorld, count 1
   Writing HelloWorld, count 2
   Writing HelloWorld, count 3
   Writing HelloWorld, count 4
   ...
   

2. Open another command prompt window, and from within the 2_hello_world/python directory, enter the following:

   $ python hello_world_program.py -s
   

   You should see this in the window for the subscriber:

   Running HelloWorldSubscriber on domain 0
   Hello World subscriber sleeping for 1 seconds...
   Received: HelloWorld(msg='Hello world! 2')
   Hello World subscriber sleeping for 1 seconds...
   Received: HelloWorld(msg='Hello world! 3')
   Hello World subscriber sleeping for 1 seconds...
   Hello World subscriber sleeping for 1 seconds...
   Received: HelloWorld(msg='Hello world! 4')
   Hello World subscriber sleeping for 1 seconds...
   ...
   

   The HelloWorld(msg='Hello world! 4') line is the data being sent by the DataWriter. If the DataWriter weren’t communicating with the DataReader, you would just see the Hello World subscriber sleeping for 1 seconds... lines and not the “Received:” lines. (The subscribing application prints the “sleeping” lines after the WaitSet times out while waiting for data, then it prints the “Received:” lines when it receives data from the DataWriter.)

   Note

   If you don’t get the results described here, see Troubleshooting.

2.2.7. Taking It Further

Under the hood, the publishing and subscribing applications are doing a lot of work:

Before communication starts, the DataWriter and DataReader discover each other and check that they have the same Topic name, compatible data types, and compatible QoS. (We will talk more about discovery in a later module). After discovery, the DataWriter sends data directly to the DataReader, with no message broker required.

When you run the applications on the same machine, by default they communicate over shared memory. If you run one on another machine, they communicate over the network using UDP.

2.2.7.1. Start up Multiple Publishing or Subscribing Applications

Try starting up multiple publishing or subscribing applications, and you will see that they will also send or receive data. (Remember to run from the 2_hello_world/python directory.)

Figure 2.2 Two applications publishing, and two subscribing, to the same Topic. Notice that each subscriber is receiving data from both publishers.

Figure 2.3 Two applications publishing, and two subscribing, to the same Topic.

2.2.7.2. Publish/Subscribe across Multiple Machines

To publish/subscribe between two machines:

1. Clone the repository on both machines. See Clone Repository.
   
   

2. In the 2_hello_world directory on one machine, modify and run the publishing application as described in Open/Modify Publishing Application. See also Run the Applications.
   
   

3. In the 2_hello_world directory on the other machine, modify and run the subscribing application as described in Open/Modify Subscribing Application. See also Run the Applications.

   Note

   If you are running both applications and they aren’t communicating (you don’t see the “msg:” lines shown at the end of Run the Applications), see Troubleshooting.

2.2.7.3. Create Multiple DataWriters, DataReaders, and Topics in a Single Application

So far, you have created two applications: one that uses a DataReader to subscribe to “HelloWorld Topic” and one that uses a DataWriter to publish “HelloWorld Topic.” You have seen that these applications automatically discover each other and communicate, and that you can run multiple copies of them.

In Data Types, you’ll add a second DataWriter to an application, and in Keys and Instances, you’ll create an application that contains multiple DataWriters, DataReaders, and Topics.

Tip

Even though these initial example applications each do only one thing, typical real-world applications contain a combination of DataWriters and DataReaders for multiple Topics in a single application. We will illustrate this in later modules.

Figure 2.4 Sneak Preview: In a later module, we will create a tempering application that will write a “ChocolateTemperature” Topic and read a “ChocolateLotState” Topic. An application can write and read multiple Topics by creating more DataWriters and DataReaders.

2.3. Troubleshooting

2.3.1. Why aren’t my applications communicating?

If you are running both applications and they aren’t communicating (you don’t see the HelloWorld(msg='Hello world! 2') lines shown at the end of Run the Applications), here are some things to check:

• Did you change the Topic name in both applications before compiling? They should match.

• Are you running both applications from the 2_hello_world/python directory, so they load the same USER_QOS_PROFILES.xml file?

  You must be in the 2_hello_world/python directory when you run python.

• If you are running on multiple machines, does your network support multicast? If it does not, see How do I set my discovery peers? below, for how to specify the addresses of the remote machines your application plans to communicate with.

• Check to see if one or both machines use a firewall. You may need to disable your firewall or configure it to allow multicast traffic for communication to be established.

See also Discovery.

2.3.2. How do I set my discovery peers?

If you are running Connext on multiple machines and your network does not support multicast, specify the address(es) of the remote machine(s) you want to communicate with:

1. In the 2_hello_world\python directory, find USER_QOS_PROFILES.xml.
   
   

2. Identify the following lines in USER_QOS_PROFILES.xml:

   <domain_participant_qos>
       <!--
       The participant name, if it is set, will be displayed in the
       RTI tools, making it easier for you to tell one
       application from another when you're debugging.
       -->
       <participant_name>
           <name>HelloWorldParticipant</name>
       </participant_name>
   
   </domain_participant_qos>
   

3. Add the <discovery> section as follows, and replace the IP address with the IP address or hostname of the other machine you want to communicate with:

   <domain_participant_qos>
       <!--
       The participant name, if it is set, will be displayed in the
       RTI tools, making it easier for you to tell one
       application from another when you're debugging.
       -->
       <participant_name>
           <name>HelloWorldParticipant</name>
       </participant_name>
       <discovery>
           <initial_peers>
               <!-- Add an element for each machine you want to communicate with -->
               <element>192.168.1.14</element>
           </initial_peers>
       </discovery>
   
   </domain_participant_qos>
   

If you want more information about discovery peers, see Configuring the Peers List Used in Discovery, in the RTI Connext DDS Core Libraries User’s Manual.

2.3.3. Why does the DataReader miss the first samples?

Discovery is not an instantaneous event. It takes some time for the discovery process between applications to complete. The DataWriter and DataReader must discover each other before they can start communicating. Therefore, if you send data immediately after creating the Connext entities, DataReaders will not receive the first few samples because they are still in-process of discovering the DataWriters and vice versa. This is true even when the DataWriters and DataReaders are reliable, because the Reliability QoS on its own does not guarantee delivery to DataReaders that have not been discovered yet.

You can overcome this behavior with the Durability QoS Policy, which can be set to deliver historical samples (that DataWriters already sent) to late-joining DataReaders. The DataReaders will then receive the first samples they originally missed. We’ll talk about this more in Basic QoS.

2.4. Hands-On 2: Viewing Your Data

Now that you’ve created applications that are publishing data, you can visualize that data using the Admin Console tool.

Note

The applications from Hands-On 1 above should be running while you perform the Admin Console steps below. See Run the Applications.

2.4.1. Open Admin Console

Start by opening Admin Console from RTI Launcher:

The following sections guide you through Admin Console for the purposes of this exercise, but you can find more information in the Admin Console User’s Manual.

2.4.2. Choose Automatically Join

You may be prompted to automatically or manually join domains when you first open Admin Console. For the purposes of this exercise, choose to automatically join (the default). We’ll discuss domains in a later module.

2.4.3. Switch to Data Visualization Perspective

Select the Data Visualization Perspective entry under the Visualization menu. (You may need to close a Welcome tab first.) If you can’t select the Data Visualization Perspective menu item, you may already be in that mode.

2.4.4. Open Topic Data Tab

From the DDS Logical View, click on the “HelloWorld Topic” to open the Topic View.

Select the Topic Data tab at the bottom of the window.

Click Subscribe:

2.4.5. Subscribe to “HelloWorld Topic”

The Admin Console tool itself is a DDS application, so it must also create DataReaders to subscribe to the “HelloWorld Topic.” (See the Admin Console online Help for more information about this.) When you subscribe to the “HelloWorld Topic” in Admin Console, Admin Console will create a DataReader for this Topic.

Click on the Subscribe… button or right-click on the Topic in the DDS Logical View and select Subscribe. This will open the Create Subscription dialog seen below. Click OK to subscribe to the Topic.

2.4.6. Use Topic Data Tab

After the Topic is subscribed to, you will see your “Hello world” message.

In the Admin Console tool, you’re also able to inspect DataWriters and DataReaders, and even chart your live data.

2.4.7. Use Admin Console across Machines

Admin Console is like any other Connext application. It discovers what DataWriters and DataReaders are on the network, whether they’re on the same machine as Admin Console or on different machines.

If you have trouble viewing data in Admin Console across machines, the same troubleshooting tips apply to Admin Console as apply to DataWriters and DataReaders in How do I set my discovery peers?. If your network supports multicast, you’ll see data on the other machines in Admin Console; otherwise, specify the IP addresses of the remote machines you want Admin Console to communicate with.

2.5. Next Steps

Congratulations! You’ve written your first DDS application, which publishes HelloWorld data. In this exercise, you’ve experienced a quick overview of the development process from defining a data type and using the code generator, to building an example application and using Connext Professional tools to see that data is being published. We’ll continue to build on these skills and to use these tools in more depth in subsequent exercises.

The next module takes a deeper dive into data types, including a little more information about how to define common types. We will be starting to work with an example that’s more complex than a “hello world”—we’re going to be using a chocolate factory example to showcase DDS concepts. See Data Types.