Data Types

In data-centric communications, the applications participating in the communication need to share a common view of the types of data being passed around.

The Connext DDS Python API loads type definitions from XML. Other Connext DDS APIs support static types generated from an IDL definition. You can generate XML files from those IDL files using rtiddsgen:

$ rtiddsgen -convertToXml your_types.idl

To load a type from the application:

import rti.connextdds as dds
provider = dds.QosProvider("your_types.xml")
my_type = provider.type("MyType")

You can now use my_type to create a Topic (see Topics) and to instantiate a DynamicData object:

sample = dds.DynamicData(my_type)

# Let's say my_type has an int32 field
sample["x"] = 42

Now you would be able to publish the sample, which is discussed in Publications.

Defining Types Programmatically

Types can also be defined dynamically in the application, using DynamicType and its derived classes.

The following example creates a type and instantiates a data sample:

# struct Point {
#     double x, y;
# };
point_type = dds.StructType("Point")
point_type.add_member(dds.Member("x", dds.Float64Type()))
point_type.add_member(dds.Member("y", dds.Float64Type()))

# struct MyType {
#     @key string<128> id;
#     Point location;
#     int32 int_array[5];
#     sequence<Point, 10> path;
# };
my_type = dds.StructType("MyType")
my_type.add_member(dds.Member(name="id", data_type=dds.StringType(128), is_key=True))
my_type.add_member(dds.Member(name="location", data_type=point_type))
my_type.add_member(dds.Member(name="int_array", data_type=dds.ArrayType(dds.Int32Type(), 5)))
my_type.add_member(dds.Member(name="path", data_type=dds.SequenceType(point_type, 10)))

# Instantiate the type
sample = dds.DynamicData(my_type)
sample["id"] = "object1"

Accessing Nested Members

There are a few different ways to manipulate data with nested types. The . notation allows accessing nested primitive members at any level:

sample = dds.DynamicData(my_type)
sample["location.x"] = 1.5
sample["location.y"] = 2.5

To make multiple modifications to a complex member, you can get a temporary reference (a loan) to the member:

with sample.loan_value("location") as location:["x"] = 11.5["y"] = 12.5

A nested member can be assigned from a dictionary, too:

sample["location"] = {"x": 4.5, "y": 5.5}

Accessing Sequences and Arrays

Sequences and arrays can be retrieved or set using Python lists:

# We're using the type we created before
sample = dds.DynamicData(my_type)

# Set the array field with the values of a python list
sample["int_array"] = [1, 2, 3, 4, 5]

# Get all the array elements in a python list
lst = list(sample["int_array"])

# Set and get a single element:
sample["int_array[1]"] = 4
value = sample["int_array[1]"]

Lists of structures can be accessed using lists of dictionaries:

sample["path"] = [{"x": 1, "y": 2}, {"x": 3, "y": 4}]
path = list(sample["path"])

If you only need to set a few elements or fields, you can loan the sequence and its elements. Sequences are automatically resized when you access and index above the current length:

with sample.loan_value("path") as path:
    with as point:["x"] = 111["y"] = 222
print(sample["path[2].x"]) # prints 111