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AWSCRT

❗ This is unfinished, early software. Expect bugs and breakages!

Stable Dev TagBot Build Status codecov

A high-level wrapper for the code in LibAWSCRT.jl. Currently, only an MQTT client is implemented.

Installation

pkg> add AWSCRT

MQTT Client

Create a client

A client requires a TLS context that describes how the connection should (or should not) be secured. Here, we use mutual TLS. The certificate and the private key here are those given to you by AWS IoT Core when you create a new certificate ("Device certificate" foo.pem.crt and "Private key file" foo-private.pem.key in the AWS Console).

tls_ctx_options = create_client_with_mtls(
    ENV["CERT_STRING"],
    ENV["PRI_KEY_STRING"],
    ca_filepath = joinpath(@__DIR__, "certs", "AmazonRootCA1.pem"),
    alpn_list = ["x-amzn-mqtt-ca"],
)
tls_ctx = ClientTLSContext(tls_ctx_options)
client = MQTTClient(tls_ctx)

Connect a client

We can create a connection using the client and connect it to the MQTT endpoint (the server). ENV["ENDPOINT"] is something like dsf9dh7fd7s9f8-ats.iot.us-east-1.amazonaws.com. A will is not required, but we set one here.

topic = "my-topic"
connection = MQTTConnection(client)
task = connect(
    connection,
    ENV["ENDPOINT"],
    8883,
    "my-client-id";
    will = Will(topic, AWS_MQTT_QOS_AT_LEAST_ONCE, "The client has gone offline!", false),
)
fetch(task) # wait for the connection to be opened (or fail)

Subscribe

Once we are connected, we can subscribe to a topic(s). A callback is passed with the subscribe call; this callback is called for each received message.

topic = "test-topic"
task, id = subscribe(
    connection,
    topic,
    AWS_MQTT_QOS_AT_LEAST_ONCE,
    (topic::String, payload::String, dup::Bool, qos::aws_mqtt_qos, retain::Bool) -> begin
        @info "Topic $topic received message: $payload"
    end,
)
fetch(task) # wait for the server to tell us the subscription was received

Publish

Once we are connected, we can publish a payload to a topic.

topic = "test-topic"
payload = Random.randstring(48)
task, id = publish(connection, topic, payload, AWS_MQTT_QOS_AT_LEAST_ONCE)
fetch(task) # wait for the server to tell us the published message was received

Clean Up

We can also unsubscribe and disconnect.

task, id = unsubscribe(connection, topic)
fetch(task) # wait for the server to tell us the unsubscription was received

task = disconnect(connection)
fetch(task) # wait for the connection to be closed

See Also

AWS IoT Device Shadow Service

The AWS IoT Device Shadow service adds persistent JSON documents you can use to e.g. manage device settings. This package provides both a high-level framework via the ShadowFramework and direct access via the ShadowClient object.

Create a ShadowFramework

The ShadowFramework object must first be created.

mqtt_connection = ... # create this yourself
thing_name = "thing1"
shadow_name = "settings"
doc = Dict()
sf = ShadowFramework(mqtt_connection, thing_name, shadow_name, doc)

Using the ShadowFramework

subscribe(sf) # Subscribe to all the shadow service topics and perform any initial state updates

lock(sf) do
    doc["k1"] = "v1" # update our copy of the shadow document
end

publish_current_state(sf) # tell the shadow service about it

These updates go both ways. Shadow document updates from the service are received asynchronously and the local shadow document is updated automatically. The remote state is always reconciled with the local state.

Update Callbacks: Ordering and Other Behaviors

If you need to take action before, during, or after a local shadow document update, there are callbacks available.

cbs = Dict(
    # This callback will run whenever the key `foo` is updated. We can do whatever we want, including update the
    # shadow document itself, but be careful about potential update order conflicts and deadlocks if you jump to
    # another thread and then update the shadow document.
    "foo" => it -> do_something(it)
)
sf = ShadowFramework(...; shadow_document_property_callbacks = cbs)

Persisting the Shadow Document Locally

The post-update callback is great for persisting the shadow document to the local disk:

doc = Dict()
sf = ShadowFramework(
    ...,
    doc;
    shadow_document_post_update_callback = doc -> write(shadow_path, serialize_shadow(doc))
)

The function serialize_shadow is a modified JSON serializer which handles version numbers better:

import JSON.Serializations: CommonSerialization, StandardSerialization
import JSON.Writer: StructuralContext, show_json

# Custom serialization for shadow documents so that version numbers serialize cleanly
struct ShadowSerialization <: CommonSerialization end

function show_json(io::StructuralContext, ::ShadowSerialization, f::VersionNumber)
    show_json(io, StandardSerialization(), string(f))
end

serialize_shadow(shadow) = sprint(show_json, ShadowSerialization(), shadow)

deserialize_shadow(text) = JSON.parse(text)

The next time your application starts, it can initialize the shadow document with the value from deserialize_shadow. Pass that value in to the ShadowFramework when creating it and run subscribe as usual.

See Also