Reaction Pricewatch is a demo project to monitor changes in product prices.

Read more at the announcement blog post.

One of the first inputs to the system is registering when a user would like to track a price. We create a "watch" record in Pricewatch to track a subscription for the user. The watch contains some information about the user (userId and email), about the product (product id) and the current price at the time the watch is created.

Watches could be created from a user interface or from less direct triggers such as cart activity. For now though, there's no interface so watches are created manually. Any Kafka producer will work. The Kafka CLI tools, Kafkacat or a GUI like Conduktor are good options.

Here's an example using the Kafka CLI tools, configured for use with Reaction's docker-confluent-platform.

docker run --rm -it \ --network streams.reaction.localhost \
  confluentinc/cp-enterprise-kafka:5.3.1 \
  kafka-console-producer \
    --broker-list=kafka.streams.reaction.localhost:9092 \
    --topic=reaction.pricewatch.watches.json-gen1 \
    --property "parse.key=true" \
    --property "key.separator=|"

The command will open an interactive prompt. Paste a message, like the one below, to produce a new watch.

sku1:user1|{"id":"sku1:user1","user-id":"user1","email":"[email protected]","product-id":"sku1","start-price":100.00}

Watches are stored as a compacted topic in Kafka, so we can treat this much like a database table. Kafka will always keep at least the latest version of each watch key in the topic. Records can be deleted by publishing a null value for the key.

Pricewatch consumes price changes from Kafka and then detects if those changes are significant enough to notify interested users. We call this a "match".

When a match is made, Pricewatch produces match data to an output Kafka topic. These output match messages be used to power actions such as emailing or texting users.

The matches topic is not compacted. We treat it like a stream of flowing data.

product-id:user-id

Example: sku1:user1

{
  "id" : "sku1:user1",
  "user-id" : "user1",
  "email" : "[email protected]",
  "product-id" : "sku1",
  "start-price" : 200.0
}

product-id:user-id

Example: sku1:user1

{
  "pricewatch": {
    "id" : "sku1:user1",
    "user-id" : "user1",
    "email" : "[email protected]",
    "product-id" : "sku1",
    "start-price" : 200.0
    },
  "pricing": {
    "min": 100.0
  }
}

The Pricing Engine produces messages in Avro format. The schema for the messages in the prices-by-id topic is stored in JSON format in prices-by-id.json.

• Run ./bin/setup
• Edit .env and customize if necessary

To begin developing, start with a REPL.

docker-compose run --rm --service-ports web bin/dev

Then load the development namespace.

user=> (dev)
:loaded

Run go to prep and initiate the system.

dev=> (go)
:initiated

When you make changes to your source files, use reset to reload any modified files and reset the server. The code will be reloaded and the system will be restarted.

dev=> (reset)
:reloading (...)
:resumed

It's best to explicitly stop the system before stopping the REPL else, it can hang.

dev=> (halt)
dev=> :repl/quit

If you quit and the process does hang then you can kill it with Docker in another shell.

docker-compose kill web

Testing is fastest through the REPL, as you avoid environment startup time.

dev=> (test :unit)
...

But you can also run tests through a standalone command:

docker-compose run --rm web bin/test --watch

© 2020 Reaction Commerce

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.