Technical requirements
Our sample microservices application will use fuzzy string matching to match new addresses to existing base addresses to keep our address collection uncluttered. We’ll use fuzzy string matching based on the Levenshtein Distance metric. This metric is a measure of the similarity between two strings and calculates the minimum number of operations needed to make two strings identical.
As you might expect, the Python community has already developed pip packages that provide this type of string matching. We’ll apply the rapidfuzz package, which you install with this command in your virtual environment:
$ pip install rapidfuzz
In the Creating and running asynchronous tasks section, we’ll look into the details and parameters for rapidfuzz, but if you want more information, check this URL: https://github.com/rapidfuzz/RapidFuzz.
Furthermore, Redis and RabbitMQ must be running for the microservices we’ll be creating. You already...
