For correctness you can find unit tests have been written in the client_account.rs file to validate each method and handle cases of failure. Although the unit tests rely on eachother if one of the main tests breaks we know all the tests are bad and those tests should fail too since they are using our methods.
Testing against some of the sample data is what I had also used to verify things are working as expected.
With there not being a ton of sample data to use I had AI generate a csv file with more varied data to help test edge cases and make sure things are working as expected. (see prompt )
Most of the error handling is done through Result types and using match statements to handle errors as they come up. In the ingestion module when reading in the csv file if there is an error opening the file we log that out to stderr and return early from the function.
When parsing each record from the csv if there is an error with parsing we log that out to stderr and skip that record. This way a bad record does not stop the entire processing of the file.
Claude Code: I want to talk about the architecture of @ingestion.rs the read_csv file has a lot in it and I do not think passing in a &mut hashmap is the best design decision.
Could this be refactored in a different way to make it cleaner?
Reasoning:
Originally was passing in a &mut HashMap when reading in the csv to store a client to the client_account and do the matching on the transaction type in the csv reader. I thought this looked messy and passing around the reference to the hashmap didn't seem like the best option.
I wanted to talk through some options and move to a better design which is my first commit. My plan is to get this all working in sync then migrate over to an async pattern where the vector that's being used can be turned into a stream.
Claude Code:I want to plan on working on moving my logic to be async based using Tokio.
I want to determine if I should use tokio streams or thinking about using channels.
For channels it seems like I would have to handle the Transaction coming in then broadcast it out to a client with the speicifc client ID. I want this to be used in the future for multiple tcp connections. We aren't doing that yet we are still reading from the CSV file but I want to think a head.
Help me plan out what async pattern I should use for tokio
Reasoning: I wanted to get some input on Tokio Streams as they are not something I am very familliar with. Channels seemed like it could fit here for looking for scaling this out when we talk about the efficiency category.
It'd allow us to handle connections from specific clients and ingest the messages then pass those through our dedicated per client channels. We moved to having a dispatcher in the middle, Allowing each client account to live in its own and not need to worry about locking and mutex issues that could come up with threading.
Claude Code: based on the concepts in the codebase and the way @clean.csv is setup create a file named ai_created.csv that has the same structure as the clean.csv but it has more scenarios and also possible edge cases that might not be anitcipated.
Here is a little information about the input:
The client ID will be unique per client though are not guaranteed to be ordered. Transactions to
the client account 2 could occur before transactions to the client account 1. Likewise, transaction
IDs (tx) are globally unique, though are also not guaranteed to be ordered. You can assume the
transactions occur chronologically in the file, so if transaction b appears after a in the input file
then you can assume b occurred chronologically after a. Whitespaces and decimal precisions
(up to four places past the decimal) must be accepted by your program.
Reasoning: I wanted to get some more varied data to test against. The sample data provided was good but limited in scope. I wanted to make sure things were working as expected with more edge cases and different scenarios.