That’s a good example. I would refactor that code to have a different signature and change all callers to fetch the relevant data.
I’d probably insist on doing that even in a blocking language where it’s not necessary. Interspersing database or network requests all through a codebase is horrible. Before you know it, someone is calling that function in a loop and you’re doing N serialised database queries. And you can’t even tell that that’s happening from the function signature. Your program just gets slow as your database grows. To say nothing of the correctness problems from issuing these queries outside of a transaction.
I worked on a project that was written like this in Python. The code was packed full of “convenient” sql queries. Some http requests took seconds to render. Turns out those request handlers were issuing thousands of individual sql queries, loading hundreds of megabytes from our database. A lot of the queries were redundant. The backend was just overfetching the same data over and over in tiny helper functions. Because of how the code was written, fixing performance required huge refactors all over the codebase.
File, network and database queries should not be spread all over “for convenience”. Fetching user data and processing it are different tasks. They generally shouldn’t be combined into a single function.
Comments
That’s a good example. I would refactor that code to have a different signature and change all callers to fetch the relevant data.
I’d probably insist on doing that even in a blocking language where it’s not necessary. Interspersing database or network requests all through a codebase is horrible. Before you know it, someone is calling that function in a loop and you’re doing N serialised database queries. And you can’t even tell that that’s happening from the function signature. Your program just gets slow as your database grows. To say nothing of the correctness problems from issuing these queries outside of a transaction.
I worked on a project that was written like this in Python. The code was packed full of “convenient” sql queries. Some http requests took seconds to render. Turns out those request handlers were issuing thousands of individual sql queries, loading hundreds of megabytes from our database. A lot of the queries were redundant. The backend was just overfetching the same data over and over in tiny helper functions. Because of how the code was written, fixing performance required huge refactors all over the codebase.
File, network and database queries should not be spread all over “for convenience”. Fetching user data and processing it are different tasks. They generally shouldn’t be combined into a single function.