In this episode, we’re taking an extra step to polish our CSV importer by improving how we handle required columns and their validation messages. We start off by mapping our database column names to friendlier labels—so instead of seeing something like first_name
, the interface and messages now show "First Name". This makes the whole import process more user-friendly.
Next, we update how these labels are displayed in both the UI and within validation errors. Instead of static, hardcoded arrays, we make it dynamic, so whatever columns are being used get the right label—even falling back gracefully to the original column name if a custom label doesn't exist.
We then tackle the validation messages. Rather than generic errors like "columns to map dot email is required", we build a method so error messages use the nice human-readable field names, making things much clearer for users. And, to make it future-proof, we generate this validation mapping dynamically based on whatever required columns are in play.
Finally, there’s a quick tip on tidying up the messages even more, like lowercasing the field names if you want things to be extra pretty. All in all, this episode really improves both the look and clarity of feedback users get when importing their CSVs.