When I think of validation I think of receiving a data file and checking that all rows and columns are correct and generating a report about all the problems. Does my thing have a different name? Where can I read up on how to do that best?
Here's validating a CSV in Python (which I'm using because it's a language that's, well, less excited about types than the author's choice of Haskell, to show that the principle still applies):
def validate_data(filename):
reader = csv.DictReader(open(filename))
for row in reader:
try:
date = datetime.datetime.fromisoformat(row["date"])
except ValueError:
print("ERROR: Invalid date", row)
if date The insight is that the work of reporting errors in the data is exactly the same as the work of getting non-erroneous data into a usable form. If a row of data doesn't have an error, that means it's usable; if you can't turn it into a directly usable format, that necessarily means it has some sort of error.
So what you want is a function that takes the data and does both of these at the same time, because it's actually just a single task.
In a language like Haskell or Rust, there's a built-in type for "either a result or an error", and the convention is to pass errors back as data. In a language like Python, there isn't a similar concept and the convention is to pass errors as exceptions. Since you want to accumulate all the errors, I'd probably just put them into a separate list:
@attr.s # or @dataclasses.dataclass, whichever
class Order:
name: str
date: datetime.datetime
...
def parse(filename):
data = []
errors = []
reader = csv.DictReader(open(filename))
for row in reader:
try:
date = datetime.datetime.fromisoformat(row["date"])
except ValueError:
errors.append(("Invalid date", row))
continue
if date And if your file format changes, you make the change in one spot; you've kept the code DRY.