fceruti
Hey everyone!
Saša Jurić on his talk called Clarity @ ElixirConf EU 2021, mentions a way of architecting your code that uses a function that he names normalize/2, but sadly, he says he doesn’t have time to share it.
I want to implement this programming style, but I’m missing this key ingredient. Do you know any libraries or gist that accomplish this? Thanks ![]()
def register(conn, params) do
schema = [
email: {:string, required: true},
password: {:string, required: true}
date_of_birth: :datetime,
# ...
]
with {:ok, params} <- normalize(params, schema),
{:ok, user} <- MySystem.register(params) do
# respond success
else
{:error, reason} ->
# respond error
end
end
update: if it’s not clear, I’m looking for a way of checking the existence and type of all the fields specified in schema.
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vrcca
I believe this is what you’re looking for: https://medium.com/very-big-things/towards-maintainable-elixir-the-core-and-the-interface-c267f0da43#1572
From my understanding, he just extracted the previous version of
registerinto the normalize function.stefanchrobot
As mentioned in the article, the author is suggesting using Ecto’ schemaless changesets for this. I think the
normalizefunction can be written in a pretty generic way.fceruti
Thank @vrcca & @stefanchrobot for your pointers. I was able to recreate this function. I’ll leave it here for anyone who may find this post later.
If you see anyway I can improve this code, please let me know
sasajuric
Yes, on both accounts. I can’t share the code (it’s owned by the clients), but the basic take is something like
This is probably not enough (e.g. you may want to handle nils and missing keys), but it’s a solid start.
stefanchrobot
Just a few remarks if you don’t mind:
I’d go with something longer and less generic than
k(key?) andv(value?). Maybe{field, schema}? Plus in this case I think it makes sense to use{_k, v}to explain the meaning of the first element.Using more pattern matching would be more idiomatic:
And one more thing:
can be replaced with:
tomekowal
I wanted to reply on Twitter but I saw there is already a solution in here. I’d like to share my anyway
Since we need to traverse the schema many times, I normalize it first and then use list comprehensions like this:
The line computing defaults might be tricky to understand because it is long and introduces a variable inside the comprehension filter.
Also, I’d vote for naming that function “parse” instead of normalize. Parsing is an action of taking a bunch of data and trying to transform it into a structure that is understandable. In the spirit of Parse, don’t validate
It would be possible to push the schema specification even more to introduce validations like:

email: {:string, format: ~r/@/}and then call
Changeset.validate_format(changeset, key, format)for each. But that would require another option for each Ecto.Changeset validatior. It might be an overkill but the schema format is very readable so it is temptingfceruti
Noted. Definitely it’s a little cryptic.
Oh yeah, the code looks much better.
I’m not convinced of this point. I’ve taken most of your ideas, but I kinda like normalize. To me parse means the data is going to change type.
Anyways, here is the revisited version with my take on @stefanchrobot and @tomekowal suggestions
vrcca
I’d change String.to_atom by String.to_existing_atom, since this data comes from untrusted source.
fceruti
Good catch. I dindn’t know about that function
LostKobrakai
I’d be intersted in how you handled the return value of the core, especially for errors. It might be easy if db schema and normalized schema are similar, but becomes tricky when that’s not the case.