fceruti
How to normalize function params
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.
Marked As Solved
riebeekn
I’ve not used it myself, but the tarams library looks like it might handle your use case if you want to go with a library instead of a custom solution GitHub - bluzky/tarams: Cast and validate external data and request parameters for Elixir and Phoenix · GitHub
Also Liked
sasajuric
Yes, on both accounts. I can’t share the code (it’s owned by the clients), but the basic take is something like
def normalize(data, types) do
{%{}, types}
|> Ecto.Changeset.cast(data, Map.keys(types))
|> Ecto.Changeset.apply_action(:insert)
end
This is probably not enough (e.g. you may want to handle nils and missing keys), but it’s a solid start.
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:
def parse(params, schema) do
# First I want to have entire schema in one format [{key, {type, opts}}]
normalized_schema = for {key, type_spec} <- schema, do: {key, apply_default_opts(type_spec)}
keys = for {key, _} <- normalized_schema, do: key
types = for {key, {type, _opts}} <- normalized_schema, into: %{}, do: {key, type}
required_fields = for {key, {_type, opts}} <- normalized_schema, Keyword.get(opts, :required), do: key
defaults = for {key, {_type, opts}} <- normalized_schema, default = Keyword.get(opts, :default), into: %{}, do: {key, default}
{defaults, types}
|> cast(params, keys)
|> validate_required(required_fields)
|> apply_action(:normalize)
end
@default_opts [required: false]
defp apply_default_opts(type) when is_atom(type), do: {type, @default_opts}
defp apply_default_opts({type, opts}), do: {type, Keyword.merge(@default_opts, opts)}
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 tempting ![]()
stefanchrobot
Just a few remarks if you don’t mind:
Enum.reject(schema, fn {_, v}
I’d go with something longer and less generic than k (key?) and v (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.
cond do
is_tuple(v) -> {k, elem(v, 0)}
is_atom(v) -> {k, v}
true -> raise(ArgumentError, "Bad formed schema")
end
Using more pattern matching would be more idiomatic:
case v do
{type, _opts} when is_atom(type) -> {k, type}
type when is_atom(type) -> {k, type}
_ -> raise ArgumentError, "bad schema: #{inspect(v)}"
end
And one more thing:
schema |> Enum.map(fn {k, v} -> ... end) |> Enum.into(%{})
can be replaced with:
Map.new(schema, fn {k, v} -> ... end)








