Adzz
Data_schema - declarative schemas for data transformations
Data schemas are declarative descriptions of how to create a struct from some input data. You can set up different schemas to handle different kinds of input data. By default we assume the incoming data is a map, but you can configure schemas to work with any arbitrary data input including XML and json.
Data is selected from the input data and passed to a casting function before being set as a value under a key on the struct you want to build.
Check out the docs / guides and README for more detailed information on how it works but below is a flavour of what you can do.
A simple struct
First, let’s assume that your input data is a map with string keys. DataSchemas really shine when working with APIs because we can quickly convert an API response into trusted elixir data:
input = %{
"content" => "This is a blog post",
"comments" => [%{"text" => "This is a comment"},%{"text" => "This is another comment"}],
"draft" => %{"content" => "This is a draft blog post"},
"date" => "2021-11-11",
"time" => "14:00:00",
"metadata" => %{ "rating" => 0}
}
Now let’s define a schema to create a BlogPost struct from the above input data:
defmodule BlogPost do
import DataSchema, only: [data_schema: 1]
data_schema([
field: {:content, "content", &BlogPost.to_okay_string/1},
])
def to_okay_string(value) do
{:ok, to_string(value)}
end
end
The above is equivalent to:
defmodule StringType do
@behaviour DataSchema.CastBehaviour
@impl true
def cast(value) do
{:ok, to_string(value)}
end
end
defmodule BlogPost do
import DataSchema, only: [data_schema: 1]
data_schema([
field: {:content, "content", StringType},
])
end
Now you have defined your schema you can simple call DataSchema.to_struct/2:
DataSchema.to_struct(input, BlogPost)
# => %BlogPost{content: "This is a blog post"}
A more complex example
You can define a few kinds of fields, see the docs for more info but here is a more complex example introducing more field types:
defmodule DraftPost do
import DataSchema, only: [data_schema: 1]
data_schema(field: {:content, "content", StringType})
end
defmodule Comment do
import DataSchema, only: [data_schema: 1]
data_schema(field: {:text, "text", StringType})
end
defmodule BlogPost do
import DataSchema, only: [data_schema: 1]
@mapping [
field: {:date, "date", &Date.from_iso8601/1},
field: {:time, "time", &Time.from_iso8601/1}
]
data_schema(
field: {:content, "content", &DataSchemaTest.to_stringg/1},
has_many: {:comments, "comments", Comment},
has_one: {:draft, "draft", DraftPost},
list_of: {:list_of, "comments", &{:ok, &1["text"]} },
aggregate: {:post_datetime, @mapping, &BlogPost.to_datetime/1}
)
def to_datetime(%{date: date, time: time}) do
NaiveDateTime.new(date, time)
end
end
DataSchema.to_struct(input, BlogPost)
# The above returns:
{:ok, %DataSchemaTest.BlogPost{
list_of: ["This is a comment", "This is another comment"],
comments: [
%DataSchemaTest.Comment{text: "This is a comment"},
%DataSchemaTest.Comment{text: "This is another comment"}
],
content: "This is a blog post",
draft: %DataSchemaTest.DraftPost{content: "This is a draft blog post"},
post_datetime: ~N[2021-11-11 14:00:00]
}}
Different Input Data - aka Are these not just embedded_schemas from ecto?
The examples so far have shown functionality that is very similar to what you can get from Ecto’s embedded schemas and data casting capabilities. However, in DataSchema we can also provide different data accessors. This allows us to defines schemas that can be casted from different input data, for example…
XML Schemas
Let’s imagine that we have some XML that we wish to turn into a struct. What would it require to enable that? First a new Xpath data accessor:
defmodule XpathAccessor do
@behaviour DataSchema.DataAccessBehaviour
import SweetXml, only: [sigil_x: 2]
@impl true
def field(data, path) do
SweetXml.xpath(data, ~x"#{path}"s)
end
@impl true
def list_of(data, path) do
SweetXml.xpath(data, ~x"#{path}"l)
end
@impl true
def has_one(data, path) do
SweetXml.xpath(data, ~x"#{path}")
end
@impl true
def has_many(data, path) do
SweetXml.xpath(data, ~x"#{path}"l)
end
end
Let’s define our schemas like so:
defmodule DraftPost do
import DataSchema, only: [data_schema: 1]
@data_accessor XpathAccessor
data_schema([
field: {:content, "./Content/text()", StringType}
])
end
defmodule Comment do
import DataSchema, only: [data_schema: 1]
@data_accessor XpathAccessor
data_schema([
field: {:text, "./text()", StringType}
])
end
defmodule BlogPost do
import DataSchema, only: [data_schema: 1]
@data_accessor XpathAccessor
@datetime_fields [
field: {:date, "/Blog/@date", &Date.from_iso8601/1},
field: {:time, "/Blog/@time", &Time.from_iso8601/1},
]
data_schema([
field: {:content, "/Blog/Content/text()", StringType},
has_many: {:comments, "//Comment", Comment},
has_one: {:draft, "/Blog/Draft", DraftPost},
aggregate: {:post_datetime, @datetime_fields, &NaiveDateTime.new(&1.date, &1.time)},
])
end
And now we can transform as above:
source_data = """
<Blog date="2021-11-11" time="14:00:00">
<Content>This is a blog post</Content>
<Comments>
<Comment>This is a comment</Comment>
<Comment>This is another comment</Comment>
</Comments>
<Draft>
<Content>This is a draft blog post</Content>
</Draft>
</Blog>
"""
DataSchema.to_struct(source_data, BlogPost)
# This will output:
{:ok, %BlogPost{
comments: [
%Comment{text: "This is a comment"},
%Comment{text: "This is another comment"}
],
content: "This is a blog post",
draft: %DraftPost{content: "This is a draft blog post"},
post_datetime: ~N[2021-11-11 14:00:00]
}}
Data Accessor - An Access example.
Let’s look back at our map version.
input = %{
"content" => "This is a blog post",
"comments" => [%{"text" => "This is a comment"},%{"text" => "This is another comment"}],
"draft" => %{"content" => "This is a draft blog post"},
"date" => "2021-11-11",
"time" => "14:00:00",
"metadata" => %{ "rating" => 0}
}
We could define a data accessor that looks like this:
defmodule AccessDataAccessor do
@behaviour DataSchema.DataAccessBehaviour
@impl true
def field(data, path) do
get_in(data, path)
end
@impl true
def list_of(data, path) do
get_in(data, path)
end
@impl true
def has_one(data, path) do
get_in(data, path)
end
@impl true
def has_many(data, path) do
get_in(data, path)
end
end
Now we can define our schema:
defmodule Blog do
import DataSchema, only: [data_schema: 1]
@data_accessor AccessDataAccessor
data_schema([
list_of: {:comments, ["comments", Access.all(), "text"], &{:ok, to_string(&1)}},
])
end
And create a struct from this:
input = %{
"content" => "This is a blog post",
"comments" => [%{"text" => "This is a comment"},%{"text" => "This is another comment"}],
"draft" => %{"content" => "This is a draft blog post"},
"date" => "2021-11-11",
"time" => "14:00:00",
"metadata" => %{ "rating" => 0}
}
DataSchema.to_struct(input, Blog)
# Returns:
{:ok, %Blog{comments: ["This is a comment", "This is another comment"]}}
This is still an early version. There are some planned upcoming features before a v1 but it is certainly useable as is.
Most Liked
Adzz
New Version Released!
Version 0.2.4:
Features
This release adds runtime schemas. Runtime schemas are schemas that are defined at runtime and allow for casting to existing structs or to a bare map instead of a struct. This makes it really easy to integrate with Ecto for example to save an XML response into a db.
See the livebook for more details: data_schema/livebooks/runtime_schemas.livemd at main · Adzz/data_schema · GitHub
Here is a small example of what is possible:
defmodule User do
use Ecto.Schema
schema "users" do
field :name, :string
field :age, :integer
end
def update_details_from_xml(user_id, xml) do
schema = [
field: {:name, "/Response/User/@name", &{:ok, &1}},
field: {:age, "/Response/User/@age", &parse_in/1t}
]
with {:ok, changes} <- DataSchema.to_struct(xml, %{}, schema, XpathAccessor),
%User{} = user <- Repo.get(user_id, User),
%{valid?: true} = changeset <- Ecto.Changeset.change(%User{}, changes) do
Repo.update(changeset)
end
end
defp parse_int(string) do
case Integer.parse(string) do
{int, _} -> {:ok, int}
_error -> :error
end
end
end
xml = """
<Response>
<User name="Jeff" age="12" />
</Response>
"""
User.update_details_from_xml("123", xml)
Adzz
I’m also now realising I don’t think I ever actually linked to the repo:
Adzz
Great questions!
Validations
Can I run validations on my data?
Right now the focus is on parsing over validation. What I mean by that is instead of doing something like this:
input = %{"name" => ""}
input
|> DataSchema.to_struct(User)
|> validate_name_not_blank()
Or even:
input = %{"name" => ""}
input
|> validate_name_not_blank()
|> DataSchema.to_struct(User)
we can define our casting function to return an :error if it receives an empty string:
defmodule NonBlankString do
@behaviour DataSchema.CastBehaviour
@impl true
def cast(""), do: {:error, "Field was blank!"}
def cast(value), do: {:ok, to_string(value)}
end
defmodule User do
import DataSchema, only: [data_schema: 1]
data_schema([
field: {:user, "user", NonBlankString}
])
end
My current take on validations is that they are for when you can’t design away the need for them (via making illegal states unrepresentable). So the idea is that the schema defines what is valid.
HOWEVER - as you can see in the above examples you could define your own functions before / after struct creation if you felt the need.
It’s possible that some validations can’t be expressed per field, in which case we could add some in the future.
Phoenix Forms
There is nothing specially added yet for phoenix forms, but off the top of my head there are a few ways you could approach it. One way is to use a schemaless changeset in the form:
def index(conn, _params) do
types = %{name: :string}
user = %User{}
changeset = Ecto.Changeset.change({user, types}, %{})
render(conn, "index.html", changeset: changeset)
end
# With a form like this
<%= form_for @changeset, Routes.user_path(@conn, :create), fn f -> %>
<label>
Name: <%= text_input f, :name %>
</label>
<%= submit "Submit" %>
<% end %>
Then when you post the form:
def create(conn, %{"user" => user_input}) do
case DataSchema.to_struct(user_input, User) do
{:error, error} -> ...
{:ok, struct} -> ...
end
end
We could possibly make this easier by supplying a function something like DataSchema.schemaless_changeset_from_schema(User):
def index(conn, _params) do
changeset = DataSchema.schemaless_changeset_from_schema(User)
render(conn, "index.html", changeset: changeset)
end
You’d also have to do the work of converting the error to a changeset error, which we could probably write some functions to help with, but it might be as easy as:
def create(conn, %{"user" => user_input}) do
case DataSchema.to_struct(user_input, User) do
{:error, %{errors: [{field, message}]}} ->
changeset =
{%User{}, %{name: :string}}
|> Ecto.Changeset.change(user_input)
|> Ecto.Changeset.add_error(field, message)
render(conn, changeset: changeset)
{:ok, struct} ->
render(...)
end
end
My feel is that ecto might feel more natural, but open to the use case.
Last Post!
Adzz
New Version 0.5.0
This version provides much richer information when a casting function unexpectedly raises.
Often we write cast functions as modules that implement a cast function. This means if they raise the stacktrace unhelpfully points to that module and tells you nothing about which field in the schema blew up.
This release captures all unexpected raises in a cast function and re-raises a DataSchema.CastFunctionError with information about which field blew up.
This has proven very helpful for larger schemas.
The DataSchema.CastFunctionError wraps the exception that it catches meaning you can still pattern match on it if you wish to catch some exceptions yourself, for example:
try do
DataSchema.to_struct(my_input, MySchema)
rescue
%DataSchema.CastFunctionError{wrapped_error: %RuntimeError{}} ->
Logger.error("Runtime Error!")
...
error ->
reraise error, __STACKTRACE__
end
Example error message:
** (DataSchema.CastFunctionError)
Unexpected error when casting value "my_input_value"
for field :comments in this part of the schema:
list_of: {:comments, "comments", StringType},
Full path to field was:
Field :comments in MySchema
Under Field :metadata in MyParentSchema
The casting function raised the following error:
** (RuntimeError) An error occured!
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