marshmallow-toplevel

marshmallow-toplevel

Load and validate top-level lists with all the power of marshmallow.

Installation

pip install marshmallow-toplevel

Usage

from marshmallow import fields
from marshmallow_toplevel import TopLevelSchema


class BatchOfSomething(TopLevelSchema):
    _toplevel = fields.Nested(
        SomethingSchema,
        required=True,
        many=True,
        validate=any_validation_logic_applied_to_list
    )

Rationale

Imagine that you have an API endpoint (or any other program that accepts user input), which is intended to accept multiple blog articles and save them to a database. Semantically, your data is a list of dictionaries:

[
    {"id": 1, "title": "Hello World!"},
    {"id": 2, "title": "Yet another awesome article."},
    ...
]

You describe article object schema and put constraints on your data:

from marshmallow import Schema, fields, validate


class ArticleSchema(Schema):
    id = fields.Int(required=True)
    title = fields.Str(required=True, validate=validate.Length(min=2, max=256))

But you also want to put some constraints onto outer list itself, for example, you want it to have length between 1 and 10. How do you describe it in terms of marshmallow?

Obvious solution: nest your data

class BatchOfArticles(Schema):
    articles = fields.Nested(
        ArticleSchema,
        required=True,
        many=True,
        validate=validate.Length(1, 10)
    )

But now a client have to send data this way, with this extra dictionary around:

{
    "articles": [
        {"id": 1, "title": "Hello World!"},
        {"id": 2, "title": "Yet another awesome article."},
        ...
    ]
}

It makes your API not so beautiful and user-friendly.

Good solution: use marshmallow-toplevel

With marshmallow-toplevel you can describe you data this way:

from marshmallow_toplevel import TopLevelSchema


class BatchOfArticles(TopLevelSchema):
    _toplevel = fields.Nested(
        ArticleSchema,
        required=True,
        many=True,
        validate=validate.Length(1, 10)
    )

Notice that schema inherits from TopLevelSchema and uses this special _toplevel key. It means that the field under this key describes top level object. You can define any constrains that you can define in marshmallow and it will just work:

schema = BatchOfArticles()

# validation should fail
errors = schema.validate([])
assert errors  # length < 1
errors = schema.validate([{"id": i, "title": "title"} for i in range(100)])
assert errors  # length > 10

# validation should succeed
errors = schema.validate([{"id": i, "title": "title"} for i in range(5)])
assert not errors

You can also use load for this schema as usual:

data = schema.load([{"id": "10", "title": "wow!"}])
print(data)
# [{"id": 10, "title": "wow!"}]

Now a client can send data as a list without redundancy.