Validate top-level lists with all the power of marshmallow
Project description
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.
Project details
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