A backend agnostic data modeling entity library
Project description
SpringField makes API data easy.
SpringField makes it simple to model structured data. Once the data is modeled, SpringField can parse API responses into easy to use Python objects and types. It can also generate the same structured data for making API request.
SpringField is ideal for:
Restful JSON API data structures
Parsing CSV data structures from csv.DictReader
Turning anything Python can parse into a dict or list into a structured object
There is also a helper library for using SpringField with Mongo: springfield- mongo
Quickstart
To define an springfield.Entity, subclass springfield.Entity. Define your attributes by specifying fields. This library provides the follow self-describing fields to start with:
IntField
FloatField
BooleanField
StringField
BytesField
DateTimeField
EmailField
UrlField
EntityField
CollectionField
A quick example:
#!/usr/bin/env python from springfield import Entity, fields from springfield.timeutil import utcnow class Bookmark(Entity): uri = fields.UrlField(doc='The bookmark uri.') verified = fields.BooleanField(doc='Whether or not this bookmark URI has been verified to exist.') added = fields.DateTimeField() class User(Entity): id = fields.IntField(doc='Auto-incremented database id.') email = fields.EmailField(doc='The user\'s email address.') bookmarks = fields.CollectionField(fields.EntityField(Bookmark)) created = fields.DateTimeField() if __name__ == '__main__': user = User() user.id = 5 user.email = 'foobar@example.com' user.bookmarks = [ {'uri': 'https://github.com'}, {'uri': 'ftp://google.com', 'verified': True} ] user.created = utcnow() data = user.to_json() # `data` is suitable to return in something like a JSON API. print data # Similarly, `data` can be adapted from a JSON API request body. user = User.from_json(data) print user.email print user.created print user.bookmarks
Will print (the json was prettified to protect the innocent):
{ "bookmarks":[ { "uri":"https://github.com" }, { "uri":"ftp://google.com", "verified":true } ], "created":"2017-01-25T20:25:54Z", "email":"foobar@example.com", "id":5 } foobar@example.com 2017-01-25 20:47:37+00:00 [<Bookmark {uri: https://github.com}>, <Bookmark {verified: True, uri: ftp://google.com}>]
Notice a few things:
Not every field is required for an entity. This is useful for doing sparse updates on an API.
SpringField will adapt types in a non-destructive way.
You can also create entities by adapting JSON, which is really handy at API boundaries.
Field Validation
SpringField does field validation when constructing entities, according to the types defined by the fields on that entity. For example:
You can define more complex field adaptation behavior by subclassing springfield.fields.Field and implementing your own fields. See the documentation on springfield.fields.Field for more information.
Similar Projects
Changelog
0.9.1
Fixed Entity.get() for Python 3
0.9.0
Switched from future to six Python 2/3 compatibility libraries because future’s modified str does not play well with adapters.
0.8.0
Added support for Python 3.6+
Dropped support for Python <2.7
0.7.17
Fix packages for pytest plugin
0.7.16
Allow EntityFields to use dotted-name class strings. This was done to allow circular references in entities that may refer to one another.
Added BytesField
0.7.15
Allow empty values for URL
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