Appengine-Fixture-Loader 0.1.3

Appengine fixture loader

A simple way to load Django-like fixtures into the local development datastore, originally intended to be used by testable_appengine.

Single-kind loads

Let’s say you have a model like this:

class Person(ndb.Model):
    """Our sample class"""
    first_name = ndb.StringProperty()
    last_name = ndb.StringProperty()
    born = ndb.DateTimeProperty()
    userid = ndb.IntegerProperty()
    thermostat_set_to = ndb.FloatProperty()
    snores = ndb.BooleanProperty()
    started_school = ndb.DateProperty()
    sleeptime = ndb.TimeProperty()
    favorite_movies = ndb.JsonProperty()
    processed = ndb.BooleanProperty(default=False)

If you want to load a data file like this:

[
    {
        "born": "1968-03-03T00:00:00",
        "first_name": "John",
        "last_name": "Doe",
        "favorite_movies": [
            "2001",
            "The Day The Earth Stood Still (1951)"
        ],
        "snores": false,
        "sleeptime": "23:00",
        "started_school": "1974-02-15",
        "thermostat_set_to": 18.34,
        "userid": 1
    },

...

    {
        "born": "1980-05-25T00:00:00",
        "first_name": "Bob",
        "last_name": "Schneier",
        "favorite_movies": [
            "2001",
            "Superman"
        ],
        "snores": true,
        "sleeptime": "22:00",
        "started_school": "1985-08-01",
        "thermostat_set_to": 18.34,
        "userid": -5
    }
]

All you need to do is to:

from appengine_fixture_loader.loader import load_fixture

and then:

loaded_data = load_fixture('tests/persons.json', kind = Person)

In our example, loaded_data will contain a list of already persisted Person models you can then manipulate and persist again.

Multi-kind loads

It’s convenient to be able to load multiple kinds of objects from a single file. For those cases, we provide a simple way to identify the kind of object being loaded and to provide a set of models to use when loading the objects.

Consider our original example model:

class Person(ndb.Model):
    """Our sample class"""
    first_name = ndb.StringProperty()
    last_name = ndb.StringProperty()
    born = ndb.DateTimeProperty()
    userid = ndb.IntegerProperty()
    thermostat_set_to = ndb.FloatProperty()
    snores = ndb.BooleanProperty()
    started_school = ndb.DateProperty()
    sleeptime = ndb.TimeProperty()
    favorite_movies = ndb.JsonProperty()
    processed = ndb.BooleanProperty(default=False)

and let’s add a second one:

class Dog(ndb.Model):
    """Another sample class"""
    name = ndb.StringProperty()

Now, if we wanted to make a single file load objects of the two kinds, we’d need to use the “__kind__” attribute in the JSON:

[
    {
        "__kind__": "Person",
        "born": "1968-03-03T00:00:00",
        "first_name": "John",
        "last_name": "Doe",
        "favorite_movies": [
            "2001",
            "The Day The Earth Stood Still (1951)"
        ],
        "snores": false,
        "sleeptime": "23:00",
        "started_school": "1974-02-15",
        "thermostat_set_to": 18.34,
        "userid": 1
    },
    {
        "__kind__": "Dog",
        "name": "Fido"
    }
]

And, to load the file, we’d have to:

from appengine_fixture_loader.loader import load_fixture

and:

loaded_data = load_fixture('tests/persons_and_dogs.json',
                           kinds={'Person': Person, 'Dog': Dog})

will result in a list of Persons and Dogs (in this case, one person and one dog).

Multi-kind, multi-level loads

Anther common case is having hierarchies of entities that you want to reconstruct for your tests.

Using slightly modified versions of our example classes:

class Person(ndb.Model):
    """Our sample class"""
    first_name = ndb.StringProperty()
    last_name = ndb.StringProperty()
    born = ndb.DateTimeProperty()
    userid = ndb.IntegerProperty()
    thermostat_set_to = ndb.FloatProperty()
    snores = ndb.BooleanProperty()
    started_school = ndb.DateProperty()
    sleeptime = ndb.TimeProperty()
    favorite_movies = ndb.JsonProperty()
    processed = ndb.BooleanProperty(default=False)
    appropriate_adult = ndb.KeyProperty()

and:

class Dog(ndb.Model):
    """Another sample class"""
    name = ndb.StringProperty()
    processed = ndb.BooleanProperty(default=False)
    owner = ndb.KeyProperty()

And using __children__[attribute_name]__ like meta-attributes, as in:

[
    {
        "__kind__": "Person",
        "born": "1968-03-03T00:00:00",
        "first_name": "John",
        "last_name": "Doe",

        ...

        "__children__appropriate_adult__": [
            {
                "__kind__": "Person",
                "born": "1970-04-27T00:00:00",

                ...

                "__children__appropriate_adult__": [
                    {
                        "__kind__": "Person",
                        "born": "1980-05-25T00:00:00",
                        "first_name": "Bob",

                        ...

                        "userid": 3
                    }
                ]
            }
        ]
    },
    {
        "__kind__": "Person",
        "born": "1999-09-19T00:00:00",
        "first_name": "Alice",

        ...

        "__children__appropriate_adult__": [
            {
                "__kind__": "Person",

                ...

                "__children__owner__": [
                    {
                        "__kind__": "Dog",
                        "name": "Fido"
                    }
                ]
            }
        ]
    }
]

you can reconstruct entire entity trees for your tests.

Note: As it is now, parent/ancestor relationships are not supported.

History

0.1.0 (2014-10-13)

• First release on GitHub.

0.1.1 (2014-12-4)

• Add support for multi-kind JSON files

0.1.2 (2014-12-4)

• Minor fixes

0.1.3 (2014-12-5)

• Added support for PropertyKey-based child entities