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https://github.com/rbanffy/appengine-fixture-loader
A simple way to load Django-like fixtures into the datastore.
https://github.com/rbanffy/appengine-fixture-loader
google-appengine python
Last synced: 13 days ago
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A simple way to load Django-like fixtures into the datastore.
- Host: GitHub
- URL: https://github.com/rbanffy/appengine-fixture-loader
- Owner: rbanffy
- License: apache-2.0
- Created: 2014-10-13T19:20:47.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2017-01-26T22:53:53.000Z (almost 8 years ago)
- Last Synced: 2024-12-16T12:11:49.666Z (26 days ago)
- Topics: google-appengine, python
- Language: Python
- Size: 78.1 KB
- Stars: 15
- Watchers: 3
- Forks: 3
- Open Issues: 3
-
Metadata Files:
- Readme: README.rst
- Changelog: HISTORY.rst
- Contributing: CONTRIBUTING.rst
- License: LICENSE
Awesome Lists containing this project
- starred-awesome - appengine-fixture-loader - A simple way to load Django-like fixtures into the datastore. (Python)
README
appengine-fixture-loader
========================A simple way to load Django-like fixtures into the local development datastore, originally intended to be used by `testable_appengine `_.
.. image:: https://img.shields.io/pypi/l/appengine-fixture-loader.svg
:target: ./LICENSE.. image:: https://badge.fury.io/py/Appengine-Fixture-Loader.svg
:target: https://pypi.python.org/pypi/appengine-fixture-loader/.. image:: https://api.travis-ci.org/rbanffy/appengine-fixture-loader.svg
:target: https://travis-ci.org/rbanffy/appengine-fixture-loader.. image:: https://img.shields.io/pypi/pyversions/appengine-fixture-loader.svg
:target: https://pypi.python.org/pypi/appengine-fixture-loader/.. image:: https://img.shields.io/pypi/dm/appengine-fixture-loader.svg
:target: https://pypi.python.org/pypi/appengine-fixture-loader/.. image:: https://coveralls.io/repos/rbanffy/appengine-fixture-loader/badge.svg?branch=master&service=github
:target: https://coveralls.io/github/rbanffy/appengine-fixture-loader?branch=masterInstalling
----------For the less adventurous, Appengine-Fixture-Loader is available on PyPI at https://pypi.python.org/pypi/Appengine-Fixture-Loader.
Single-kind loads
------------------Let's say you have a model like this:
.. code-block:: python
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:
.. code-block:: javascript
[
{
"__id__": "jdoe",
"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:
.. code-block:: python
from appengine_fixture_loader.loader import load_fixture
and then:
.. code-block:: python
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.
The `__id__` attribute, when defined, will save the object with that given id. In our case, the key to the first object defined will be a `ndb.Key('Person', 'jdoe')`. The key may be defined on an object by object base - where the `__id__` parameter is omitted, an automatic id will be generated - the key to the second one will be something like `ndb.Key('Person', 1)`.
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:
.. code-block:: python
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:
.. code-block:: python
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:
.. code-block:: javascript
[
{
"__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:
.. code-block:: python
from appengine_fixture_loader.loader import load_fixture
and:
.. code-block:: python
loaded_data = load_fixture('tests/persons_and_dogs.json',
kind={'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:
.. code-block:: python
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:
.. code-block:: python
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:
.. code-block:: javascript
[
{
"__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.
Parent/Ancestor-based relationships with automatic keys
-------------------------------------------------------It's also possible to set the `parent` by using the `__children__` attribute.
For our example classes, importing:
.. code-block:: javascript
[
{
"__kind__": "Person",
"first_name": "Alice",...
"__children__": [
{
"__kind__": "Person",
"first_name": "Bob",
..."__children__owner__": [
{
"__kind__": "Dog",
"name": "Fido"
}
]
}
]
}
]should be equivalent to:
.. code-block:: python
alice = Person(first_name='Alice')
alice.put()
bob = Person(first_name='Bob', parent=alice)
bob.put()
fido = Dog(name='Fido', parent=bob)
fido.put()You can then retrieve fido with:
.. code-block:: python
fido = Dog.query(ancestor=alice.key).get()
Development
===========There are two recommended ways to work on this codebase. If you want to keep
one and only one App Engine SDK install, you may clone the repository and run
the tests by::$ PYTHONPATH=path/to/appengine/library python setup.py test
Alternatively, this project contains code and support files derived from the
testable_appengine project. Testable_appengine was conceived to make it easier
to write (and run) tests for Google App Engine applications and to hook your
application to Travis CI. In essence, it creates a virtualenv and downloads the
most up-to-date SDK and other support tools into it. To use it, you run
`make`. Calling `make help` will give you a quick list of available make
targets::$ make venv
Running virtualenv with interpreter /usr/bin/python2
New python executable in /export/home/ricardo/projects/appengine-fixture-loader/.env/bin/python2
Also creating executable in /export/home/ricardo/projects/appengine-fixture-loader/.env/bin/python
(...)
‘/export/home/ricardo/projects/appengine-fixture-loader/.env/bin/run_tests.py’ -> ‘/export/home/ricardo/projects/appengine-fixture-loader/.env/lib/google_appengine/run_tests.py’
‘/export/home/ricardo/projects/appengine-fixture-loader/.env/bin/wrapper_util.py’ -> ‘/export/home/ricardo/projects/appengine-fixture-loader/.env/lib/google_appengine/wrapper_util.py’
$ source .env/bin/activate
(.env) $ nosetests
..............
----------------------------------------------------------------------
Ran 14 tests in 2.708sOK