Mongo Dynamic Fixture
Project description
Motivation
Using static json fixtures can be a pain as they are hard to maintain if the data evolves
Adding new tests usually require the addition of new static json fixtures
If a static json fixture is used in more than one test case even a little change can break all test cases
Inspiration
This library is inspired from django-dynamic-fixture.
Basic usage
The basic functions are N and G that stand for New and Get respectively. First you have to define the schema of the data that you want to generate:
from mongo_dynamic_fixture.schema import BaseSchema from mongo_dynamic_fixture.fields import IntegerField from mongo_dynamic_fixture.fields import DoubleField from mongo_dynamic_fixture.fields import BooleanField from mongo_dynamic_fixture.fields import StringField from mongo_dynamic_fixture.fields import ArrayField class SiteSchema(BaseSchema): schema = { 'name': StringField(), 'aliases': ArrayField(StringField()), 'active': BooleanField(), 'stats': { 'last_day_visits': IntegerField(), 'average_daily_visits': DoubleField() } }
After that you can already generate your fixtures!
In [1]: from mongo_dynamic_fixture import N In [2]: N(SiteSchema) Out[2]: {'active': True, 'aliases': ['kisxcp', 'lG', 'vH5', 'Q7oT1xi', 'RyooxkzB', 'FSFnP'], 'name': 'oCmy0ZsGS', 'stats': {'average_daily_visits': 0.02137056342099064, 'last_day_visits': 21}}
The function N takes an instance of BaseSchema as first argument and generates a fixture which is compliant with the schema provided. Obviously sometimes we would like to have more control over the fixture that we want generate, for this reason the N function also takes **kwargs optional arguments to fix some specific fields:
In [3]: N(SiteSchema, active=False, stats__last_day_visits=30) Out[3]: {'active': False, 'aliases': ['Euheq6sRgF', '9ajFi', 'xhCiZfxSsZ', 'wf', 'k9pkIXS', 'kX10H5j4', 'ZH', '142uYHlJvD'], 'name': 'KEKasgW', 'stats': {'average_daily_visits': 0.44985850259520865, 'last_day_visits': 30}}
As you can see both active and last_day_visits has been set to the values provided. If the key you want to fix is at the top level of the object then just use the variable name, otherwise list all its ancestors by separating them with _ as for stats__last_day_visits. If the resulting **kwargs key is not a valid python variable name, then pass it inside the extra argument:
In [3]: N(MySchema, field1=False, extra={'field2__some-invalid-name!': 30})
The G function does the same thing of the N function but additionaly takes a pymongo connection to a mongo collection as first argument:
In [4]: G(conn['test-db']['test-coll'], SiteSchema, active=False, stats__last_day_visits=30) Out[4]: {'active': False, 'aliases': ['K8ae2uwdW', '8P1lkRBC6', 'NUoyht', 'YG', 'BS9iV6Yy', 'gHgRVCq'], 'name': 'ihccMMs', 'stats': {'average_daily_visits': 0.5553574439909581, 'last_day_visits': 30}}
we have just created a fixture and inserted it inside the collection ‘test-coll’ of the database ‘test-db’.
The available fields that are all importable from mongo_dynamic_fixture.fields are the following:
IntegerField
DoubleField
BooleanField
StringField
ArrayField
ObjectField
A little more than basic usage
Each fields takes the following optional arguments:
required (default: True)
null (default: False)
blank (default: False)
not_present_prob (default: 0)
null_prob (default: 0)
blank_prob (default: 0)
If required is False, then with a probability given by not_present_prob the field will not be present in the document.
If null is True, then with a probability given by null_prob the field will have a value of None.
If blank is True, then with a probability given by blank_prob the field will have a blank value which depends on the field.
The blank fields for each fields are the following:
IntegerField -> 0
DoubleField -> 0.0
BooleanField -> False
StringField -> ''
ArrayField -> []
ObjectField -> {}
IntegerField and DoubleField also take min_value and max_value as optional arguments, and StringField and ArrayField also take min_length and max_length. IntegerField, DoubleField and StringField also take choices as optional argument which must be an iterable. In case that this argument is provided the generated value will one those present in the iterable. With StringField it’s also possible to specify the charset of the string to generate by passing it to the charset optional argument (default: string.ascii_letters + string.digits).
Now you might ask “And what is the purpose of ObjectField”? Suppose that you have a schema like the following:
class SiteSchema(BaseSchema): schema = { 'name': StringField(), 'aliases': ArrayField(StringField()), 'active': BooleanField(), 'stats-hourly': { 'last_visits': IntegerField(), 'average_visits': DoubleField() }, 'stats-daily': { 'last_visits': IntegerField(), 'average_visits': DoubleField() }, 'stats-monthly': { 'last_visits': IntegerField(), 'average_visits': DoubleField() } }
you can use ObjectField to write it in a more concise way:
from mongo_dynamic_fixture.fields import ObjectField obj_field = ObjectField({'last_visits': IntegerField(), 'average_visits': DoubleField()}) class SiteSchema(BaseSchema): schema = { 'name': StringField(), 'aliases': ArrayField(StringField()), 'active': BooleanField(), 'stats-hourly': obj_field, 'stats-daily': obj_field, 'stats-monthly': obj_field }
Installation
pip install mongo-dynamic-fixture
Compatiblity
Tested with:
python2.7 and pymongo>=2.0
python3.3, python3.4 and pymongo>=2.2
Contributing
For any suggestion, improvements, issues and bugs please open an Issue.
Release History
v0.2.1
Fixed min_length of StringField and ArrayField from 0 to 1
Simplified interface of functions N and G
v0.2.0
Added python3.3 and python3.4 compatibility
Configured testing with tox
Integrated Travis CI
Integrated Coveralls
v0.1.0
Added modules mongo_dynamic_fixture.fields, mongo_dynamic_fixture.fixture and mongo_dynamic_fixture.schema to generate datas
Added module mongo_dynamic_fixture.facades containing facades functions N and G
Added module mongo_dynamic_fixture.test containing MongoTestCase to run tests with a sandboxed mongo instance
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