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Library to generate random test data using Hypothesis based on Lollipop schema.

Example

from collections import namedtuple
import lollipop.types as lt
import lollipop.validators as lv
import string

EMAIL_REGEXP = r"^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]{2,}\.[a-zA-Z0-9-.]{2,}$"
Email = lt.validated_type(lt.String, 'Email', lv.Regexp(EMAIL_REGEXP))

User = namedtuple('User', ['name', 'email', 'age'])

USER = lt.Object({
    'name': lt.String(validate=lv.Length(min=1)),
    'email': Email(),
    'age': lt.Optional(lt.Integer(validate=lv.Range(min=18))),
}, constructor=User)

import hypothesis as h
import hypothesis.strategies as hs
import lollipop_hypothesis as lh

# Write a test using data generation strategy based on Lollipop schema
@h.given(lh.type_strategy(USER))
def test_can_register_any_valid_user(user):
    register(user)

# Configure custom strategy for Email type
lh.register(
    Email,
    lambda _, type, context=None: \
        hs.tuples(
            hs.text('abcdefghijklmnopqrstuvwxyz'
                    'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
                    '0123456789'
                    '_.+-', min_size=1),
            hs.lists(
                hs.text('abcdefghijklmnopqrstuvwxyz'
                        'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
                        '0123456789', min_size=2),
                min_size=2,
                average_size=3,
            )
        ).map(lambda (name, domain_parts): name + '@' + '.'.join(domain_parts)),
)

# Or configure custom strategy for the whole type instance
lh.register(
    USER,
    lambda registry, type, context=None: \
        hs.builds(
            User,
            name=hs.text(min_size=1),
            email=registry.convert(Email(), context),
            age=hs.integers(min_value=0, max_value=100),
        )
)

Installation

$ pip install lollipop-hypothesis

# install optional package for regex support
$ pip install lollipop-hypothesis[regex]

Requirements

License

MIT licensed. See the bundled LICENSE file for more details.

Release files for lollipop-hypothesis 0.2

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