Simple validation tool for API
Project description
data-spec-validator
Why
- To get rid of code snippet like these (... cumbersome and tedious validation)
def do_something(params):
val_a_must_int = params.get('a', 0)
val_b_must_be_non_empty_list = params.get('b', [])
# if key c presents, value c must be a date string between '2000-01-01' to '2020-01-01'
val_c_might_be_none = params.get('c', None)
# check type
if type(val_a_must_int) != int:
raise XXX
# check type & value
if type(val_b_must_list) != list or len(val_b_must_be_non_empty_list) == 0:
raise XXX
# if value exists, check its value
if val_c_might_be_none is not None:
date_c = datetime.strptime(val_c_might_be_present, '%Y-%m-%d')
date_20000101 = datetime.date(2000, 1, 1)
date_20200101 = datetime.date(2020, 1, 1)
if not (date_20000101 <= date_c <= date_20200101):
raise XXX
...
# do something actually
Installation
- Basic usage:
pip install data-spec-validator
- Advance usage (decorator)
- The decorator function
dsv
depends onDjango
&djangorestframework
.
- The decorator function
pip install data-spec-validator[decorator]
Quick Example
- Do
validate_data_spec
directly wherever you like (seetest_spect.py
for more)
from data_spec_validator.spec import INT, DIGIT_STR, ONE_OF, Checker, CheckerOP, validate_data_spec
class SomeSpec:
field_a = Checker([INT])
field_b = Checker([DIGIT_STR], optional=True)
field_c = Checker([DIGIT_STR, INT], op=CheckerOP.ANY)
some_data = dict(field_a=4, field_b='3', field_c=1, field_dont_care=[5,6])
validate_data_spec(some_data, SomeSpec) # return True
some_data = dict(field_a=4, field_c='1')
validate_data_spec(some_data, SomeSpec) # return True
some_data = dict(field_a=4, field_c=1)
validate_data_spec(some_data, SomeSpec) # return True
some_data = dict(field_a='4', field_c='1')
validate_data_spec(some_data, SomeSpec) # raise Exception
some_data = dict(field_a='4', field_c='1')
validate_data_spec(some_data, SomeSpec, nothrow=True) # return False
class AnotherSpec:
field = Checker([ONE_OF], extra={ONE_OF: [1, '2', [3, 4], {'5': 6}]})
another_data = dict(field=[3, 4])
validate_data_spec(another_data, AnotherSpec) # return True
another_data = dict(field='4')
validate_data_spec(another_data, AnotherSpec) # raise Exception
- Decorate a method with
dsv
, the method must meet one of the following requirements.- It's a view's member function, and the view has a WSGIRequest(
django.core.handlers.wsgi.WSGIRequest
) attribute. - It's a view's member function, and the 2nd argument of the method is a
rest_framework.request.Request
instance. - It's already decorated with
rest_framework.decorators import api_view
, the 1st argument is arest_framework.request.Request
- It's a view's member function, and the view has a WSGIRequest(
from rest_framework.decorators import api_view
from rest_framework.views import APIView
from data_spec_validator.decorator import dsv
from data_spec_validator.spec import UUID, EMAIL, Checker
class SomeViewSpec:
param_a = Checker([UUID])
param_b = Checker([EMAIL])
class SomeView(APIView):
@dsv(SomeViewSpec)
def get(self, request):
pass
@api_view(('POST',))
@dsv(SomeViewSpec)
def customer_create(request):
pass
- Decorate another method with
dsv_request_meta
can help you validate the META in request header.
Register Custom Spec Check & Validator
- Define custom CHECK constant (
gt_check
in this case) and write custom Validator(GreaterThanValidator
in this case)
gt_check = 'gt_check'
from data_spec_validator.spec.defines import BaseValidator
class GreaterThanValidator(BaseValidator):
name = gt_check
@staticmethod
def validate(value, extra, data):
criteria = extra.get(GreaterThanValidator.name)
return value > criteria, ValueError(f'{value} is not greater than {criteria}')
- Register custom check & validator into data_spec_validator
from data_spec_validator.spec import custom_spec, Checker, validate_data_spec
custom_spec.register(dict(gt_check=GreaterThanValidator()))
class GreaterThanSpec:
key = Checker([gt_check], extra={gt_check: 10})
ok_data = dict(key=11)
validate_data_spec(ok_data, GreaterThanSpec) # return True
nok_data = dict(key=9)
validate_data_spec(ok_data, GreaterThanSpec) # raise Exception
Test
python -m unittest test.test_spec
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