Brand new way to test your API
Project description
apitist
Brand new way to test your API
Main features:
- Adding hooks for requests library
- Default hooks for:
- Logging
- Structuring/Unstructuring data
Installation
Run the following command in your command line::
pip install apitist
Default hooks
- RequestDebugLoggingHook - logs request content with level DEBUG
- RequestInfoLoggingHook - logs request content with level INFO
- PrepRequestDebugLoggingHook - logs prepared request content (e.g. you will see query parameters in URL) with level DEBUG
- PrepRequestInfoLoggingHook - logs prepared request content with level INFO
- ResponseDebugLoggingHook - logs response content with level DEBUG
- ResponseInfoLoggingHook - logs response content with level INFO
- RequestAttrsConverterHook - converts attrs class in
data
field into json - RequestDataclassConverterHook - converts dataclass class in
data
field into json - ResponseAttrsConverterHook - adds
structure(type)
function torequests.Response
class, which will structure response according to attrs class given to it - ResponseDataclassConverterHook - adds
structure(type)
function torequests.Response
class, which will structure response according to dataclass class given to it
Example usage
from apitist.hooks import PrepRequestInfoLoggingHook, ResponseInfoLoggingHook
from apitist.requests import session
s = session()
PrepRequestInfoLoggingHook.formatter = "Best formatter {req.method} {req.url}"
s.add_prep_request_hook(PrepRequestInfoLoggingHook)
s.add_response_hook(ResponseInfoLoggingHook)
s.post("https://httpbin.org/post", params={"q": "test"})
Custom Hooks
from requests import Request, PreparedRequest, Response
from apitist.requests import session, RequestHook, PreparedRequestHook, ResponseHook
s = session()
class ReqHook(RequestHook):
def run(self, request: Request) -> Request:
print(request.url)
return request
class PrepReqHook(PreparedRequestHook):
def run(self, request: PreparedRequest) -> PreparedRequest:
print(request.url)
return request
class RespHook(ResponseHook):
def run(self, response: Response) -> Response:
print(response.url)
return response
s.add_request_hook(ReqHook)
s.add_prep_request_hook(PrepReqHook)
s.add_response_hook(RespHook)
s.get("https://ya.ru", params={"q": "test"})
Working with constructor
import attr
import typing
from apitist.constructor import converter
from apitist.hooks import RequestConverterHook, ResponseConverterHook
from apitist.requests import session
class ExampleType:
test = None
@attr.s
class ExampleStructure:
test: ExampleType = attr.ib()
@attr.s
class TestResponse:
args: typing.Dict = attr.ib()
data: str = attr.ib()
files: typing.Dict = attr.ib()
form: typing.Dict = attr.ib()
headers: typing.Dict = attr.ib()
json: ExampleStructure = attr.ib()
origin: str = attr.ib()
url: str = attr.ib()
s = session()
s.add_hook(RequestConverterHook)
s.add_hook(ResponseConverterHook)
def structure_example_type(data, type_):
example = ExampleType()
example.test = data
return example
def unstructure_example_type(data):
return data.test
converter.register_hooks(
ExampleType, structure_example_type, unstructure_example_type
)
t = ExampleType()
t.test = "test"
struc = ExampleStructure(t)
res = s.post("https://httpbin.org/post", data=struc).structure(TestResponse)
print(res.structured.json.test.test) # test
Using random data generator
First of all create an instance of random class:
from apitist.random import Randomer
rand = Randomer()
Now, you can add custom hooks for different types:
rand.add_type(str, lambda: str(random.random()))
rand.add_type(float, lambda: random.random())
Or using add_types
:
types = {
str: lambda: str(random.random()),
float: lambda: random.random()
}
rand.add_types(types)
Now you can create random object for given type or any attrs class with defined types:
import attr
import dataclasses
import typing
rand.object(str) # '0.6147789314561384'
rand.object(float) # 0.4664297665239271
@attr.s
class Data:
value1: str = attr.ib()
value2: typing.List[str] = attr.ib()
value3: typing.Tuple[float] = attr.ib()
@dataclasses.dataclass
class Dataclass:
value1: str
value2: typing.List[str]
value3: typing.Tuple[float]
print(rand.object(Data))
# Data(
# value1='0.491058956716827',
# value2=['0.6568036485871975'],
# value3=(0.8603579349502298,)
# )
# Also works for dataclasses
print(rand.object(Dataclass))
# Data(
# value1='0.491058956716827',
# value2=['0.6568036485871975'],
# value3=(0.8603579349502298,)
# )
It is better to use it with Faker.
Just define different subclasses for str
and add different hooks for them.
By this you could create different data for different str
fields.
Also, using with RequestConverterHook
and ResponseConverterHook
you could easily create random json objects which would be send to server.
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