First of all I am aware of flask-testing library with LiveServerTestCase class but it hasn't updated since 2017 and GitHub full of issues of it not working neither on Windows or MacOs and I haven't found any other solutions.
I am trying to write some tests for flask app using selenium to validate FlaskForms inside this app.
Simple test like this:
def test_start(app):
driver.get("http://127.0.0.1:5000/endpoint")
authenticate(driver)
falls on selenium.common.exceptions.WebDriverException: Message: unknown error: net::ERR_CONNECTION_REFUSED error. (As far as I understood in my case app creates in #pytest.fixtures and immediately shuts down and I need to find a way to keep it running for the whole test duration)
My question is: Is it possible to to create some live server in each test that will remain working so I could call API endpoints via selenium?
Simple fixtures if it helps:
#pytest.fixture
def app():
app = create_app()
...
with app.context():
# creating db
...
yield app
also:
#pytest.fixture
def client(app):
"""Test client"""
return app.test_client()
Finally got it all working. My conftest.py
import multiprocessing
import pytest
from app import create_app
#pytest.fixture(scope="session")
def app():
app = create_app()
multiprocessing.set_start_method("fork")
return app
#pytest.fixture
def client(app):
return app.test_client()
Important note that using python <3.8 line multiprocessing.set_start_method("fork") is not necessary (as far as I understood in v.3.8 they refactored multiprocessing module so further upon without this line you would get pickle Error on windows and Mac).
And one simple test looks like
def test_add_endpoint_to_live_server(live_server):
#live_server.app.route('/tests-endpoint')
def test_endpoint():
return 'got it', 200
live_server.start()
res = urlopen(url_for('.te', _external=True))# ".te is a method path I am calling"
assert url_for('.te', _external=True) == "some url"
assert res.code == 200
assert b'got it' in res.read()
Also I am using url_for. The point is every time live server starts on a random port and url_for function generates url with correct port internally. So now live server is running and it is possible to implement selenium tests.
I have a python server that is currently keeping track of the location of all the buses in my university and generating predictions of arrivals to specific locations.
Now, I wanted to attach a lightweight REST API to this server but I have been running intro problems.
I tried using flask with the following code:
from flask import Flask, jsonify
from PredictionWrapper import *
import threading
class RequestHandler():
def __init__(self,predictionWrapper):
self.app = Flask(__name__)
self.predictor = predictionWrapper
self.app.debug = False
self.app.add_url_rule('/<route>/<int:busStop>','getSinglePrediction',self.getSinglePrediction)
t = threading.Thread(target=self.app.run, kwargs={'host':'0.0.0.0', 'port':80, 'threaded':True})
t.start()
def getSinglePrediction(self, route, busStop):
# TODO Get the actual prediction with given parameters
prediction = self.predictor.getPredictionForStop(route, busStop)
return jsonify({'busStop': busStop, 'prediction': prediction})
def getStopPrediction(self, busStop):
# TODO Get the actual prediction with given parameters
return jsonify({'busStop': busStop, 'prediction': 2})
def run(self):
self.app.run(host='0.0.0.0', port=80, threaded=True)
The problem is that I have been encountering the error below after about half a day of running the server. Note that no requests were made to the server around the time it failed with the following error:
ERROR:werkzeug: - - [01/May/2016 09:55:55] code 400, message Bad request syntax ('\x02\xfd\xb1\xc5!')
After investigating I believe I need to deploy to a WSGI production server. But I have no clue what it means in this specific approach given that 1)the flask server is being threaded in order to run the rest of the prediction application, and 2)I am using classes which none of the documentation uses.
Any help on how to setup the wsgi file with apache, gunicorn, or the technology of your choice would be appreciated. Also, any comments on a better approach on making a non-blocking REST API would be helpful.
Let me know if you need any further clarification!
Not sure if this can actually solve your problem but you can use the coroutine based web server gevent. They have a WSGI server that you can use if that's what you meant by saying that you need to deploy a WSGI production server.
If you want to implement the server to your flask application just do the following:
from gevent.pywsgi import WSGIServer
app = Flask(__name__)
http_server = WSGIServer(('', 5000), app)
http_server.serve_forever()
Gevent in general is a very powerful tool and by issuing context switches as necessary it can handle multiple clients very easily. Also, gevent fully supports flask.
First thing to do would be to put exception handling to deal with bad JSON request data (which maybe is what's happening) something like
def getSinglePrediction(self, route, busStop):
try:
prediction = self.predictor.getPredictionForStop(route, busStop)
return jsonify({'busStop': busStop, 'prediction': prediction})
except:
return jsonify({'busStop': 'error', 'prediction': 'error'})
I' trying to combine two independent Flask apps like the example below:
from geventwebsocket import WebSocketServer, Resource
...
server = WebSocketServer(('', 8080), Resource({
'/': frontend,
'/one': flask_app_one,
'/two': flask_app_two}))
server.serve_forever()
Inside each Flask app I declare the full path, isn't that suppose to be relative path, inside flask_app_one:
from flask import Flask
app = Flask(__name__)
#app.route('/one/ping')
def ping():
return 'hello\n'
Why I should specify in #app.route('/one/ping') instead of just #app.route('/ping') since all traffic to /one will be forwarded to the corresponding app?
Let me know if you need any additional info I kept my example clean
Thank you
Finally I have managed to do it with the so called Application Dispatching and the resources found in this page:
http://flask.pocoo.org/docs/0.10/patterns/appdispatch/#app-dispatch
Thanks
I am developing my API server with Python-eve, and would like to know how to test the API endpoints. A few things that I would like to test specifically:
Validation of POST/PATCH requests
Authentication of different endpoints
Before_ and after_ hooks working property
Returning correct JSON response
Currently I am testing the app against a real MongoDB, and I can imagine the testing will take a long time to run once I have hundreds or thousands of tests to run. Mocking up stuff is another approach but I couldn't find tools that allow me to do that while keeping the tests as realistic as possible. I am wondering if there is a recommended way to test eve apps. Thanks!
Here is what I am having now:
from pymongo import MongoClient
from myModule import create_app
import unittest, json
class ClientAppsTests(unittest.TestCase):
def setUp(self):
app = create_app()
app.config['TESTING'] = True
self.app = app.test_client()
# Insert some fake data
client = MongoClient(app.config['MONGO_HOST'], app.config['MONGO_PORT'])
self.db = client[app.config['MONGO_DBNAME']]
new_app = {
'client_id' : 'test',
'client_secret' : 'secret',
'token' : 'token'
}
self.db.client_apps.insert(new_app)
def tearDown(self):
self.db.client_apps.remove()
def test_access_public_token(self):
res = self.app.get('/token')
assert res.status_code == 200
def test_get_token(self):
query = { 'client_id': 'test', 'client_secret': 'secret' }
res = self.app.get('/token', query_string=query)
res_obj = json.loads(res.get_data())
assert res_obj['token'] == 'token'
The Eve test suite itself is using a test db and not mocking anything. The test db gets created and dropped on every run to guarantee isolation (not super fast yes, but as close as possible to a production environment). While of course you should test your own code, you probably don't need to write tests like test_access_public_token above since, stuff like that is covered by the Eve suite already. You might want to check the Eve Mocker extension too.
Also make yourself familiar with Authentication and Authorization tutorials. It looks like the way you're going get the whole token thing going is not really appropriate (you want to use request headers for that kind of stuff).
I'm needing some help setting up unittests for Google Cloud Endpoints. Using WebTest all requests answer with AppError: Bad response: 404 Not Found. I'm not really sure if endpoints is compatible with WebTest.
This is how the application is generated:
application = endpoints.api_server([TestEndpoint], restricted=False)
Then I use WebTest this way:
client = webtest.TestApp(application)
client.post('/_ah/api/test/v1/test', params)
Testing with curl works fine.
Should I write tests for endpoints different? What is the suggestion from GAE Endpoints team?
After much experimenting and looking at the SDK code I've come up with two ways to test endpoints within python:
1. Using webtest + testbed to test the SPI side
You are on the right track with webtest, but just need to make sure you correctly transform your requests for the SPI endpoint.
The Cloud Endpoints API front-end and the EndpointsDispatcher in dev_appserver transforms calls to /_ah/api/* into corresponding "backend" calls to /_ah/spi/*. The transformation seems to be:
All calls are application/json HTTP POSTs (even if the REST endpoint is something else).
The request parameters (path, query and JSON body) are all merged together into a single JSON body message.
The "backend" endpoint uses the actual python class and method names in the URL, e.g. POST /_ah/spi/TestEndpoint.insert_message will call TestEndpoint.insert_message() in your code.
The JSON response is only reformatted before being returned to the original client.
This means you can test the endpoint with the following setup:
from google.appengine.ext import testbed
import webtest
# ...
def setUp(self):
tb = testbed.Testbed()
tb.setup_env(current_version_id='testbed.version') #needed because endpoints expects a . in this value
tb.activate()
tb.init_all_stubs()
self.testbed = tb
def tearDown(self):
self.testbed.deactivate()
def test_endpoint_insert(self):
app = endpoints.api_server([TestEndpoint], restricted=False)
testapp = webtest.TestApp(app)
msg = {...} # a dict representing the message object expected by insert
# To be serialised to JSON by webtest
resp = testapp.post_json('/_ah/spi/TestEndpoint.insert', msg)
self.assertEqual(resp.json, {'expected': 'json response msg as dict'})
The thing here is you can easily setup appropriate fixtures in the datastore or other GAE services prior to calling the endpoint, thus you can more fully assert the expected side effects of the call.
2. Starting the development server for full integration test
You can start the dev server within the same python environment using something like the following:
import sys
import os
import dev_appserver
sys.path[1:1] = dev_appserver._DEVAPPSERVER2_PATHS
from google.appengine.tools.devappserver2 import devappserver2
from google.appengine.tools.devappserver2 import python_runtime
# ...
def setUp(self):
APP_CONFIGS = ['/path/to/app.yaml']
python_runtime._RUNTIME_ARGS = [
sys.executable,
os.path.join(os.path.dirname(dev_appserver.__file__),
'_python_runtime.py')
]
options = devappserver2.PARSER.parse_args([
'--admin_port', '0',
'--port', '8123',
'--datastore_path', ':memory:',
'--logs_path', ':memory:',
'--skip_sdk_update_check',
'--',
] + APP_CONFIGS)
server = devappserver2.DevelopmentServer()
server.start(options)
self.server = server
def tearDown(self):
self.server.stop()
Now you need to issue actual HTTP requests to localhost:8123 to run tests against the API, but again can interact with GAE APIs to set up fixtures, etc. This is obviously slow as you're creating and destroying a new dev server for every test run.
At this point I use the Google API Python client to consume the API instead of building the HTTP requests myself:
import apiclient.discovery
# ...
def test_something(self):
apiurl = 'http://%s/_ah/api/discovery/v1/apis/{api}/{apiVersion}/rest' \
% self.server.module_to_address('default')
service = apiclient.discovery.build('testendpoint', 'v1', apiurl)
res = service.testresource().insert({... message ... }).execute()
self.assertEquals(res, { ... expected reponse as dict ... })
This is an improvement over testing with CURL as it gives you direct access to the GAE APIs to easily set up fixtures and inspect internal state. I suspect there is an even better way to do integration testing that bypasses HTTP by stitching together the minimal components in the dev server that implement the endpoint dispatch mechanism, but that requires more research time than I have right now.
webtest can be simplified to reduce naming bugs
for the following TestApi
import endpoints
import protorpc
import logging
class ResponseMessageClass(protorpc.messages.Message):
message = protorpc.messages.StringField(1)
class RequestMessageClass(protorpc.messages.Message):
message = protorpc.messages.StringField(1)
#endpoints.api(name='testApi',version='v1',
description='Test API',
allowed_client_ids=[endpoints.API_EXPLORER_CLIENT_ID])
class TestApi(protorpc.remote.Service):
#endpoints.method(RequestMessageClass,
ResponseMessageClass,
name='test',
path='test',
http_method='POST')
def test(self, request):
logging.info(request.message)
return ResponseMessageClass(message="response message")
the tests.py should look like this
import webtest
import logging
import unittest
from google.appengine.ext import testbed
from protorpc.remote import protojson
import endpoints
from api.test_api import TestApi, RequestMessageClass, ResponseMessageClass
class AppTest(unittest.TestCase):
def setUp(self):
logging.getLogger().setLevel(logging.DEBUG)
tb = testbed.Testbed()
tb.setup_env(current_version_id='testbed.version')
tb.activate()
tb.init_all_stubs()
self.testbed = tb
def tearDown(self):
self.testbed.deactivate()
def test_endpoint_testApi(self):
application = endpoints.api_server([TestApi], restricted=False)
testapp = webtest.TestApp(application)
req = RequestMessageClass(message="request message")
response = testapp.post('/_ah/spi/' + TestApi.__name__ + '.' + TestApi.test.__name__, protojson.encode_message(req),content_type='application/json')
res = protojson.decode_message(ResponseMessageClass,response.body)
self.assertEqual(res.message, 'response message')
if __name__ == '__main__':
unittest.main()
I tried everything I could think of to allow these to be tested in the normal way. I tried hitting the /_ah/spi methods directly as well as even trying to create a new protorpc app using service_mappings to no avail. I'm not a Googler on the endpoints team so maybe they have something clever to allow this to work but it doesn't appear that simply using webtest will work (unless I missed something obvious).
In the meantime you can write a test script that starts the app engine test server with an isolated environment and just issue http requests to it.
Example to run the server with an isolated environment (bash but you can easily run this from python):
DATA_PATH=/tmp/appengine_data
if [ ! -d "$DATA_PATH" ]; then
mkdir -p $DATA_PATH
fi
dev_appserver.py --storage_path=$DATA_PATH/storage --blobstore_path=$DATA_PATH/blobstore --datastore_path=$DATA_PATH/datastore --search_indexes_path=$DATA_PATH/searchindexes --show_mail_body=yes --clear_search_indexes --clear_datastore .
You can then just use requests to test ala curl:
requests.get('http://localhost:8080/_ah/...')
If you don't want to test the full HTTP stack as described by Ezequiel Muns, you can also just mock out endpoints.method and test your API definition directly:
def null_decorator(*args, **kwargs):
def decorator(method):
def wrapper(*args, **kwargs):
return method(*args, **kwargs)
return wrapper
return decorator
from google.appengine.api.users import User
import endpoints
endpoints.method = null_decorator
# decorator needs to be mocked out before you load you endpoint api definitions
from mymodule import api
class FooTest(unittest.TestCase):
def setUp(self):
self.api = api.FooService()
def test_bar(self):
# pass protorpc messages directly
self.api.foo_bar(api.MyRequestMessage(some='field'))
My solution uses one dev_appserver instance for the entire test module, which is faster than restarting the dev_appserver for each test method.
By using Google's Python API client library, I also get the simplest and at the same time most powerful way of interacting with my API.
import unittest
import sys
import os
from apiclient.discovery import build
import dev_appserver
sys.path[1:1] = dev_appserver.EXTRA_PATHS
from google.appengine.tools.devappserver2 import devappserver2
from google.appengine.tools.devappserver2 import python_runtime
server = None
def setUpModule():
# starting a dev_appserver instance for testing
path_to_app_yaml = os.path.normpath('path_to_app_yaml')
app_configs = [path_to_app_yaml]
python_runtime._RUNTIME_ARGS = [
sys.executable,
os.path.join(os.path.dirname(dev_appserver.__file__),
'_python_runtime.py')
]
options = devappserver2.PARSER.parse_args(['--port', '8080',
'--datastore_path', ':memory:',
'--logs_path', ':memory:',
'--skip_sdk_update_check',
'--',
] + app_configs)
global server
server = devappserver2.DevelopmentServer()
server.start(options)
def tearDownModule():
# shutting down dev_appserver instance after testing
server.stop()
class MyTest(unittest.TestCase):
#classmethod
def setUpClass(cls):
# build a service object for interacting with the api
# dev_appserver must be running and listening on port 8080
api_root = 'http://127.0.0.1:8080/_ah/api'
api = 'my_api'
version = 'v0.1'
discovery_url = '%s/discovery/v1/apis/%s/%s/rest' % (api_root, api,
version)
cls.service = build(api, version, discoveryServiceUrl=discovery_url)
def setUp(self):
# create a parent entity and store its key for each test run
body = {'name': 'test parent'}
response = self.service.parent().post(body=body).execute()
self.parent_key = response['parent_key']
def test_post(self):
# test my post method
# the tested method also requires a path argument "parent_key"
# .../_ah/api/my_api/sub_api/post/{parent_key}
body = {'SomeProjectEntity': {'SomeId': 'abcdefgh'}}
parent_key = self.parent_key
req = self.service.sub_api().post(body=body,parent_key=parent_key)
response = req.execute()
etc..
After digging through the sources, I believe things have changed in endpoints since Ezequiel Muns's (excellent) answer in 2014. For method 1 you now need to request from /_ah/api/* directly and use the correct HTTP method instead of using the /_ah/spi/* transformation. This makes the test file look like this:
from google.appengine.ext import testbed
import webtest
# ...
def setUp(self):
tb = testbed.Testbed()
# Setting current_version_id doesn't seem necessary anymore
tb.activate()
tb.init_all_stubs()
self.testbed = tb
def tearDown(self):
self.testbed.deactivate()
def test_endpoint_insert(self):
app = endpoints.api_server([TestEndpoint]) # restricted is no longer required
testapp = webtest.TestApp(app)
msg = {...} # a dict representing the message object expected by insert
# To be serialised to JSON by webtest
resp = testapp.post_json('/_ah/api/test/v1/insert', msg)
self.assertEqual(resp.json, {'expected': 'json response msg as dict'})
For searching's sake, the symptom of using the old method is endpoints raising a ValueError with Invalid request path: /_ah/spi/whatever. Hope that saves someone some time!