Initialize a python class only once on webpy - python

I am using web.py to host a simple web service. The web service runs an analytics application in the backend (inside ClassA). During the initialization of web.py, I'd like to pre-load all data into the memory (i.e call a = ClassA() only once when web server is started), and when the user sends a web request, the web server will just response with the pre-calculated result (i.e return a.do_something).
The code below seems to run init() of class 'add' everytime a HTTP POST request is received. This is a waste of time because the initialization stage takes pretty long. Is it possible to initialize ClassA only once?
import web
from aclass import ClassA
urls = (
'/add', 'add'
)
class add:
def __init__(self):
a = ClassA()
def POST(self):
return a.do_something()
if __name__ == "__main__":
app = web.application(urls, globals())
app.run()

Try:
class add:
a = ClassA()
def POST(self):
return add.a.do_something()
This will make it a class-bound parameter instead of a instance-bound one, i.e. only initializing it once.

Related

AssertionError: View function mapping is overwriting an existing endpoint function: api.users

I am trying to write a simple unittest case for my app but it crashes after the first test with error:
AssertionError: View function mapping is overwriting an existing endpoint function: api.users
Below is my test case (I use Flask-Testing):
class RestApiTestCase(TestCase):
def create_app(self):
app = create_app('config.testing')
self.client = app.test_client()
return app
def setUp(self):
self.db = DAO(db)
init_db(db)
def tearDown(self):
db.session.remove()
drop_db(db)
self.db = None
I didn't post tests because of it doesn't play any role, it always completes the first test and crashes on the next.
I tried to call app_context.push() on setUp and app_context.pop() on tearDown but it didn't help, I tried to use simple unittest and it still fails.
Where can problem be? I use blueprint and Flask-RESTful in my app, should I unbind it manually on shutting down app event?

How can I run a coroutine in Python?

My webscraper takes about 10 mins to run, I am trying to use the threading library to allow my webscraper to run in the background after data has been returned to whomever made a call to my API I created with Flask.
My code looks something like this:
from threading import Thread
from flask import Flask
application = Flask(__name__)
class Compute(Thread):
def __init__(self, request):
print("init")
Thread.__init__(self)
self.request = request
def run(self):
print("RUN")
command = './webscrape.py -us "{user}" -p "{password}" -url "{url}"'.format(**self.request.json)
output = subprocess.call(['bash','-c', command])
#application.route('/scraper/run', methods=['POST'])
def init_scrape():
thread_a = Compute(request.__copy__())
thread_a.start()
return jsonify({'Scraping this site: ': request.json["url"]}), 201
if __name__ == '__main__':
application.run(host="0.0.0.0", port="8080")
Now I am testing my API with postman and when I make a POST request it prints out "init" but dosen't seem to go any further to start the run() function, what am I doing wrong?

Python3 Flask - missing 1 required positional argument: 'self'

I have very simple python code to access Amazon Simple Queue Service. But I get
builtins.TypeError
TypeError: get_queue() missing 1 required positional argument: 'self'
My code:
class CloudQueue(object):
conn = boto.sqs.connect_to_region("eu-west-1",
aws_access_key_id="abc",
aws_secret_access_key="abc")
#app.route('/get/<name>')
def get_queue(self, name):
if(name != None):
queue = self.conn.get_queue(str(name)) <--------- HERE
return conn.get_all_queues()
if __name__ == "__main__":
cq = CloudQueue()
app.debug = True
app.run()
You cannot register methods as routes; at the time the decorator runs the class is still being defined and all you registered is the unbound function object. Since it is not bound to an instance there is no self to pass in.
Do not use a class here; create the connection anew for each request:
#app.route('/get/<name>')
def get_queue(name):
conn = boto.sqs.connect_to_region("eu-west-1",
aws_access_key_id="abc",
aws_secret_access_key="abc")
queue = conn.get_queue(name)
return 'some response string'
You could set it as a global but then you need to make sure you re-create the connection on the first request (so it continues to work even when using a WSGI server using child processes to handle requests):
#app.before_first_request()
def connect_to_boto():
global conn
conn = boto.sqs.connect_to_region("eu-west-1",
aws_access_key_id="abc",
aws_secret_access_key="abc")
#app.route('/get/<name>')
def get_queue(name):
queue = conn.get_queue(name)
return 'some response string'
Use this only if you are sure that boto connection objects are thread-safe.

How to unit test Google Cloud Endpoints

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!

Run a function once on bottle.py startup

I have a bottle app that I eventually wan't to deploy on apache (just fyi in case that's important).
Now I need to run a function once after the bottle app is started. I can't just put it into a routed function because it has to run even if no user has accessed the site yet.
Any best pratice to do this ?
The function starts a APScheduler Instance and adds a jobstore to it.
Here's what I do.
def initialize():
//init whatever you need.
if __name__ == '__main__':
initialize()
#bottle.run(port='8080', yatta yatta)
Honestly your problem is simply a sync vs async issue. Use gevent to easily convert to microthreads, and then launch each separately. You can even add a delay either in your function or before with gevent.sleep if you want to wait for the web server to finish launching.
import gevent
from gevent import monkey, signal, spawn, joinall
monkey.patch_all()
from gevent.pywsgi import WSGIServer
from bottle import Bottle, get, post, request, response, template, redirect, hook, abort
import bottle
#get('/')
def mainindex():
return "Hello World"
def apScheduler():
print "AFTER SERVER START"
if __name__ == "__main__":
botapp = bottle.app()
server = WSGIServer(("0.0.0.0", 80), botapp)
threads = []
threads.append(spawn(server.serve_forever))
threads.append(spawn(apScheduler))
joinall(threads)
Create an APScheduler class.
Look at examples of object use and creation in this same site bacause it's too general to give an especific example to copy.
I don't know if this helps.
class Shed(object):
def __init__(self): # this to start it
# instruccions here
def Newshed(self, data):
# Call from bottle
# more methods ...
...
# init
aps = Shed() # this activates Shed.__init__()
...
# in the #router
x = aps.Newshed(data) # or whatever
Anyway I'm still learning this stuff and it's just an idea.
import threading
import bottle
def init_app():
def my_function_on_startup():
# some code here
pass
app = bottle.app()
t = threading.Thread(target=my_function_on_startup)
t.daemon = True
t.start()
return app
app = init_app()
#app.route("/")
def hello():
return "App is running"
if __name__ == "__main__":
bottle.run(app, host='localhost', port=8080, debug=True)

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