import tornado.web
import tornado.ioloop
from apiApplicationModel import userData
from cleanArray import Label_Correction
import json
import requests
colName=['age', 'resting_blood_pressure', 'cholesterol', 'max_heart_rate_achieved', 'st_depression', 'num_major_vessels', 'st_slope_downsloping', 'st_slope_flat', 'st_slope_upsloping', 'sex_male', 'chest_pain_type_atypical angina', 'chest_pain_type_non-anginal pain', 'chest_pain_type_typical angina', 'fasting_blood_sugar_lower than 120mg/ml', 'rest_ecg_left ventricular hypertrophy', 'rest_ecg_normal', 'exercise_induced_angina_yes', 'thalassemia_fixed defect', 'thalassemia_normal',
'thalassemia_reversable defect']
class processRequestHandler(tornado.web.RequestHandler):
def post(self):
data_input_array = []
for name in colName:
x = self.get_body_argument(name, default=0)
data_input_array.append(int(x))
label = Label_Correction(data_input_array)
finalResult = int(userData(label))
output = json.dumps({"Giveput":finalResult})
self.write(output)
class basicRequestHandler(tornado.web.RequestHandler):
def get(self):
self.render('report.html')
class staticRequestHandler(tornado.web.RequestHandler):
def post(self):
data_input_array = []
for name in colName:
x = self.get_body_argument(name, default=0)
data_input_array.append(str(x))
send_data = dict(zip(colName, data_input_array))
print(send_data)
print(type(send_data))
url = "http://localhost:8887/output"
headers={}
response = requests.request('POST',url,headers=headers,data=send_data)
print(response.text.encode('utf8'))
print("DONE")
if __name__=='__main__':
app = tornado.web.Application([(r"/",basicRequestHandler),
(r"/result",staticRequestHandler),
(r"/output",processRequestHandler)])
print("API IS RUNNING.......")
app.listen(8887)
tornado.ioloop.IOLoop.current().start()
Actually I am trying to create an API and the result of the API can be used but
The page keeps on loading, and no response is shown.
Response should be a python dictionary send by post function of class processRequestHandler
After using a debugger the lines after response = requests.request('POST',url,headers=headers,data=send_data) are not executed.
The class processRequestHandler is working fine when checked with POSTMAN.
requests.request is a blocking method. This blocks the event loop and prevents any other handlers from running. In a Tornado handler, you need to use Tornado's AsyncHTTPClient (or another non-blocking HTTP client such as aiohttp) instead.
async def post(self):
...
response = await AsyncHTTPClient().fetch(url, method='POST', headers=headers, body=send_data)
See the Tornado users's guide for more information.
Related
I have a ros2 publisher script that sends custom messages from ros2 nodes. What I need to do is to have a subscriber (which is also my websocket server) to listen to the message that the pulisher sends then convert it to a dictionary and send it as a json from the websocket server to a connected websocket client. I have already checked the rosbridge repo but I could not make it work. It doesn't have enough documentation and I am new to ros.
I need something like this:
import rclpy
import sys
from rclpy.node import Node
import tornado.ioloop
import tornado.httpserver
import tornado.web
import threading
from custom.msg import CustomMsg
from .convert import message_to_ordereddict
wss = []
class wsHandler(tornado.websocket.WebSocketHandler):
def open(self):
print 'Online'
if self not in wss:
wss.append(self)
def on_close(self):
print 'Offline'
if self in wss:
wss.remove(self)
def wsSend(message):
for ws in wss:
ws.write_message(message)
class MinimalSubscriber(Node):
def __init__(self):
super().__init__('minimal_subscriber')
self.subscription = self.create_subscription(CustomMsg, 'topic', self.CustomMsg_callback, 10)
self.subscription # prevent unused variable warning
def CustomMsg_callback(self, msg):
ws_message = message_to_ordereddict(msg)
wsSend(ws_message)
if __name__ == "__main__":
http_server = tornado.httpserver.HTTPServer(tornado.web.Application(wsHandler))
http_server.listen(8888)
main_loop = tornado.ioloop.IOLoop.instance()
# Start main loop
main_loop.start()
so the callback function in MinimalSubscriber class, receives the ros message, converts it to dictionary and sends it to websocket client. I am a bit confused how to make these two threads (ros and websocket) to communicate with each other.
So I think I got a bit confused myself going through the threading. So I changed my approach and made it work using the tornado periodic callback and the spin_once function of rclpy as the callback function. I would post my solution as it might help some people who has the same issue.
import queue
import rclpy
from rclpy.node import Node
import tornado.ioloop
import tornado.httpserver
import tornado.web
from custom.msg import CustomMsg
from .convert import message_to_ordereddict
wss = []
class wsHandler(tornado.websocket.WebSocketHandler):
#classmethod
def route_urls(cls):
return [(r'/',cls, {}),]
def open(self):
print 'Online'
if self not in wss:
wss.append(self)
def on_close(self):
print 'Offline'
if self in wss:
wss.remove(self)
def make_app():
myWebHandler = wsHandler.route_urls()
return tornado.web.Application(myWebHandler)
message_queue = queue.Queue
class MinimalSubscriber(Node):
def __init__(self):
super().__init__('minimal_subscriber')
self.subscription = self.create_subscription(CustomMsg, 'topic', self.CustomMsg_callback, 10)
self.subscription # prevent unused variable warning
def CustomMsg_callback(self, msg):
msg_dict = message_to_ordereddict(msg)
msg_queue.put(msg_dict)
if __name__ == "__main__":
rclpy.init(args=args)
minimal_subscriber = MinimalSubscriber()
def send_ros_to_clients():
rclpy.spin_once(minimal_subscriber)
my_msg = msg_queue.get()
for client in ws_clients:
client.write_message(my_msg)
app = make_app()
server = tornado.httpserver.HTTPServer(app)
server.listen(8888)
tornado.ioloop.PeriodicCallback(send_ros_to_clients, 1).start()
tornado.ioloop.IOLoop.current().start()
minimal_subscriber.destroy_node()
rclpy.shutdown()
I also implemented the wsSend function into the send_ros_to_clients function. Some might say that using a global queue is not the best practice but I could not come up with another solution. I would appreciate any suggestions or corrections on my solution.
What would be the best approach for setting a timeout condition on a task/function that's been submitted to a ThreadPoolExecutor using tornado.concurrent's #run_on_executor decorator? Example Tornado handler below:
import json
import time
import tornado.web
from concurrent.futures import ThreadPoolExecutor
from tornado.concurrent import run_on_executor
class MyHandler(tornado.web.RequestHandler):
def initialize(self) -> None:
self.executor = ThreadPoolExecutor(1)
#run_on_executor
def blocking_function(self) -> None:
""" Run Blocking Function on ThreadPoolExecutor. """
seconds = 10
time.sleep(seconds)
response = json.dumps({"message": f"Slept for {seconds} seconds."})
return response
async def get(self) -> None:
response = await self.blocking_function()
self.write(response)
Does something like tornado.gen.with_timeout found here exist for #run_on_executor?
Thank you for your time.
Since run_on_executor returns a Future object, you can use it with gen.with_timetout:
from datetime import timedelta
async def get(self):
response = await gen.with_timeout(
timedelta(seconds=5),
self.blocking_function()
)
...
Don't forget to handle the timeout exception.
I have begun writing unit tests for my Flask API. I have gotten them to work when declared outside of a class. However, for simplicity and OOP constraints, I am trying to have everything run from a class. The issue is I cannot seem to pass any fixture methods to my test class. The code I have here is as follow:
#conftest.py
import os, json, pytest
from ..app import create_app
from flask import Flask
#pytest.fixture
def env_setup():
env_name = os.getenv('FLASK_ENV')
app = create_app(env_name)
return app
I am trying to import env_setup into the following file.
# test_BaseURL.py
import pytest
#pytest.mark.usefixtures("env_setup")
class TestStaticPages:
def setUp(self, env_setup):
"""
Setup Test
"""
self.client = env_setup.test_client()
def test_base_route(self, env_setup):
#client = env_setup.test_client()
url = '/'
html1 = b'Welcome to the API. Please visit '
html2 = b'https://example.com to learn more about this app.'
response = self.client.get(url)
assert response.get_data() == html1 + html2
assert response.status_code == 200
I keep geeting the following error when I run this test:
> response = self.client.get(url)
E AttributeError: 'TestStaticPages' object has no attribute 'client'
src/tests/test_BaseURL.py:18: AttributeError
However if I should uncomment the line with client = env_setup.test_client() it works. For whatever reason it cannot seem to grab the setup from the setUP method and keeps erroring out.
Here is how I fixed my issue:
#conftest.py
import os, json, pytest
from ..app import create_app
from flask import Flask
#pytest.fixture
def client():
env_name = os.getenv('FLASK_ENV')
app = create_app(env_name)
client = app.test_client()
return client
I was then able to import the client into my other test class like so.
#test_StaticView.py
import pytest
#pytest.mark.usefixtures("client")
class TestStaticPages:
def test_base_route(self, client):
url = '/'
html1 = b'Welcome to the API. Please visit '
html2 = b'https://example.com to learn more about this app.'
response = client.get(url)
assert response.get_data() == html1 + html2
assert response.status_code == 200
The Python3 fetch_token method in this library does not check the response status before consuming the response. If the API call it makes fails, then the response will be invalid and the script crashes. Is there something I can set so that an exception will be raised on a non-success response before the library can read the response?
import requests
from requests.auth import HTTPBasicAuth
from requests_oauthlib import OAuth2Session
from oauthlib.oauth2 import BackendApplicationClient
from oauthlib.oauth2 import OAuth2Error
AUTH_TOKEN_URL = "https://httpstat.us/500" # For testing
AUTH = HTTPBasicAuth("anID", "aSecret")
CLIENT = BackendApplicationClient(client_id="anID")
SCOPES = "retailer.orders.write"
MAX_API_RETRIES = 4
class MyApp:
def __init__(self):
"""Initialize ... and obtain initial auth token for request"""
self.client = OAuth2Session(client=CLIENT)
self.client.headers.update(
{
"Content-Type": "application/json"
}
)
self.__authenticate()
def __authenticate(self):
"""Obtain auth token."""
server_errors = 0
# This needs more work. fetch_token is not raising errors but failing
# instead.
while True:
try:
self.token = self.client.fetch_token(
token_url=AUTH_TOKEN_URL, auth=AUTH, scope=SCOPES
)
break
except (OAuth2Error, requests.exceptions.RequestException) as e:
server_errors = MyApp.__process_retry(
server_errors, e, None, MAX_API_RETRIES
)
#staticmethod
def __process_retry(errors, exception, resp, max_retries):
# Log and process retries
# ...
return errors + 1
MyApp() # Try it out
You can add a "compliance hook" that will be passed the Response object from requests before the library attempts to parse it, like so:
def raise_on_error(response):
response.raise_for_status()
return response
self.client.register_compliance_hook('access_token_response', raise_on_error)
Depending on exactly when you may get errors, you might want to do this with 'refresh_token_response' and/or 'protected_request' as well. See the docstring for the register_compliance_hook method for more info.
I am trying to implement asynchronous http reverse proxy with tornado on Python3.
Handler class is as follows:
class RProxyHandler(tornado.web.RequestHandler):
#tornado.web.asynchronous
def get(self):
backend_url = 'http://backend-host/content.html' # temporary fixed
req = tornado.httpclient.HTTPRequest(
url=backend_url)
http_client = tornado.httpclient.AsyncHTTPClient()
http_client.fetch(req, self.backend_callback)
def backend_callback(self, response):
self.write(response.body)
self.finish()
When content.html is small, this code works fine. But with large content.html, this code raises Exception:
ERROR:tornado.general:Reached maximum read buffer size
I found the way to handle large contents with pycurl. Though, it seems does not work with Python3.
In addition, I added streaming_callback option to HTTPRequest. But the callback won't be called when disabled chunked response by backend server.
How can I handle large contents?
Thanks.
You should be able to pass max_buffer_size to the tornado.httpclient.AsyncHTTPClient()
call to set the max buffer size. for a 50MB buffer:
import tornado.ioloop
import tornado.web
from tornado.httpclient import AsyncHTTPClient
from tornado import gen
from tornado.web import asynchronous
class MainHandler(tornado.web.RequestHandler):
client = AsyncHTTPClient(max_buffer_size=1024*1024*150)
#gen.coroutine
#asynchronous
def get(self):
response = yield self.client.fetch("http://test.gorillaservers.com/100mb.bin", request_timeout=180)
self.finish("%s\n" % len(response.body))
application = tornado.web.Application([
(r"/", MainHandler),
])
if __name__ == "__main__":
application.listen(8888)
tornado.ioloop.IOLoop.instance().start()
Update: Now a full example program.