def test_get_candidate(self):
service = Service.get_instance()
candidate = service.get_candidate(candidate_id=1)
self.assertIsNotNone(candidate, "Candidate should not be None")
print(candidate.id, candidate.name)
print("Evaluation size", len(candidate.evaluations))
somme = 0
for evaluation in candidate.evaluations:
somme += evaluation.grade
print(evaluation.grade)
print("Grade sum", somme)
def parse_services(configuration):
services = {}
exposed_port = 5000
for name, config in configuration:
service = Service(name)
service.exposed_port = exposed_port
exposed_port += 1
service.load_home_route()
for route_ in config['routes']:
service.load_route(route_)
services[name] = service
return services
def test_get_candidates(self):
service = Service.get_instance()
candidates = service.all_candidates()
self.assertIsNotNone(candidates, "Candidates should not be null")
for candidate in candidates:
print(candidate.id, candidate.name)
def test_missing_evaluators(self):
service = Service.get_instance()
missing = service.get_missing_evaluators()
for missin in missing:
print(missin)
from flask import Flask, request
from nltk.corpus import stopwords
from src.service import Service
app = Flask(__name__)
app.config["DEBUG"] = True
#stop_words = set(stopwords.words('english'))
address = "mongodb://*****:*****@app.route('/api/q1', methods=['GET'])
def get_task1():
if 'country' in request.args:
country = str(request.args['country'])
else:
country = "all"
return obj.task1(country)
@app.route('/api/q1_spark', methods=['GET'])
def get_task1_spark():
if 'country' in request.args:
country = str(request.args['country'])
else:
country = "all"
return obj.task1_spark(country)
@app.route('/api/q2', methods=['GET'])
from src.service import load_etox_model
from src.service import Service
from src.service import CHECKPOINTS_BASEDIR, FRAMEWORK_BASEDIR
import os
root = os.path.dirname(os.path.realpath(__file__))
mdl = load_etox_model(
os.path.join(root, "model", FRAMEWORK_BASEDIR),
os.path.join(root, "model", CHECKPOINTS_BASEDIR),
)
service = Service()
service.pack("model", mdl)
service.save()
from src.service import Service
service = Service()
service.pack("model", None)
service.save()
def __init__(self):
print('Controller class')
global service
service = Service()
def __init__(self):
self.service = Service().instance()
self.user_id = "me"
self.messagesQueue = collections.deque()
self.failedMessagesQueue = collections.deque()
class Processor:
# Talk to google api, fetch results and decorate them
def __init__(self):
self.service = Service().instance()
self.user_id = "me"
self.messagesQueue = collections.deque()
self.failedMessagesQueue = collections.deque()
def get_messages(self):
# Get all messages of user
# Output format:
# [{'id': '13c...7', 'threadId': '13c...7'}, ...]
# if os.path.exists("messages.pickle"):
# with open("messages.pickle", "rb") as token:
# messages = pickle.load(token)
# return messages
# includeSpamTrash
# labelIds
response = self.service.users().messages().list(
userId=self.user_id).execute()
messages = []
est_max = response["resultSizeEstimate"] * 5
progress = Counter(
f"{helpers.loader_icn} Fetching messages page ".ljust(
_progressPadding, " "))
if "messages" in response:
messages.extend(response["messages"])
while "nextPageToken" in response:
page_token = response["nextPageToken"]
response = (self.service.users().messages().list(
userId=self.user_id, pageToken=page_token).execute())
messages.extend(response["messages"])
progress.next()
progress.finish()
return messages
def process_message(self, request_id, response, exception):
if exception is not None:
self.failedMessagesQueue.append(exception.uri)
return
headers = response["payload"]["headers"]
_date = next((header["value"]
for header in headers if header["name"] == "Date"), None)
_from = next((header["value"]
for header in headers if header["name"] == "From"), None)
self.messagesQueue.append({
"id": response["id"],
"labels": response["labelIds"],
"fields": {
"from": _from,
"date": _date
},
})
def get_metadata(self, messages):
# Get metadata for all messages:
# 1. Create a batch get message request for all messages
# 2. Process the returned output
#
# Output format:
# {
# 'id': '16f....427',
# 'labels': ['UNREAD', 'CATEGORY_UPDATES', 'INBOX'],
# 'fields': [
# {'name': 'Date', 'value': 'Tue, 24 Dec 2019 22:13:09 +0000'},
# {'name': 'From', 'value': 'Coursera <*****@*****.**>'}
# ]
# }
# if os.path.exists("success.pickle"):
# with open("success.pickle", "rb") as token:
# self.messagesQueue = pickle.load(token)
# return
progress = IncrementalBar(
f"{helpers.loader_icn} Fetching messages meta data ".ljust(
_progressPadding, " "),
max=len(messages),
)
for messages_batch in helpers.chunks(messages, 250):
# for messages_batch in [messages[0:1000]]:
batch = self.service.new_batch_http_request()
for message in messages_batch:
msg_id = message["id"]
batch.add(
self.service.users().messages().get(userId=self.user_id,
id=msg_id),
callback=self.process_message,
)
batch.execute()
progress.next(len(messages_batch))
progress.finish()
from src.service import Service
service = Service()
service.pack('model', None)
service.save()