class Jobs(Resource):
parser = api.parser()
parser.add_argument('page_size',
required=False,
type=str,
help="Job Listing Pagination Size")
parser.add_argument('offset',
required=False,
type=str,
help="Job Listing Pagination Offset")
def get(self, username):
"""
This will return run a list of jobs for a specified user
:return:
"""
# request_xml = request.data
# job_id = ogc.parse_status_request(request_xml)
try:
logging.info("Finding jobs for user: {}".format(username))
size = request.form.get('page_size',
request.args.get('page_size', 100))
offset = request.form.get('offset', request.args.get('offset', 0))
response = hysds.get_mozart_jobs(username=username,
page_size=size,
offset=offset)
job_list = response.get("result")
logging.info("Found Jobs: {}".format(job_list))
response_body = dict()
response_body["code"] = 200
response_body["jobs"] = job_list
response_body["message"] = "success"
"""
<?xml version="1.0" encoding="UTF-8"?>
<Jobs>
<Job>
<JobID></JobID>
<JobStatus></JobStatus>
<JobType></JobType>
<JobParams></JobParams>
</Job>
<Job>...</Job>
<Job>...</Job>
...
<Jobs>
"""
return response_body
except Exception as ex:
return Response(ogc.get_exception(type="FailedGetJobs", origin_process="GetJobs",
ex_message="Failed to get jobs for user {}. " \
" please contact administrator " \
"of DPS".format(username)), mimetype='text/xml', status=500)
from flask_restplus import Resource
from werkzeug.datastructures import FileStorage
from flask import current_app as app
from ..models import timeplan_item
from api.restplus import api
ns = api.namespace(
'timeplan',
description='Operations related to the injection timeplan of the host')
timeplan_parser = api.parser()
timeplan_parser.add_argument('timeplan',
location='files',
type=FileStorage,
required=True)
@ns.route('/')
class HostTimePlan(Resource):
@api.doc(responses={
200: 'Timeplan has been returned.',
400: 'No Timeplan exists.'
})
@api.marshal_with(timeplan_item)
def get(self):
"""
Returns the currently injected timeplan as JSON Object.
"""
AnomalyEngine = app.config['AnomalyEngine']
timeplan = AnomalyEngine.timeplan
from flask_restplus import Resource, fields
from api.restplus import api
from api.ende.logic.tf_client import make_prediction
from werkzeug.datastructures import FileStorage
from nltk import sent_tokenize
# create dedicated namespace for ENDE client
ns = api.namespace(
'ende_client',
description=
'Operations for Translating the ende model using the sentence piece model')
# Flask-RestPlus specific parser for file uploading
UPLOAD_KEY = 'file'
UPLOAD_LOCATION = 'files'
upload_parser = api.parser()
upload_parser.add_argument(UPLOAD_KEY,
location=UPLOAD_LOCATION,
type=FileStorage,
required=True)
text_parser = api.parser()
text_parser.add_argument('text', required=True, help='enter sentences')
@ns.route('/prediction/file')
class EndePredictionFile(Resource):
@ns.doc(description='input is text file, output json',
responses={
200: "Success",
400: "Bad request",
500: "Internal server error"
import logging
from flask import request
from flask_restplus import Resource
from api.restplus import api
from api.gan.logic.tf_serving_client import make_prediction
from werkzeug.datastructures import FileStorage
log = logging.getLogger(__name__)
# create dedicated namespace for GAN client
ns = api.namespace('gan_client', description='Operations for GAN client')
# Flask-RestPlus specific parser for image uploading
UPLOAD_KEY = 'inputs'
UPLOAD_LOCATION = 'files'
upload_parser = api.parser()
upload_parser.add_argument(UPLOAD_KEY,
location=UPLOAD_LOCATION,
type=FileStorage,
required=True)
@ns.route('/prediction')
class GanPrediction(Resource):
@ns.doc(
description='Predict the house number on the image using GAN model. ' +
'Return 3 most probable digits with their probabilities',
responses={
200: "Success",
400: "Bad request",
500: "Internal server error"
import json
from flask import request
from flask_restplus import Resource
from api.restplus import api
from api.gan.logic.tf_serving_client import make_prediction
from werkzeug.datastructures import FileStorage
# create dedicated namespace for GAN client
ns = api.namespace('gan_client', description='Operations for GAN client')
# Flask-RestPlus specific parser for image uploading
UPLOAD_KEY = 'image'
UPLOAD_LOCATION = 'files'
upload_parser = api.parser()
upload_parser.add_argument(UPLOAD_KEY,
location=UPLOAD_LOCATION,
type=FileStorage,
required=True)
@ns.route('/prediction')
class GanPrediction(Resource):
@ns.doc(description='Predict the house number on the image using GAN model. ' +
'Return 3 most probable digits with their probabilities',
responses={
200: "Success",
400: "Bad request",
500: "Internal server error"
})
from flask_restplus import Resource, reqparse
from flask import current_app as app
from api.restplus import api
from ..models import wan_simulation
import logging
import json
ns = api.namespace('wan_simulation',
description='Simulate a Wide Area Network')
simulation_parser = api.parser()
simulation_parser.add_argument('rate',
type=str,
required=False,
help="Network bandwidth rate")
simulation_parser.add_argument('delay',
type=str,
required=False,
help="Round trip network delay in ms")
simulation_parser.add_argument('delay-distro',
type=str,
required=False,
help="Distribution of network latency")
simulation_parser.add_argument('loss',
type=str,
required=False,
help="Round trip packet loss rate")
simulation_parser.add_argument('duplicate',
type=str,
required=False,
help="Round trip packet duplicate rat")