raise req.exceptions.RequestException(
'Missing or invalid request body')
names = np.array(body['data']['names'])
data = np.array(body['data']['ndarray'])
query_df = pd.DataFrame(data=data, columns=names)
prediction, labels = model.predict(query_df)
pred_pkgd = [[p] for p in prediction]
return jsonify({
"status": {
"code": 200,
"status": "SUCCESS"
},
"meta": {
"tags": {
"model_version": VERSION
}
},
"data": {
"names": labels,
"ndarray": pred_pkgd
}
})
if __name__ == '__main__':
port = 5000
app.run(port=port, debug=True)
from flask import Flask
from flask_restplus import Api, Resource
from flask import Flask, render_template, url_for, request
flask_app = Flask(__name__)
app = Api(app=flask_app)
name_space = app.namespace('main', description='Main APIs')
@name_space.route("/")
class MainClass(Resource):
def get(self):
return {"status": "Got new data"}
def post(self):
choice = request.form['taskoption']
rawtext = request.form['rawtext']
if __name__ == '__main__':
app.run(debug=True)
"name" : list_of_names[id],
"details" : content['details']
}
except KeyError as e:
flask_app.logger.error('Error 500 Could not retrieve information ' + e.__doc__ )
name_space.abort(500, e.__doc__, status = "Could not retrieve information", statusCode = "500")
except Exception as e:
flask_app.logger.error('Error 400 Could not retrieve information ' + e.__doc__ )
name_space.abort(400, e.__doc__, status = "Could not retrieve information", statusCode = "400")
@app.doc(responses={ 200: 'OK', 400: 'Invalid Argument', 500: 'Mapping Key Error' })
@app.expect(model)
def post(self, id):
try:
list_of_names[id] = request.json['name']
flask_app.logger.info('Post Request succeeded ' + list_of_names[id])
return {
"status": "New Product added to Product Catalog",
"name": list_of_names[id]
}
except KeyError as e:
flask_app.logger.error('Error 500 Could not retrieve information ' + e.__doc__ )
name_space.abort(500, e.__doc__, status = "Could not save information", statusCode = "500")
except Exception as e:
flask_app.logger.error('Error 400 Could not retrieve information ' + e.__doc__ )
name_space.abort(400, e.__doc__, status = "Could not save information", statusCode = "400")
if __name__ == '__main__':
app.run(host="0.0.0.0", debug=True)
from flask import Flask
from flask_restplus import Api, Resource
flask_app = Flask(__name__)
app = Api(app=flask_app)
name_space = app.namespace('main', description='Main APIs')
@app.route('/')
def hello_world():
return 'Hello, World!'
if __name__ == "__main__":
app.run(host='0.0.0.0')
# @app.expect(model)
# def post(self, name):
# try:
# res = recommendation.results(request.json['name'])
# return jsonify(res)
# # list_of_names[id] = request.json['name']
# # return {
# # "status": "New person added",
# # "name": list_of_names[id]
# # }
# except KeyError as e:
# name_space.abort(500, e.__doc__, status="Could not save information", statusCode="500")
# except Exception as e:
# name_space.abort(400, e.__doc__, status="Could not save information", statusCode="400")
# @app.route('/movie', methods=['GET'])
# def recommend_movies():
# res = recommendation.results(request.args.get('title'))
# return jsonify(res)
#
# def recommend_movies():
# res = results(request.args.get('title'))
# return jsonify(res)
if __name__ == '__main__':
port = int(os.environ.get("PORT" or 5000))
app.run(host="0.0.0.0", port=port)
response = make_response()
response.headers.add("Access-Control-Allow-Origin", "*")
response.headers.add('Access-Control-Allow-Headers', "*")
response.headers.add('Access-Control-Allow-Methods', "*")
return response
@app.expect(model)
def post(self):
try:
formData = request.json
data = [val for val in formData.values()]
print(data)
prediction = classifier.predict(np.array(data))
response = jsonify({
"statusCode": 200,
"status": "Prediction made",
"result": "The Bitcoin Market Value must be: " + prediction
})
response.headers.add('Access-Control-Allow-Origin', '*')
return response
except Exception as error:
return jsonify({
"statusCode": 500,
"status": "Could not make prediction",
"error": str(error)
})
if __name__ == "__main__":
port = int(os.environ.get("PORT", 5000))
app.run(host='0.0.0.0', port=port)
params={
'start_date': 'Starting date for the prediction window',
'end_date': 'Ending date for the prediction window'
})
@app.expect(truth_parser)
def get(self):
"""Get critical violation truths"""
args = truth_parser.parse_args()
self.start_date = args['start_date']
self.end_date = args['end_date']
self.model_name = args['model']
self.model = self.load_model()
inspecs = pd.read_csv('./data/inspec_scores.csv', parse_dates=[DATE])
df = select_by_date(inspecs, self.start_date, self.end_date)
output = {
'camis': df.camis.values.tolist(),
DATE: df[DATE].strftime("%Y-%m-%d").values.tolist(),
'critical': df.critical.values.tolist()
}
return jsonify(output)
def load_model(self):
pass
if __name__ == '__main__':
app.run(port='5000', debug=True)
