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)