2023-04-05 16:28:39 -05:00
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from flask import Flask
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from flask_restful import Resource, Api, reqparse
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import pandas as pd
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2023-04-05 18:27:14 -05:00
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import numpy as np
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2023-04-05 16:28:39 -05:00
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import ast
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2023-04-05 17:36:16 -05:00
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import kiss
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2023-04-05 18:21:37 -05:00
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import glob
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2023-04-05 16:28:39 -05:00
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app = Flask(__name__)
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2023-04-05 16:58:35 -05:00
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api = Api(app)
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class Users(Resource):
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def get(self):
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data = pd.read_csv('users.csv') # read CSV
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2023-04-05 19:05:57 -05:00
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data = data.to_dict(orient = 'records') # convert dataframe to dictionary
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2023-04-05 16:58:35 -05:00
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return {'data': data}, 200 # return data and 200 OK code
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2023-04-05 17:36:16 -05:00
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2023-04-05 16:58:35 -05:00
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class Locations(Resource):
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def get(self):
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data = pd.read_csv('locations.csv') # read CSV
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2023-04-05 19:05:57 -05:00
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data = data.to_dict(orient = 'records') # convert dataframe to dictionary
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2023-04-05 16:58:35 -05:00
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return {'data': data}, 200 # return data and 200 OK code
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2023-04-05 17:36:16 -05:00
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2023-04-05 18:21:37 -05:00
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# Read some log files
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list_stacked = pd.DataFrame()
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file_list = glob.glob("logs/*.log")
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#print(file_list)
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2023-04-05 18:21:37 -05:00
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for file in file_list:
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file1 = pd.read_csv(file)
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list_stacked = pd.concat([list_stacked, file1])
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2023-04-05 18:27:14 -05:00
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# TODO Can we do this without numpy?
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list_stacked.replace(np.nan, 0, inplace=True)
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#print(list_stacked.head())
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class Packets(Resource):
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def get(self):
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data = list_stacked
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data = data.to_dict(orient = 'records') # convert dataframe to dictionary
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#data = data.to_json(orient='records')
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2023-04-05 18:21:37 -05:00
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return {'data': data}, 200 # return data and 200 OK code
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2023-04-05 16:58:35 -05:00
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api.add_resource(Users, '/users') # '/users' is our entry point for Users
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api.add_resource(Locations, '/locations') # and '/locations' is our entry point for Locations
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2023-04-05 18:21:37 -05:00
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api.add_resource(Packets, '/packets') # and '/locations' is our entry point for Locations
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if __name__ == '__main__':
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app.run(debug=True) # run our Flask app
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