def load_sample_data():
"""
This will load sample data. The following users are created:
Root / password
Jim / bunny
Bill / gopher
:return:
"""
db = Database()
db.start_engine()
content_key = generate_key()
user1_key = generate_key()
content_key_encrypted = Encrypter(user1_key).encrypt(content_key)
user1 = User(username='******',password='******',content_key=content_key_encrypted,encrypt_key=user1_key)
db.session.add(user1)
user2_key = generate_key()
content_key_encrypted = Encrypter(user2_key).encrypt(content_key)
user2 = User(username='******',password='******',content_key=content_key_encrypted,encrypt_key=user2_key)
db.session.add(user2)
user3_key = generate_key()
content_key_encrypted = Encrypter(user3_key).encrypt(content_key)
user3 = User(username='******',password='******',content_key=content_key_encrypted,encrypt_key=user3_key)
db.session.add(user3)
db.session.commit()
def setup():
db = Database()
db.createMatchTable()
employeePath = '../data/employees.csv'
employerPath = '../data/employers.csv'
model = pickle.load(open('/data/model.pickle', 'rb'))
employeeData = pd.read_csv(employeePath, sep=',')
employeeData['merge'] = 1
employerDataReader = pd.read_csv(employerPath, sep=',', chunksize=1)
for employerData in employerDataReader:
employerData['merge'] = 1
df = pd.merge(employerData, employeeData, on='merge')
del df['merge']
attrs = set(df.columns.values)
ignoredAttrs = set([
'id_x', 'id_y', 'nameFirst_x', 'nameFirst_y', 'nameLast_x',
'nameLast_y', 'origin_x', 'origin_y'
])
inputAttrs = list(attrs - ignoredAttrs)
inputsMap = DataFrameMapper([(inputAttrs, None)])
inputSamples = inputsMap.fit_transform(df)
#print(df)
result = pd.DataFrame(
data={
'id_x': df['id_x'],
'id_y': df['id_y'],
'score': model.predict(inputSamples)
})
id = 0
result.sort_values(by=['score'], ascending=False, inplace=True)
result = result.head(5)
for index, row in result.iterrows():
id += 1
print(row)
print(row[0])
print(row[1])
print(row[2])
db.insertMatchTable(id, row[0], row[1], row[2])
# -*- coding: utf-8 -*-
from flask import Flask,request, jsonify
from dbmanager import Database
db = Database()
db.start_engine()
app = Flask(__name__)
@app.route('/api/v1.0/data',methods=['GET','POST'])
def index():
if request.method == 'GET':
#Fetch data
username = request.args.get('user','')
password = request.args.get('password','')
print 'Username = %s, password = %s'%(username,password)
content = db.get_data(username,password)
return jsonify(data=content)
elif request.method == 'POST':
#Update data
username = request.form.get('user','')
password = request.form.get('password','')
data = request.form.get('content','')
print 'Username = %s, password = %s'%(username,password)
print 'Data %s'%data
db.save_data(data,username,password)
else :
print 'Not handling it'
return jsonify(data=data)
@app.route('/api/v1.0/rotate',methods=['GET'])
config = SafeConfigParser()
config.read('hermes.cfg')
notifyAgent = hermes.Hermes(config)
server_ipaddr = config.get('server', 'addr')
server_port = config.get('server', 'port')
server_whitelist = config.get('server', 'whitelist')
server_debug = config.get('server', 'debug')
#--- valid parameters ---
twitter_required_parameters = set(['msg', 'log_level'])
mail_required_parameters = set(['msg', 'log_level', 'to', 'subject'])
#--- init dbmanager ---
db = Database()
app = Flask(__name__)
#--- Loggining ---
app.secret_key = '\x16\x91\xa4ZPL\xe6=%\xb6\x94\xe3<Cg\x1e\x00f21\x92\x8aq\x15'
login_manager = LoginManager()
login_manager.init_app(app)
login_manager.login_view = 'login'
user = user.User(config)
@app.before_request
def before_request():
g.user = current_user
#!/usr/bin/env python3
# match.py
import sys
import pickle
import pandas as pd
from sklearn_pandas import DataFrameMapper
from dbmanager import Database
db = Database()
db.createMatchTable()
employeePath = '../data/employees.csv'
employerPath = '../data/employers.csv'
model = pickle.load(open('../data/model.pickle', 'rb'))
employeeData = pd.read_csv(employeePath, sep=',')
employeeData['merge'] = 1
employerDataReader = pd.read_csv(employerPath, sep=',', chunksize=1)
for employerData in employerDataReader:
employerData['merge'] = 1
df = pd.merge(employerData, employeeData, on='merge')
del df['merge']
attrs = set(df.columns.values)
ignoredAttrs = set([
'id_x',
'id_y',
'nameFirst_x',