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package main

import (
	"fmt"
	"strings"
)

func parseSplit(tags string, key string) string {
	for _, tag := range strings.Split(tags, ",") {
		parts := strings.Split(tag, ":")

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import datetime
from datalayer.metrics_api import metric_query, OK_STATUS
from dd.utils.query import QuerySource, QuerySourceTypes

t_from = datetime.datetime.strptime("2022-06-01 00:00:00", '%Y-%m-%d %H:%M:%S')
t_to = datetime.datetime.strptime("2022-06-08 00:00:00", '%Y-%m-%d %H:%M:%S')

def parse_agent_version_tag(agent_version_tag):
    agent_version = agent_version_tag[8:] # "version:" prefix
    parts = agent_version.split(".")

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Detect which are the IPs and polls that are triggering our fraud activity notifications:

SELECT
  user_ip,
  poll_id,
  COUNT(*) AS fraud_votes
FROM
  events.fraudvote
WHERE

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#!/usr/bin/python
import sys
import csv
import sqlite3


def main(dbfile, csvfile):
    conn = sqlite3.connect(dbfile)
    conn.text_factory = str

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from json import load, JSONEncoder
from optparse import OptionParser
from re import compile
import os

float_pat = compile(r'^-?\d+\.\d+(e-?\d+)?$')
charfloat_pat = compile(r'^[\[,\,]-?\d+\.\d+(e-?\d+)?$')

parser = OptionParser(usage="""%prog [options]

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#!/usr/bin/python
import sys
import csv

OUTPUT = "data.csv"  # Output file, holding the curated set of data

# Columns
NAME_0 = 3
NAME_1 = 5
NAME_2 = 7

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#!/usr/bin/python
import sys
import csv
import sqlite3
from os.path import basename, splitext


def main(filename):
    dbname = splitext(basename(filename))[0]
    dbfile = '{filename}.sqlite'.format(filename=dbname)