otobrglez

#!/usr/bin/env python

from pprint import pprint

servers = {
    "0.0.1.1": {
        "status": "OK"
    },
    "0.0.1.2": {
        "status": "ERROR"

otobrglez

# Single line of Ruby <3.
ruby -rjson -ryaml -e "puts YAML.load_file('my_file.yml').to_json"

# You can also pipe it to Python to get pretty ouput
ruby -rjson -ryaml -e "puts YAML.load_file('my_file.yml').to_json" | \
  python -mjson.tool

# Thats all. :)

otobrglez

#!/usr/bin/env bash

redis-cli \
  -h <host> \
  -p <port> \
	-a <pass> \
  keys \* | sed 's/.*query=//' | sort -u

otobrglez

"use strict";

// Experimenting with ES6 on NodeJS
// node --harmony --harmony_default_parameters ./little_es6.js

var numbers = [1, 1, 2, 5, 3];
var littleSum = numbers.filter(x => x % 2).reduce((s, b) => s + b);
console.log(`Sum is ${littleSum}.`);

numbers.forEach(l => console.log(l));

otobrglez

import scala.math.{pow}
import scala.concurrent._
import scala.concurrent.ExecutionContext.Implicits.global
import scala.concurrent.duration._
import scala.collection.mutable.ArrayBuffer

object Regression {
  def linear(pairs: IndexedSeq[Seq[Double]]) = {
    val n = pairs.size

otobrglez

// successful jobs grouped by type maped by req/sec
r.db('qm_production').table('jobs')
  .filter({'last_event_type': 'success'})
  .map(function(doc) {
    return {
      'ds_type': doc('ds_type'),
      'last_event_type': doc('last_event_type'),
      'res_sec': doc("stats_event_response_count").div(doc('stats_run_duration')),
      'req_sec': doc("stats_event_request_count").div(doc('stats_run_duration'))
    };

otobrglez

Keybase proof

I hereby claim:

• I am otobrglez on github.
• I am otobrglez (https://keybase.io/otobrglez) on keybase.
• I have a public key whose fingerprint is 4FE7 0346 C546 B9C0 31D9 B91B 0441 9BCA 2621 C2E3

To claim this, I am signing this object:

otobrglez

run: test
	./test

test:
	clang -ansi test.c -o test

clean:
	rm -rf test

otobrglez

#!/usr/bin/env bash

docker exec -ti $(docker ps -f 'image=databox/qm' -q | head -n1) bash -lc "cd /home/app/qm; $*"

# Usage:
# ./in_qm uname -a

otobrglez

#!/usr/bin/env python

# http://bogdan-ivanov.com/recipe-text-clustering-using-nltk-and-scikit-learn/
#!/usr/bin/env python

import nltk
import string
import collections
from data.feeds import feed
from math import sqrt, ceil, floor