bugcy013

from functools import wraps
from time import time

def measure(func):
    @wraps(func)
    def _time_it(*args, **kwargs):
        start = int(round(time() * 1000))
        try:
            return func(*args, **kwargs)
        finally:

bugcy013

Currently, there is an explosion of tools that aim to manage secrets for automated, cloud native infrastructure management. Daniel Somerfield did some work classifying the various approaches, but (as far as I know) no one has made a recent effort to summarize the various tools.

This is an attempt to give a quick overview of what can be found out there. The list is alphabetical. There will be tools that are missing, and some of the facts might be wrong--I welcome your corrections. For the purpose, I can be reached via @maxvt on Twitter, or just leave me a comment here.

There is a companion feature matrix of various tools. Comments are welcome in the same manner.

bugcy013

Was looking for an answer to the same question. Found that connecting without specifying the database will allow you to query multiple tables:

db = _mysql.connect('localhost', 'user', 'password')

Then you can query different tables from different databases:

select table1.field1,
       table2.field2
from database1.table1 inner join
 database2.table2 on database2.table2.join_field = database1.field1.join_field

bugcy013

Tips to pass Certified Kubernetes Application Developer (CKAD) exam

Getting started Kubernetes :- 
  a) Book : Kubernetes: Up & Running 
  b) Practice practice & practice with CKAD Exercises 
          the Best Kubernetes CKAD sample exercises which cover all parts of the exam https://github.com/dgkanatsios/CKAD-exercises.
  c) Again, the best practice is use kubectl command well. Use kubectl to create resources (such as deployment, service, cronjobs, secret, configmap…) instead of creating them from manifest files. 
     Incase you have to edit manifest, use dry-run and -o yamlto save yaml file then edit manifest files.
   d) Kubernetes in Action by Mario Luksa. The book is the holy bible of Kubernetes, and it basically answer all questions you may have ;
   e) Whether or not you use Kubernetes at work, you should still provision your own cluster somewhere and play with it. 

bugcy013

#!/usr/bin/env bash

print_usage() {
        echo "Usage: $( basename $1 ) <process name> <SCHED_FIFO | SCHED_RR> <priority (1-99)>"
}

if [ $# != 3 ]; then
        print_usage $0
        exit 1
fi

bugcy013

import pandas as pd
import numpy as np

randn = np.random.randn
df = pd.DataFrame(randn(15, 20))
df1 = pd.DataFrame(randn(10, 5))
df2 = pd.DataFrame(randn(5, 10))

writer = pd.ExcelWriter("test.xlsx", engine='xlsxwriter')

bugcy013

import os
import subprocess

def run_cmd(cmd="hostname",  work_dir=None):
    try:
        logging.critical("let's execute cmd=%s", cmd)
        pipe = subprocess.Popen(cmd, shell=True, cwd=work_dir, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
        out, error = pipe.communicate()
        print(out, error)
        pipe.wait()

bugcy013

import difflib
from termcolor import colored

# Colorize text.
#
# Available text colors:
# red, green, yellow, blue, magenta, cyan, white.
# Available text highlights:
# on_red, on_green, on_yellow, on_blue, on_magenta, on_cyan, on_white.
# Available attributes:

bugcy013

exec > >(tee /var/log/user-data.log|logger -t user-data -s 2>/dev/console) 2>&1

bugcy013

from datetime import datetime
import pytz

date_str = "2019-10-22T10:45:35Z"
utc_datetime_obj = pytz.utc.localize(datetime.strptime(date_str, "%Y-%m-%dT%H:%M:%SZ"))
ist_datetime_obj = utc_datetime_obj.astimezone(pytz.timezone("Asia/Kolkata"))\
    # .strftime("%Y-%m-%d %H:%M:%S")

# print(type(datetime_obj))
# datetime_obj_utc = datetime_obj.replace(tzinfo=timezone('UTC'))