freedomofkeima

import cv2
import numpy as np
import pafy
import pytesseract


TESSERACT_PARAMETERS = '--oem 3 --psm 6 -c tessedit_char_whitelist="Ckmtv0123456789.:"'


def cleanup_dist(dist: str) -> str:

freedomofkeima

#include <stdio.h>
#include <iostream>

using namespace std;

inline string IntToString(int a){
    char x[100];
    sprintf(x,"%d",a); string s = x;
    return s;
}

freedomofkeima

#include <stdio.h>
#include <iostream>
#include <algorithm>
#include <vector>

using namespace std;

string corrected_wires[] = {"abcefg", "cf", "acdeg", "acdfg", "bcdf", "abdfg", "abdefg", "acf", "abcdefg", "abcdfg"};

vector<string> build_wires(int config[]) {

freedomofkeima

result = 0

def new_calculate(line):
	if '+' not in line and '*' not in line:
		return int(line)
	flatten = ""
	idx = 0
	ctx = 0
	temp = ""
	while len(line) > idx:

freedomofkeima

Number of repositories, Number of user which has repositories higher than or equal to
0,36472511
1,15928613
2,9075049
3,6396362
4,4938517
5,4012281
6,3366805
7,2886263
8,2515052

freedomofkeima

Followers, Number of user which has followers higher than or equal to
0,36468019
1,3975425
2,2104615
3,1429842
4,1082890
5,872123
6,728161
7,623424
8,543446

freedomofkeima

#!/usr/bin/env python
# Lambda Script for spot instances failover
# NOTE 1: Re-failover from on-demand to spot will be done if all desired ECS tasks are currently running
# NOTE 2: The maximum number of spot instances is taken from its DesiredCapacity
# WARNING: You cannot increase DesiredCapacity of on-demand from the console without changing this script,
#          however, you can increase DesiredCapacity of spot instances from the console and if it fails,
#          this script will start on-demand instead of spot instances
#
import boto3
import json

freedomofkeima

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import gzip
import os

import tensorflow.python.platform

import numpy

freedomofkeima

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import gzip
import os

import tensorflow.python.platform

import numpy