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lst1 = list(str1)
lst2 = list(str2)
for char in lst1:
    if char in lst2:
        count += 1
        lst2.remove(char)
return count

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trayer --edge top --align right --SetDockType true --SetPartialStrut true --expand true --width 6 --transparent true --alpha 0 --tint 0x000000 --height 16 & 

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, ((mod4Mask .|. controlMask, xK_j), spawn "amixer set Master 5%-")
, ((mod4Mask .|. controlMask, xK_k), spawn "amixer set Master 5%+")

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    int array[];

    int prev2 = array[0];
    int prev1 = array[1];
    int sum_prev = prev1 + prev2;
    bool seg_good = true;
    for (int i = 2; i < n; ++i)
    {
        int cur = array[i];
        if (cur == sum_prev)

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int f(const vector<int> &x)
{
    int longest = 2;
    int p = 0;
    int q = 0;
    while (q < x.size())
    {
        int len = q - p + 1;
        if (admissible(x, p, q))
        {

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ans3 = Import["Anscombe3", "Table", "HeaderLines" -> 1];
ansModel = LinearModelFit[ans3, x, x];
residuals = ansModel["FitResiduals"]
KolmogorovSmirnovTest[residuals]
KolmogorovSmirnovTest[residuals, NormalDistribution[]]

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a=read.table("Anscombe3", header=TRUE)
model=lm(formula=y~x, data=a)
e=residuals(model)
ks.test(e, pnorm)

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ages = {40, 34, 23, 40, 31, 33, 49, 33, 34, 43, 26, 39};
dates = {1543, 1600, 1665, 1746, 1774, 1839, 1858, 1864, 1896, 1901, 
   1905, 1926};
data = Transpose[{dates, ages}];
model = LinearModelFit[data, t, t]
residuals = model["FitResiduals"]
KolmogorovSmirnovTest[residuals]
KolmogorovSmirnovTest[residuals, NormalDistribution[], 
  "HypothesisTestData"]["TestDataTable"]

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from queue import PriorityQueue
import config

class EventQueue:
    def __init__(self):
        self.q = PriorityQueue()

    def get(self):
        if self.q.empty():
            return -1

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#!/bin/sh

# Alot of these configs have been taken from the various places
# on the web, most from here
# https://github.com/mathiasbynens/dotfiles/blob/master/.osx

# Set the colours you can use
black='\033[0;30m'
white='\033[0;37m'
red='\033[0;31m'