The information you sent was amazing. I think you definitely have a future in computers.
I am sharing your information with the manufacture of the Home Access Center (HAC), SunGard.
I will share their findings with you as well.
Thank you again for your honorable and ethical approach to an issue.
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from xml.dom import minidom | |
import requests | |
import time | |
Q_ID = 17937 | |
LOC_ID = 3532 | |
DAYS = 3 | |
AUTH = "fill me" | |
TARGET_MONTH = "fill me" |
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import matplotlib.pyplot as plt | |
import random | |
import math | |
def get_prob(n, k, trials=200000): | |
perfect = 0 | |
for _ in range(trials): |
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def get_scores(nums, turn=0, a=0, b=0): | |
if len(nums) == 0: | |
return (a, b) | |
else: | |
left = get_scores(nums[1:], |
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def multiadder(n): | |
if n == 1: | |
return lambda t: t | |
else: | |
return lambda a: lambda b: multiadder(n-1)(a+b) | |
def multiadder2(n): | |
if n == 1: | |
def f(x): | |
return x |
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import glob | |
import os | |
## Count | |
exts = ['.py', '.js', '.md', 'java', '.html', '.css', '.pde'] | |
def count_lines(fn): | |
i = 0 |
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from textblob.classifiers import DecisionTreeClassifier as TextClassifier | |
from datetime import datetime | |
import matplotlib.pyplot as plt | |
import csv | |
num_months = 13 | |
with open('train.csv', 'r') as fp: | |
clf = TextClassifier(fp, format="csv") |
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public class ArrayMaker { | |
public static void main(String[] args) { | |
int N = 150000; | |
for(int n = 500; n < N; n += 100) { | |
long sumInt = 0, sumLong = 0, sumObject = 0; |
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import numpy as np | |
import cv2 | |
class CellularAutomaton: | |
def __init__(self, size=1000, rule=0): | |
self.size = size | |
self.rule = rule |
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