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import json

USERNAME = '<adminname>'
BACKUP = '<backup_file>.json'

def parse_item_json(item_json):
    name = item_json['item']['type']
    amt = item_json['item'].get('amount', 1)
    return name, amt

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from PIL import Image
im = Image.open('banner.png').convert('RGB')

width, height = im.size
col_start = -1
for c in range(width):
    content = False
    for r in range(height):
        color = im.getpixel((c, r))
        if color != (255, 255, 255):

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// Shridux - A superior global state management library 

class GlobalStore {

  _initState = {};
  _bindings = {};

  setStore(newState) {
    for(let key in newState) {
      if(!(key in this._bindings)) {

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# http://www.saitek.com/uk/prod-bak/multi.html

from pynput.keyboard import Key, Controller
import hid
import time

keyboard = Controller()

name = 'Pro Flight Multi Panel'
vend_id, product_id = None, None

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from matching import Player, HospitalResident
from collections import defaultdict
import csv

    
def read_csv_ranks_v1(fn, other_fields=2):

    users = {}
    items = []

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import cv2
import numpy as np
import pyaudio
import librosa
import librosa.display
import matplotlib.pyplot as plt
import time

rate = 16000
chunk_size = rate // 4

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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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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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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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