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# install
# pip3 install pandas
# pip3 install xlrd
# pip3 install openpyxl

import pandas as pd
from glob import glob
import argparse
import os
from multiprocessing import Pool, cpu_count

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; From https://www.youtube.com/watch?v=OyfBQmvr2Hc

(define eval-expr
  (lambda (expr env)
    (pmatch expr
            [,x (guard (symbol? x))
                (env x)]
            [(lambda (,x) ,body)
             (lambda arg)
               (eval-expr body (lambda (y)

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/*

# PigeonLab Engineering Test

## Overview

Your task is to create a TCP based calculator service and deploy it. It'll take 
in simple math operations such as `1+1`, or `5*10` and reply with the answer.

You should implement the server in node.js, with no dependancies, and in a single

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#!/bin/bash
set -o noglob # prevent bash from auto glob file extensions
set -e # exit if any commands yield error

# constants
readonly CRed='\033[0;31m'          # Red
readonly CGreen='\033[0;32m'        # Green
readonly CYellow='\033[0;33m'       # Yellow
readonly CBlue='\033[0;34m'         # Blue
readonly CWhite='\033[0;37m'        # White

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PROMPT="%{$fg_bold[green]%}$USER::"
PROMPT+='%{$fg[cyan]%}%~%{$reset_color%} $(git_prompt_info)'
PROMPT+="%(?:%{$fg_bold[green]%}:%{$fg_bold[red]%})➜ %{$reset_color%}"

ZSH_THEME_GIT_PROMPT_PREFIX="%{$fg_bold[blue]%}git:(%{$fg[red]%}"
ZSH_THEME_GIT_PROMPT_SUFFIX="%{$reset_color%} "
ZSH_THEME_GIT_PROMPT_DIRTY="%{$fg[blue]%}) %{$fg[yellow]%}✗"
ZSH_THEME_GIT_PROMPT_CLEAN="%{$fg[blue]%})"

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import os
import sys
import logging

from datetime import datetime, timedelta
import pytz

def local_time(sec, what, tz="Asia/Ho_Chi_Minh"):
    """get datetime now with viet name timezone for logger"""
    lc_time = datetime.now(tz=pytz.timezone(tz))

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%load_ext autoreload
%autoreload 2

import pandas as pd
pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 1000)

import numpy as np

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from pathlib import Path
from glob import glob

Path.ls = lambda x : [o.name for o in x.iterdir()]
Path.ls_p = lambda x : [str(o) for o in x.iterdir()]
Path.str = lambda x : str(x)

def insensitive_glob(root, pattern):
    def either(c):
        return '[%s%s]' % (c.lower(), c.upper()) if c.isalpha() else c

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from contextlib import contextmanager
import time

@contextmanager
def timing(description: str = '') -> None:
    start = time.time()
    yield
    print(f"Elasped {description}: {time.time() - start}")
    
    

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from fastai.vision import Image,pil2tensor
import cv2

def array2tensor(x):
    """ Return an tensor image from cv2 array """
    x = cv2.cvtColor(x,cv2.COLOR_BGR2RGB)
    return Image(pil2tensor(x,np.float32).div_(255))
    
    
### USAGE