tirinox

# Prints pseudo 3D image in ASCII 
import shutil
c, r = shutil.get_terminal_size()
print(''.join(('*' if (j-c/2) % (i+1) == 1 else '-' if 4*r/(i+1)%2==0 else ' ') for i in range(r) for j in range(c)), end='')

tirinox

text = """
We develop a methodology for automatically analyzing text to aid in discriminating firms that encounter catastrophic 
financial events. The dictionaries we create from Management Discussion and Analysis Sections (MD&A) of 10-Ks 
discriminate fraudulent from non-fraudulent firms 75% of the time and bankrupt from nonbankrupt firms 80% of the 
time. Our results compare favorably with quantitative prediction methods. We further test for complementarities by 
merging quantitative data with text data. We achieve our best prediction results for both bankruptcy (83.87%) and 
fraud (81.97%) with the combined data, showing that that the text of the MD&A complements the quantitative financial 
information.
"""

tirinox

import random
from flask import Flask, request


class Game:
    X = 'X'
    O = 'O'
    N = ' '

    def __init__(self, size=3, to_win=3):

tirinox

import random
from flask import Flask, request


class Game:
    X = 'X'
    O = 'O'
    N = ' '

    def __init__(self, size=3, to_win=3):

tirinox

import random


class ASCIICanvas:
    def __init__(self, w=50, h=100):
        assert 0 < w < 1000 and 0 < h < 1000
        self.w = w
        self.h = h
        self.buffer = []
        self.clear()

tirinox

# this is Radix sort prove of O(n) time complexity

import random
import matplotlib.pyplot as plt
import time


def radix_sort(a_list, radix=10):
    max_length_achieved = False
    tmp, placement = -1, 1

tirinox

import operator


class Item:
    def __init__(self, name, price, qty):
        self.name = name
        self.price = price
        self.qty = qty

    def total_cost(self):

tirinox

import socket
import select
from urllib.parse import urlsplit


def brutal_download(url, save_to):
    url_components = urlsplit(url)
    host = url_components.netloc
    s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
    s.connect((host, 80))

tirinox

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# нажми здесь shift+enter, чтобы увидеть список магий\n",
    "%lsmagic"

tirinox

import heapq
from collections import namedtuple

Task = namedtuple('Task', 'priority, id, content')


class TaskFlow:
    def __init__(self):
        self._queue = []
        self._id = 0