amaurs

from flask import Flask, send_file
import math
from PIL import Image
import numpy as np
import os.path
from io import BytesIO
from numba import jit

app = Flask(__name__)

amaurs

if (process.env.NODE_ENV !== 'production') {
  require('dotenv').load();
}
var Connection = require('tedious').Connection;
var Request = require('tedious').Request;
var fs = require('fs');
var query = fs.readFileSync("query.sql", "utf8");
var port = 3000;
var config = {
  userName: process.env.USER_NAME,

amaurs

{
  "name": "literature",
  "version": "1.0.0",
  "description": "",
  "main": "app.js",
  "scripts": {
    "test": "echo \"Error: no test specified\" && exit 1"
  },
  "author": "",
  "license": "ISC",

amaurs

class A:
    some_value = {}

class B(A):

    def modify_value(self):
        self.some_value.update({"some_value": "b"})

class C(A):

amaurs

class A:
    def __init__(self):
        self.some_value = {}

class B(A):

    def modify_value(self):
        self.some_value.update({"some_value": "b"})

class C(A):

amaurs

from typing import List
import markovify
import argparse

# Example:
# python sentence_generator.py text_1.txt text_2.txt text_2.txt --state-size 2
# python sentence_generator.py text_1.txt text_2.txt

def main(filenames: List[str], state_size: int) -> str:
    text_model = markovify.combine([load_text_model(filename, state_size=state_size) for filename in filenames])