i-zaitsev

import os
import re
from pdb import set_trace
from multiprocessing import cpu_count
from pprint import pprint as pp

from imageio import imread
import numpy as np
import pandas as pd
import PIL.Image

i-zaitsev

import argparse
from pathlib import Path
import signature


def concat(folder: str, output: str = 'concat.txt', include_names: bool = True):
    """Concatenates a list of files from a folder and saves them into a single file."""
    p = Path(folder)
    files = []
    for filename in p.iterdir():

i-zaitsev

import argparse
import signature

def make_cli(func: callable):
    parser = argparse.ArgumentParser()
    sig = inspect.signature(func)
    empty = inspect._empty

    for param in sig.parameters.values():
        annot = param.annotation

i-zaitsev

from pathlib import Path

def concat(folder: str, output: str = 'concat.txt', include_names: bool = True):
    """Concatenates a list of files from a folder and saves them into a single file."""
    p = Path(folder)
    files = []
    for filename in p.iterdir():
        content = filename.open('r').read().strip()
        if include_names:
            content = f'{filename}\n{content}\n'

i-zaitsev

import pytest

@pytest.mark.parametrize('state', [
    'ooo|x.x|..x',
    'xo.|xo.|x..',
    'x..|.xo|o.x'
])
def test_game_has_winner(state):
    game = Game(state)
    assert game.has_winner()

i-zaitsev

i-zaitsev

i-zaitsev

def generate_dataset(n_rows, num_count, cat_count, max_nan=0.1, max_cat_size=100):
    """Randomly generate datasets with numerical and categorical features.
    
    The numerical features are taken from the normal distribution X ~ N(0, 1).
    The categorical features are generated as random uuid4 strings with 
    cardinality C where 2 <= C <= max_cat_size.
    
    Also, a max_nan proportion of both numerical and categorical features is replaces
    with NaN values.
    """

i-zaitsev

import curses

def main(term):
    term.clear()
    for i in range(10):
        # try to debug after curses mangled the terminal
        breakpoint()
        term.addstr(i, 0, f'String: {i + 1:d}')
    term.refresh()
    term.getkey()

i-zaitsev

from itertools import chain
import click
import matplotlib.pyplot as plt
from matplotlib import rcParams


default_style = {
    'font.family': 'monospace',
    'font.size': 18,
    'figure.figsize': (8, 6)