Veedrac

\begin{tikzpicture}
    \draw%

        (6, 0) coordinate (dividerlength)
        (0, -1.5) coordinate (dividerbracegap)
        (0, -1.3) coordinate (braceLCRgap);

    \draw%

        (0, -0.6)

Veedrac

totally_a_database = {
    "in 1": "out 1",
    "in 2": "out 2",
    "in 3": "out 3"
}

class MyClass:
    def __init__(self):
        self.dbitems = DatabaseView(totally_a_database)

Veedrac

### [A] Only code
Although the code is appreciated, it should always have an accompanying explanation. This doesn't have to be long but it is expected.

### [A] Only code (moderation queue)
Although the code is appreciated, it should always have an accompanying explanation. This doesn't have to be long but it is expected. I've arrived here from a moderation queue because this was automatically flagged. Keeping answers to high quality will help prevent that.

### [Q] Truncated error
When showing errors, please *copy the whole error*. All of the information that you have is useful, so if you want better help you should tell us everything you see.

### [Q] Not on topic; not answerable

Veedrac

import random
import sys
from itertools import count

def read_map(map_path):
    """
    Read map from the file given by map_path.

    returns: iterable of (name, {neighbor: direction, ...})
        name: string of current city

Veedrac

"""
Aliquot Chainz

Badly tested, but eh.

usage:
    aliquot_chainz <n>
"""

import docopt

Veedrac

import numpy

from collections import defaultdict
from numpy import newaxis

def rotate_packed(packed):
    """
    Return a rotated version of a 55-length
    array packed into 55 bits. Eg.

Veedrac

import random
import sys

from functools import partial
from timeit import Timer


def values_in_sentinel(keys, dict):
    sentinel = object()
    items = (dict.get(k, sentinel) for k in keys)

Veedrac

from __future__ import nested_scopes, print_function
 
import bisect
import numpy

from collections import namedtuple
from itertools import combinations

Num = namedtuple("Num", ["value", "i"])
 

Veedrac

import sys
from math import ceil, sqrt

import cv2
import mahotas
import numpy
from scipy.spatial import distance

def preprocess(image, diameter, d=8, sigma=15, k=0):
    raw = image = cv2.resize(image, (diameter, diameter))

Veedrac

let square x = x * x;;

let rec accumulate combiner start n term =
    if n = 0 then
        start
    else
        let start = combiner (term n) start
        in accumulate combiner start (n-1) term;;

let summation_using_accumulate n term =