mdamien

import itertools

def solve(S):
    for people_added in itertools.count():
        standing = people_added
        Sp = S[:]
        for i,n in enumerate(Sp):
            if i <= standing:
                standing += n
                Sp[i] = 0

mdamien

public static char NULL = '\u0000';    

public static int cout(char x, char y){
	if(x == NULL){ //insertion
		return 1;
	}
	if(y == NULL){ //insertion
		return 1;
	}
	if(x != y){ //substitution

mdamien

import requests
from bs4 import BeautifulSoup

with open('urls','w') as f:
    while True:
        r = requests.get("https://login.corp.google.com/")
        soup = BeautifulSoup(r.text)
        src = soup.find("img","login-image")['src']
        print(src)
        f.write(src+"\n")

mdamien

import os,json,csv
from os.path import join, getsize

header = True
with open('status.csv', 'w', newline='') as csvfile:
    c = csv.writer(csvfile)
    for root, dirs, files in os.walk('pool'):
        for filename in files:
            with open(join(root,filename)) as fp:
                r = json.load(fp)

mdamien

Experimental Generation of Interpersonal Closeness

Instructions to Subjects Included With Task Slips Packet

This is a study of interpersonal closeness, and your task, which we think will be quite enjoyable, is simply to get close to your partner. We believe that the best way for you to get close to your partner is for you to share with them and for them to share with you. Of course, when we advise you about getting close to your partner, we are giving advice regarding your behavior in this demonstration only, we are not advising you about your behavior outside of this demonstration.

In order to help you get close we've arranged for the two of you to engage in a kind of sharing game. You're sharing time will be for about one hour, after which time we ask you to fill out a questionnaire concerning your experience of getting close to your partner.

You have been given three sets of slips. Each slip has a question or a task written on it. As soon as you both finish reading these instructions, you should

mdamien

def csv_as_dict(filename, limit=None):
    with open(filename) as f:
        reader = csv.reader(f, delimiter=';')
        header = [k.lower() for k in reader.__next__()]
        for c,row in enumerate(reader):
            if limit and c >= limit:
                break
            yield {key:row[i] for i,key in enumerate(header)}

#now I know about csv.DictReader! Thanks pydanny!

mdamien

HTML to txt:

cat all.html | node node_modules/html-to-text/bin/cli.js > all.txt

mdamien

Don't worry about what anybody else is going to do. The best way to
predict the future is to invent it.
-- Alan Kay

Premature optimization is the root of all evil (or at least most of it)
in programming.
-- Donald Knuth

Lisp has jokingly been called "the most intelligent way to misuse a
computer". I think that description is a great compliment because it

mdamien

import glob
import json
from pprint import pprint as pp
from pathlib import Path
from bs4 import BeautifulSoup
import csv

data = []

for i, filename in enumerate(glob.glob("html/*")):

mdamien

from pprint import pprint as pp
from collections import Counter
import sys

class Node:
    def __init__(self,p, parent=None, descr=""):
        self.p = p
        self.parent = parent
        self.descr = descr