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function get_atts_from_shortcode_with_a_good_old_regex($content) {
	$regexp = '/(.?)\[(shop)\b(.*?)(?:(\/))?\](?:(.+?)\[\/\2\])?(.?)/s';
	$m = array();
	preg_match($regexp, $content, $m);
	$arr = array('content' => $m[5]);
	$arr = array_merge(shortcode_parse_atts($m[3]),$arr);
	return $arr;
}

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from collections import Counter

class State(dict):
    """
A state contains the previous value of each modified key
and the previous Counter object
"""
    def __init__(self,counter):
        self.counter = counter

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import sys

def execute(code):
        code = ''.join([x for x in code if x in '.,+-<>[]'])
        cells,ptr,i = [0]*3000,0,0
        while i < len(code):
                c = code[i]
                if c == '>': ptr += 1
                if c == '<': ptr -= 1
                if c == '+': cells[ptr] += 1

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Log.d(TAG, "API CALL: POST "+url);
OutputStream output = null;
try {
	String query = "furnail_name=hell&hi=2";//use URLEncode here
	URLConnection connection = new URL("https://your-url.com/action/save").openConnection();
	String authString = "Basic " + Base64.encodeToString((username + ":" + password).getBytes(),Base64.NO_WRAP);
	connection.setRequestProperty("Authorization", authString); 
	connection.setDoOutput(true);
	connection.setRequestProperty("Accept-Charset", "UTF-8");
	connection.setRequestProperty("Content-Type", "application/x-www-form-urlencoded;charset=" + "UTF-8");

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<RelativeLayout
android:layout_width="match_parent"
android:layout_height="40dp"
android:clickable="false"
android:paddingLeft="10dp"
android:paddingRight="10dp" >
<View
    android:id="@+id/item_separator"
    android:layout_width="match_parent"
    android:layout_height="1dp"

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def cross(X,Y):
    if len(X) == 0:
        for y in Y:
            yield y
    for x in X:
        for y in Y:
            yield (x,y)


def combination(n):

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function rainbow(step) {
var r, g, b;
var h = step / 70;
var i = ~~(h * 6);
var f = h * 6 - i;
var q = 1 - f;
switch (i % 6) {
    case 0:
        r = 1, g = f, b = 0;
        break;

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defs = {}

for i, line in enumerate(open('data.noun')):
    if not line.startswith('0'):
        continue
    splits = line.split(' ')
    word = splits[4]
    seps = line.split('|')
    bla = seps[1].split(';')
    definition = bla[0]

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Because every word in a dictionnary is referenced by another word, there must be a lot of circular dependency

Example:

• Definition of the: denoting one or more people or things already mentioned or assumed to be common knowledge
• Definition of one: the lowest cardinal number; half of two; 1.

Using the Wordnet dictionnary, I looked for circular dependency. But I found so many direct dependency, I'm now looking for a better dictionnary (Wiktionnary most probably).

So, here is the result of the direct dependency lookup and the script to obtain the result.

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{"A Discriminative Latent Variable Model for Online Clustering":["Rajhans Samdani"],"Affinity Weighted Embedding":["Ron Weiss","Hector Yee"],"Applications of Maximum Entropy Rankers to Problems in Spoken Language Processing":["Richard Sproat","Keith Hall"],"Asynchronous Stochastic Optimization for Sequence Training of Deep Neural\n Networks":["Georg Heigold","Erik McDermott","Vincent Vanhoucke","Andrew Senior","Michiel Bacchiani"],"Autoregressive Product of Multi-frame Predictions Can Improve the Accuracy of\n Hybrid Models":["Vincent Vanhoucke"],"Bayesian Sampling Using Stochastic Gradient Thermostats":[],"Bridging Text and Knowledge with Frames":["Srini Narayanan"],"Cicada: Predictive Guarantees for Cloud Network Bandwidth":[],"Corporate learning at scale: Lessons from a large online course at Google":["Mehryar Mohri","Afshin Rostamizadeh","Umar Syed"],"DaMN – Discriminative and Mutually Nearest: Exploiting Pairwise Category\n Proximity for Video Action Recognition":["Rahul\n Sukthankar"],"Deep Convolutiona