HAKSOAT

"ace in the hole"
"across the board"
"against the grain"
"airs and graces"
"airy fairy"
"albatross around (his|her|their) neck"
"all bark and no bite"
"all ears"
"all hat and no cattle"
"all piss and wind"

HAKSOAT

"10 Downing Street"
"11 Downing Street"
"15 minutes of fame"
"1600 Pennsylvania Avenue"
"23 Skidoo Street"
"a (bridge too far|cold day in July|day late and a dollar short|good deal|great deal|hundred and ten percent|life of its own|little bird told me|little bit of bread and no cheese|little from column A, a little from column B|notch above|pound to a penny|Roland for an Oliver|short drop and a sudden stop|week from next Tuesday|week is a long time in politics|wild goose never laid a tame egg|woman without a man is like a fish without a bicycle)"
"above (one's bend|the curve|the law|the salt)"
"absence makes the heart grow fonder"
"abuse of distress"
"accident (of birth|waiting to happen)"

HAKSOAT

"10 Downing Street"
"11 Downing Street"
"15 minutes of fame"
"1600 Pennsylvania Avenue"
"23 Skidoo Street"
"a bridge too far"
"a cold day in July"
"a day late and a dollar short"
"a good deal"
"a great deal"

HAKSOAT

def generate_multiplications(multipicand):
    if not (isinstance(multipicand, int) or isinstance(multipicand, float)):
        return None
    multiplications = []
    for multiplier in range(1, 13):
        answer = multipicand * multiplier
        multiplications.append(answer)
    return multiplications

HAKSOAT

{{about|the programming language||Python (disambiguation)}}
{{Short description|General-purpose, high-level programming language}}
{{Use dmy dates |date=August 2015}}
{{Infobox programming language
| logo = Python logo and wordmark.svg
| logo size = 250px
| paradigm = [[Multi-paradigm programming language|Multi-paradigm]]: [[functional programming|functional]], [[imperative programming|imperative]], [[object-oriented programming|object-oriented]], [[structured programming|structured]], [[reflective programming|reflective]]
| released = {{start date and age|1990}}<ref name=guttag />
| designer = [[Guido van Rossum]]
| developer = [[Python Software Foundation]]

HAKSOAT

def decorate_text(text):
    decoration = "\n\n**********{}**********\n\n"
    decorated_text = decoration.format(text)
    return decorated_text
 
# Unpacking of values

def generate_multiplications_1(multiplicand, start, stop):
    multiplications = []
    for multiplier in range(start, stop + 1):

HAKSOAT

{
    "tokens": [
        {
            "token": "As",
            "start_offset": 0,
            "end_offset": 2,
            "type": "word",
            "position": 0
        },
        {

HAKSOAT

Python's regex

(?P<comment_start><!--)|(?P<comment_end>-->)|(?P<url>((bitcoin|geo|magnet|mailto|news|sips?|tel|urn)\:|((|ftp|ftps|git|gopher|https?|ircs?|mms|nntp|redis|sftp|ssh|svn|telnet|worldwind|xmpp)\:)?\/\/)[^\s/$.?#].[^\s]*)|(?P<entity>&[a-z][a-z0-9]*;)|(?P<cjk>[\u4E00-\u62FF\u6300-\u77FF\u7800-\u8CFF\u8D00-\u9FCC\u3400-\u4DFF\U00020000-\U000215FF\U00021600-\U000230FF\U00023100-\U000245FF\U00024600-\U000260FF\U00026100-\U000275FF\U00027600-\U000290FF\U00029100-\U0002A6DF\uF900-\uFAFF\U0002F800-\U0002FA1F\u3041-\u3096\u30A0-\u30FF\u3400-\u4DB5\u4E00-\u9FCB\uF900-\uFA6A\u2E80-\u2FD5\uFF5F-\uFF9F\u31F0-\u31FF\u3220-\u3243\u3280-\u337F])|(?P<ref_open><ref\b[^>/]*>)|(?P<ref_close></ref\b[^>]*>)|(?P<ref_singleton><ref\b[^>/]*/>)|(?P<tag></?([a-z][a-z0-9]*)\b[^>]*>)|(?P<number>[\d]+)|(?P<japan_punct>[\u3000-\u303F])|(?P<danda>।|॥)|(?P<bold>''')|(?P<italic>'')|(?P<word>([^\W\d]|[\u0901-\u0963\u0601-\u061A\u061C-\u0669\u06D5-\u06EF\u0980-\u09FF])[\w\u0901-\u0963\u0601-\u061A\u061C-\u0669\u06D5-\u06EF\u0980-\u0

HAKSOAT

# Creates an index for the tokenizer

import requests

param = (('v', ''),)
data = r"""{
  "settings": {
    "index.analyze.max_token_count" : 1000000,
    "analysis": {
      "analyzer": {

HAKSOAT

# Extracts the text used for the performance test
import time
import mwapi

session = mwapi.Session("https://en.wikipedia.org")
doc = session.get(action='query', prop='revisions', rvprop='content', titles='Alan Turing', formatversion=2)
text = doc['query']['pages'][0]['revisions'][0]['content']

# Functions for tokenization
import json