codeofzen

Task

Write a Python function which takes the text from the file data.txt and outputs a list with all words from the text and the count of their occurrences, ordered by the occurrences. The result should look like result.txt.

Rules

• Read the rules carefully and act according to them.
• Please use 4 spaces for indentation, no tabs.
• Send the result as a github gist like this file.
• Stop immediately after 15 minutes - we don't need, want or honor a working solution, we are interested in your approach.
• The code should work on a unix based system.

codeofzen

Task

Write a javascript function which takes the text in the html file and outputs a list with all words from the text and the count of their occurrences, ordered by the occurrences. The result should look like result.html.

Rules

• Read the rules carefully and act according to them.
• No external libararies.
• Please use 2 spaces for indentation, no tabs.
• Don't pollute the global namespace, don't leak any variables.
• Send the result as a github gist like this file.

codeofzen

<!-- Drift Chat Integration -->
<script>
  
  // identify user handler          
  var query = window.location.search.substring(1);
  var vars = query.split("&");
  
  //

codeofzen

#!/usr/bin/env python3
import boto3
import time

#Athena configuration
s3_ouput = 's3://athena-results-tmp/'
database = 'behavioural_tracking'
table = 'bt_event_direct'
region = "eu-west-1"

codeofzen

from collections import Counter
import csv
import numpy as np
import random
import requests
import time


def read_itp_urls(filename, sample=0):

codeofzen

from urllib import request, parse
import json
import datetime
import time


API_KEY = 'ur364580-157321bf29cadf16c9ab4c9f'

def get_all_monitors():
	url_get_monitors = 'https://api.uptimerobot.com/v2/getMonitors?format=json'	

codeofzen

{  
   "maxResult": 10,
   "sorting": [
      {
         "field":"price",
         "order":"desc"
      }
   ],
   "location": ["ZA", "CPT"],
   "tripStyle": ["xxx", "yyy"],

codeofzen

import pytest
from deepeval import assert_test
from typing import Dict, List, Union
from deepeval.metrics import AnswerRelevancyMetric
from deepeval.test_case import LLMTestCase

import zenetics

def get_context(input):
    """