




'''simple docstring'''






from __future__ import annotations

import math
from collections import Counter
from string import ascii_lowercase


def 				snake_case_  (      _lowerCAmelCase						:		Tuple						)   ->     Optional[Any]:
							UpperCAmelCase							,	UpperCAmelCase				: Optional[int]											=	analyze_text(UpperCamelCase__						)
							UpperCAmelCase				: List[str]											=	list(''' ''' + ascii_lowercase						)
							# what is our total sum of probabilities.
							UpperCAmelCase				: Optional[int]											=	sum(single_char_strings.values()						)

							# one length string
							UpperCAmelCase				: Union[str, Any]											=	0
							# for each alpha we go in our dict and if it is in it we calculate entropy
							for ch in my_alphas:
														if ch in single_char_strings:
																					UpperCAmelCase				: str											=	single_char_strings[ch]
																					UpperCAmelCase				: Tuple											=	my_str / all_sum
																					my_fir_sum += prob * math.loga(UpperCamelCase__						)  # entropy formula.

    # print entropy
							print(f"""{round(-1 * my_fir_sum						):.1f}"""						)

							# two len string
							UpperCAmelCase				: Any											=	sum(two_char_strings.values()						)
							UpperCAmelCase				: List[Any]											=	0
							# for each alpha (two in size) calculate entropy.
							for cha in my_alphas:
														for cha in my_alphas:
																					UpperCAmelCase				: str											=	cha + cha
																					if sequence in two_char_strings:
																												UpperCAmelCase				: Dict											=	two_char_strings[sequence]
																												UpperCAmelCase				: str											=	int(UpperCamelCase__						) / all_sum
																												my_sec_sum += prob * math.loga(UpperCamelCase__						)

    # print second entropy
							print(f"""{round(-1 * my_sec_sum						):.1f}"""						)

							# print the difference between them
							print(f"""{round((-1 * my_sec_sum) - (-1 * my_fir_sum)						):.1f}"""						)


def 				snake_case_  (      _lowerCAmelCase						:		Union[str, Any]						)   ->     Optional[Any]:
							UpperCAmelCase				: Optional[Any]											=	Counter()  # type: ignore
							UpperCAmelCase				: Tuple											=	Counter()  # type: ignore
							single_char_strings[text[-1]] += 1

							# first case when we have space at start.
							two_char_strings[" " + text[0]] += 1
							for i in range(0     ,   len(UpperCamelCase__						) - 1						):
														single_char_strings[text[i]] += 1
														two_char_strings[text[i : i + 2]] += 1
							return single_char_strings, two_char_strings


def 				snake_case_  (      )   ->     List[str]:
							import doctest

							doctest.testmod()
							# text = (
							#     "Had repulsive dashwoods suspicion sincerity but advantage now him. Remark "
							#     "easily garret nor nay. Civil those mrs enjoy shy fat merry. You greatest "
							#     "jointure saw horrible. He private he on be imagine suppose. Fertile "
							#     "beloved evident through no service elderly is. Blind there if every no so "
							#     "at. Own neglected you preferred way sincerity delivered his attempted. To "
							#     "of message cottage windows do besides against uncivil.  Delightful "
							#     "unreserved impossible few estimating men favourable see entreaties. She "
							#     "propriety immediate was improving. He or entrance humoured likewise "
							#     "moderate. Much nor game son say feel. Fat make met can must form into "
							#     "gate. Me we offending prevailed discovery. "
							# )

							# calculate_prob(text)


if __name__ == "__main__":
						main()










'''simple docstring'''






from __future__ import annotations

from collections.abc import Generator

import requests
from bsa import BeautifulSoup

UpperCamelCase__:     Union[str, Any]										=    "https://www.indeed.co.in/jobs?q=mobile+app+development&l="


def 				snake_case_  (      _lowerCAmelCase						:		str = "mumbai"						)   ->     Generator[tuple[str, str], None, None]:
							UpperCAmelCase				: Optional[int]											=	BeautifulSoup(requests.get(url + location						).content     ,   '''html.parser'''						)
							# This attribute finds out all the specifics listed in a job
							for job in soup.find_all('''div'''     ,   attrs={'''data-tn-component''': '''organicJob'''}						):
														UpperCAmelCase				: Optional[Any]											=	job.find('''a'''     ,   attrs={'''data-tn-element''': '''jobTitle'''}						).text.strip()
														UpperCAmelCase				: int											=	job.find('''span'''     ,   {'''class''': '''company'''}						).text.strip()
														yield job_title, company_name


if __name__ == "__main__":
						for i, job in enumerate(fetch_jobs("Bangalore"), 1):
												print(F"Job {i:>2} is {job[0]} at {job[1]}")





