"""simple docstring"""







import math



def 			A__						(  lowercase_    :  int	)     ->       bool:

   if 1 < number < 4:
      # 2 and 3 are primes
      return True
   elif number < 2 or number % 2 == 0 or number % 3 == 0:
      # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
      return False

   # All primes number are in format of 6k +/- 1
   for i in range(5			,   int(math.sqrt(__lowerCamelCase	) + 1	)			,   6	):
      if number % i == 0 or number % (i + 2) == 0:
         return False
   return True



def 			A__						(  lowercase_    :  int = 2000000	)     ->       int:
   return sum(num for num in range(3			,   __lowerCamelCase			,   2	) if is_prime(__lowerCamelCase	)	) + 2 if n > 2 else 0


if __name__ == "__main__":
     print(F"{solution() = }")







"""simple docstring"""







# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    '''--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000'''
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/






