text: """
  This is pure Python implementation of binary search algorithms
  
  For doctests run following command:
  python -m doctest -v binary_search.py
  or
  python3 -m doctest -v binary_search.py
  
  For manual testing run:
  python binary_search.py
  """
  import bisect
  
  
  def bisect_left(sorted_collection, item, lo=0, hi=None):
      """
      Locates the first element in a sorted array that is larger or equal to a given
      value.
  
      It has the same interface as
      https://docs.python.org/3/library/bisect.html#bisect.bisect_left .
  
      :param sorted_collection: some ascending sorted collection with comparable items
      :param item: item to bisect
      :param lo: lowest index to consider (as in sorted_collection[lo:hi])
      :param hi: past the highest index to consider (as in sorted_collection[lo:hi])
      :return: index i such that all values in sorted_collection[lo:i] are < item and all
          values in sorted_collection[i:hi] are >= item.
  
      Examples:
      >>> bisect_left([0, 5, 7, 10, 15], 0)
      0
  
      >>> bisect_left([0, 5, 7, 10, 15], 6)
      2
  
      >>> bisect_left([0, 5, 7, 10, 15], 20)
      5
  
      >>> bisect_left([0, 5, 7, 10, 15], 15, 1, 3)
      3
  
      >>> bisect_left([0, 5, 7, 10, 15], 6, 2)
      2
      """
      if hi is None:
          hi = len(sorted_collection)
  
      while lo < hi:
          mid = (lo + hi) // 2
          if sorted_collection[mid] < item:
              lo = mid + 1
          else:
              hi = mid
  
      return lo
  
  
  def bisect_right(sorted_collection, item, lo=0, hi=None):
      """
      Locates the first element in a sorted array that is larger than a given value.
  
      It has the same interface as
      https://docs.python.org/3/library/bisect.html#bisect.bisect_right .
  
      :param sorted_collection: some ascending sorted collection with comparable items
      :param item: item to bisect
      :param lo: lowest index to consider (as in sorted_collection[lo:hi])
      :param hi: past the highest index to consider (as in sorted_collection[lo:hi])
      :return: index i such that all values in sorted_collection[lo:i] are <= item and
          all values in sorted_collection[i:hi] are > item.
  
      Examples:
      >>> bisect_right([0, 5, 7, 10, 15], 0)
      1
  
      >>> bisect_right([0, 5, 7, 10, 15], 15)
      5
  
      >>> bisect_right([0, 5, 7, 10, 15], 6)
      2
  
      >>> bisect_right([0, 5, 7, 10, 15], 15, 1, 3)
      3
  
      >>> bisect_right([0, 5, 7, 10, 15], 6, 2)
      2
      """
      if hi is None:
          hi = len(sorted_collection)
  
      while lo < hi:
          mid = (lo + hi) // 2
          if sorted_collection[mid] <= item:
              
              lo = mid + 1
              
          else:
              
              hi = mid
  
      return lo
  
  
  def insort_left(sorted_collection, item, lo=0, hi=None):
      """
      Inserts a given value into a sorted array before other values with the same value.
  
      It has the same interface as
      https://docs.python.org/3/library/bisect.html#bisect.insort_left .
  
      :param sorted_collection: some ascending sorted collection with comparable items
      :param item: item to insert
      :param lo: lowest index to consider (as in sorted_collection[lo:hi])
      :param hi: past the highest index to consider (as in sorted_collection[lo:hi])
  
      Examples:
      >>> sorted_collection = [0, 5, 7, 10, 15]
      >>> insort_left(sorted_collection, 6)
      >>> sorted_collection
      [0, 5, 6, 7, 10, 15]
  
      >>> sorted_collection = [(0, 0), (5, 5), (7, 7), (10, 10), (15, 15)]
      >>> item = (5, 5)
      >>> insort_left(sorted_collection, item)
      >>> sorted_collection
      [(0, 0), (5, 5), (5, 5), (7, 7), (10, 10), (15, 15)]
      >>> item is sorted_collection[1]
      True
      >>> item is sorted_collection[2]
      False
  
      >>> sorted_collection = [0, 5, 7, 10, 15]
      >>> insort_left(sorted_collection, 20)
      >>> sorted_collection
      [0, 5, 7, 10, 15, 20]
  
      >>> sorted_collection = [0, 5, 7, 10, 15]
      >>> insort_left(sorted_collection, 15, 1, 3)
      >>> sorted_collection
      [0, 5, 7, 15, 10, 15]
      """
      sorted_collection.insert(bisect_left(sorted_collection, item, lo, hi), item)
  
  
  def insort_right(sorted_collection, item, lo=0, hi=None):
      """
      Inserts a given value into a sorted array after other values with the same value.
  
      It has the same interface as
      https://docs.python.org/3/library/bisect.html#bisect.insort_right .
  
      :param sorted_collection: some ascending sorted collection with comparable items
      :param item: item to insert
      :param lo: lowest index to consider (as in sorted_collection[lo:hi])
      :param hi: past the highest index to consider (as in sorted_collection[lo:hi])
  
      Examples:
      >>> sorted_collection = [0, 5, 7, 10, 15]
      >>> insort_right(sorted_collection, 6)
      >>> sorted_collection
      [0, 5, 6, 7, 10, 15]
  
      >>> sorted_collection = [(0, 0), (5, 5), (7, 7), (10, 10), (15, 15)]
      >>> item = (5, 5)
      >>> insort_right(sorted_collection, item)
      >>> sorted_collection
      [(0, 0), (5, 5), (5, 5), (7, 7), (10, 10), (15, 15)]
      >>> item is sorted_collection[1]
      False
      >>> item is sorted_collection[2]
      True
  
      >>> sorted_collection = [0, 5, 7, 10, 15]
      >>> insort_right(sorted_collection, 20)
      >>> sorted_collection
      [0, 5, 7, 10, 15, 20]
  
      >>> sorted_collection = [0, 5, 7, 10, 15]
      >>> insort_right(sorted_collection, 15, 1, 3)
      >>> sorted_collection
      [0, 5, 7, 15, 10, 15]
      """
      sorted_collection.insert(bisect_right(sorted_collection, item, lo, hi), item)
  
  
  def binary_search(sorted_collection, item):
      """Pure implementation of binary search algorithm in Python
  
      Be careful collection must be ascending sorted, otherwise result will be
      unpredictable
  
      :param sorted_collection: some ascending sorted collection with comparable items
      :param item: item value to search
      :return: index of found item or None if item is not found
  
      Examples:
      >>> binary_search([0, 5, 7, 10, 15], 0)
      0
  
      >>> binary_search([0, 5, 7, 10, 15], 10)
      3
  
      >>> binary_search([0, 5, 7, 10, 15], 5)
      1
  
      >>> binary_search([0, 5, 7, 10, 15], 6)
  
      """
      left = 0
      right = len(sorted_collection) - 1
  
      while left <= right:
          
          midpoint = left + (right - left) // 2
          current_item = sorted_collection[midpoint]
          if current_item == item:
              
              return midpoint
          
          elif item < current_item:
              
              right = midpoint - 1
              
          else:
              
              left = midpoint + 1
              
      return None
  
  
  def binary_search_std_lib(sorted_collection, item):
      """Pure implementation of binary search algorithm in Python using stdlib
  
      Be careful collection must be ascending sorted, otherwise result will be
      unpredictable
  
      :param sorted_collection: some ascending sorted collection with comparable items
      :param item: item value to search
      :return: index of found item or None if item is not found
  
      Examples:
      >>> binary_search_std_lib([0, 5, 7, 10, 15], 0)
      0
  
      >>> binary_search_std_lib([0, 5, 7, 10, 15], 10)
      3
  
      >>> binary_search_std_lib([0, 5, 7, 10, 15], 5)
      1
  
      >>> binary_search_std_lib([0, 5, 7, 10, 15], 6)
  
      """
      index = bisect.bisect_left(sorted_collection, item)
      if index != len(sorted_collection) and sorted_collection[index] == item:
          
          return index
      
      return None
  
  
  def binary_search_by_recursion(sorted_collection, item, left, right):
  
      """Pure implementation of binary search algorithm in Python by recursion
  
      Be careful collection must be ascending sorted, otherwise result will be
      unpredictable
      First recursion should be started with left=0 and right=(len(sorted_collection)-1)
  
      :param sorted_collection: some ascending sorted collection with comparable items
      :param item: item value to search
      :return: index of found item or None if item is not found
  
      Examples:
      >>> binary_search_by_recursion([0, 5, 7, 10, 15], 0, 0, 4)
      0
  
      >>> binary_search_by_recursion([0, 5, 7, 10, 15], 15, 0, 4)
      4
  
      >>> binary_search_by_recursion([0, 5, 7, 10, 15], 5, 0, 4)
      1
  
      >>> binary_search_by_recursion([0, 5, 7, 10, 15], 6, 0, 4)
  
      """
      if right < left:
          
          return None
  
      midpoint = left + (right - left) // 2
  
      if sorted_collection[midpoint] == item:
          
          return midpoint
      
      elif sorted_collection[midpoint] > item:
          
          return binary_search_by_recursion(sorted_collection, item, left, midpoint - 1)
      
      else:
          
          return binary_search_by_recursion(sorted_collection, item, midpoint + 1, right)
  
  
  def __assert_sorted(collection):
      """Check if collection is ascending sorted, if not - raises :py:class:`ValueError`
  
      :param collection: collection
      :return: True if collection is ascending sorted
      :raise: :py:class:`ValueError` if collection is not ascending sorted
  
      Examples:
      >>> __assert_sorted([0, 1, 2, 4])
      True
  
      >>> __assert_sorted([10, -1, 5])
      Traceback (most recent call last):
      ...
      ValueError: Collection must be ascending sorted
      """
      if collection != sorted(collection):
          raise ValueError("Collection must be ascending sorted")
      return True
  
  
  if __name__ == "__main__":
      import sys
  
      user_input = input("Enter numbers separated by comma:\n").strip()
      collection = [int(item) for item in user_input.split(",")]
      try:
          __assert_sorted(collection)
      except ValueError:
          sys.exit("Sequence must be ascending sorted to apply binary search")
  
      target_input = input("Enter a single number to be found in the list:\n")
      target = int(target_input)
      result = binary_search(collection, target)
      if result is not None:
          print(f"{target} found at positions: {result}")
      else:
          print("Not found")
  