Python bisect.html() Examples

def __init__(self, name, buckets, verbose_pretty_print=False):
    """Initializes the histogram with the given ranges.

    Args:
      name: String name of this histogram.
      buckets: The ranges the histogram counts over. This is a list of values,
          where each value is the inclusive lower bound of the range. An extra
          range will be implicitly defined which spans from negative infinity
          to the lowest given lower bound. The highest given lower bound
          defines a range spaning to positive infinity. This way any value will
          be included in the histogram counts. For example, if `buckets` is
          [4, 6, 10] the histogram will have ranges
          [-inf, 4), [4, 6), [6, 10), [10, inf).
      verbose_pretty_print: If True, self.pretty_print will print the count for
          every bucket. If False, only buckets with positive counts will be
          printed.
    """
    super(Histogram, self).__init__(name)

    # List of inclusive lowest values in each bucket.
    self.buckets = [float('-inf')] + sorted(set(buckets))
    self.counters = dict((bucket_lower, 0) for bucket_lower in self.buckets)
    self.verbose_pretty_print = verbose_pretty_print

  # https://docs.python.org/2/library/bisect.html#searching-sorted-lists 

def __init__(self, name, buckets, verbose_pretty_print=False):
    """Initializes the histogram with the given ranges.

    Args:
      name: String name of this histogram.
      buckets: The ranges the histogram counts over. This is a list of values,
          where each value is the inclusive lower bound of the range. An extra
          range will be implicitly defined which spans from negative infinity
          to the lowest given lower bound. The highest given lower bound
          defines a range spaning to positive infinity. This way any value will
          be included in the histogram counts. For example, if `buckets` is
          [4, 6, 10] the histogram will have ranges
          [-inf, 4), [4, 6), [6, 10), [10, inf).
      verbose_pretty_print: If True, self.pretty_print will print the count for
          every bucket. If False, only buckets with positive counts will be
          printed.
    """
    super(Histogram, self).__init__(name)

    # List of inclusive lowest values in each bucket.
    self.buckets = [float('-inf')] + sorted(set(buckets))
    self.counters = dict((bucket_lower, 0) for bucket_lower in self.buckets)
    self.verbose_pretty_print = verbose_pretty_print

  # https://docs.python.org/2/library/bisect.html#searching-sorted-lists 

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 get_machine(self,key):
        '''Returns the number of the machine which key gets sent to.'''
        h = my_hash(key)
        # edge case where we cycle past hash value of 1 and back to 0.
        if h > self.hash_tuples[-1][2]:
            return self.hash_tuples[0][0]
        hash_values = map(lambda x: x[2],self.hash_tuples)
        # bitsect is used to find the index that we want to insert h
        # the index will be used same as finding the first clockwise node
        # https://docs.python.org/2/library/bisect.html
        index = bisect.bisect_left(hash_values,h)
        return self.hash_tuples[index][0] 

def spookyrating(self, ctx: commands.Context, who: discord.Member = None) -> None:
        """
        Calculates the spooky rating of someone.

        Any user will always yield the same result, no matter who calls the command
        """
        if who is None:
            who = ctx.author

        # This ensures that the same result over multiple runtimes
        self.local_random.seed(who.id)
        spooky_percent = self.local_random.randint(1, 101)

        # We need the -1 due to how bisect returns the point
        # see the documentation for further detail
        # https://docs.python.org/3/library/bisect.html#bisect.bisect
        index = bisect.bisect(SPOOKY_DATA, (spooky_percent,)) - 1

        _, data = SPOOKY_DATA[index]

        embed = discord.Embed(
            title=data['title'],
            description=f'{who} scored {spooky_percent}%!',
            color=Colours.orange
        )
        embed.add_field(
            name='A whisper from Satan',
            value=data['text']
        )
        embed.set_thumbnail(
            url=data['image']
        )

        await ctx.send(embed=embed) 

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