mirror of
https://github.com/pocketpy/pocketpy
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124 lines
3.8 KiB
Python
124 lines
3.8 KiB
Python
"""
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Optimized bisection algorithms for sorted list insertions.
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These functions provide efficient binary search implementations for finding insertion points
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in sorted sequences and inserting elements while maintaining sorted order.
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"""
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def bisect_right(a, x, lo=0, hi=None):
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"""Return the index where to insert item x in list a, assuming a is sorted.
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The return value i is such that all e in a[:i] have e <= x, and all e in
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a[i:] have e > x. So if x already appears in the list, the insertion
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point will be after (to the right of) any existing entries.
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Args:
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a: A sorted list-like object supporting comparison and __len__
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x: The item to be inserted
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lo: Lower bound of the slice to be searched (inclusive)
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hi: Upper bound of the slice to be searched (exclusive)
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Returns:
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The index where x should be inserted to maintain sorted order
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Raises:
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ValueError: If lo is negative
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"""
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if lo < 0:
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raise ValueError('lo must be non-negative')
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if hi is None:
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hi = len(a)
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# Fast path for common case: appending to the end
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if hi > 0 and hi == len(a) and x > a[-1]:
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return hi
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# Normal binary search
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while lo < hi:
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mid = (lo + hi) // 2
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if x < a[mid]:
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hi = mid
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else:
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lo = mid + 1
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return lo
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def bisect_left(a, x, lo=0, hi=None):
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"""Return the index where to insert item x in list a, assuming a is sorted.
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The return value i is such that all e in a[:i] have e < x, and all e in
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a[i:] have e >= x. So if x already appears in the list, the insertion
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point will be before (to the left of) any existing entries.
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Args:
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a: A sorted list-like object supporting comparison and __len__
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x: The item to be inserted
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lo: Lower bound of the slice to be searched (inclusive)
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hi: Upper bound of the slice to be searched (exclusive)
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Returns:
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The index where x should be inserted to maintain sorted order
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Raises:
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ValueError: If lo is negative
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"""
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if lo < 0:
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raise ValueError('lo must be non-negative')
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if hi is None:
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hi = len(a)
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# Fast path for common case: appending to the end
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if hi > 0 and hi == len(a) and x > a[-1]:
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return hi
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# Fast path for common case: inserting at the beginning
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if lo == 0 and hi > 0 and x < a[0]:
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return 0
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# Normal binary search
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while lo < hi:
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mid = (lo + hi) // 2
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if a[mid] < x:
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lo = mid + 1
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else:
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hi = mid
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return lo
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def insort_right(a, x, lo=0, hi=None):
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"""Insert item x in list a, and keep it sorted assuming a is sorted.
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If x is already in a, insert it to the right of the rightmost x.
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Args:
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a: A sorted list-like object supporting comparison, __len__, and insert
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x: The item to be inserted
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lo: Lower bound of the slice to be searched (inclusive)
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hi: Upper bound of the slice to be searched (exclusive)
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"""
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# Use bisect_right to find the insertion point
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insertion_point = bisect_right(a, x, lo, hi)
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a.insert(insertion_point, x)
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def insort_left(a, x, lo=0, hi=None):
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"""Insert item x in list a, and keep it sorted assuming a is sorted.
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If x is already in a, insert it to the left of the leftmost x.
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Args:
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a: A sorted list-like object supporting comparison, __len__, and insert
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x: The item to be inserted
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lo: Lower bound of the slice to be searched (inclusive)
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hi: Upper bound of the slice to be searched (exclusive)
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"""
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# Use bisect_left to find the insertion point
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insertion_point = bisect_left(a, x, lo, hi)
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a.insert(insertion_point, x)
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# Create aliases for backward compatibility
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bisect = bisect_right
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insort = insort_right
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