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GH-104145: Use fully-qualified cross reference types for the bisect module #104172

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22 changes: 12 additions & 10 deletions Doc/library/bisect.rst
Original file line number Diff line number Diff line change
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expensive comparison operations, this can be an improvement over
linear searches or frequent resorting.

The module is called :mod:`bisect` because it uses a basic bisection

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algorithm to do its work. Unlike other bisection tools that search for a
specific value, the functions in this module are designed to locate an
insertion point. Accordingly, the functions never call an :meth:`__eq__`
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functions only call the :meth:`__lt__` method and will return an insertion
point between values in an array.

.. _bisect functions:

The following functions are provided:


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.. function:: bisect_right(a, x, lo=0, hi=len(a), *, key=None)
bisect(a, x, lo=0, hi=len(a), *, key=None)

Similar to :func:`bisect_left`, but returns an insertion point which comes
Similar to :py:func:`~bisect.bisect_left`, but returns an insertion point which comes
after (to the right of) any existing entries of *x* in *a*.

The returned insertion point *ip* partitions the array *a* into two slices
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Insert *x* in *a* in sorted order.

This function first runs :func:`bisect_left` to locate an insertion point.
This function first runs :py:func:`~bisect.bisect_left` to locate an insertion point.

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Next, it runs the :meth:`insert` method on *a* to insert *x* at the
appropriate position to maintain sort order.

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.. function:: insort_right(a, x, lo=0, hi=len(a), *, key=None)
insort(a, x, lo=0, hi=len(a), *, key=None)

Similar to :func:`insort_left`, but inserting *x* in *a* after any existing
Similar to :py:func:`~bisect.insort_left`, but inserting *x* in *a* after any existing
entries of *x*.

This function first runs :func:`bisect_right` to locate an insertion point.
This function first runs :py:func:`~bisect.bisect_right` to locate an insertion point.

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Next, it runs the :meth:`insert` method on *a* to insert *x* at the
appropriate position to maintain sort order.

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they are used. Consequently, if the search functions are used in a loop,
the key function may be called again and again on the same array elements.
If the key function isn't fast, consider wrapping it with
:func:`functools.cache` to avoid duplicate computations. Alternatively,
:py:func:`functools.cache` to avoid duplicate computations. Alternatively,
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consider searching an array of precomputed keys to locate the insertion
point (as shown in the examples section below).

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Searching Sorted Lists
----------------------

The above :func:`bisect` functions are useful for finding insertion points but
The above `bisect functions`_ are useful for finding insertion points but
can be tricky or awkward to use for common searching tasks. The following five
functions show how to transform them into the standard lookups for sorted
lists::
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.. _bisect-example:

The :func:`bisect` function can be useful for numeric table lookups. This
example uses :func:`bisect` to look up a letter grade for an exam score (say)
The :py:func:`~bisect.bisect` function can be useful for numeric table lookups. This
example uses :py:func:`~bisect.bisect` to look up a letter grade for an exam score (say)
based on a set of ordered numeric breakpoints: 90 and up is an 'A', 80 to 89 is
a 'B', and so on::

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>>> [grade(score) for score in [33, 99, 77, 70, 89, 90, 100]]
['F', 'A', 'C', 'C', 'B', 'A', 'A']

The :func:`bisect` and :func:`insort` functions also work with lists of
tuples. The *key* argument can serve to extract the field used for ordering
The :py:func:`~bisect.bisect` and :py:func:`~bisect.insort` functions also work with
lists of tuples. The *key* argument can serve to extract the field used for ordering
records in a table::

>>> from collections import namedtuple
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