Examples (LL) continued

"""
You are given two non-empty linked lists representing
two non-negative integers. The digits are stored in reverse order
and each of their nodes contain a single digit.
Add the two numbers and return it as a linked list.

You may assume the two numbers do not contain any leading zero,
except the number 0 itself.

Input: (2 -> 4 -> 3) + (5 -> 6 -> 4)
Output: 7 -> 0 -> 8
"""

import unittest


class Node:
    def __init__(self, x):
        self.val = x
        self.next = None


def add_two_numbers(left: Node, right: Node) -> Node:
    head = Node(0)
    current = head
    sum = 0
    while left or right:
        print("adding: ", left.val, right.val)
        sum //= 10
        if left:
            sum += left.val
            left = left.next
        if right:
            sum += right.val
            right = right.next
        current.next = Node(sum % 10)
        current = current.next
    if sum // 10 == 1:
        current.next = Node(1)
    return head.next


def convert_to_list(number: int) -> Node:
    """
        converts a positive integer into a (reversed) linked list.
        for example: give 112
        result 2 -> 1 -> 1
    """
    if number >= 0:
        head = Node(0)
        current = head
        remainder = number % 10
        quotient = number // 10

        while quotient != 0:
            current.next = Node(remainder)
            current = current.next
            remainder = quotient % 10
            quotient //= 10
        current.next = Node(remainder)
        return head.next
    else:
        print("number must be positive!")


def convert_to_str(l: Node) -> str:
    """
        converts the non-negative number list into a string.
    """
    result = ""
    while l:
        result += str(l.val)
        l = l.next
    return result


class TestSuite(unittest.TestCase):
    """
        testsuite for the linked list structure and
        the adding function, above.
    """

    def test_convert_to_str(self):
        number1 = Node(2)
        number1.next = Node(4)
        number1.next.next = Node(3)
        self.assertEqual("243", convert_to_str(number1))

    def test_add_two_numbers(self):
        # 1. test case
        number1 = Node(2)
        number1.next = Node(4)
        number1.next.next = Node(3)
        number2 = Node(5)
        number2.next = Node(6)
        number2.next.next = Node(4)
        result = convert_to_str(add_two_numbers(number1, number2))
        self.assertEqual("708", result)

        # 2. test case
        number3 = Node(1)
        number3.next = Node(1)
        number3.next.next = Node(9)
        number4 = Node(1)
        number4.next = Node(0)
        number4.next.next = Node(1)
        result = convert_to_str(add_two_numbers(number3, number4))
        self.assertEqual("2101", result)

        # 3. test case
        number5 = Node(1)
        number6 = Node(0)
        result = convert_to_str(add_two_numbers(number5, number6))
        self.assertEqual("1", result)

        # 4. test case
        number7 = Node(9)
        number7.next = Node(1)
        number7.next.next = Node(1)
        number8 = Node(1)
        number8.next = Node(0)
        number8.next.next = Node(1)
        result = convert_to_str(add_two_numbers(number7, number8))
        self.assertEqual("022", result)

    def test_convert_to_list(self):
        result = convert_to_str(convert_to_list(112))
        self.assertEqual("211", result)


if __name__ == "__main__":
    unittest.main()

"""
A linked list is given such that each node contains an additional random
pointer which could point to any node in the list or null.

Return a deep copy of the list.
"""
from collections import defaultdict


class RandomListNode(object):
    def __init__(self, label):
        self.label = label
        self.next = None
        self.random = None


def copy_random_pointer_v1(head):
    """
    :type head: RandomListNode
    :rtype: RandomListNode
    """
    dic = dict()
    m = n = head
    while m:
        dic[m] = RandomListNode(m.label)
        m = m.next
    while n:
        dic[n].next = dic.get(n.next)
        dic[n].random = dic.get(n.random)
        n = n.next
    return dic.get(head)


# O(n)
def copy_random_pointer_v2(head):
    """
    :type head: RandomListNode
    :rtype: RandomListNode
    """
    copy = defaultdict(lambda: RandomListNode(0))
    copy[None] = None
    node = head
    while node:
        copy[node].label = node.label
        copy[node].next = copy[node.next]
        copy[node].random = copy[node.random]
        node = node.next
    return copy[head]

"""
Write a function to delete a node (except the tail)
in a singly linked list, given only access to that node.

Supposed the linked list is 1 -> 2 -> 3 -> 4 and
you are given the third node with value 3,
the linked list should become 1 -> 2 -> 4 after calling your function.
"""
import unittest


class Node:
    def __init__(self, x):
        self.val = x
        self.next = None


def delete_node(node):
    if node is None or node.next is None:
        raise ValueError
    node.val = node.next.val
    node.next = node.next.next


class TestSuite(unittest.TestCase):
    def test_delete_node(self):

        # make linkedlist 1 -> 2 -> 3 -> 4
        head = Node(1)
        curr = head
        for i in range(2, 6):
            curr.next = Node(i)
            curr = curr.next

        # node3 = 3
        node3 = head.next.next

        # after delete_node => 1 -> 2 -> 4
        delete_node(node3)

        curr = head
        self.assertEqual(1, curr.val)

        curr = curr.next
        self.assertEqual(2, curr.val)

        curr = curr.next
        self.assertEqual(4, curr.val)

        curr = curr.next
        self.assertEqual(5, curr.val)

        tail = curr
        self.assertIsNone(tail.next)

        self.assertRaises(ValueError, delete_node, tail)
        self.assertRaises(ValueError, delete_node, tail.next)


if __name__ == "__main__":

    unittest.main()

"""
    Given a linked list, find the first node of a cycle in it.
    1 -> 2 -> 3 -> 4 -> 5 -> 1  => 1
    A -> B -> C -> D -> E -> C  => C

    Note: The solution is a direct implementation
          Floyd's cycle-finding algorithm (Floyd's Tortoise and Hare).
"""
import unittest


class Node:
    def __init__(self, x):
        self.val = x
        self.next = None


def first_cyclic_node(head):
    """
    :type head: Node
    :rtype: Node
    """
    runner = walker = head
    while runner and runner.next:
        runner = runner.next.next
        walker = walker.next
        if runner is walker:
            break

    if runner is None or runner.next is None:
        return None

    walker = head
    while runner is not walker:
        runner, walker = runner.next, walker.next
    return runner


class TestSuite(unittest.TestCase):
    def test_first_cyclic_node(self):

        # create linked list => A -> B -> C -> D -> E -> C
        head = Node("A")
        head.next = Node("B")
        curr = head.next

        cyclic_node = Node("C")
        curr.next = cyclic_node

        curr = curr.next
        curr.next = Node("D")
        curr = curr.next
        curr.next = Node("E")
        curr = curr.next
        curr.next = cyclic_node

        self.assertEqual("C", first_cyclic_node(head).val)


if __name__ == "__main__":

    unittest.main()

from .reverse import *
from .is_sorted import *
from .remove_range import *
from .swap_in_pairs import *
from .rotate_list import *
from .is_cyclic import *
from .merge_two_list import *
from .is_palindrome import *
from .copy_random_pointer import *

"""
   This function takes two lists and returns the node they have in common, if any.
   In this example:
   1 -> 3 -> 5
               \
                7 -> 9 -> 11
               /
   2 -> 4 -> 6
   ...we would return 7.
   Note that the node itself is the unique identifier, not the value of the node.
   """
import unittest


class Node(object):
    def __init__(self, val=None):
        self.val = val
        self.next = None


def intersection(h1, h2):

    count = 0
    flag = None
    h1_orig = h1
    h2_orig = h2

    while h1 or h2:
        count += 1

        if not flag and (h1.next is None or h2.next is None):
            # We hit the end of one of the lists, set a flag for this
            flag = (count, h1.next, h2.next)

        if h1:
            h1 = h1.next
        if h2:
            h2 = h2.next

    long_len = count  # Mark the length of the longer of the two lists
    short_len = flag[0]

    if flag[1] is None:
        shorter = h1_orig
        longer = h2_orig
    elif flag[2] is None:
        shorter = h2_orig
        longer = h1_orig

    while longer and shorter:

        while long_len > short_len:
            # force the longer of the two lists to "catch up"
            longer = longer.next
            long_len -= 1

        if longer == shorter:
            # The nodes match, return the node
            return longer
        else:
            longer = longer.next
            shorter = shorter.next

    return None


class TestSuite(unittest.TestCase):
    def test_intersection(self):

        # create linked list as:
        # 1 -> 3 -> 5
        #            \
        #             7 -> 9 -> 11
        #            /
        # 2 -> 4 -> 6
        a1 = Node(1)
        b1 = Node(3)
        c1 = Node(5)
        d = Node(7)
        a2 = Node(2)
        b2 = Node(4)
        c2 = Node(6)
        e = Node(9)
        f = Node(11)

        a1.next = b1
        b1.next = c1
        c1.next = d
        a2.next = b2
        b2.next = c2
        c2.next = d
        d.next = e
        e.next = f

        self.assertEqual(7, intersection(a1, a2).val)


if __name__ == "__main__":

    unittest.main()

"""
Given a linked list, determine if it has a cycle in it.

Follow up:
Can you solve it without using extra space?
"""


class Node:
    def __init__(self, x):
        self.val = x
        self.next = None


def is_cyclic(head):
    """
    :type head: Node
    :rtype: bool
    """
    if not head:
        return False
    runner = head
    walker = head
    while runner.next and runner.next.next:
        runner = runner.next.next
        walker = walker.next
        if runner == walker:
            return True
    return False

def is_palindrome(head):
    if not head:
        return True
    # split the list to two parts
    fast, slow = head.next, head
    while fast and fast.next:
        fast = fast.next.next
        slow = slow.next
    second = slow.next
    slow.next = None  # Don't forget here! But forget still works!
    # reverse the second part
    node = None
    while second:
        nxt = second.next
        second.next = node
        node = second
        second = nxt
    # compare two parts
    # second part has the same or one less node
    while node:
        if node.val != head.val:
            return False
        node = node.next
        head = head.next
    return True


def is_palindrome_stack(head):
    if not head or not head.next:
        return True

    # 1. Get the midpoint (slow)
    slow = fast = cur = head
    while fast and fast.next:
        fast, slow = fast.next.next, slow.next

    # 2. Push the second half into the stack
    stack = [slow.val]
    while slow.next:
        slow = slow.next
        stack.append(slow.val)

    # 3. Comparison
    while stack:
        if stack.pop() != cur.val:
            return False
        cur = cur.next

    return True


def is_palindrome_dict(head):
    """
    This function builds up a dictionary where the keys are the values of the list,
    and the values are the positions at which these values occur in the list.
    We then iterate over the dict and if there is more than one key with an odd
    number of occurrences, bail out and return False.
    Otherwise, we want to ensure that the positions of occurrence sum to the
    value of the length of the list - 1, working from the outside of the list inward.
    For example:
    Input: 1 -> 1 -> 2 -> 3 -> 2 -> 1 -> 1
    d = {1: [0,1,5,6], 2: [2,4], 3: [3]}
    '3' is the middle outlier, 2+4=6, 0+6=6 and 5+1=6 so we have a palindrome.
    """
    if not head or not head.next:
        return True
    d = {}
    pos = 0
    while head:
        if head.val in d.keys():
            d[head.val].append(pos)
        else:
            d[head.val] = [pos]
        head = head.next
        pos += 1
    checksum = pos - 1
    middle = 0
    for v in d.values():
        if len(v) % 2 != 0:
            middle += 1
        else:
            step = 0
            for i in range(0, len(v)):
                if v[i] + v[len(v) - 1 - step] != checksum:
                    return False
                step += 1
        if middle > 1:
            return False
    return True

"""
Given a linked list, is_sort function returns true if the list is in sorted
(increasing) order and return false otherwise. An empty list is considered
to be sorted.

For example:
Null :List is sorted
1 2 3 4 :List is sorted
1 2 -1 3 :List is not sorted
"""


def is_sorted(head):
    if not head:
        return True
    current = head
    while current.next:
        if current.val > current.next.val:
            return False
        current = current.next
    return True

class Node:
    def __init__(self, val=None):
        self.val = val
        self.next = None


def kth_to_last_eval(head, k):
    """
    This is a suboptimal, hacky method using eval(), which is not
     safe for user input. We guard against danger by ensuring k in an int
    """
    if not isinstance(k, int) or not head.val:
        return False

    nexts = ".".join(["next" for n in range(1, k + 1)])
    seeker = str(".".join(["head", nexts]))

    while head:
        if eval(seeker) is None:
            return head
        else:
            head = head.next

    return False


def kth_to_last_dict(head, k):
    """
    This is a brute force method where we keep a dict the size of the list
    Then we check it for the value we need. If the key is not in the dict,
    our and statement will short circuit and return False
    """
    if not (head and k > -1):
        return False
    d = dict()
    count = 0
    while head:
        d[count] = head
        head = head.next
        count += 1
    return len(d) - k in d and d[len(d) - k]


def kth_to_last(head, k):
    """
    This is an optimal method using iteration.
    We move p1 k steps ahead into the list.
    Then we move p1 and p2 together until p1 hits the end.
    """
    if not (head or k > -1):
        return False
    p1 = head
    p2 = head
    for i in range(1, k + 1):
        if p1 is None:
            # Went too far, k is not valid
            raise IndexError
        p1 = p1.next
    while p1:
        p1 = p1.next
        p2 = p2.next
    return p2


def print_linked_list(head):
    string = ""
    while head.next:
        string += head.val + " -> "
        head = head.next
    string += head.val
    print(string)


def test():
    # def make_test_li
    # A A B C D C F G
    a1 = Node("A")
    a2 = Node("A")
    b = Node("B")
    c1 = Node("C")
    d = Node("D")
    c2 = Node("C")
    f = Node("F")
    g = Node("G")
    a1.next = a2
    a2.next = b
    b.next = c1
    c1.next = d
    d.next = c2
    c2.next = f
    f.next = g
    print_linked_list(a1)

    # test kth_to_last_eval
    kth = kth_to_last_eval(a1, 4)
    try:
        assert kth.val == "D"
    except AssertionError as e:
        e.args += ("Expecting D, got %s" % kth.val,)
        raise

    # test kth_to_last_dict
    kth = kth_to_last_dict(a1, 4)
    try:
        assert kth.val == "D"
    except AssertionError as e:
        e.args += ("Expecting D, got %s" % kth.val,)
        raise

    # test kth_to_last
    kth = kth_to_last(a1, 4)
    try:
        assert kth.val == "D"
    except AssertionError as e:
        e.args += ("Expecting D, got %s" % kth.val,)
        raise
    print("all passed.")


if __name__ == "__main__":
    test()

# Pros
# Linked Lists have constant-time insertions and deletions in any position,
# in comparison, arrays require O(n) time to do the same thing.
# Linked lists can continue to expand without having to specify
# their size ahead of time (remember our lectures on Array sizing
# from the Array Sequence section of the course!)

# Cons
# To access an element in a linked list, you need to take O(k) time
# to go from the head of the list to the kth element.
# In contrast, arrays have constant time operations to access
# elements in an array.


class DoublyLinkedListNode(object):
    def __init__(self, value):
        self.value = value
        self.next = None
        self.prev = None


class SinglyLinkedListNode(object):
    def __init__(self, value):
        self.value = value
        self.next = None

"""
Merge two sorted linked lists and return it as a new list. The new list should
be made by splicing together the nodes of the first two lists.

For example:
Input: 1->2->4, 1->3->4
Output: 1->1->2->3->4->4
"""


class Node:
    def __init__(self, x):
        self.val = x
        self.next = None


def merge_two_list(l1, l2):
    ret = cur = Node(0)
    while l1 and l2:
        if l1.val < l2.val:
            cur.next = l1
            l1 = l1.next
        else:
            cur.next = l2
            l2 = l2.next
        cur = cur.next
    cur.next = l1 or l2
    return ret.next


# recursively
def merge_two_list_recur(l1, l2):
    if not l1 or not l2:
        return l1 or l2
    if l1.val < l2.val:
        l1.next = merge_two_list_recur(l1.next, l2)
        return l1
    else:
        l2.next = merge_two_list_recur(l1, l2.next)
        return l2

"""
Write code to partition a linked list around a value x, such that all nodes less
than x come before all nodes greater than or equal to x.  If x is contained
within the list, the values of x only need to be after the elements less than x.
The partition element x can appear anywhere in the "right partition";
it does not need to appear between the left and right partitions.

3 -> 5 -> 8 -> 5 -> 10 -> 2 -> 1 [partition=5]
3 -> 1 -> 2 -> 10 -> 5 -> 5 -> 8

We assume the values of all linked list nodes are int and that x in an int.
"""


class Node:
    def __init__(self, val=None):
        self.val = int(val)
        self.next = None


def print_linked_list(head):
    string = ""
    while head.next:
        string += str(head.val) + " -> "
        head = head.next
    string += str(head.val)
    print(string)


def partition(head, x):
    left = None
    right = None
    prev = None
    current = head
    while current:
        if int(current.val) >= x:
            if not right:
                right = current
        else:
            if not left:
                left = current
            else:
                prev.next = current.next
                left.next = current
                left = current
                left.next = right
        if prev and prev.next is None:
            break
        # cache previous value in case it needs to be pointed elsewhere
        prev = current
        current = current.next


def test():
    a = Node("3")
    b = Node("5")
    c = Node("8")
    d = Node("5")
    e = Node("10")
    f = Node("2")
    g = Node("1")

    a.next = b
    b.next = c
    c.next = d
    d.next = e
    e.next = f
    f.next = g

    print_linked_list(a)
    partition(a, 5)
    print_linked_list(a)


if __name__ == "__main__":
    test()

class Node:
    def __init__(self, val=None):
        self.val = val
        self.next = None


def remove_dups(head):
    """
    Time Complexity: O(N)
    Space Complexity: O(N)
    """
    hashset = set()
    prev = Node()
    while head:
        if head.val in hashset:
            prev.next = head.next
        else:
            hashset.add(head.val)
            prev = head
        head = head.next


def remove_dups_wothout_set(head):
    """
    Time Complexity: O(N^2)
    Space Complexity: O(1)
    """
    current = head
    while current:
        runner = current
        while runner.next:
            if runner.next.val == current.val:
                runner.next = runner.next.next
            else:
                runner = runner.next
        current = current.next


def print_linked_list(head):
    string = ""
    while head.next:
        string += head.val + " -> "
        head = head.next
    string += head.val
    print(string)


# A A B C D C F G

a1 = Node("A")
a2 = Node("A")
b = Node("B")
c1 = Node("C")
d = Node("D")
c2 = Node("C")
f = Node("F")
g = Node("G")

a1.next = a2
a2.next = b
b.next = c1
c1.next = d
d.next = c2
c2.next = f
f.next = g

remove_dups(a1)
print_linked_list(a1)
remove_dups_wothout_set(a1)
print_linked_list(a1)

"""
Given a linked list, remove_range function accepts a starting and ending index
as parameters and removes the elements at those indexes (inclusive) from the list

For example:
List: [8, 13, 17, 4, 9, 12, 98, 41, 7, 23, 0, 92]
remove_range(list, 3, 8);
List becomes: [8, 13, 17, 23, 0, 92]

legal range of the list (0 < start index < end index < size of list).
"""


def remove_range(head, start, end):
    assert start <= end
    # Case: remove node at head
    if start == 0:
        for i in range(0, end + 1):
            if head != None:
                head = head.next
    else:
        current = head
        # Move pointer to start position
        for i in range(0, start - 1):
            current = current.next
        # Remove data until the end
        for i in range(0, end - start + 1):
            if current != None and current.next != None:
                current.next = current.next.next
    return head

"""
Reverse a singly linked list. For example:

1 --> 2 --> 3 --> 4
After reverse:
4 --> 3 --> 2 --> 1
"""
#
# Iterative solution
# T(n)- O(n)
#
def reverse_list(head):
    """
    :type head: ListNode
    :rtype: ListNode
    """
    if not head or not head.next:
        return head
    prev = None
    while head:
        current = head
        head = head.next
        current.next = prev
        prev = current
    return prev


#
# Recursive solution
# T(n)- O(n)
#
def reverse_list_recursive(head):
    """
    :type head: ListNode
    :rtype: ListNode
    """
    if head is None or head.next is None:
        return head
    p = head.next
    head.next = None
    revrest = reverse_list_recursive(p)
    p.next = head
    return revrest

"""
Given a list, rotate the list to the right by k places,
where k is non-negative.

For example:
Given 1->2->3->4->5->NULL and k = 2,
return 4->5->1->2->3->NULL.
"""

# Definition for singly-linked list.
# class ListNode(object):
#     def __init__(self, x):
#         self.val = x
#         self.next = None


def rotate_right(head, k):
    """
    :type head: ListNode
    :type k: int
    :rtype: ListNode
    """
    if not head or not head.next:
        return head
    current = head
    length = 1
    # count length of the list
    while current.next:
        current = current.next
        length += 1
    # make it circular
    current.next = head
    k = k % length
    # rotate until length-k
    for i in range(length - k):
        current = current.next
    head = current.next
    current.next = None
    return head

"""
Given a linked list, swap every two adjacent nodes
and return its head.

For example,
Given 1->2->3->4, you should return the list as 2->1->4->3.

Your algorithm should use only constant space.
You may not modify the values in the list,
only nodes itself can be changed.
"""


class Node(object):
    def __init__(self, x):
        self.val = x
        self.next = None


def swap_pairs(head):
    if not head:
        return head
    start = Node(0)
    start.next = head
    current = start
    while current.next and current.next.next:
        first = current.next
        second = current.next.next
        first.next = second.next
        current.next = second
        current.next.next = first
        current = current.next.next
    return start.next