Duplicates and Special Characters

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from typing import TypeVar
from collections import Counter
 
T = TypeVar('T')
 
 
# ============================================
# SEARCH WITH DUPLICATES
# ============================================
 
def find_first_occurrence(arr: list[int], target: int) -> int:
    """
    Find first occurrence of target in sorted array with duplicates.
    """
    left, right = 0, len(arr) - 1
    result = -1
    
    while left <= right:
        mid = left + (right - left) // 2
        
        if arr[mid] == target:
            result = mid      # Record this, but keep searching left
            right = mid - 1
        elif arr[mid] < target:
            left = mid + 1
        else:
            right = mid - 1
    
    return result
 
 
def find_last_occurrence(arr: list[int], target: int) -> int:
    """
    Find last occurrence of target in sorted array with duplicates.
    """
    left, right = 0, len(arr) - 1
    result = -1
    
    while left <= right:
        mid = left + (right - left) // 2
        
        if arr[mid] == target:
            result = mid      # Record this, but keep searching right
            left = mid + 1
        elif arr[mid] < target:
            left = mid + 1
        else:
            right = mid - 1
    
    return result
 
 
def count_occurrences(arr: list[int], target: int) -> int:
    """
    Count occurrences of target in sorted array.
    Uses first and last occurrence to compute count.
    """
    first = find_first_occurrence(arr, target)
    if first == -1:
        return 0
    last = find_last_occurrence(arr, target)
    return last - first + 1
 
 
# ============================================
# REMOVAL WITH DUPLICATES  
# ============================================
 
def remove_first_occurrence(arr: list[T], value: T) -> list[T]:
    """Remove first occurrence of value."""
    for i, item in enumerate(arr):
        if item == value:
            return arr[:i] + arr[i+1:]
    return arr[:]  # Not found, return copy
 
 
def remove_last_occurrence(arr: list[T], value: T) -> list[T]:
    """Remove last occurrence of value."""
    for i in range(len(arr) - 1, -1, -1):
        if arr[i] == value:
            return arr[:i] + arr[i+1:]
    return arr[:]
 
 
def remove_all_occurrences(arr: list[T], value: T) -> list[T]:
    """Remove all occurrences of value."""
    return [item for item in arr if item != value]
 
 
def remove_duplicates_sorted(arr: list[int]) -> list[int]:
    """
    Remove duplicates from sorted array, keeping one of each.
    Modifies in place and returns new length.
    
    Standard LeetCode problem approach.
    """
    if not arr:
        return []
    
    if len(arr) == 1:
        return arr[:]
    
    write_index = 1
    
    for read_index in range(1, len(arr)):
        if arr[read_index] != arr[read_index - 1]:
            arr[write_index] = arr[read_index]
            write_index += 1
    
    return arr[:write_index]
 
 
# ============================================
# DUPLICATE DETECTION AND COUNTING
# ============================================
 
def has_duplicates(arr: list[T]) -> bool:
    """Check if array contains any duplicates."""
    return len(arr) != len(set(arr))
 
 
def find_duplicates(arr: list[int]) -> list[int]:
    """
    Find all duplicate values (appear more than once).
    Returns list of duplicated values (each appears once in result).
    """
    counts = Counter(arr)
    return [val for val, count in counts.items() if count > 1]
 
 
def find_all_duplicate_indices(arr: list[T], value: T) -> list[int]:
    """Find all indices where value appears."""
    return [i for i, item in enumerate(arr) if item == value]
 
 
# ============================================
# HANDLING DUPLICATES IN SPECIFIC PROBLEMS
# ============================================
 
def two_sum_with_duplicates(nums: list[int], target: int) -> list[tuple[int, int]]:
    """
    Find ALL pairs of indices that sum to target.
    Handles duplicates correctly.
    """
    from collections import defaultdict
    
    # Map value to list of indices
    value_indices = defaultdict(list)
    for i, num in enumerate(nums):
        value_indices[num].append(i)
    
    result = []
    seen_pairs = set()  # Avoid duplicate pairs
    
    for i, num in enumerate(nums):
        complement = target - num
        
        if complement in value_indices:
            for j in value_indices[complement]:
                if i < j:  # Ensure unique pairs with i < j
                    pair = (i, j)
                    if pair not in seen_pairs:
                        seen_pairs.add(pair)
                        result.append(pair)
    
    return result
 
 
def three_way_partition(arr: list[int], pivot: int) -> list[int]:
    """
    Dutch National Flag algorithm: partition into <pivot, =pivot, >pivot.
    Crucial for efficient QuickSort with many duplicates.
    """
    low = 0           # Boundary of < section
    mid = 0           # Current element
    high = len(arr) - 1  # Boundary of > section
    
    while mid <= high:
        if arr[mid] < pivot:
            arr[low], arr[mid] = arr[mid], arr[low]
            low += 1
            mid += 1
        elif arr[mid] > pivot:
            arr[mid], arr[high] = arr[high], arr[mid]
            high -= 1
            # Don't increment mid - swapped element needs checking
        else:  # arr[mid] == pivot
            mid += 1
    
    return arr

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from collections import defaultdict, Counter
from typing import Callable, TypeVar
 
T = TypeVar('T')
K = TypeVar('K')
 
 
# ============================================
# PATTERN: Group by Key with Duplicates
# ============================================
 
def group_anagrams(strs: list[str]) -> list[list[str]]:
    """
    Group strings that are anagrams.
    Demonstrates grouping with potential duplicates.
    
    Edge cases:
    - Duplicate strings: grouped together
    - Empty string: valid, forms its own group
    """
    groups = defaultdict(list)
    
    for s in strs:
        # Key = sorted characters (anagram signature)
        key = tuple(sorted(s))
        groups[key].append(s)  # Duplicates allowed in list
    
    return list(groups.values())
 
 
# ============================================
# PATTERN: First/Last with Duplicates
# ============================================
 
def first_unique_character(s: str) -> int:
    """
    Find index of first character that appears only once.
    
    Edge cases:
    - All duplicates: return -1
    - All unique: return 0
    - Duplicate characters interspersed with unique
    """
    char_count = Counter(s)
    
    for i, char in enumerate(s):
        if char_count[char] == 1:
            return i
    
    return -1  # All characters are duplicates
 
 
def last_unique_character(s: str) -> int:
    """Find index of last character that appears only once."""
    char_count = Counter(s)
    
    for i in range(len(s) - 1, -1, -1):
        if char_count[s[i]] == 1:
            return i
    
    return -1
 
 
# ============================================
# PATTERN: Frequency-Based Operations
# ============================================
 
def top_k_frequent(nums: list[int], k: int) -> list[int]:
    """
    Return k most frequent elements.
    
    Edge case: Ties in frequency - which k to return?
    This implementation returns any valid k.
    """
    if k <= 0:
        return []
    
    counts = Counter(nums)
    
    # Sort by frequency (descending), then by value for consistency
    sorted_items = sorted(
        counts.items(),
        key=lambda x: (-x[1], x[0])
    )
    
    return [item[0] for item in sorted_items[:k]]
 
 
def find_majority_element(nums: list[int]) -> int | None:
    """
    Find element that appears more than n/2 times.
    Returns None if no majority exists.
    
    Uses Boyer-Moore Voting Algorithm.
    """
    if not nums:
        return None
    
    # Find candidate
    candidate = nums[0]
    count = 1
    
    for i in range(1, len(nums)):
        if count == 0:
            candidate = nums[i]
            count = 1
        elif nums[i] == candidate:
            count += 1
        else:
            count -= 1
    
    # Verify candidate is actually majority
    actual_count = sum(1 for num in nums if num == candidate)
    if actual_count > len(nums) // 2:
        return candidate
    
    return None
 
 
# ============================================
# PATTERN: Set Operations with Duplicates (Multiset)
# ============================================
 
def intersection_with_duplicates(nums1: list[int], nums2: list[int]) -> list[int]:
    """
    Intersection of two arrays, including duplicate handling.
    If element appears k1 times in nums1 and k2 times in nums2,
    it appears min(k1, k2) times in result.
    """
    counts1 = Counter(nums1)
    counts2 = Counter(nums2)
    
    result = []
    for num in counts1:
        if num in counts2:
            # Include min of the two counts
            for _ in range(min(counts1[num], counts2[num])):
                result.append(num)
    
    return result
 
 
def union_with_duplicates(nums1: list[int], nums2: list[int]) -> list[int]:
    """
    Union of two arrays with duplicates.
    Element appears max(count1, count2) times.
    """
    counts1 = Counter(nums1)
    counts2 = Counter(nums2)
    
    # Combine all keys
    all_keys = set(counts1.keys()) | set(counts2.keys())
    
    result = []
    for num in all_keys:
        count = max(counts1.get(num, 0), counts2.get(num, 0))
        result.extend([num] * count)
    
    return result

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import unicodedata
import re
 
 
# ============================================
# WHITESPACE HANDLING
# ============================================
 
def normalize_whitespace(s: str) -> str:
    """
    Normalize all whitespace: trim ends, collapse internal spaces.
    
    Handles: spaces, tabs, newlines, multiple spaces
    """
    if not s:
        return ""
    
    # Replace all whitespace with single space, then trim
    return " ".join(s.split())
 
 
def is_blank(s: str) -> bool:
    """
    Check if string is empty or contains only whitespace.
    """
    return not s or s.isspace()
 
 
def split_lines_universal(text: str) -> list[str]:
    """
    Split text into lines, handling all newline conventions.
    Handles: 
 (Unix), \r
 (Windows), \r (old Mac)
    """
    # splitlines() handles all conventions
    return text.splitlines()
 
 
# ============================================
# CASE NORMALIZATION
# ============================================
 
def case_insensitive_compare(s1: str, s2: str) -> bool:
    """
    Case-insensitive comparison.
    
    Note: casefold() is better than lower() for international text.
    Example: German 'ß' casefolds to 'ss'
    """
    return s1.casefold() == s2.casefold()
 
 
def case_insensitive_find(text: str, pattern: str) -> int:
    """
    Case-insensitive search.
    """
    return text.casefold().find(pattern.casefold())
 
 
# ============================================
# UNICODE HANDLING
# ============================================
 
def normalize_unicode(s: str, form: str = 'NFC') -> str:
    """
    Normalize Unicode string.
    
    Forms:
    - NFC: Canonical Decomposition, followed by Canonical Composition
    - NFD: Canonical Decomposition
    - NFKC: Compatibility Decomposition, followed by Canonical Composition
    - NFKD: Compatibility Decomposition
    
    Example: 'café' can be 'cafe\u0301' (e + combining accent)
    or 'caf\xe9' (é as single character). NFC makes them the same.
    """
    return unicodedata.normalize(form, s)
 
 
def remove_accents(s: str) -> str:
    """
    Remove accents/diacritics from characters.
    'café' → 'cafe'
    """
    # Decompose to base + combining characters
    decomposed = unicodedata.normalize('NFD', s)
    # Keep only non-combining characters
    return ''.join(
        char for char in decomposed
        if unicodedata.category(char) != 'Mn'  # Mn = Mark, Nonspacing
    )
 
 
def string_length_unicode_aware(s: str) -> int:
    """
    Get visual length (grapheme clusters) not code units.
    
    'café' = 4 graphemes (might be 5 code points with combining accent)
    'Hello 👋' = 7 graphemes (emoji is 1 grapheme, might be 2+ code units)
    """
    # For precise grapheme counting, use regex or third-party library
    # This is an approximation
    import regex  # pip install regex (more Unicode-aware than re)
    return len(regex.findall(r'\X', s))
 
 
# ============================================
# ALPHANUMERIC EXTRACTION
# ============================================
 
def extract_alphanumeric(s: str) -> str:
    """
    Extract only alphanumeric characters.
    Useful for palindrome checking, normalization.
    """
    return ''.join(char for char in s if char.isalnum())
 
 
def is_palindrome_ignoring_non_alphanumeric(s: str) -> bool:
    """
    Check if string is palindrome, ignoring non-alphanumerics and case.
    
    "A man, a plan, a canal: Panama" → True
    """
    cleaned = extract_alphanumeric(s).lower()
    return cleaned == cleaned[::-1]
 
 
# ============================================
# CONTROL CHARACTER HANDLING
# ============================================
 
def remove_control_characters(s: str) -> str:
    """
    Remove control characters (except whitespace).
    Control characters can break display and processing.
    """
    return ''.join(
        char for char in s
        if unicodedata.category(char) not in ('Cc', 'Cf')
        or char in '\t
\r'  # Keep common whitespace
    )
 
 
def escape_for_display(s: str) -> str:
    """
    Escape control characters for safe display.
    """
    result = []
    for char in s:
        if char == '
':
            result.append('
')
        elif char == '\r':
            result.append('\\r')
        elif char == '\t':
            result.append('\\t')
        elif ord(char) < 32 or ord(char) == 127:
            result.append(f'\\x{ord(char):02x}')
        else:
            result.append(char)
    return ''.join(result)
 
 
# ============================================
# STRING VALIDATION
# ============================================
 
def is_valid_identifier(s: str) -> bool:
    """
    Check if string is a valid programming identifier.
    Starts with letter/underscore, contains only alphanum/underscore.
    """
    if not s:
        return False
    
    if not (s[0].isalpha() or s[0] == '_'):
        return False
    
    return all(c.isalnum() or c == '_' for c in s)
 
 
def sanitize_filename(filename: str) -> str:
    """
    Sanitize string for use as filename.
    Removes/replaces characters invalid in file systems.
    """
    # Characters not allowed in Windows filenames
    invalid_chars = r'[<>:"/\\|?*]'
    
    # Replace invalid characters with underscore
    sanitized = re.sub(invalid_chars, '_', filename)
    
    # Remove control characters
    sanitized = remove_control_characters(sanitized)
    
    # Remove leading/trailing whitespace and dots
    sanitized = sanitized.strip(' .')
    
    # Ensure non-empty
    return sanitized or 'unnamed'

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# ============================================
# SUBSTRING EDGE CASES
# ============================================
 
def find_all_substrings(text: str, pattern: str) -> list[int]:
    """
    Find all occurrences of pattern in text.
    
    Edge cases:
    - Empty pattern: Every position is a match? Or invalid?
    - Pattern longer than text: No matches
    - Overlapping matches: "aaa" in "aaaa" has indices [0, 1]
    """
    if not pattern:
        return []  # Or raise ValueError("Empty pattern")
    
    if len(pattern) > len(text):
        return []
    
    indices = []
    start = 0
    
    while True:
        pos = text.find(pattern, start)
        if pos == -1:
            break
        indices.append(pos)
        start = pos + 1  # Allow overlapping matches
    
    return indices
 
 
def longest_substring_without_repeating(s: str) -> str:
    """
    Find longest substring with all unique characters.
    
    Edge cases:
    - Empty string: Return ""
    - Single character: Return that character
    - All same characters: Return any single character
    - All unique: Return entire string
    """
    if not s:
        return ""
    
    char_index = {}
    start = 0
    max_len = 0
    max_start = 0
    
    for end, char in enumerate(s):
        if char in char_index and char_index[char] >= start:
            start = char_index[char] + 1
        
        char_index[char] = end
        
        if end - start + 1 > max_len:
            max_len = end - start + 1
            max_start = start
    
    return s[max_start:max_start + max_len]
 
 
def count_substrings(text: str, pattern: str, overlap: bool = True) -> int:
    """
    Count occurrences of pattern in text.
    
    Edge cases:
    - Empty pattern: undefined behavior
    - overlap=True: "aa" in "aaa" → 2
    - overlap=False: "aa" in "aaa" → 1
    """
    if not pattern:
        return 0
    
    count = 0
    start = 0
    
    while True:
        pos = text.find(pattern, start)
        if pos == -1:
            break
        count += 1
        start = pos + (1 if overlap else len(pattern))
    
    return count
 
 
# ============================================
# ANAGRAM AND PERMUTATION EDGE CASES
# ============================================
 
def are_anagrams(s1: str, s2: str, case_sensitive: bool = True) -> bool:
    """
    Check if two strings are anagrams.
    
    Edge cases:
    - Empty strings: Two empty strings ARE anagrams
    - Different lengths: Cannot be anagrams
    - Spaces: Should spaces count? Depends on requirements
    - Case: 'Listen' vs 'Silent' - depends on case_sensitive
    """
    from collections import Counter
    
    # Length check first (optimization)
    if len(s1) != len(s2):
        return False
    
    if not case_sensitive:
        s1 = s1.lower()
        s2 = s2.lower()
    
    return Counter(s1) == Counter(s2)
 
 
def find_anagrams_in_text(text: str, pattern: str) -> list[int]:
    """
    Find starting indices of all anagram occurrences of pattern in text.
    Uses sliding window with character frequency counting.
    
    Edge cases:
    - Empty pattern: Return []
    - Pattern longer than text: Return []
    - Single character pattern: Every occurrence
    """
    from collections import Counter
    
    if not pattern or len(pattern) > len(text):
        return []
    
    pattern_count = Counter(pattern)
    window_count = Counter()
    result = []
    k = len(pattern)
    
    for i, char in enumerate(text):
        # Add new character to window
        window_count[char] += 1
        
        # Remove character that fell out of window
        if i >= k:
            left_char = text[i - k]
            window_count[left_char] -= 1
            if window_count[left_char] == 0:
                del window_count[left_char]
        
        # Check for anagram match
        if i >= k - 1 and window_count == pattern_count:
            result.append(i - k + 1)
    
    return result
 
 
# ============================================
# PALINDROME EDGE CASES
# ============================================
 
def longest_palindromic_substring(s: str) -> str:
    """
    Find longest palindromic substring.
    
    Edge cases:
    - Empty string: Return ""
    - Single character: Return that character
    - All same characters: Return entire string
    - No palindrome longer than 1: Return first character
    """
    if not s:
        return ""
    
    if len(s) == 1:
        return s
    
    start = 0
    max_len = 1
    
    def expand_around_center(left: int, right: int) -> tuple[int, int]:
        while left >= 0 and right < len(s) and s[left] == s[right]:
            left -= 1
            right += 1
        return left + 1, right - left - 1  # Return start and length
    
    for i in range(len(s)):
        # Odd length palindromes
        left1, len1 = expand_around_center(i, i)
        if len1 > max_len:
            start = left1
            max_len = len1
        
        # Even length palindromes
        if i + 1 < len(s):
            left2, len2 = expand_around_center(i, i + 1)
            if len2 > max_len:
                start = left2
                max_len = len2
    
    return s[start:start + max_len]
 
 
def count_palindromic_substrings(s: str) -> int:
    """
    Count total number of palindromic substrings.
    
    Edge cases:
    - Empty string: 0 palindromes
    - Single character: 1 palindrome (itself)
    - All same: n(n+1)/2 palindromes (every substring)
    """
    if not s:
        return 0
    
    count = 0
    
    for i in range(len(s)):
        # Odd length
        left, right = i, i
        while left >= 0 and right < len(s) and s[left] == s[right]:
            count += 1
            left -= 1
            right += 1
        
        # Even length
        left, right = i, i + 1
        while left >= 0 and right < len(s) and s[left] == s[right]:
            count += 1
            left -= 1
            right += 1
    
    return count

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def generate_duplicate_test_cases(base_values: list) -> list[list]:
    """
    Generate comprehensive duplicate test cases from base values.
    """
    test_cases = []
    
    if not base_values:
        return test_cases
    
    # All unique
    test_cases.append(list(base_values))
    
    # All same (first element)
    test_cases.append([base_values[0]] * len(base_values))
    
    # Pair duplicated at start
    if len(base_values) >= 2:
        case = list(base_values)
        case[1] = case[0]
        test_cases.append(case)
    
    # Pair duplicated at end
    if len(base_values) >= 2:
        case = list(base_values)
        case[-1] = case[-2]
        test_cases.append(case)
    
    # First and last are same
    if len(base_values) >= 2:
        case = list(base_values)
        case[-1] = case[0]
        test_cases.append(case)
    
    # All same except middle
    if len(base_values) >= 3:
        mid = len(base_values) // 2
        case = [base_values[0]] * len(base_values)
        case[mid] = base_values[1] if len(base_values) > 1 else base_values[0] + 1
        test_cases.append(case)
    
    return test_cases
 
 
def generate_string_edge_cases() -> list[str]:
    """
    Generate comprehensive string edge case test cases.
    """
    return [
        "",                          # Empty
        " ",                         # Single space
        "   ",                       # Multiple spaces
        "\t",                        # Tab
        "
",                        # Newline
        "\r
",                      # Windows newline
        "a",                         # Single char
        "A",                         # Single uppercase
        "1",                         # Single digit
        "hello",                     # Simple lowercase
        "HELLO",                     # Simple uppercase
        "Hello World",               # Mixed case with space
        "  hello  ",                 # Leading/trailing spaces
        "hello
world",              # Internal newline
        "hello\tworld",              # Internal tab
        "café",                      # Accented characters
        "naïve",                     # More accents
        "Hello 👋",                  # Emoji
        "你好",                       # Chinese
        "مرحبا",                     # Arabic (RTL)
        "hello123",                  # Alphanumeric
        "123hello",                  # Number prefix
        "12345",                     # Only digits
        "!@#$%",                     # Only special chars
        "hello, world!",             # Punctuation
        "a" * 1000,                  # Long string same char
        "".join(chr(i) for i in range(32, 127)),  # All printable ASCII
    ]
 
 
def test_string_function(func, test_cases: list[str] = None):
    """
    Test a string function with comprehensive edge cases.
    """
    if test_cases is None:
        test_cases = generate_string_edge_cases()
    
    results = []
    for test in test_cases:
        try:
            result = func(test)
            results.append({
                'input': repr(test),
                'output': repr(result),
                'error': None
            })
        except Exception as e:
            results.append({
                'input': repr(test),
                'output': None,
                'error': str(e)
            })
    
    return results