Unordered lists with different indentation

• aaa
  • bbb
    • ccc
      • ddd
      • eee
    • fff
  • ggg
• hhh

Mixed lists with different indentation

1. aaa
   • bbb
     1. ccc
        • ddd
          1. eee
          2. test
        • fff
     2. ggg
   • hhh
2. iii

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Margins before/after list

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• Test 1
• Test 2
• Test 3

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• Test 1
  • Test 2
    • Test 3

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~ Someone

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$$S_n(x)=\sum_{k=1}^n \frac{\sin(kx)}{k} \gt 0\quad (n\geq 1,\quad 0 \lt x \lt \pi)$$

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def sum(a, b):
    c = a + b
    return c

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Multicolumn overflow

Large code base

# Knuth-Morris-Pratt (KMP) Algorithm for Pattern Matching
 
# Function to create the Longest Prefix Suffix (LPS) array
def compute_lps_array(pattern):
    length = 0  # length of the previous longest prefix suffix
    lps = [0] * len(pattern)  # lps[i] is the length of the longest prefix suffix of pattern[0...i]
    i = 1  # Start from the second character of the pattern
 
    # Loop to calculate lps[i] for i = 1 to len(pattern) - 1
    while i < len(pattern):
        if pattern[i] == pattern[length]:
            length += 1
            lps[i] = length
            i += 1
        else:
            if length != 0:
                length = lps[length - 1]
            else:
                lps[i] = 0
                i += 1
    return lps
 
# Function implementing the KMP algorithm
def kmp_search(text, pattern):
    # Get the length of text and pattern
    n = len(text)
    m = len(pattern)
 
    # Preprocess the pattern to compute the lps array
    lps = compute_lps_array(pattern)
 
    i = 0  # index for text[]
    j = 0  # index for pattern[]
 
    # List to store the starting indices of pattern matches
    match_positions = []
 
    while i < n:
        if pattern[j] == text[i]:
            i += 1
            j += 1
 
        if j == m:
            # Pattern found, record the starting index
            match_positions.append(i - j)
            j = lps[j - 1]  # Reset j using the lps array
 
        elif i < n and pattern[j] != text[i]:
            # Mismatch after j matches
            if j != 0:
                j = lps[j - 1]
            else:
                i += 1
 
    return match_positions
 
# Example usage
if __name__ == "__main__":
    text = "ababcabcabababd"
    pattern = "ababd"
 
    result = kmp_search(text, pattern)
 
    if result:
        print(f"Pattern found at indices: {result}")
    else:
        print("Pattern not found in the text.")
# Knuth-Morris-Pratt (KMP) Algorithm for Pattern Matching
 
# Function to create the Longest Prefix Suffix (LPS) array
def compute_lps_array(pattern):
    length = 0  # length of the previous longest prefix suffix
    lps = [0] * len(pattern)  # lps[i] is the length of the longest prefix suffix of pattern[0...i]
    i = 1  # Start from the second character of the pattern
 
    # Loop to calculate lps[i] for i = 1 to len(pattern) - 1
    while i < len(pattern):
        if pattern[i] == pattern[length]:
            length += 1
            lps[i] = length
            i += 1
        else:
            if length != 0:
                length = lps[length - 1]
            else:
                lps[i] = 0
                i += 1
    return lps
 
# Function implementing the KMP algorithm
def kmp_search(text, pattern):
    # Get the length of text and pattern
    n = len(text)
    m = len(pattern)
 
    # Preprocess the pattern to compute the lps array
    lps = compute_lps_array(pattern)
 
    i = 0  # index for text[]
    j = 0  # index for pattern[]
 
    # List to store the starting indices of pattern matches
    match_positions = []
 
    while i < n:
        if pattern[j] == text[i]:
            i += 1
            j += 1
 
        if j == m:
            # Pattern found, record the starting index
            match_positions.append(i - j)
            j = lps[j - 1]  # Reset j using the lps array
 
        elif i < n and pattern[j] != text[i]:
            # Mismatch after j matches
            if j != 0:
                j = lps[j - 1]
            else:
                i += 1
 
    return match_positions
 
# Example usage
if __name__ == "__main__":
    text = "ababcabcabababd"
    pattern = "ababd"
 
    result = kmp_search(text, pattern)
 
    if result:
        print(f"Pattern found at indices: {result}")
    else:
        print("Pattern not found in the text.")
# Knuth-Morris-Pratt (KMP) Algorithm for Pattern Matching
 
# Function to create the Longest Prefix Suffix (LPS) array
def compute_lps_array(pattern):
    length = 0  # length of the previous longest prefix suffix
    lps = [0] * len(pattern)  # lps[i] is the length of the longest prefix suffix of pattern[0...i]
    i = 1  # Start from the second character of the pattern
 
    # Loop to calculate lps[i] for i = 1 to len(pattern) - 1
    while i < len(pattern):
        if pattern[i] == pattern[length]:
            length += 1
            lps[i] = length
            i += 1
        else:
            if length != 0:
                length = lps[length - 1]
            else:
                lps[i] = 0
                i += 1
    return lps
 
# Function implementing the KMP algorithm
def kmp_search(text, pattern):
    # Get the length of text and pattern
    n = len(text)
    m = len(pattern)
 
    # Preprocess the pattern to compute the lps array
    lps = compute_lps_array(pattern)
 
    i = 0  # index for text[]
    j = 0  # index for pattern[]
 
    # List to store the starting indices of pattern matches
    match_positions = []
 
    while i < n:
        if pattern[j] == text[i]:
            i += 1
            j += 1
 
        if j == m:
            # Pattern found, record the starting index
            match_positions.append(i - j)
            j = lps[j - 1]  # Reset j using the lps array
 
        elif i < n and pattern[j] != text[i]:
            # Mismatch after j matches
            if j != 0:
                j = lps[j - 1]
            else:
                i += 1
 
    return match_positions
 
# Example usage
if __name__ == "__main__":
    text = "ababcabcabababd"
    pattern = "ababd"
 
    result = kmp_search(text, pattern)
 
    if result:
        print(f"Pattern found at indices: {result}")
    else:
        print("Pattern not found in the text.")

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