class Solution:
def simplifyPath(self, path: str) -> str:
"""
Simplify an absolute Unix-style file path.
Parameters:
path (str): A valid absolute Unix file path which may contain redundant slashes,
'.' (current directory) or '..' (parent directory).
Returns:
str: The simplified canonical path adhering to Unix-style rules.
"""
stack = [] # Stack to keep track of the valid directory names in the path.
# Split the path by '/' to handle each directory or file component.
components = path.split('/')
for component in components:
# Skip empty components and '.' which signifies the current directory.
if component == '' or component == '.':
continue
# For '..', pop the last valid directory if there is one (if not, we're at root).
elif component == '..':
if stack:
stack.pop()
# Push valid directory or file names onto the stack.
else:
stack.append(component)
# Rebuild the simplified path by joining the stack with '/' and prefixing with a slash.
return '/' + '/'.join(stack)
Summary of Techniques and Approaches:
Stack-Based Data Structure: The solution employs a stack to manage directory names. This pattern is useful for problems involving reversal, backtracking, or tracking nested structures.
String Splitting and Iteration: By splitting the input string into components with a delimiter, it becomes straightforward to iterate over and process each token. This technique is applicable for various text parsing problems.
Condition-Based Processing: The use of conditionals to ignore irrelevant tokens (empty strings, ‘.’) or to handle special tokens (‘..’) is crucial. Such pattern recognition is a common and effective method for cleaning and normalizing data.
In-Place-like Data Construction: Instead of modifying the original string step-by-step, constructing a new valid sequence with a stack ensures clarity and efficiency. This is a frequently used approach in problems that require building an output based on filtering and modifying an input sequence.
These techniques can be applied broadly to file system path simplification, expression evaluation, or any scenario where hierarchical and sequential data processing is required.