This project has been created as part of the 42 curriculum by dporhomo.

🐍 Exam 03 — Pythonic Refactors

A comprehensive masterclass transitioning from imperative C-style memory management to highly optimized, idiomatic modern Python.

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📌 Overview

This repository contains pure Python refactors of the standard Exam Rank 03 exercises. Successfully completed on April 28, 2026, this collection demonstrates how imperative C paradigms—such as double pointers, manual memory allocation (malloc/free), null-terminated buffers, and accumulator loops—translate into highly optimized, clean, and modern Python 3.13 code.

Every solution is strictly typed, heavily optimized for time/space complexity, and entirely compliant with Flake8 linting standards.

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📂 Repository Structure & Solutions

Exercise	Description	Key Pythonic Upgrades
ft_atoi_base.py	Base-N string to decimal conversion	int(s, base) standard fallback handling
ft_list_size.py	Linked list node counting	Class wrappers, Optional/Union type hinting
ft_range.py	Dynamic array allocation	Inclusive stepping (end + step), inline ternaries
ft_rrange.py	Native reversed array allocation	$O(1)$ space allocation avoiding [::-1] duplicate buffers
hidenp.py	Subsequence character matching	Stateful iterators (iter()) + short-circuiting all()
lcm.py	Lowest Common Multiple	Euclidean GCD formula unpacking, optimized manual looping
paramsum.py	Argument parsing	Native sys.argv off-by-one slicing
pgcd.py	Greatest Common Divisor	Instant Euclidean modulo swapping (a, b = b, a % b)
print_hex.py	Decimal to base-16 output	Formatted f-strings (f"{val:x}")
rstr_capitalizer.py	Strict whitespace-aware capitalization	enumerate() lookaheads, zero-destructive parsing
tab_mult.py	Multiplication tables	range() sequences + inline formatted f-strings
fprime.py	Ascending prime factorization	Generators (yield), lazy memory snapshots, *.join()
ft_itoa.py	Integer to string conversion	Arbitrary precision handling (INT_MIN safe), C-level str()
ft_list_foreach.py	Higher-order mapping	First-class Callables, lambda anonymous operations
ft_list_remove_if.py	Conditional node deletion	Sentinel/Dummy Node pattern, automatic garbage collection
ft_split.py	Whitespace delimiter parsing	Stateful generators, zero-argument .split() whitespace sweeps
ft_strmapi.py	Character-by-character mapping	Immutable generator expressions + chr()/ord() ASCII math
lst_all_full.py	Comprehensive List Capstone	Full suite (insertion, sentinel deletion, tuple-unpack bubble sort)
rev_wstr.py	Word sequence reversal	Slicing arrays, zero-allocation manual two-pointer traversal
sort_int_tab.py	In-place numeric sorting	Timsort (.sort()), Level 4 tuple unpacking swaps
sort_list.py	Linked list Gnome sort	In-place pointers, first-class Callable[[int, int], int]

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⚡ Core Architectural Paradigms

1. Advanced Iterators & Lazy Evaluation

Instead of allocating massive buffers in RAM, heavy data generation (like fprime and ft_split) utilizes Generators (yield). This freezes execution state in tiny stack frames, keeping memory footprints near zero regardless of dataset size.

2. The Death of Boilerplate

Imperative helpers (ft_atoi, ft_strcmp, ft_putnbr, ft_swap) are completely omitted. They are replaced by native containment checks (in), built-in constructors, and highly optimized C-level standard libraries (math.gcd).

3. Elegant Memory Management

• No Double Pointers (**head): Linked list mutations explicitly return the new head, mapping references cleanly to variables.
• Sentinel Nodes: Edge cases involving deleting or inserting at the absolute head are mitigated using dummy/sentinel nodes (dummy = Node(None)).
• Garbage Collection: Manual sweeps (free()) are abandoned. Dropping pointers automatically triggers Python's Garbage Collector to sweep orphaned memory.

4. Flawless Variable Swapping

Temporary swap variables are eradicated. Python's tuple unpacking safely evaluates the right-side expression entirely before updating references on the left:

# Instantly swap values or pointers in memory safely
current.data, current.next.data = current.next.data, current.data

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🚀 Execution & Usage

Ensure you are running Python 3.10+ (optimized for 3.13). Most programs accept standard system arguments:

# Run prime factorizer
python3 fprime.py 225225
# Output: 3*3*5*5*7*11*13

# Run hidden string check
python3 hidenp.py "abc" "2altrb53c.sse"
# Output: 1

# Run full linked list capstone tests
python3 lst_all_full.py

Linting Check

To confirm strict adherence to PEP 8 standards:

flake8 . --count --show-source --statistics

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