C++ to Python Converter
Transform complex C++ codebases to Python with AI-powered conversion. Automatically converts STL containers (vector, map, set) to Python collections, templates to generic type hints, and smart pointers to automatic memory management. Handles C++11/14/17 features including lambda expressions, range-based loops, and auto type deduction for rapid modernization.
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Issue Description
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How It Works
- Step 1: Paste your C++ source code including template definitions, STL container usage, class declarations with inheritance, and modern C++ features.
- Step 2: The AI parses C++-specific constructs like template specialization, RAII patterns, smart pointer usage (unique_ptr, shared_ptr), and namespace declarations.
- Step 3: Advanced models transform C++ complexity to Pythonic simplicity—templates become generic types, STL algorithms convert to list comprehensions, and manual memory management eliminates entirely.
- Step 4: Receive clean Python code with dataclasses, type hints from the typing module, and idiomatic patterns following PEP 8 style guidelines.
C++ vs Python: Language Comparison
| Feature | C++ | Python |
|---|---|---|
| Syntax Style | Complex, template-heavy | Simple, readable |
| Type System | Static with templates | Dynamic with optional generics |
| Memory Management | Manual/RAII with smart pointers | Automatic garbage collection |
| Concurrency | std::thread, mutexes | asyncio, threading, multiprocessing |
| Standard Library | STL (vector, map, algorithm) | Built-in list, dict, itertools |
Code Conversion Examples
Example 1: STL Containers and Algorithms
#include <iostream>
#include <vector>
#include <algorithm>
#include <string>
class Student {
public:
std::string name;
int score;
Student(std::string n, int s) : name(n), score(s) {}
};
int main() {
std::vector<Student> students = {
Student("Alice", 85),
Student("Bob", 92),
Student("Charlie", 78)
};
auto filtered = std::vector<Student>();
std::copy_if(students.begin(), students.end(),
std::back_inserter(filtered),
[](const Student& s) { return s.score > 80; });
for (const auto& student : filtered) {
std::cout << student.name << ": " << student.score << std::endl;
}
return 0;
}from dataclasses import dataclass
from typing import List
@dataclass
class Student:
name: str
score: int
if __name__ == "__main__":
students: List[Student] = [
Student("Alice", 85),
Student("Bob", 92),
Student("Charlie", 78)
]
filtered = [s for s in students if s.score > 80]
for student in filtered:
print(f"{student.name}: {student.score}")Key Changes:
C++ std::vector becomes Python's built-in list. The complex STL algorithm (std::copy_if with lambda) transforms to a simple list comprehension. C++ class constructors with initializer lists convert to Python dataclass with automatic __init__. Range-based for loops translate directly. Manual includes disappear—Python imports only what's needed.
Example 2: Templates to Generic Types
#include <iostream>
#include <memory>
template<typename T>
class Stack {
private:
std::vector<T> elements;
public:
void push(const T& element) {
elements.push_back(element);
}
T pop() {
if (elements.empty()) {
throw std::runtime_error("Stack is empty");
}
T top = elements.back();
elements.pop_back();
return top;
}
bool isEmpty() const {
return elements.empty();
}
};
int main() {
auto intStack = std::make_unique<Stack<int>>();
intStack->push(10);
intStack->push(20);
std::cout << intStack->pop() << std::endl;
}from typing import TypeVar, Generic, List
T = TypeVar('T')
class Stack(Generic[T]):
def __init__(self):
self.elements: List[T] = []
def push(self, element: T) -> None:
self.elements.append(element)
def pop(self) -> T:
if not self.elements:
raise RuntimeError("Stack is empty")
return self.elements.pop()
def is_empty(self) -> bool:
return len(self.elements) == 0
if __name__ == "__main__":
int_stack: Stack[int] = Stack()
int_stack.push(10)
int_stack.push(20)
print(int_stack.pop())Key Changes:
C++ templates become Python generics using TypeVar and Generic from the typing module. Smart pointers (std::make_unique) are unnecessary—Python handles memory automatically. Method naming converts from camelCase to snake_case. Exceptions translate directly (throw becomes raise), maintaining error handling patterns. The empty() method becomes Pythonic is_empty() with len() checks.
Frequently Asked Questions
Can I customize how templates are converted to Python generics?
The converter applies standard template-to-Generic mappings by default. Template parameters become TypeVar declarations, and template classes use Generic[T]. You can manually adjust the output to use Protocol for structural typing or remove type hints entirely for simpler code. Future versions may support configuration for typing style preferences.
Is my C++ code sent to external servers during conversion?
No. All parsing and transformation run client-side using JavaScript-based AST analyzers. Your C++ source code—whether proprietary algorithms, embedded firmware, or confidential business logic—never leaves your browser. Zero network transmission occurs, eliminating IP exposure risk.
What C++ features cannot be automatically converted?
Low-level features like inline assembly, compiler intrinsics, and hardware-specific code have no Python equivalents. Complex template metaprogramming with SFINAE or constexpr may require manual simplification. Multiple inheritance with virtual base classes needs careful review. The converter focuses on standard C++ syntax, STL usage, and common OOP patterns.