Revert "Restructure {reasoning_gym, tests}/{core, exercises, curricula}"

This reverts commit 10dbb374b0.

reasoning_gym/arithmetic/prime_factorization.py

@@ -0,0 +1,69 @@
+"""Prime factorization task generator"""
+
+from dataclasses import dataclass
+from random import Random
+from typing import List, Optional, Tuple
+
+from ..factory import ProceduralDataset, register_dataset
+
+
+@dataclass
+class PrimeFactorizationConfig:
+    """Configuration for prime factorization task generation"""
+
+    min_value: int = 2  # Minimum number to factorize
+    max_value: int = 1000  # Maximum number to factorize
+    seed: Optional[int] = None
+    size: int = 500  # Virtual dataset size
+
+    def validate(self) -> None:
+        """Validate configuration parameters"""
+        assert self.min_value >= 2, "min_value must be >= 2"
+        assert self.max_value >= self.min_value, "max_value must be >= min_value"
+
+
+class PrimeFactorizationDataset(ProceduralDataset):
+    """Generates prime factorization tasks"""
+
+    def __init__(self, config: PrimeFactorizationConfig):
+        super().__init__(config=config, seed=config.seed, size=config.size)
+
+    def _prime_factors(self, n: int) -> List[int]:
+        """Compute prime factors of a number"""
+        factors = []
+        d = 2
+        while n > 1:
+            while n % d == 0:
+                factors.append(d)
+                n //= d
+            d += 1
+            if d * d > n:
+                if n > 1:
+                    factors.append(n)
+                break
+        return factors
+
+    def __getitem__(self, idx: int) -> dict:
+        """Generate a single prime factorization task"""
+        rng = Random(self.seed + idx)
+
+        # Generate random number to factorize
+        number = rng.randint(self.config.min_value, self.config.max_value)
+
+        # Calculate prime factors
+        factors = self._prime_factors(number)
+
+        # Format answer as multiplication of prime factors
+        answer = " × ".join(map(str, factors))
+
+        return {
+            "question": (
+                f"Find the prime factorization of {number}. Write the factors separated by × "
+                f"(Example: for 12 the answer would be: 2 × 2 × 3)"
+            ),
+            "answer": answer,
+            "metadata": {"number": number, "factors": factors},
+        }
+
+
+register_dataset("prime_factorization", PrimeFactorizationDataset, PrimeFactorizationConfig)