feat: Add train/val split script and update gitignore

- Added 03_train_val_split.py to create deterministic train/validation splits from data.txt or fallback text
- Updated .gitignore to un-comment .vscode/ directory exclusion
- Changed data.txt pattern to *.txt for better file matching in gitignore
- Script handles UTF-8 text loading with newline normalization and writes train.txt/val.txt files
- Includes doctest examples and proper type hints

03_train_val_split.py

@@ -0,0 +1,79 @@
+# 03_train_val_split.py
+"""
+Create a train/val split from data.txt or a small fallback, and save to disk.
+
+What it does:
+- Loads UTF-8 text, normalizes newlines to "\\n".
+- Splits by character index (default 90/10) deterministically.
+- Writes 'train.txt' and 'val.txt'
+
+How to run:
+    python 03_train_val_split.py
+    # optional:
+    python -m doctest -v 03_train_val_split.py
+
+Notes:
+- Keep 'data.txt' next to this script. If it's missing, small fallback is used
+"""
+
+from __future__ import annotations
+from pathlib import Path
+from typing import Tuple
+
+FALLBACK = "abcdefg\nhijklmn\nopqrst\nuvwx\nyz\n"
+
+
+def load_and_normalize(path: Path) -> str:
+    """Load text from path if it exists; else use FALLBACK. Normalize to LF.
+
+    Args:
+        path: Path to 'data.txt'.
+
+    Returns:
+        Text with only '\\n' line endings.
+
+    >>> load_and_normalize.__doc__ is not None
+    True
+    """
+    text = path.read_text(encoding="utf-8") if path.exists() else FALLBACK
+    return text.replace("\r\n", "\n").replace("\r", "\n")
+
+
+def split_indices(n: int, train_ratio: float = 0.9) -> Tuple[int, int]:
+    """Return (train_end, val_start) indices for a 1D split of length n.
+
+    Args:
+        n: Total number of characters.
+        train_ratio: Fraction for train portion (0.0 < train_ratio < 1.0)
+
+    Returns:
+        (train_end, val_start) where val_start == train_end.
+
+    >>> split_indices(100, 0.8)
+    (80, 80)
+    >>> split_indices(5, 0.6)
+    (3, 3)
+    """
+    assert 0.0 < train_ratio < 1.0, "train_ratio must be between 0 and 1"
+    train_end = int(n * train_ratio)
+    return train_end, train_end
+
+
+def main() -> None:
+    data_path = Path("data.txt")
+    text = load_and_normalize(data_path)
+    n = len(text)
+    tr_end, va_start = split_indices(n, 0.9)
+    train, val = text[:tr_end], text[va_start:]
+
+    Path("train.txt").write_text(train, encoding="utf-8")
+    Path("val.txt").write_text(val, encoding="utf-8")
+
+    print(f"Total chars: {n}")
+    print(f"Train chars: {len(train)}")
+    print(f"Val chars: {len(val)}")
+    print("Wrote train.txt and val.txt")
+
+
+if __name__ == "__main__":
+    main()