feat(log): add SimpleLogger for terminal logging without external backends

src/experiment_logger/simple_logger.py

@@ -0,0 +1,83 @@
+"""Simple terminal logger for running without external backends.
+
+This is used for standalone package usage where WandB or TensorBoard are not desired.
+It preserves the same API as UnifiedLogger but simply prints to stdout.
+"""
+
+import logging
+from typing import Any, Dict, Optional
+
+
+class SimpleLogger:
+    """Simple logger that implements the UnifiedLogger interface via print statements."""
+
+    def __init__(
+        self,
+        run_name: str = "simple_run",
+        config: Optional[Dict[str, Any]] = None,
+        project_name: str = "none",
+        entity: Optional[str] = None,
+        base_dir: str = "runs",
+        use_wandb: bool = False,
+        save_code: bool = False,
+        log_level: int = logging.INFO,
+        _set_as_global: bool = False,
+    ):
+        self.is_interactive = True
+        self.run_name = run_name
+        self.config = config or {}
+        print(f"[INIT] SimpleLogger initialized for run: {run_name}")
+
+    def set_level(self, level: int):
+        pass
+
+    def log_non_interactive(self, msg: str, *args, **kwargs):
+        """In SimpleLogger, we just print everything as we assume interactive use."""
+        self.info(msg, *args, **kwargs)
+
+    def progress_bar(self, iterable=None, *args, **kwargs):
+        """Standard tqdm wrapper that falls back to range if tqdm is missing."""
+        try:
+            import tqdm
+
+            return tqdm.tqdm(iterable, *args, **kwargs)
+        except ImportError:
+            return iterable
+
+    def info(self, msg: str, *args, **kwargs):
+        print(f"[INFO] {msg}")
+
+    def warning(self, msg: str, *args, **kwargs):
+        print(f"[WARNING] {msg}")
+
+    def error(self, msg: str, *args, **kwargs):
+        print(f"[ERROR] {msg}")
+
+    def debug(self, msg: str, *args, **kwargs):
+        print(f"[DEBUG] {msg}")
+
+    def log(self, metrics: Dict[str, Any], step: Optional[int] = None, commit: bool = True):
+        step_str = f"Step {step}" if step is not None else "Log"
+        metric_str = ", ".join(f"{k}: {v}" for k, v in metrics.items())
+        print(f"[{step_str}] {metric_str}")
+
+    def save_checkpoint(
+        self,
+        params: Any,
+        step: int,
+        prefix: str = "checkpoint",
+        metadata: Optional[Dict[str, Any]] = None,
+    ):
+        print(f"[SAVE] Checkpoint '{prefix}' would be saved at step {step} (SimpleLogger: No-Op)")
+
+    def save_final_model(self, params: Any, metadata: Optional[Dict[str, Any]] = None):
+        print("[SAVE] Final model would be saved (SimpleLogger: No-Op)")
+
+    def finish(self):
+        print(f"[FINISH] SimpleLogger finished for run: {self.run_name}")
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        self.finish()