Changed saving and loading function so the logs can be saved as valid JSON objects

Author: Fdms-3741

bayes_opt/logger.py

@@ -298,7 +298,15 @@ def update(self, event: str, instance: BayesianOptimization) -> None:
             if "constraint" in data and isinstance(data["constraint"], np.ndarray):
                 data["constraint"] = data["constraint"].tolist()
 
-            with self._path.open("a") as f:
-                f.write(json.dumps(data) + "\n")
+            # Read current data
+            with self._path.open("r") as f:
+                fileData = json.load(f)
+
+            # Append next data point
+            fileData.append(data)
+
+            # Writes content back to a file
+            with self._path.open("w") as f:
+                json.dumps(fileData)
 
         self._update_tracker(event, instance)

bayes_opt/util.py

@@ -39,22 +39,22 @@ def load_logs(
         logs = [logs]
 
     for log in logs:
-        with Path(log).open("r") as j:
-            while True:
-                try:
-                    iteration = next(j)
-                except StopIteration:
-                    break
-
-                iteration = json.loads(iteration)
-                try:
-                    optimizer.register(
-                        params=iteration["params"],
-                        target=iteration["target"],
-                        constraint_value=(iteration["constraint"] if optimizer.is_constrained else None),
-                    )
-                except NotUniqueError:
-                    continue
+        try:
+            with Path(log).open("r") as fil:
+                fileData = json.load(fil)
+        except json.JSONDecodeError:
+            print(f"ERROR: JSON decode error when decoding '{log}'")
+            continue
+
+        for iteration in fileData:
+            try:
+                optimizer.register(
+                    params=iteration["params"],
+                    target=iteration["target"],
+                    constraint_value=(iteration["constraint"] if optimizer.is_constrained else None),
+                )
+            except NotUniqueError:
+                continue
 
     return optimizer