use logging code from template repo

src/image_prediction/utils/logger.py

@@ -1,5 +1,8 @@
 import logging
-
+import os
+import pathlib
+import sys
+from typing import Union
 from image_prediction.config import CONFIG
 
 
@@ -25,3 +28,37 @@ def make_logger_getter():
 
 
 get_logger = make_logger_getter()
+
+
+def setup_logger(
+    level: Union[int, str] = "DEBUG",
+    file: Union[str, pathlib.Path] = "./logs/dev.log",
+    save: bool = False
+) -> logging.Logger:
+
+    LOG_FORMAT = "%(asctime)s [%(levelname)s] - [%(filename)s -> %(funcName)s() -> %(lineno)s] : %(message)s"
+    DATE_FORMAT = "%Y-%m-%d %H:%M:%S"
+
+    logger = logging.getLogger()
+    logger.setLevel(level)
+
+    stream_handler = logging.StreamHandler(sys.stdout)
+    stream_handler_format = logging.Formatter(LOG_FORMAT, datefmt=DATE_FORMAT)
+    stream_handler.setFormatter(stream_handler_format)
+
+    logger.addHandler(stream_handler)
+
+    if save:
+        file = pathlib.Path(file).absolute()
+        path = file.parent
+
+        if not os.path.exists(path):
+            os.mkdir(path)
+
+        file_handler = logging.FileHandler(file)
+        file_handler_format = logging.Formatter(LOG_FORMAT, datefmt=DATE_FORMAT)
+        file_handler.setFormatter(file_handler_format)
+
+        logger.addHandler(file_handler)
+
+    return logger

src/serve.py

@@ -12,6 +12,7 @@ from image_prediction.locations import CONFIG_FILE, MLRUNS_DIR
 from image_prediction.pipeline import load_model, load_pipeline
 from image_prediction.utils.banner import load_banner
 from image_prediction.utils.process_wrapping import wrap_in_process
+from image_prediction.utils.logger import setup_logger
 
 PYINFRA_CONFIG = config.get_config()
 IMAGE_CONFIG = Config(CONFIG_FILE)
@@ -19,9 +20,11 @@ MODEL = load_model(MLRUNS_DIR, CONFIG)
 BUCKET = PYINFRA_CONFIG.storage_bucket
 STORAGE = get_storage(PYINFRA_CONFIG)
 
-logging.getLogger().addHandler(logging.StreamHandler())
+# logger = logging.getLogger(__name__)
-logger = logging.getLogger("main")
+# logger.addHandler(logging.StreamHandler())
-logger.setLevel(PYINFRA_CONFIG.logging_level_root)
+# logger = logging.getLogger("main")
+# logger.setLevel(PYINFRA_CONFIG.logging_level_root)
+logger = setup_logger()
 
 
 # A component of the callback (probably tensorflow) does not release allocated memory (see RED-4206).