Merge branch 'linus_dev' into sentry

Author: lamhoangtung

mlchain/cli/run.py

@@ -2,6 +2,7 @@
 import click
 import importlib
 import sys
+import copy
 import GPUtil
 from mlchain import logger
 from mlchain.server import MLServer
@@ -92,25 +93,33 @@ def run_command(entry_file, host, port, bind, wrapper, server, workers, config,
                 name, mode, api_format, ngrok, kws):
     kws = list(kws)
     if isinstance(entry_file, str) and not os.path.exists(entry_file):
-        kws = [entry_file] + kws
+        kws = [f'--entry_file={entry_file}'] + kws
         entry_file = None
     from mlchain import config as mlconfig
     default_config = False
+
     if config is None:
         default_config = True
         config = 'mlconfig.yaml'
 
-    if os.path.isfile(config):
-        config = mlconfig.load_file(config)
+    config_path = copy.deepcopy(config)
+    if os.path.isfile(config_path) and os.path.exists(config_path):
+        config = mlconfig.load_file(config_path)
         if config is None:
-            raise AssertionError("Not support file config {0}".format(config))
+            raise SystemExit("Config file {0} are not supported".format(config_path))
     else:
         if not default_config:
-            raise FileNotFoundError("Not found file {0}".format(config))
-        config = {}
+            raise SystemExit("Can't find config file {0}".format(config_path))
+        else:
+            raise SystemExit("Can't find mlchain config file. Please double check your current working directory. Or use `mlchain init` to initialize a new ones here.")
     if 'mode' in config and 'env' in config['mode']:
         if mode in config['mode']['env']:
             config['mode']['default'] = mode
+        elif mode is not None:
+            available_mode = list(config['mode']['env'].keys())
+            available_mode = [each for each in available_mode if each != 'default']
+            raise SystemExit(
+                f"No {mode} mode are available. Found these mode in config file: {available_mode}")
     mlconfig.load_config(config)
     for kw in kws:
         if kw.startswith('--'):
@@ -124,6 +133,8 @@ def run_command(entry_file, host, port, bind, wrapper, server, workers, config,
             raise AssertionError("Unexpected param {0}".format(kw))
     model_id = mlconfig.get_value(None, config, 'model_id', None)
     entry_file = mlconfig.get_value(entry_file, config, 'entry_file', 'server.py')
+    if not os.path.exists(entry_file):
+        raise SystemExit(f"Entry file {entry_file} not found in current working directory.")
     host = mlconfig.get_value(host, config, 'host', 'localhost')
     port = mlconfig.get_value(port, config, 'port', 5000)
     server = mlconfig.get_value(server, config, 'server', 'flask')

mlchain/config.py

@@ -102,7 +102,10 @@ def load_config(self, path, mode=None):
                 for mode in ['default', default]:
                     if mode in data['mode']['env']:
                         for k, v in data['mode']['env'][mode].items():
-                            environ[k] = str(v)
+                            if k in environ:
+                                data['mode']['env'][mode][k] = environ[k]
+                            else:
+                                environ[k] = str(v)
                         self.update(data['mode']['env'][mode])
 
     def get_client_config(self, name):
@@ -150,6 +153,11 @@ def load_config(data):
         if 'env' in data['mode']:
             for mode in ['default', default]:
                 if mode in data['mode']['env']:
+                    for k, v in data['mode']['env'][mode].items():
+                        if k in environ:
+                            data['mode']['env'][mode][k] = environ[k]
+                        else:
+                            environ[k] = str(v)
                     mlconfig.update(data['mode']['env'][mode])
 
     if mlconfig.MLCHAIN_SENTRY_DSN is not None and data.get('wrapper', None) != 'gunicorn': 

tests/dummy_server/server.py

@@ -10,14 +10,16 @@ def __init__(self):
         pass
 
 
-    def predict(self, image: np.ndarray):
+    def predict(self, image: np.ndarray = None):
         """
         Resize input to 100 by 100.
         Args:
             image (numpy.ndarray): An input image.
         Returns:
             The image (np.ndarray) at 100 by 100.
         """
+        if image is None:
+            return 'Hihi'
         image = cv2.resize(image, (100, 100))
         return image
 

tests/test_limiter.py

@@ -30,5 +30,30 @@ def test_limiter_2(self):
         total_time = time.time() - start_time
         assert total_time >= 3
 
+    def test_limiter_fail(self):
+        try:
+            limiter = RateLimiter(max_calls=1, period=0)
+        except ValueError:
+            pass
+
+        try:
+            limiter = RateLimiter(max_calls=0, period=1)
+        except ValueError:
+            pass
+
+    def test_limiter_with_callback(self):
+        start_time = time.time()
+        global abc
+        abc = 0
+        def callback(i):
+            global abc
+            abc += 1
+        limiter = RateLimiter(max_calls=3, period=1, callback=callback)
+        for i in range(10):
+            with limiter:
+                pass
+        total_time = time.time() - start_time
+        assert total_time >= 3
+
 if __name__ == '__main__':
     unittest.main()

tests/test_utils.py

@@ -0,0 +1,16 @@
+import logging
+import unittest
+
+from mlchain.base.utils import *
+logger = logging.getLogger()
+
+class TestUtils(unittest.TestCase):
+    def __init__(self, *args, **kwargs):
+        unittest.TestCase.__init__(self, *args, **kwargs)
+        logger.info("Running utils test")
+
+    def test_nothing(self):
+        pass
+
+if __name__ == '__main__':
+    unittest.main()

tests/test_workflow.py

@@ -104,6 +104,14 @@ def dummy_task():
         logger.info(x)
         background.stop()
 
+        try:
+            background = Background(task, interval=0.01).run(pass_fail_job=False)
+            time.sleep(0.02)
+            logger.info(x)
+            background.stop()
+        except:
+            pass
+
     def test_mlchain_async_task(self):
         async def dummy_task(n):
             return n+1