Use a proper temp folder for creating the archive of an MLflow model

Author: lpenet

dataikuapi/dss/savedmodel.py

@@ -1,3 +1,5 @@
+import tempfile
+
 from .metrics import ComputedMetrics
 from .ml import DSSMLTask
 from .ml import DSSTrainedClusteringModelDetails
@@ -131,18 +133,19 @@ def import_mlflow_version_from_path(self, version_id, path, code_env_name = "INH
         :return a :class:MLFlowVersionHandler in order to interact with the new MLFlow model version
         """
         # TODO: Add a check that it's indeed a MLFlow model folder
-        # TODO: Put it in a proper temp folder
         # TODO: cleanup the archive
         import shutil
         import os
-        shutil.make_archive("tmpmodel", "zip", path) #[, root_dir[, base_dir[, verbose[, dry_run[, owner[, group[, logger]]]]]]])
-        
-        with open("tmpmodel.zip", "rb") as fp:
-            self.client._perform_empty("POST", "/projects/%s/savedmodels/%s/versions/%s?codeEnvName=%s" % (self.project_key, self.sm_id, version_id, code_env_name),
-                files={"file":("tmpmodel.zip", fp)})
-        os.remove("tmpmodel.zip")
-
-        return self.get_mlflow_version_handler(version_id)
+        archive_temp_dir = tempfile.mkdtemp()
+        try:
+            archive_filename = shutil.make_archive(os.path.join(archive_temp_dir, "tmpmodel"), "zip", path) #[, root_dir[, base_dir[, verbose[, dry_run[, owner[, group[, logger]]]]]]])
+
+            with open("tmpmodel.zip", "rb") as fp:
+                self.client._perform_empty("POST", "/projects/%s/savedmodels/%s/versions/%s?codeEnvName=%s" % (self.project_key, self.sm_id, version_id, code_env_name),
+                    files={"file":(archive_filename, fp)})
+            return self.get_mlflow_version_handler(version_id)
+        finally:
+            shutil.rmtree(archive_temp_dir)
 
     def get_mlflow_version_handler(self, version_id):
         """