Fix support for MLFlow 2.0.1 and fix linting

.flake8

@@ -1,3 +1,3 @@
 [flake8]
-exclude = .git,__pycache__,data,tools
-ignore = E101, E111, E114, E115, E116, E117, E121, E122, E123, E124, E125, E126, E127, E128, E129, E131, E133, E2, E3, E5, E501, E701, E702, E703, E704, W1, W2, W3, W503, W504
+max-line-length = 100
+extend-ignore = E203

.pre-commit-config.yaml

@@ -11,6 +11,7 @@ repos:
     rev: 5.0.4
     hooks:
     -   id: flake8
+        args: ['--config=.flake8']
         additional_dependencies: ['flake8-coding==1.3.2', 'flake8-copyright==0.2.3', 'flake8-debugger==4.1.2', 'flake8-mypy==17.8.0']
 -   repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.3.0

comet_for_mlflow/comet_for_mlflow.py

@@ -41,13 +41,19 @@
 from comet_ml.exceptions import CometRestApiException
 from comet_ml.offline import upload_single_offline_experiment
 from mlflow.entities.run_tag import RunTag
-from mlflow.entities.view_type import ViewType
 from mlflow.tracking import _get_store
 from mlflow.tracking._model_registry.utils import _get_store as get_model_registry_store
 from mlflow.tracking.registry import UnsupportedModelRegistryStoreURIException
 from tabulate import tabulate
 from tqdm import tqdm
 
+from .compat import (
+    get_artifact_repository,
+    get_mlflow_model_name,
+    get_mlflow_run_id,
+    search_mlflow_store_experiments,
+    search_mlflow_store_runs,
+)
 from .file_writer import JsonLinesFile
 from .utils import (
     get_comet_project_name,
@@ -65,18 +71,10 @@
     pass
 
 
-try:
-    # MLFLOW version 1.4.0
-    from mlflow.store.artifact.artifact_repository_registry import (
-        get_artifact_repository,
-    )
-except ImportError:
-    # MLFLOW version < 1.4.0
-    from mlflow.store.artifact_repository_registry import get_artifact_repository
-
 logging.basicConfig(level=logging.INFO, format="%(message)s")
 LOGGER = logging.getLogger()
 
+
 # Install a global exception hook
 def except_hook(exc_type, exc_value, exc_traceback):
     Reporting.report(
@@ -137,8 +135,7 @@ def __init__(
         except UnsupportedModelRegistryStoreURIException:
             self.model_registry_store = None
 
-        # Most of list_experiments returns a list anyway
-        self.mlflow_experiments = list(self.store.list_experiments())
+        self.mlflow_experiments = search_mlflow_store_experiments(self.store)
         self.len_experiments = len(self.mlflow_experiments)  # We start counting at 0
 
         self.summary = {
@@ -239,22 +236,28 @@ def prepare(self):
 
         LOGGER.info("")
         LOGGER.info(
-            "If you need support, you can contact us at http://chat.comet.ml/ or https://comet.ml/docs/quick-start/#getting-support"
+            """If you need support, you can contact us at http://chat.comet.ml/"""
+            """ or https://comet.ml/docs/quick-start/#getting-support"""
         )
         LOGGER.info("")
 
     def prepare_mlflow_exp(
-        self, exp,
+        self,
+        exp,
     ):
-        runs_info = self.store.list_run_infos(exp.experiment_id, ViewType.ALL)
+        runs_info = search_mlflow_store_runs(self.store, exp.experiment_id)
         len_runs = len(runs_info)
 
         for run_number, run_info in enumerate(runs_info):
             try:
-                run_id = run_info.run_id
+                run_id = get_mlflow_run_id(run_info)
+
                 run = self.store.get_run(run_id)
                 LOGGER.info(
-                    "## Preparing run %d/%d [%s]", run_number + 1, len_runs, run_id,
+                    "## Preparing run %d/%d [%s]",
+                    run_number + 1,
+                    len_runs,
+                    run_id,
                 )
                 LOGGER.debug(
                     "## Preparing run %d/%d: %r", run_number + 1, len_runs, run
@@ -410,15 +413,25 @@ def prepare_single_mlflow_run(self, run, original_experiment_name):
                         break
 
                 if matching_model:
+                    model_name = get_mlflow_model_name(matching_model)
+
+                    prefix = "models/"
+                    if artifact_path.startswith(prefix):
+                        comet_artifact_path = artifact_path[len(prefix) :]
+                    else:
+                        comet_artifact_path = artifact_path
+
                     json_writer.log_artifact_as_model(
                         local_artifact_path,
-                        artifact_path,
+                        comet_artifact_path,
                         run_start_time,
-                        matching_model.registered_model.name,
+                        model_name,
                     )
                 else:
                     json_writer.log_artifact_as_asset(
-                        local_artifact_path, artifact_path, run_start_time,
+                        local_artifact_path,
+                        artifact_path,
+                        run_start_time,
                     )
 
         return self.compress_archive(run.info.run_id)
@@ -438,12 +451,15 @@ def upload(self, prepared_data):
                 project_note = experiment.tags.get("mlflow.note.content", None)
                 if project_note:
                     note_template = (
-                        u"/!\\ This project notes has been copied from MLFlow. It might be overwritten if you run comet_for_mlflow again/!\\ \n%s"
+                        "/!\\ This project notes has been copied from MLFlow."
+                        " It might be overwritten if you run comet_for_mlflow again/!\\ \n%s"
                         % project_note
                     )
                     # We don't support Unicode project notes yet
                     self.api_client.set_project_notes(
-                        self.workspace, project_name, note_template,
+                        self.workspace,
+                        project_name,
+                        note_template,
                     )
 
                 all_project_names.append(project_name)
@@ -487,7 +503,8 @@ def upload(self, prepared_data):
             LOGGER.info("\t- %s", url)
 
         LOGGER.info(
-            "Get deeper instrumentation by adding Comet SDK to your project: https://comet.ml/docs/python-sdk/mlflow/"
+            "Get deeper instrumentation by adding Comet SDK to your project:"
+            " https://comet.ml/docs/python-sdk/mlflow/"
         )
         LOGGER.info("")
 
@@ -598,19 +615,23 @@ def create_or_login(self):
             Reporting.report("mlflow_new_user", api_key=new_account["apiKey"])
 
             LOGGER.info(
-                "A Comet.ml account has been created for you and an email was sent to you to setup your password later."
+                "A Comet.ml account has been created for you and an email was sent to"
+                " you to setup your password later."
             )
             save_api_key(new_account["apiKey"])
             LOGGER.info(
-                "Your Comet API Key has been saved to ~/.comet.ini, it is also available on your Comet.ml dashboard."
+                "Your Comet API Key has been saved to ~/.comet.ini, it is also"
+                " available on your Comet.ml dashboard."
             )
             return (
                 new_account["apiKey"],
                 new_account["token"],
             )
         else:
             LOGGER.info(
-                "An account already exists for this account, please input your API Key below (you can find it in your Settings page, https://comet.ml/docs/quick-start/#getting-your-comet-api-key):"
+                "An account already exists for this account, please input your API Key"
+                " below (you can find it in your Settings page,"
+                " https://comet.ml/docs/quick-start/#getting-your-comet-api-key):"
             )
             api_key = input("API Key: ")
 

comet_for_mlflow/compat.py

@@ -0,0 +1,76 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+#
+# Copyright (c) 2020 Comet.ml Team.
+#
+# This file is part of Comet-For-MLFlow
+# (see https://github.com/comet-ml/comet-for-mlflow).
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program. If not, see <http://www.gnu.org/licenses/>.
+#
+
+"""
+Contains code to support multiple versions of MLFlow
+"""
+from mlflow.entities.view_type import ViewType
+
+try:
+    # MLFLOW version 1.4.0
+    from mlflow.store.artifact.artifact_repository_registry import (  # noqa
+        get_artifact_repository,
+    )
+except ImportError:
+    # MLFLOW version < 1.4.0
+    from mlflow.store.artifact_repository_registry import (  # noqa
+        get_artifact_repository,
+    )
+
+
+def search_mlflow_store_experiments(mlflow_store):
+    if hasattr(mlflow_store, "search_experiments"):
+        # MLflow supports search for up to 50000 experiments, defined in
+        # mlflow/store/tracking/__init__.py
+        mlflow_experiments = mlflow_store.search_experiments(max_results=50000)
+        # TODO: Check if there are more than 50000 experiments
+        return list(mlflow_experiments)
+    else:
+        return list(mlflow_store.list_experiments())
+
+
+def search_mlflow_store_runs(mlflow_store, experiment_id):
+    if hasattr(mlflow_store, "search_runs"):
+        # MLflow supports search for up to 50000 experiments, defined in
+        # mlflow/store/tracking/__init__.py
+        return mlflow_store.search_runs(
+            [experiment_id],
+            filter_string="",
+            run_view_type=ViewType.ALL,
+            max_results=50000,
+        )
+    else:
+        return mlflow_store.list_run_infos(experiment_id, ViewType.ALL)
+
+
+def get_mlflow_run_id(mlflow_run):
+    if hasattr(mlflow_run, "info"):
+        return mlflow_run.info.run_id
+    else:
+        return mlflow_run.run_id
+
+
+def get_mlflow_model_name(mlflow_model):
+    if hasattr(mlflow_model, "name"):
+        return mlflow_model.name
+    else:
+        return mlflow_model.registered_model.name