Security update 12.2024 (#1405)

* Security update 12.2024

* Fix AttributeError: 'super' object has no attribute '__sklearn_tags__'

* Trying to fix mypy complains

* Black reformating

Dockerfile

@@ -11,7 +11,7 @@ RUN apt-get update && apt-get install -y \
     && rm -rf /var/lib/apt/lists/*
 
 # Fix CVE-2024-6345
-RUN pip install setuptools==70.0.0
+RUN pip install setuptools~=75.0
 
 WORKDIR /code
 RUN rm -rf /code/dist \
@@ -38,7 +38,7 @@ RUN apt-get update && apt-get install -y \
     && rm -rf /var/lib/apt/lists/*
 
 # Fix CVE-2024-6345
-RUN pip install setuptools==70.0.0
+RUN pip install setuptools~=75.0
 
 # Install requirements separately for improved docker caching
 COPY --from=builder /code/prereq.txt .
@@ -80,7 +80,7 @@ RUN cp ${HOME}/build.sh /usr/bin/build \
 WORKDIR ${HOME}
 
 #download & install argo
-ENV ARGO_VERSIONS="[{\"number\":3,\"version\":\"3.5.11\"}]"
+ENV ARGO_VERSIONS="[{\"number\":3,\"version\":\"3.6.2\"}]"
 COPY scripts/download_argo.py ./download_argo.py
 RUN python3 ./download_argo.py -o /usr/local/bin
 

gordo/reporters/mlflow.py

@@ -4,7 +4,8 @@
 import logging
 import os
 import tempfile
-from typing import Dict, List, Union, Tuple, Optional, Type, cast
+from typing import Dict, List, Union, Tuple, Optional, Type, TypedDict, cast
+from collections.abc import Sequence
 from uuid import uuid4
 
 from azureml.core import Workspace
@@ -34,6 +35,11 @@ class MlflowLoggingError(ReporterException):
     pass
 
 
+class LogBatchKwargs(TypedDict):
+    metrics: Sequence[Metric]
+    params: Sequence[Param]
+
+
 def _validate_dict(d: dict, required_keys: List[str]):
     """
     Validate the required keys are contained in provided dictionary
@@ -88,7 +94,7 @@ def get_mlflow_client(
     """
     logger.info("Creating MLflow tracking client.")
 
-    tracking_uri = None
+    tracking_uri: str = ""
 
     # Get AzureML tracking_uri if using Azure as backend
     if workspace_kwargs:
@@ -278,7 +284,7 @@ def batch_log_items(
     params: List[Param],
     n_max_metrics: int = 200,
     n_max_params: int = 100,
-) -> List[Dict[str, Union[Metric, Param]]]:
+) -> List[LogBatchKwargs]:
     """
     Split metrics, params and tags to batches that satisfy limits imposed by MLFlow and AzureML
 
@@ -320,7 +326,7 @@ def _calc_n_batches(n: int, n_max: int):
 
     i = 0
     j = 0
-    log_batches = list()
+    log_batches: List[LogBatchKwargs] = list()
     for _ in range(n_batches):
         log_batches.append(
             {