updated precommit

.pre-commit-config.yaml

@@ -1,22 +1,37 @@
 repos:
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v3.2.0
+    rev: v4.3.0
     hooks:
     -   id: trailing-whitespace
     -   id: end-of-file-fixer
     -   id: check-yaml
     -   id: check-added-large-files
+    -   id: check-merge-conflict
+    -   id: debug-statements
+    -   id: detect-private-key
+    -   id: name-tests-test
+        args: [--pytest-test-first]
+    -   id: requirements-txt-fixer
 -   repo: https://github.com/pycqa/flake8
-    rev: 3.9.2
+    rev: 5.0.4
     hooks:
     -   id: flake8
+        args: ["--statistics", "--count", "--max-complexity=10", "--max-line-length=120", "--per-file-ignore=__init__.py: F401"]
 -   repo: https://github.com/psf/black
     rev: 22.3.0
     hooks:
     -   id: black
         args: [--line-length=120]
 -   repo: https://github.com/PyCQA/isort
-    rev: 5.9.1
+    rev: 5.12.0
     hooks:
     -   id: isort
         args: ["--profile", "black", --line-length=120]
+-   repo: local
+    hooks:
+    -   id: check-requirements
+        name: Check requirements
+        description: Check if requirements in setup.cfg and requirements.txt are equal
+        language: python
+        entry: python scripts/check_setupcfg_and_requirements_equal.py
+        pass_filenames: false

df_to_azure/export.py

@@ -9,7 +9,17 @@
 import pandas as pd
 from azure.storage.blob import BlobServiceClient
 from numpy import dtype
-from pandas import BooleanDtype, DataFrame, Float64Dtype, Int8Dtype, Int16Dtype, Int32Dtype, Int64Dtype, StringDtype
+from pandas import (
+    BooleanDtype,
+    DataFrame,
+    DatetimeTZDtype,
+    Float64Dtype,
+    Int8Dtype,
+    Int16Dtype,
+    Int32Dtype,
+    Int64Dtype,
+    StringDtype,
+)
 from sqlalchemy.sql.visitors import VisitableType
 from sqlalchemy.types import BigInteger, Boolean, DateTime, Integer, Numeric, String
 
@@ -241,6 +251,7 @@ def column_types(self) -> dict:
             dtype("<M8[ns]"): DateTime(),
             dtype("bool"): Boolean(),
             BooleanDtype(): Boolean(),
+            DatetimeTZDtype(tz="utc"): DateTime(),
         }
 
         col_types = {col_name: type_conversion[col_type] for col_name, col_type in self.df.dtypes.to_dict().items()}