chore: add support for Python 3.12

.circleci/config.yml

@@ -202,6 +202,9 @@ workflows:
       - tests-python:
           name: test-3.11
           python-image: "cimg/python:3.11"
+      - tests-python:
+          name: test-3.12
+          python-image: "cimg/python:3.12"
 
   nightly:
     when:

CHANGELOG.md

@@ -1,5 +1,8 @@
 ## 1.41.0 [unreleased]
 
+### Features
+1. [#643](https://github.com/influxdata/influxdb-client-python/pull/643): Add a support for Python 3.12
+
 ### Bug Fixes
 1. [#636](https://github.com/influxdata/influxdb-client-python/pull/636): Handle missing data in data frames
 2. [#638](https://github.com/influxdata/influxdb-client-python/pull/638), [#642](https://github.com/influxdata/influxdb-client-python/pull/642): Refactor DataFrame operations to avoid chained assignment and resolve FutureWarning in pandas, ensuring compatibility with pandas 3.0.

scripts/ci-test.sh

@@ -8,13 +8,13 @@ ENABLED_CISO_8601="${ENABLED_CISO_8601:-true}"
 # Install requirements
 #
 python --version
-pip install -e . --user
-pip install -e .\[extra\] --user
-pip install -e .\[test\] --user
-pip install -e .\[async\] --user
+pip install . --user
+pip install .\[extra\] --user
+pip install .\[test\] --user
+pip install .\[async\] --user
 if [ "$ENABLED_CISO_8601" = true ] ; then
   echo "ciso8601 is enabled"
-  pip install -e .\[ciso\] --user
+  pip install .\[ciso\] --user
 else
   echo "ciso8601 is disabled"
 fi

setup.py

@@ -78,6 +78,7 @@
         'Programming Language :: Python :: 3.9',
         'Programming Language :: Python :: 3.10',
         'Programming Language :: Python :: 3.11',
+        'Programming Language :: Python :: 3.12',
         'Topic :: Database',
         'Topic :: Software Development :: Libraries',
         'Topic :: Software Development :: Libraries :: Python Modules',

tests/test_InfluxDBClient.py

@@ -248,8 +248,9 @@ def _start_http_server(self):
         urllib3.disable_warnings()
         # Configure HTTP server
         self.httpd = http.server.HTTPServer(('localhost', 0), ServerWithSelfSingedSSL)
-        self.httpd.socket = ssl.wrap_socket(self.httpd.socket, certfile=f'{os.path.dirname(__file__)}/server.pem',
-                                            server_side=True)
+        context = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER)
+        context.load_cert_chain(f'{os.path.dirname(__file__)}/server.pem')
+        self.httpd.socket = context.wrap_socket(self.httpd.socket, server_side=True)
         # Start server at background
         self.httpd_thread = threading.Thread(target=self.httpd.serve_forever)
         self.httpd_thread.start()

tests/test_QueryApiDataFrame.py

@@ -268,7 +268,7 @@ def test_query_with_warning(self):
                 '|> range(start: -5s, stop: now()) '
                 '|> filter(fn: (r) => r._measurement == "mem") '
                 "my-org")
-        self.assertEqual(1, len(warnings))
+        self.assertEqual(1, len([w for w in warnings if w.category == MissingPivotFunction]))
 
     def test_query_without_warning(self):
         httpretty.register_uri(httpretty.POST, uri="http://localhost/api/v2/query", status=200, body='\n')
@@ -284,7 +284,7 @@ def test_query_without_warning(self):
                 '|> filter(fn: (r) => r._measurement == "mem") '
                 '|> schema.fieldsAsCols() '
                 "my-org")
-        self.assertEqual(0, len(warns))
+        self.assertEqual(0, len([w for w in warns if w.category == MissingPivotFunction]))
 
         with warnings.catch_warnings(record=True) as warns:
             self.client.query_api().query_data_frame(
@@ -293,7 +293,7 @@ def test_query_without_warning(self):
                 '|> filter(fn: (r) => r._measurement == "mem") '
                 '|> pivot(rowKey: ["_time"], columnKey: ["_field"], valueColumn: "_value")'
                 "my-org")
-        self.assertEqual(0, len(warns))
+        self.assertEqual(0, len([w for w in warns if w.category == MissingPivotFunction]))
 
     def test_pivoted_data(self):
         query_response = \

tests/test_Warnings.py

@@ -27,4 +27,5 @@ def test_cloud_only_warning(self):
             with InfluxDBClient(url="http://localhost", token="my-token", org="my-org") as client:
                 service = BucketSchemasService(api_client=client.api_client)
                 service.get_measurement_schemas(bucket_id="01010101")
+        warnings = [w for w in warnings if w.category == CloudOnlyWarning]
         self.assertEqual(1, len(warnings))

tests/test_WriteApiDataFrame.py

@@ -313,7 +313,7 @@ def test_with_period_index(self):
         data_frame = pd.DataFrame(data={
                                       'value': [1, 2],
                                 },
-                                index=pd.period_range(start='2020-04-05 01:00', freq='H', periods=2))
+                                index=pd.period_range(start='2020-04-05 01:00', freq='h', periods=2))
 
         points = data_frame_to_list_of_points(data_frame=data_frame,
                                               point_settings=PointSettings(),
@@ -498,7 +498,7 @@ def test_specify_timezone_period_time_index(self):
         data_frame = pd.DataFrame(data={
             'value1': [10, 20],
             'value2': [30, 40],
-        }, index=pd.period_range(start='2020-05-24 10:00', freq='H', periods=2))
+        }, index=pd.period_range(start='2020-05-24 10:00', freq='h', periods=2))
 
         print(data_frame.to_string())
 
@@ -519,7 +519,7 @@ def test_serialization_for_nan_in_columns_starting_with_digits(self):
             '2value': [30.0, np.nan, np.nan, np.nan, np.nan],
             '3value': [30.0, 30.0, 30.0, np.nan, np.nan],
             'avalue': [30.0, 30.0, 30.0, 30.0, 30.0]
-        }, index=pd.period_range('2020-05-24 10:00', freq='H', periods=5))
+        }, index=pd.period_range('2020-05-24 10:00', freq='h', periods=5))
 
         points = data_frame_to_list_of_points(data_frame,
                                               PointSettings(),
@@ -536,7 +536,7 @@ def test_serialization_for_nan_in_columns_starting_with_digits(self):
             '1value': [np.nan],
             'avalue': [30.0],
             'bvalue': [30.0]
-        }, index=pd.period_range('2020-05-24 10:00', freq='H', periods=1))
+        }, index=pd.period_range('2020-05-24 10:00', freq='h', periods=1))
 
         points = data_frame_to_list_of_points(data_frame,
                                               PointSettings(),