Exception ignored in: <function InfluxDBClient.__del__ at 0x00000232E7BBC430>

Specifications

Client Version: 1.37.0
InfluxDB v2.6.1
Server: 9dcf880
Frontend: 5ba8e15

Code sample to reproduce problem

When writing a pandas dataframe to the InfluxDB server using below write function:

class SetupInflux:
    def __init__(self, influx_url, token, org_id, influx_bucket, res, debug=False, verbose=True):
        from influxdb_client import InfluxDBClient

        self.influx_url = influx_url
        self.token = token
        self.org_id = org_id
        self.influx_bucket = influx_bucket
        self.debug = debug
        self.verbose = verbose
        self.res = res
        self.client = InfluxDBClient(url=self.influx_url, token=self.token, org=self.org_id, debug=False)
        self.test = self.test_influx()
        return

    def __del__(self):
        self.client.__del__()

    def get_start_times(self, devices, default_start, dynamic):
        """Get latest InfluxDB timestamps for devices for use as 'start times' for listing log files from S3"""
        from datetime import datetime, timedelta
        from dateutil.tz import tzutc

        default_start_dt = datetime.strptime(default_start, "%Y-%m-%d %H:%M:%S").replace(tzinfo=tzutc())
        
        device_ids = [device.split("/")[1] for device in devices]
            
        start_times = []

        if dynamic == False or self.test == 0:
            for device in device_ids:
                last_time = default_start_dt
                start_times.append(last_time)
        elif self.test != 0:
            for device in device_ids:
               
                influx_time = self.client.query_api().query(
                    f'from(bucket:"{self.influx_bucket}") |> range(start: -100d) |> filter(fn: (r) => r["_measurement"] == "{device}") |> group() |> last()'
                )

                if len(influx_time) == 0:
                    last_time = default_start_dt
                else:
                    last_time = influx_time[0].records[0]["_time"]
                    last_time = last_time + timedelta(seconds=2)

                start_times.append(last_time)

                if self.verbose:
                    print(f"Log files will be fetched for {device} from {last_time}")

        return start_times

    def add_signal_tags(self, df_signal):
        """Advanced: This can be used to add custom tags to the signals
        based on a specific use case logic. In effect, this will
        split the signal into multiple timeseries
        """
        tag_columns = ["tag"]

        def event_test(row):
            return "event" if row[0] > 1200 else "no event"

        for tag in tag_columns:
            df_signal[tag] = df_signal.apply(lambda row: event_test(row), axis=1)

        return tag_columns, df_signal

    def write_signals(self, device_id, df_phys):
        """Given a device ID and a dataframe of physical values,
        resample and write each signal to a time series database

        :param device_id:   ID of device (used as the 'measurement name')
        :param df_phys:     Dataframe of physical values (e.g. as per output of can_decoder)
        """
        tag_columns = []

        if df_phys.empty:
            print("Warning: Dataframe is empty, no data written")
            return
        else:
            if self.res != "":
                self.write_influx(device_id, df_phys, [])

            else:
                for signal, group in df_phys.groupby("Signal")["Physical Value"]:
                    df_signal = group.to_frame().rename(columns={"Physical Value": signal})

                    if self.res != "":
                        df_signal = df_signal.resample(self.res).ffill().dropna()

                    if self.verbose:
                        print(f"Signal: {signal} (mean: {round(df_signal[signal].mean(),2)} | records: {len(df_signal)} | resampling: {self.res})")

                    # tag_columns, df_signal = self.add_signal_tags(df_signal)

                    self.write_influx(device_id, df_signal, tag_columns)

    def write_influx(self, name, df, tag_columns):
        """Helper function to write signal dataframes to InfluxDB"""
        from influxdb_client import WriteOptions

        if self.test == 0:
            print("Please check your InfluxDB credentials")
            return

        with self.client.write_api(
                write_options=WriteOptions(
                    batch_size=20_000,
                    flush_interval=1_000,
                    jitter_interval=0,
                    retry_interval=5_000,
                )
        ) as _write_client:
            _write_client.write(self.influx_bucket, record=df, data_frame_measurement_name=name,
                                data_frame_tag_columns=tag_columns)

        if self.verbose:
            print(f"- SUCCESS: {len(df.index)} records of {name} written to InfluxDB\n\n")

        if self.test != 0:
            _write_client.__del__()

Expected behavior

I expect that the data is simply written without exceptions or errors. It works as intended in terms of writing the data.

Actual behavior

When the script has run, I get below error:

Exception ignored in: <function InfluxDBClient.__del__ at 0x00000232E7BBC430>
Traceback (most recent call last):
  File "C:\Users\marti\AppData\Local\Programs\Python\Python39\lib\site-packages\influxdb_client\client\influxdb_client.py", line 320, in __del__
  File "C:\Users\marti\AppData\Local\Programs\Python\Python39\lib\site-packages\influxdb_client\_sync\api_client.py", line 84, in __del__
  File "C:\Users\marti\AppData\Local\Programs\Python\Python39\lib\site-packages\influxdb_client\_sync\api_client.py", line 661, in _signout
TypeError: 'NoneType' object is not callable
Exception ignored in: <function ApiClient.__del__ at 0x00000232E7BFE700>
Traceback (most recent call last):
  File "C:\Users\marti\AppData\Local\Programs\Python\Python39\lib\site-packages\influxdb_client\_sync\api_client.py", line 84, in __del__
  File "C:\Users\marti\AppData\Local\Programs\Python\Python39\lib\site-packages\influxdb_client\_sync\api_client.py", line 661, in _signout
TypeError: 'NoneType' object is not callable

Additional info

No response

Bắt đầu với influxdb_client/client/influxdb_client.py và influxdb_client/_sync/api_client.py tại các lệnh gọi del và _signout được hiển thị trong traceback. Tái hiện lỗi cleanup bằng cách sử dụng InfluxDBClient và write_api được cung cấp, sau đó kiểm tra cách shutdown hoạt động trong quá trình teardown của trình thông dịch. Hoàn tất khi việc cleanup của client và API hoàn thành mà không có ngoại lệ NoneType được báo cáo.