ThreadPoolExecutor alway alive after close batching API and database client

Comienza siguiendo InfluxDBClient.write_api() con WriteOptions y WriteType.batching, y después sigue las rutas de close() y flush() para ThreadPoolExecutor. Reproduce el problema con el script proporcionado; se considera terminado cuando el hilo del executor ya no aparece en la lista después de cerrar la batching API y el cliente.

Specifications

• Client Version: 1.40.0
• InfluxDB Version: 2.7.1
• Platform: Ubuntu
• Python Version: 3.10.9

Code sample to reproduce problem

import threading
import time
from influxdb_client import (
    InfluxDBClient
)
from influxdb_client.client.write_api import (
    WriteOptions,
    WriteType,
)


def check_thread_alive():
    """Check if all thread are correctly closed."""
    msg: str = f"{len(threading.enumerate())} threads running"
    for thread in threading.enumerate():
        msg += f"\n > {thread.name}"
    print(msg)


data_points = [
    {
        "measurement": "temperature",
        "tags": {"location": "room1"},
        "time": "2024-02-02T12:00:00Z",
        "fields": {"value": 25.5}
    },
    {
        "measurement": "humidity",
        "tags": {"location": "room1"},
        "time": "2024-02-02T12:00:00Z",
        "fields": {"value": 60}
    },
]

print(">>>>>> START")
check_thread_alive()

print(">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> create InfluxDBClient")
client = InfluxDBClient(
    url="localhost:8086",
    org="test",
    token="LLxHucOTfD1zSHVSadNRJRzZh_nNZGNf1KrHCieOj847ucB2RcLCBJZogP2zNtMxvAZMlAWsSOHgSJChaO7b3A==")
check_thread_alive()

print(">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> create write_api")
batch_write_api = client.write_api(
    write_options=WriteOptions(
        write_type=WriteType.batching))
check_thread_alive()

print(">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> close write_api")
batch_write_api.close()
batch_write_api.flush()
check_thread_alive()

print(">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> close InfluxDBClient")
client.close()
check_thread_alive()

print(">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> wait 5 s")
time.sleep(5)
check_thread_alive()
print(">>>>>> STOP")

Expected behavior

When we close the batching API, associated threads are closed

Actual behavior

When we close the batching API, the associated thread ThreadPoolExecutor is alway alive

Additional info

My output

>>>>>> START
1 threads running
 > MainThread
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> create InfluxDBClient
1 threads running
 > MainThread
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> create write_api
2 threads running
 > MainThread
 > ThreadPoolExecutor-1_0
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> close write_api
2 threads running
 > MainThread
 > ThreadPoolExecutor-1_0
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> close InfluxDBClient
2 threads running
 > MainThread
 > ThreadPoolExecutor-1_0
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> wait 5 s
2 threads running
 > MainThread
 > ThreadPoolExecutor-1_0
>>>>>> STOP