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**Apache Airflow version**: 2.1.1
**Docker Image:** `apache/airflow:2.1.1-python3.8`


**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): Not running on k8s.

**Environment**:

- **Cloud provider or hardware configuration**: DigitalOcean
- **OS** (e.g. from /etc/os-release): Ubuntu
- **Kernel** (e.g. `uname -a`): `Linux airflow 5.11.0-22-generic #23-Ubuntu SMP Thu Jun 17 00:34:23 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux`
- **Install tools**: Installed via Docker & Docker Compose following instructions from [official docker-compose installation docs](https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#docker-compose-yaml).
- **Others**: N/A

**What happened**:

<!-- (please include exact error messages if you can) -->

**What you expected to happen**:

<!-- What do you think went wrong? -->

**How to reproduce it**:
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Running with the `DockerOperator` causes the following error:
```
*** Reading local file: /opt/airflow/logs/docker_eod_us_equities/docker_command_sleep/2021-07-04T23:19:48.431208+00:00/2.log
[2021-07-04 23:49:53,886] {taskinstance.py:896} INFO - Dependencies all met for <TaskInstance: docker_eod_us_equities.docker_command_sleep 2021-07-04T23:19:48.431208+00:00 [queued]>
[2021-07-04 23:49:53,902] {taskinstance.py:896} INFO - Dependencies all met for <TaskInstance: docker_eod_us_equities.docker_command_sleep 2021-07-04T23:19:48.431208+00:00 [queued]>
[2021-07-04 23:49:53,903] {taskinstance.py:1087} INFO - 
--------------------------------------------------------------------------------
[2021-07-04 23:49:53,903] {taskinstance.py:1088} INFO - Starting attempt 2 of 2
[2021-07-04 23:49:53,903] {taskinstance.py:1089} INFO - 
--------------------------------------------------------------------------------
[2021-07-04 23:49:53,911] {taskinstance.py:1107} INFO - Executing <Task(DockerOperator): docker_command_sleep> on 2021-07-04T23:19:48.431208+00:00
[2021-07-04 23:49:53,914] {standard_task_runner.py:52} INFO - Started process 3583 to run task
[2021-07-04 23:49:53,920] {standard_task_runner.py:76} INFO - Running: ['***', 'tasks', 'run', 'docker_eod_us_equities', 'docker_command_sleep', '2021-07-04T23:19:48.431208+00:00', '--job-id', '52', '--pool', 'default_pool', '--raw', '--subdir', 'DAGS_FOLDER/eod_us_equities.py', '--cfg-path', '/tmp/tmp5iz14yg9', '--error-file', '/tmp/tmpleaymjfa']
[2021-07-04 23:49:53,920] {standard_task_runner.py:77} INFO - Job 52: Subtask docker_command_sleep
[2021-07-04 23:49:54,016] {logging_mixin.py:104} INFO - Running <TaskInstance: docker_eod_us_equities.docker_command_sleep 2021-07-04T23:19:48.431208+00:00 [running]> on host 0dff7922cb76
[2021-07-04 23:49:54,172] {taskinstance.py:1300} INFO - Exporting the following env vars:
AIRFLOW_CTX_DAG_OWNER=***
AIRFLOW_CTX_DAG_ID=docker_eod_us_equities
AIRFLOW_CTX_TASK_ID=docker_command_sleep
AIRFLOW_CTX_EXECUTION_DATE=2021-07-04T23:19:48.431208+00:00
AIRFLOW_CTX_DAG_RUN_ID=manual__2021-07-04T23:19:48.431208+00:00
[2021-07-04 23:49:54,205] {docker.py:231} INFO - Starting docker container from image alpine
[2021-07-04 23:49:54,216] {taskinstance.py:1501} ERROR - Task failed with exception
Traceback (most recent call last):
  File "/home/airflow/.local/lib/python3.8/site-packages/docker/api/client.py", line 268, in _raise_for_status
    response.raise_for_status()
  File "/home/airflow/.local/lib/python3.8/site-packages/requests/models.py", line 943, in raise_for_status
    raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: http+docker://localhost/v1.30/containers/create?name=docker_command_sleep

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/airflow/.local/lib/python3.8/site-packages/airflow/models/taskinstance.py", line 1157, in _run_raw_task
    self._prepare_and_execute_task_with_callbacks(context, task)
  File "/home/airflow/.local/lib/python3.8/site-packages/airflow/models/taskinstance.py", line 1331, in _prepare_and_execute_task_with_callbacks
    result = self._execute_task(context, task_copy)
  File "/home/airflow/.local/lib/python3.8/site-packages/airflow/models/taskinstance.py", line 1361, in _execute_task
    result = task_copy.execute(context=context)
  File "/home/airflow/.local/lib/python3.8/site-packages/airflow/providers/docker/operators/docker.py", line 319, in execute
    return self._run_image()
  File "/home/airflow/.local/lib/python3.8/site-packages/airflow/providers/docker/operators/docker.py", line 237, in _run_image
    self.container = self.cli.create_container(
  File "/home/airflow/.local/lib/python3.8/site-packages/docker/api/container.py", line 430, in create_container
    return self.create_container_from_config(config, name)
  File "/home/airflow/.local/lib/python3.8/site-packages/docker/api/container.py", line 441, in create_container_from_config
    return self._result(res, True)
  File "/home/airflow/.local/lib/python3.8/site-packages/docker/api/client.py", line 274, in _result
    self._raise_for_status(response)
  File "/home/airflow/.local/lib/python3.8/site-packages/docker/api/client.py", line 270, in _raise_for_status
    raise create_api_error_from_http_exception(e)
  File "/home/airflow/.local/lib/python3.8/site-packages/docker/errors.py", line 31, in create_api_error_from_http_exception
    raise cls(e, response=response, explanation=explanation)
docker.errors.APIError: 400 Client Error for http+docker://localhost/v1.30/containers/create?name=docker_command_sleep: Bad Request ("invalid mount config for type "bind": bind source path does not exist: /tmp/airflowtmpw5gvv6dj")
[2021-07-04 23:49:54,222] {taskinstance.py:1544} INFO - Marking task as FAILED. dag_id=docker_eod_us_equities, task_id=docker_command_sleep, execution_date=20210704T231948, start_date=20210704T234953, end_date=20210704T234954
[2021-07-04 23:49:54,297] {local_task_job.py:151} INFO - Task exited with return code 1
```

I have even tried with Docker API v1.41 (latest) and same issue. I have bound the `/var/run/docker.sock` as a bind mount into the container.

**Docker Compose:**
```yaml
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
#

# Basic Airflow cluster configuration for CeleryExecutor with Redis and PostgreSQL.
#
# WARNING: This configuration is for local development. Do not use it in a production deployment.
#
# This configuration supports basic configuration using environment variables or an .env file
# The following variables are supported:
#
# AIRFLOW_IMAGE_NAME           - Docker image name used to run Airflow.
#                                Default: apache/airflow:master-python3.8
# AIRFLOW_UID                  - User ID in Airflow containers
#                                Default: 50000
# AIRFLOW_GID                  - Group ID in Airflow containers
#                                Default: 50000
#
# Those configurations are useful mostly in case of standalone testing/running Airflow in test/try-out mode
#
# _AIRFLOW_WWW_USER_USERNAME   - Username for the administrator account (if requested).
#                                Default: airflow
# _AIRFLOW_WWW_USER_PASSWORD   - Password for the administrator account (if requested).
#                                Default: airflow
# _PIP_ADDITIONAL_REQUIREMENTS - Additional PIP requirements to add when starting all containers.
#                                Default: ''
#
# Feel free to modify this file to suit your needs.
---
version: '3'
x-airflow-common: &airflow-common
  image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.1.1-python3.8}
  environment: &airflow-common-env
    AIRFLOW__CORE__EXECUTOR: CeleryExecutor
    AIRFLOW__CORE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
    AIRFLOW__CELERY__RESULT_BACKEND: db+postgresql://airflow:airflow@postgres/airflow
    AIRFLOW__CELERY__BROKER_URL: redis://:@redis:6379/0
    AIRFLOW__CORE__FERNET_KEY: ''
    AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
    AIRFLOW__CORE__LOAD_EXAMPLES: 'false'
    AIRFLOW__SCHEDULER__DAG_DIR_LIST_INTERVAL: 300 # Just to have a fast load in the front-end. Do not use it in production with those configurations.
    AIRFLOW__API__AUTH_BACKEND: 'airflow.api.auth.backend.basic_auth'
    AIRFLOW__CORE__ENABLE_XCOM_PICKLING: 'true' # "_run_image of the DockerOperator returns now a python string, not a byte string" Ref: https://github.com/apache/airflow/issues/13487
    _PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
  volumes:
    - ./dags:/opt/airflow/dags
    - ./logs:/opt/airflow/logs
    - ./plugins:/opt/airflow/plugins
    - '/var/run/docker.sock:/var/run/docker.sock' # We will pass the Docker Deamon as a volume to allow the webserver containers start docker images. Ref: https://stackoverflow.com/q/51342810/7024760
  user: '${AIRFLOW_UID:-50000}:${AIRFLOW_GID:-50000}'
  depends_on:
    redis:
      condition: service_healthy
    postgres:
      condition: service_healthy

services:
  postgres:
    image: postgres:13
    environment:
      POSTGRES_USER: airflow
      POSTGRES_PASSWORD: airflow
      POSTGRES_DB: airflow
    volumes:
      - postgres-db-volume:/var/lib/postgresql/data
    healthcheck:
      test: ['CMD', 'pg_isready', '-U', 'airflow']
      interval: 5s
      retries: 5
    restart: always

  redis:
    image: redis:latest
    ports:
      - 6379:6379
    healthcheck:
      test: ['CMD', 'redis-cli', 'ping']
      interval: 5s
      timeout: 30s
      retries: 50
    restart: always

  airflow-webserver:
    <<: *airflow-common
    command: webserver
    ports:
      - 80:8080
    healthcheck:
      test: ['CMD', 'curl', '--fail', 'http://localhost:80/health']
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always

  airflow-scheduler:
    <<: *airflow-common
    command: scheduler
    healthcheck:
      test:
        [
          'CMD-SHELL',
          'airflow jobs check --job-type SchedulerJob --hostname "$${HOSTNAME}"',
        ]
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always

  airflow-worker:
    <<: *airflow-common
    command: celery worker
    healthcheck:
      test:
        - 'CMD-SHELL'
        - 'celery --app airflow.executors.celery_executor.app inspect ping -d "celery@$${HOSTNAME}"'
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always

  airflow-init:
    <<: *airflow-common
    command: version
    environment:
      <<: *airflow-common-env
      _AIRFLOW_DB_UPGRADE: 'true'
      _AIRFLOW_WWW_USER_CREATE: 'true'
      _AIRFLOW_WWW_USER_USERNAME: ${_AIRFLOW_WWW_USER_USERNAME:-airflow}
      _AIRFLOW_WWW_USER_PASSWORD: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow}

  flower:
    <<: *airflow-common
    command: celery flower
    ports:
      - 5555:5555
    healthcheck:
      test: ['CMD', 'curl', '--fail', 'http://localhost:5555/']
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always

volumes:
  postgres-db-volume:

```

**DAG:**
```python
from datetime import datetime, timedelta

import pendulum
from airflow import DAG
from airflow.operators.bash_operator import BashOperator
from airflow.providers.docker.operators.docker import DockerOperator
from airflow.operators.dummy_operator import DummyOperator

AMERICA_NEW_YORK_TIMEZONE = pendulum.timezone('US/Eastern')

default_args = {
    'owner': 'airflow',
    'description': 'Docker testing',
    'depend_on_past': False,
    'start_date': datetime(2021, 5, 1, tzinfo=AMERICA_NEW_YORK_TIMEZONE),
    'retries': 1,
    'retry_delay': timedelta(minutes=30),
}

with DAG(
    'docker_test',
    default_args=default_args,
    schedule_interval="15 20 * * *",
    catchup=False,
) as dag:
    start_dag = DummyOperator(task_id='start_dag')

    end_dag = DummyOperator(task_id='end_dag')

    t1 = BashOperator(task_id='print_current_date', bash_command='date')

    t2 = DockerOperator(
        task_id='docker_command_sleep',
        image='alpine',
        container_name='docker_command_sleep',
        api_version='1.30',
        auto_remove=True,
        command="/bin/sleep 3",
        docker_url="unix://var/run/docker.sock",
        network_mode="bridge",
        do_xcom_push=True,
    )

    start_dag >> t1

    t1 >> t2

    t2 >> end_dag
```


**Anything else we need to know**: Problem happens any time `DockerOperator` is being used. Not entirely sure why this happening given that the docker sock is fully permissive (has `777`) and is bind mounted into the container. When I test via *docker-py* client in Python shell under `airflow` user inside the container, it works perfectly fine to run all docker-py operations like listing running containers and such confirming the mounted docker UNIX socket is available and working. However, even with the `docker_url` pointing to the docker socket in the above DAG, I am getting this error thrown in above trace.

For whatever strange reason the logs say it's trying to connect over `http+docker://localhost/v1.30/containers/create` instead of the UNIX docker socket that's bind mounted and explicitly specified via `docker_url`. 
<!--

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Any relevant logs to include? Put them here in side a detail tag:
<details><summary>x.log</summary> lots of stuff </details>

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airflow/providers/docker/operators/docker.py
:param xcom_all: Push all the stdout or just the last line.
        The default is False (last line).
    :type xcom_all: bool
    :param docker_conn_id: The :ref:`Docker connection id <howto/connection:docker>`
    :type docker_conn_id: str
    :param dns: Docker custom DNS servers
    :type dns: list[str]
    :param dns_search: Docker custom DNS search domain
    :type dns_search: list[str]
    :param auto_remove: Auto-removal of the container on daemon side when the
        container's process exits.
        The default is False.
    :type auto_remove: bool
    :param shm_size: Size of ``/dev/shm`` in bytes. The size must be
        greater than 0. If omitted uses system default.
    :type shm_size: int
    :param tty: Allocate pseudo-TTY to the container
        This needs to be set see logs of the Docker container.
    :type tty: bool
    :param privileged: Give extended privileges to this container.
    :type privileged: bool
    :param cap_add: Include container capabilities
    :type cap_add: list[str]
    """
    template_fields = ('command', 'environment', 'container_name')
    template_ext = (
        '.sh',
        '.bash',
    )
    def __init__(