from airflow.jobs.job import Job
    from airflow.models.taskinstance import TaskInstance
SIGSEGV_MESSAGE = """
******************************************* Received SIGSEGV *******************************************
SIGSEGV (Segmentation Violation) signal indicates Segmentation Fault error which refers to
an attempt by a program/library to write or read outside its allocated memory.
In Python environment usually this signal refers to libraries which use low level C API.
Make sure that you use right libraries/Docker Images
for your architecture (Intel/ARM) and/or Operational System (Linux/macOS).
Suggested way to debug
======================
  - Set environment variable 'PYTHONFAULTHANDLER' to 'true'.
  - Start airflow services.
  - Restart failed airflow task.
  - Check 'scheduler' and 'worker' services logs for additional traceback
    which might contain information about module/library where actual error happen.
Known Issues
============
Note: Only Linux-based distros supported as "Production" execution environment for Airflow.
macOS
-----
 1. Due to limitations in Apple's libraries not every process might 'fork' safe.
    One of the general error is unable to query the macOS system configuration for network proxies.
    If your are not using a proxy you could disable it by set environment variable 'no_proxy' to '*'.
    See: https://github.com/python/cpython/issues/58037 and https://bugs.python.org/issue30385#msg293958
********************************************************************************************************"""
class LocalTaskJobRunner(BaseJobRunner, LoggingMixin):
    """LocalTaskJob runs a single task instance."""
    job_type = "LocalTaskJob"
    def __init__(