cars.orchestrator.cluster.log_wrapper
=====================================

.. py:module:: cars.orchestrator.cluster.log_wrapper

.. autoapi-nested-parse::

   Contains functions for wrapper logs



Attributes
----------

.. autoapisummary::

   cars.orchestrator.cluster.log_wrapper.THREAD_TIMEOUT


Classes
-------

.. autoapisummary::

   cars.orchestrator.cluster.log_wrapper.CarsMemProf


Functions
---------

.. autoapisummary::

   cars.orchestrator.cluster.log_wrapper.log_function
   cars.orchestrator.cluster.log_wrapper.log_message
   cars.orchestrator.cluster.log_wrapper.loop_function
   cars.orchestrator.cluster.log_wrapper.get_current_memory
   cars.orchestrator.cluster.log_wrapper.log_delta_memory
   cars.orchestrator.cluster.log_wrapper.exception_safe
   cars.orchestrator.cluster.log_wrapper.generate_summary
   cars.orchestrator.cluster.log_wrapper.generate_pdf_profiling
   cars.orchestrator.cluster.log_wrapper.filter_lists
   cars.orchestrator.cluster.log_wrapper.generate_boxplot
   cars.orchestrator.cluster.log_wrapper.generate_histo
   cars.orchestrator.cluster.log_wrapper.generate_pie_chart
   cars.orchestrator.cluster.log_wrapper.cars_profile


Module Contents
---------------

.. py:data:: THREAD_TIMEOUT
   :value: 2


.. py:function:: log_function(*argv, **kwargs)

   Create a wrapper for function running it

   :param argv: args of func
   :param kwargs: kwargs of func

   :return: path to results


.. py:function:: log_message(func, message)

   log profiling message

   :param func : logged function
   :param message : log message


.. py:function:: loop_function(argv, kwargs, func, nb_iteration=5)

   generate a loop on each cluster function to eval possible leak

   :param argv : input argv
   :param kwargs : input kwargs
   :param func : function to evaluation
   :param nb_iteration (int, optional): number of the iteration loop.
   :param Defaults to 5.

   Returns:
       _type_: result of the function


.. py:function:: get_current_memory()

   Get current memory of process

   :return: memory
   :rtype: float



.. py:function:: log_delta_memory(func, memory_start, memory_end)

   Log memory infos

   :param func: profiled function
   :param memory_start: memory before the run of function
   :type memory_start: float
   :param memory_end: memory after the run of function
   :type memory_end: float



.. py:function:: exception_safe(func)

   Decorator for consistent exception handling in profiling functions

   :param func: function to wrap
   :return: wrapped function


.. py:function:: generate_summary(out_dir, used_conf, pipeline_name, clean_worker_logs=False)

   Generate Profiling summary


.. py:function:: generate_pdf_profiling(log_dir)

   Generate PDF profiling summary for all res


.. py:function:: filter_lists(names, data, cond)

   Filter lists with condition on name


.. py:function:: generate_boxplot(axis, names, data_full, title, data_type)

   Generate boxplot


.. py:function:: generate_histo(axis, names, data, title, data_type, data_min_err=None, data_max_err=None)

   Generate histogram


.. py:function:: generate_pie_chart(axis, names, data, title)

   Generate pie chart, data in %


.. py:function:: cars_profile(name=None, interval=0.1)

   CARS profiling decorator

   :param: func: function to monitor



.. py:class:: CarsMemProf(pid, pipe, interval=0.1)

   Bases: :py:obj:`threading.Thread`


   CarsMemProf

   Profiling thread


   .. py:attribute:: pipe


   .. py:attribute:: interval
      :value: 0.1



   .. py:attribute:: cpu_interval
      :value: 0.1



   .. py:attribute:: process


   .. py:method:: run()

      Run