added code preference

# process multiple images in an exposure (RECOMMENDED, at least for MBI or SLS)

# define a single job

def one_job(dm, detector):

def one_job(dm: CsstMsDataManager, detector: int):

    """ Process a single image, defined for parallel processing. """

    filepath_input = dm.l0_detector(detector=detector)

    filepath_output = dm.l1_detector(detector=detector, post="L1_processed.fits")

    return

# parallel processing jobs

# process in serial / parallel

def process_multiple_images(

        dm: CsstMsDataManager,

        logger: Union[None, logging.Logger] = None,

   vcs.rst

   packaging.rst

   codestyle.rst

   packages/packages.rst

   preference/preference.rst

   unittest.rst

   simulation.rst

   csst_common/csst_common.rst

Package preference

==================

Code Preference

===============

Initially we want our developers to following the

`coding guidelines for astropy-affiliated packages <https://docs.astropy.org/en/latest/development/codeguide.html>`_

as much as possible.

A few important conventions and special cases should be outlined here.

Basic preference

----------------

Package preference

------------------

Several packages are favored over others if they can be used to solve the problem under study.

Developers should use them as much as possible.

For parallel computing with inter-communication or distributed computing,

we recommend developers to consider using ``mpi4py``: https://github.com/mpi4py/mpi4py.

Global variables

----------------

Usage of ``global`` should be prohibited.

In most cases, variables should be kept in their default scopes.

Using ``subprocess``

--------------------

``subprocess.run()`` is favored over ``subprocess.Popen()`` and ``os.system()`` as suggested in Python documentation:

- The ``subprocess`` module allows you to spawn new processes, connect to their input/output/error pipes,

  and obtain their return codes. This module intends to replace several older modules and functions:

  .. code-block:: python

     os.system

     os.spawn*

- The recommended approach to invoking ``subprocesses`` is to use the ``run()`` function for all use cases

  it can handle. For more advanced use cases, the underlying ``Popen`` interface can be used directly.

Numpy multithreading

--------------------

Numpy sometime automatically uses multithreading. To see if you are actually using OpenBLAS or MKL, use

.. code-block:: python

    numpy.__config__.show()

To set shut down this feature, use

.. code-block:: python

    export MKL_NUM_THREADS=1

    export NUMEXPR_NUM_THREADS=1

    export OMP_NUM_THREADS=1

    export VECLIB_MAXIMUM_THREADS=1

.. note::

    In most cases, this automatic multithreading does not enhance the performance in practice.

    Therefore, the above setting will be used in CSST pipeline globally.