{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "73496983-6bd2-413e-ae07-d8e090db51ae",
   "metadata": {},
   "source": [
    "# ... change the package settings?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fa4612a-bcb6-40f0-92a0-e9b75d3bcb44",
   "metadata": {},
   "source": [
    "Here are all settings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "18c84d99-1c68-44fb-aeb7-013e65fd45ba",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'return_xarray': True,\n",
       " 'advanced_shape_repr': True,\n",
       " 'natural_naming': True,\n",
       " 'hdf_compression': 'gzip',\n",
       " 'hdf_compression_opts': 5,\n",
       " 'adjusting_plotting_labels': True,\n",
       " 'xarray_unit_repr_in_plots': 'in',\n",
       " 'plotting_name_order': ('plot_name', 'long_name', 'standard_name'),\n",
       " 'require_unit': True,\n",
       " 'ureg_format': 'C~',\n",
       " 'init_logger_level': 'ERROR',\n",
       " 'dtime_fmt': '%Y%m%d%H%M%S%f',\n",
       " 'expose_user_prop_to_attrs': True,\n",
       " 'scale_attribute_name': 'scale',\n",
       " 'offset_attribute_name': 'offset',\n",
       " 'add_provenance': False,\n",
       " 'ignore_standard_attribute_errors': False,\n",
       " 'allow_deleting_standard_attributes': False,\n",
       " 'parallel_find': True}"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import h5rdmtoolbox as h5tbx\n",
    "\n",
    "h5tbx.get_config()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dfce8e4d-245a-44ad-8bad-2ef14dc8c522",
   "metadata": {},
   "source": [
    "Set a setting with context manager only for a block of code:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8a69b063-56ce-465e-a944-3f5ff2f01d00",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "berfore:  C~\n",
      "during:  L~\n",
      "after:  C~\n"
     ]
    }
   ],
   "source": [
    "print('berfore: ', h5tbx.get_config('ureg_format'))\n",
    "\n",
    "with h5tbx.set_config(ureg_format='L~'):\n",
    "    pass\n",
    "    print('during: ', h5tbx.get_config('ureg_format'))\n",
    "\n",
    "print('after: ', h5tbx.get_config('ureg_format'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2bfbe514-ae2d-4583-89f0-9f6ab66e3cf1",
   "metadata": {},
   "source": [
    "Set it for the session:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "22883f33-37c7-4317-80f0-4cd28ead53da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<h5rdmtoolbox._cfg.set_config at 0x1e68c2139d0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h5tbx.set_config(ureg_format='C~')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}