{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "aedbb9f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from dataclasses import dataclass, field, asdict\n",
    "from pathlib import Path\n",
    "\n",
    "import yaml\n",
    "\n",
    "\n",
    "@dataclass\n",
    "class GalleryItem:\n",
    "    name: str\n",
    "    path: Path\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "66624faf",
   "metadata": {},
   "outputs": [],
   "source": [
    "yaml_file = Path(\"config.yaml\")\n",
    "\n",
    "with open(yaml_file, \"r\") as f:\n",
    "    new_config: dict = yaml.safe_load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "40a472f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': 'test_1_plot',\n",
       " 'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/plot__proc_3_5606769559__cat_incl__var_jet1_pt.pdf'}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_config[\"sources\"][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "745c97ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[GalleryItem(name='test_1_plot', path=PosixPath('data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/plot__proc_3_5606769559__cat_incl__var_jet1_pt.pdf')),\n",
       " GalleryItem(name='test_2_dir', path=PosixPath('data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1'))]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sources = [\n",
    "    GalleryItem(name=src[\"name\"], path=Path(src[\"path\"]))\n",
    "    for src in new_config.get(\"sources\", False)\n",
    "]\n",
    "sources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a0102f9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Config(web_folder='', backup_folder='', png_dpi=400, plot_root='gallery', sources=[{'name': 'test_1_plot', 'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/plot__proc_3_5606769559__cat_incl__var_jet1_pt.pdf'}, {'name': 'test_2_dir', 'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/'}])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "@dataclass\n",
    "class Config:\n",
    "    web_folder: str = \"\"\n",
    "    backup_folder: str = \"\"\n",
    "    png_dpi: int = 400\n",
    "    plot_root: str = \"gallery\"\n",
    "    sources: list[GalleryItem] = field(default_factory=list)\n",
    "\n",
    "    @classmethod\n",
    "    def from_yaml(cls, yaml_file: str, strict: bool = False) -> \"Config\":\n",
    "        \"\"\"\n",
    "        Load configuration from a YAML file.\n",
    "\n",
    "        Args:\n",
    "            yaml_file (str): Path to the YAML file.\n",
    "            strict (bool):\n",
    "                If True, raises an error if a key in the YAML file does not exist in the Config class.\n",
    "                If False (default), adds all keys as attributes\n",
    "\n",
    "        Returns:\n",
    "            Config: Instance of this class\n",
    "        \"\"\"\n",
    "\n",
    "        with open(yaml_file, \"r\") as f:\n",
    "            new_config: dict = yaml.safe_load(f)\n",
    "\n",
    "        new_config[\"sources\"] = [\n",
    "            GalleryItem(name=src[\"name\"], path=Path(src[\"path\"]))\n",
    "            for src in new_config.get(\"sources\", False)\n",
    "        ]\n",
    "\n",
    "        instance = cls(**{\n",
    "            k: v\n",
    "            for k, v in new_config.items()\n",
    "            if hasattr(cls, k) or not strict\n",
    "        })\n",
    "\n",
    "        for key in new_config.keys():\n",
    "            if strict and not hasattr(instance, key):\n",
    "                raise KeyError(f\"Key '{key}' not found in Config class\")\n",
    "\n",
    "        return instance\n",
    "\n",
    "    def to_yaml(self, yaml_file: str) -> None:\n",
    "        \"\"\"\n",
    "        Save the current configuration to a YAML file.\n",
    "\n",
    "        Args:\n",
    "            yaml_file (str): Path to the YAML file.\n",
    "        \"\"\"\n",
    "        with open(yaml_file, \"w\") as f:\n",
    "            yaml.dump(asdict(self), f, default_flow_style=False)\n",
    "\n",
    "\n",
    "instance = Config(**{\n",
    "    k: v\n",
    "    for k, v in new_config.items()\n",
    "    #if hasattr(Config, k)\n",
    "})\n",
    "instance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0b516ae9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'name': 'test_1_plot',\n",
       "  'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/plot__proc_3_5606769559__cat_incl__var_jet1_pt.pdf'},\n",
       " {'name': 'test_2_dir',\n",
       "  'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/'}]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_config[\"sources\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b047f0c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'name': 'test_1_plot',\n",
       "  'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/plot__proc_3_5606769559__cat_incl__var_jet1_pt.pdf'},\n",
       " {'name': 'test_2_dir',\n",
       "  'path': 'data/cf_store/test_analysis/cf.PlotVariables1D/run2_2016_nano_v9/calib__test/sel__test/prod__test/weight__test/nominal/datasets_ttbar_dl/dev1/'}]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "instance.sources"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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",
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