{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.chdir('../')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# entity\n",
    "from dataclasses import dataclass\n",
    "from pathlib import Path\n",
    "\n",
    "@dataclass(frozen=True)\n",
    "class DataIngestionConfig:\n",
    "    root_dir: Path\n",
    "    source_URL: str\n",
    "    local_data_file: Path\n",
    "    unzip_dir: Path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cnnClassifier.utils.common import read_yaml, create_directories\n",
    "from cnnClassifier.constant import *\n",
    "# Configuration\n",
    "class ConfigurationManager:\n",
    "    def __init__(\n",
    "        self,\n",
    "        config_filepath = CONFIG_FILE_PATH,\n",
    "        params_filepath = PARAMS_FILE_PATH\n",
    "    ):\n",
    "        self.config = read_yaml(config_filepath)\n",
    "        self.params = read_yaml(params_filepath)\n",
    "        \n",
    "        create_directories([self.config.atifacts_root])\n",
    "        \n",
    "        \n",
    "        \n",
    "    def get_data_ingestion_config(self) -> DataIngestionConfig:\n",
    "        config = self.config.data_ingestion\n",
    "        create_directories([config.root_dir])\n",
    "        \n",
    "        data_ingestion_config = DataIngestionConfig(\n",
    "            root_dir=config.root_dir,\n",
    "            source_URL=config.source_URL,\n",
    "            local_data_file=config.local_data_file,\n",
    "            unzip_dir=config.unzip_dir\n",
    "        )\n",
    "        \n",
    "        return data_ingestion_config\n",
    "    \n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# components\n",
    "\n",
    "import os\n",
    "import zipfile\n",
    "import gdown\n",
    "from cnnClassifier import logger\n",
    "from cnnClassifier.utils.common import get_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "class DataIngestion:\n",
    "    def __init__(self, config: DataIngestionConfig):\n",
    "        self.config = config\n",
    "        \n",
    "    def download_file(self) -> str:\n",
    "        try:\n",
    "            dataset_url = self.config.source_URL\n",
    "            zip_download_dir = self.config.local_data_file\n",
    "            os.makedirs('artifacts/datasets', exist_ok=True)\n",
    "            logger.info(f'Downloading data from {dataset_url} into {zip_download_dir}')\n",
    "            \n",
    "            file_id = dataset_url.split('/')[-2]\n",
    "            prefix = 'https://drive.google.com/uc?/export=download&id='\n",
    "            gdown.download(prefix + file_id, zip_download_dir)\n",
    "            logger.info(f'Downloaded data from {dataset_url} into {zip_download_dir}')\n",
    "            \n",
    "        except Exception as e:\n",
    "            raise e\n",
    "        \n",
    "        \n",
    "        \n",
    "    def extract_zip_file(self):\n",
    "        \"\"\"\n",
    "        zip_file_path: str\n",
    "        Extracts the zip file into the data directory\n",
    "        Function returns None\n",
    "        \"\"\"\n",
    "        unzip_path = self.config.unzip_dir\n",
    "        os.makedirs(unzip_path, exist_ok=True)\n",
    "        with zipfile.ZipFile(self.config.local_data_file, 'r') as zip_ref:\n",
    "            zip_ref.extractall(unzip_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  5%|▍         | 2.62M/57.7M [00:30<03:49, 240kB/s]"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    config = ConfigurationManager()\n",
    "    data_ingestion_config = config.get_data_ingestion_config()\n",
    "    data_ingestion = DataIngestion(config=data_ingestion_config)\n",
    "    data_ingestion.download_file()\n",
    "    data_ingestion.extrat_zip_file()\n",
    "except Exception as e:\n",
    "    raise e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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