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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "8f33ab85",
"metadata": {},
"outputs": [],
"source": [
"import os"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "5b55e660",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'f:\\\\Projects\\\\End-to-End-Chest-Cancer-Classification-using-MLflow-and-DVC\\\\research'"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%pwd"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "b7338c82",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'f:\\\\Projects\\\\End-to-End-Chest-Cancer-Classification-using-MLflow-and-DVC'"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.chdir(\"../\")\n",
"%pwd"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "a770b8df",
"metadata": {},
"outputs": [],
"source": [
"from dataclasses import dataclass\n",
"from pathlib import Path\n",
"\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": 6,
"id": "979add90",
"metadata": {},
"outputs": [],
"source": [
"from cnnClassifier.constants import *\n",
"from cnnClassifier.utils.common import read_yaml, create_directories\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.artifacts_root])\n",
"\n",
" def get_data_ingestion_config(self) -> DataIngestionConfig:\n",
" config = self.config.data_ingestion\n",
"\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"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "e4fd8f68",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2025-08-18 00:24:08,669: INFO: common: yaml file: config\\config.yaml loaded successfully]\n",
"[2025-08-18 00:24:08,684: INFO: common: yaml file: params.yaml loaded successfully]\n",
"[2025-08-18 00:24:08,686: INFO: common: created directory at: artifacts]\n",
"[2025-08-18 00:24:08,688: INFO: common: created directory at: artifacts/data_ingestion]\n",
"[2025-08-18 00:24:08,692: INFO: 78466947: Downloading data from https://drive.google.com/file/d/1z0mreUtRmR-P-magILsDR3T7M6IkGXtY/view?usp=sharing into file artifacts/data_ingestion/data.zip]\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Downloading...\n",
"From (original): https://drive.google.com/uc?/export=download&id=1z0mreUtRmR-P-magILsDR3T7M6IkGXtY\n",
"From (redirected): https://drive.google.com/uc?%2Fexport=download&id=1z0mreUtRmR-P-magILsDR3T7M6IkGXtY&confirm=t&uuid=954f5f66-c0d6-4c40-a993-933880515813\n",
"To: f:\\Projects\\End-to-End-Chest-Cancer-Classification-using-MLflow-and-DVC\\artifacts\\data_ingestion\\data.zip\n",
"100%|██████████| 49.0M/49.0M [00:24<00:00, 2.03MB/s]"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2025-08-18 00:24:36,267: INFO: 78466947: Downloaded data from https://drive.google.com/file/d/1z0mreUtRmR-P-magILsDR3T7M6IkGXtY/view?usp=sharing into file artifacts/data_ingestion/data.zip]\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"import os\n",
"import zipfile\n",
"import gdown\n",
"from cnnClassifier import logger\n",
"from cnnClassifier.utils.common import get_size\n",
"\n",
"class DataIngestion:\n",
" def __init__(self, config: DataIngestionConfig):\n",
" self.config = config\n",
"\n",
"\n",
" \n",
" \n",
" def download_file(self)-> str:\n",
" '''\n",
" Fetch data from the url\n",
" '''\n",
"\n",
" try: \n",
" dataset_url = self.config.source_URL\n",
" zip_download_dir = self.config.local_data_file\n",
" os.makedirs(\"artifacts/data_ingestion\", exist_ok=True)\n",
" logger.info(f\"Downloading data from {dataset_url} into file {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",
"\n",
" logger.info(f\"Downloaded data from {dataset_url} into file {zip_download_dir}\")\n",
"\n",
" except Exception as e:\n",
" raise e\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)\n",
"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.extract_zip_file()\n",
"except Exception as e:\n",
" raise e"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "cnn_env",
"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": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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