Umang Shailesh Mistry
c210052952
Feature/ops scripts * Added comments to Aryan's script and added some more scripts * Search and Copy Script uploaded as a Python Notebook - with comments and markdown * Merged main into feature/ops_scripts * Merged main into feature/ops_scripts Approved-by: Michael McGuinness Approved-by: Chris Stobie
78 lines
3.3 KiB
Python
78 lines
3.3 KiB
Python
import boto3
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import pandas as pd
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from concurrent.futures import ThreadPoolExecutor, as_completed
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"""
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This script is used to search for files in a specific S3 bucket with a specific prefix and copy them to another S3 bucket with a different prefix.
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This is similar to the script s3_search_and_copy.py, but this script is designed to be used with a CSV file that contains a list of file names to search for in the prefix to limit the scope.
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"""
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s3_client = boto3.Session(profile_name='temp_cred').client('s3')
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def get_filenames_from_s3(bucket, prefix):
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paginator = s3_client.get_paginator('list_objects_v2')
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page_iterator = paginator.paginate(Bucket=bucket, Prefix=prefix)
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filenames = set()
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for page in page_iterator:
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if 'Contents' in page:
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for obj in page['Contents']:
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filenames.add((obj['Key'].split('/')[-1])[:-4])
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return filenames
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def copy_file_if_exists(file_name, source_bucket, source_prefix, destination_bucket, destination_prefix, existing_files):
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if file_name in existing_files:
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source_key = f"{source_prefix}/{file_name}".strip('/') + ".pdf"
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destination_key = f"{destination_prefix}/{file_name}".strip('/') + ".pdf"
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# s3_client.copy_object(
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# CopySource={'Bucket': source_bucket, 'Key': source_key},
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# Bucket=destination_bucket,
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# Key=destination_key
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# )
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response = s3_client.get_object(Bucket=source_bucket, Key=source_key)
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file_content = response['Body'].read()
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# print(f"Downloaded {source_key} from s3://{source_bucket}")
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s3_client.put_object(Bucket=destination_bucket, Key=destination_key, Body=file_content)
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print(f"Copied: {file_name} to {destination_prefix}")
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else:
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print(f"File not found: {file_name} in {source_prefix}")
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rerun = pd.concat([rerun, df[df['File name Without Extension'] == file_name]])
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def copy_files_multithreaded(file_list, source_bucket, source_prefix, destination_bucket, destination_prefix, existing_files, max_workers=20):
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with ThreadPoolExecutor(max_workers=max_workers) as executor:
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futures = [
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executor.submit(copy_file_if_exists, file_name, source_bucket, source_prefix, destination_bucket, destination_prefix, existing_files)
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for file_name in file_list
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]
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for future in as_completed(futures):
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try:
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future.result()
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except Exception as e:
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print(f"Error copying file: {e}")
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csv_path = 'new_duplicates_in_batch3.csv'
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file_name_column = 'File Name Without Extension'
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source_bucket = 'centene-national-contracting-files'
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search_prefix = 'batch_3_priority_files/txt_files'
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source_prefix = 'batch_3_priority_files/pdf_files'
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destination_bucket = 'centene-national-contracting-files'
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destination_prefix = 'batch_3_priority_files/re_run_files'
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df = pd.read_csv(csv_path)
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rerun = pd.DataFrame(columns=df.columns)
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file_names = df[file_name_column].dropna().tolist()
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print(f"Loaded {len(file_names)} file names from CSV.")
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existing_files = get_filenames_from_s3(source_bucket, search_prefix)
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print(f"Found {len(existing_files)} files in S3 source folder '{source_prefix}'.")
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copy_files_multithreaded(file_names, source_bucket, source_prefix, destination_bucket, destination_prefix, existing_files)
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rerun.reset_index(drop=True, inplace=True)
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rerun.to_csv('batch3_rerun.csv') |