from pg8000.native import Connection, InterfaceError import boto3 import csv from botocore.exceptions import ClientError import logging import json from datetime import datetime import re logger = logging.getLogger() logger.setLevel(logging.INFO) class DBConnectionException(Exception): """Wraps pg8000.native Error or DatabaseError.""" def __init__(self, e): """Initialise with provided error message.""" self.message = str(e) super().__init__(self.message) def lambda_handler(event, context): """This lambda function connects to the Totesys database, lists the contents of the ingestion bucket, and converts all tables to CSV and if any of those tables do not exist in, or are different to the ones in s3, it uploads them it uses 3 helper functions to achieve these 3 functionalities """ try: db = connect_to_database() existing_files = list_existing_s3_files() any_changes = process_and_upload_tables(db, existing_files) if not any_changes: logger.info("No changes detected in the database.") return { "statusCode": 200, "body": json.dumps("No changes detected, no CSV files were uploaded."), } else: return { "statusCode": 200, "body": json.dumps("CSV files processed and uploaded successfully."), } except Exception as e: logger.error(f"Error: {e}") return {"statusCode": 500, "body": json.dumps("Internal server error.")} finally: if db: db.close() def retrieve_secrets( sm_client=boto3.client("secretsmanager"), secret_name="bentley-secrets" ): try: response = sm_client.get_secret_value(SecretId=secret_name) if "SecretString" in response: secret = json.loads(response["SecretString"]) return secret except ClientError as e: logger.error(f"Could not retrieve secrets: {e}") raise e def connect_to_database() -> Connection: try: secrets = retrieve_secrets() host = secrets["host"] port = secrets["port"] user = secrets["user"] password = secrets["password"] database = secrets["database"] return Connection( database=database, user=user, password=password, host=host, port=port ) except InterfaceError as i: logger.error(f"Interface error: {i}") raise DBConnectionException("Failed to connect to database") def extract_bucket(client=boto3.client("s3")): response = client.list_buckets() extract_bucket_filter = [ bucket["Name"] for bucket in response["Buckets"] if "extract" in bucket["Name"] ] return extract_bucket_filter[0] def list_existing_s3_files(bucket_name=extract_bucket(), client=boto3.client("s3")): """Creates a dictionary and populates it with the results of listing the contents of the s3 bucket, then returns the populated dictionary """ existing_files = {} try: response = client.list_objects_v2(Bucket=bucket_name) if "Contents" in response: for obj in response["Contents"]: s3_key = obj["Key"] try: file_obj = client.get_object(Bucket=bucket_name, Key=s3_key) file_content = file_obj["Body"].read().decode("utf-8") existing_files[s3_key] = file_content except ClientError as e: logger.error(f"Error retrieving S3 object {s3_key}: {e}") else: logger.error("The bucket is empty") except ClientError as e: logger.error(f"Error listing S3 objects: {e}") return existing_files def process_and_upload_tables(db, existing_files, client=boto3.client("s3")): """Creates a list of the tables from a database query and then selects everything from each table in individual queries it then writes each table to CSV files and compares with the item in the existing_files dictionary with the same name. If it finds any changes to files, or new tables/files it uploads them to the s3 bucket """ # NEW CODE all_datetimes = [] for file_names in existing_files.keys(): datetime_str_on_s3 = "".join( re.search(r"\/(.+/).+_(.+)\.csv", file_names).group(1, 2) ) all_datetimes.append(datetime.strptime(datetime_str_on_s3, "%Y/%m/%d/%H:%M:%S")) latest_timestamp = max(all_datetimes) # END OF NEW CODE tables = db.run( "SELECT table_name FROM information_schema.tables WHERE table_schema='public' AND table_type='BASE TABLE';" ) print(tables) for table in tables: table_name = table[0] rows = db.run( f"SELECT * FROM {table_name} WHERE last_updated >= {datetime.strftime(latest_timestamp,'%H-%m-%d %H:%M:%S')};" ) if rows: csv_file_path = f"/tmp/{table_name}.csv" with open(csv_file_path, "w", newline="") as file: writer = csv.writer(file) # column_names = [desc["name"] for desc in db.columns(f"SELECT * FROM {table_name};")] column_names = [ col_name[0] for col_name in db.run( f"SELECT column_name FROM INFORMATION_SCHEMA.COLUMNS where table_name = '{table_name}';" ) ] writer.writerow(column_names) writer.writerows(rows) s3_key = datetime.strftime( datetime.today(), f"{table_name}/%Y/%m/%d/{table_name}_%H:%M:%S.csv" ) try: client.upload_file(csv_file_path, extract_bucket(), s3_key) logger.info(f"Uploaded {s3_key} to S3.") except ClientError as e: logger.error(f"Error uploading to S3: {e}") else: logger.info(f"No new data.")