diff options
Diffstat (limited to 'src')
| -rw-r--r-- | src/extract_lambda.py | 131 |
1 files changed, 76 insertions, 55 deletions
diff --git a/src/extract_lambda.py b/src/extract_lambda.py index 15fe785..7efaac0 100644 --- a/src/extract_lambda.py +++ b/src/extract_lambda.py @@ -1,14 +1,15 @@ -from pg8000.native import Connection, InterfaceError, identifier -import boto3 import csv -from botocore.exceptions import ClientError -import logging import json -from datetime import datetime +import logging import re +from datetime import datetime +from io import StringIO +import boto3 +from botocore.exceptions import ClientError +from pg8000.native import Connection, InterfaceError, identifier -logger = logging.getLogger() +logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) # DB Exception class @@ -28,6 +29,7 @@ def lambda_handler(event, context): 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 """ + db = None try: db = connect_to_database() existing_files = list_existing_s3_files() @@ -39,14 +41,13 @@ def lambda_handler(event, context): "statusCode": 200, "body": json.dumps("No changes detected, no CSV files were uploaded."), } - else: - return { - "statusCode": 200, - "body": json.dumps( - f"""CSV files processed for {', '.join(any_changes['updated'])} and uploaded successfully.{ - 'The following tables were not updated: '+', '.join(any_changes['no change']) if any_changes['no change'] else ''}""" - ), - } + return { + "statusCode": 200, + "body": json.dumps( + f"""CSV files processed for {', '.join(any_changes['updated'])} and uploaded successfully.{ + 'The following tables were not updated: '+', '.join(any_changes['no change']) if any_changes['no change'] else ''}""" + ), + } except Exception as e: logger.error(f"Error: {e}") return {"statusCode": 500, "body": json.dumps("Internal server error.")} @@ -55,17 +56,24 @@ def lambda_handler(event, context): db.close() -def retrieve_secrets( - sm_client=boto3.client("secretsmanager"), secret_name="bentley-secrets" -): +def retrieve_secrets(): + secret_name = "bentley-secrets" + region_name = "eu-west-2" + + # Create a Secrets Manager client + session = boto3.session.Session() + client = session.client(service_name="secretsmanager", region_name=region_name) + try: - response = sm_client.get_secret_value(SecretId=secret_name) - if "SecretString" in response: - secret = json.loads(response["SecretString"]) - return secret + get_secret_value_response = client.get_secret_value(SecretId=secret_name) except ClientError as e: - logger.error(f"Could not retrieve secrets: {e}") + logger.error(f"Failed to retrieve secret {secret_name}: {str(e)}") raise e + except KeyError: + logger.error(f"Secret {secret_name} does not contain a SecretString") + raise ValueError(f"Secret {secret_name} does not contain a SecretString") + + return get_secret_value_response["SecretString"] def connect_to_database() -> Connection: @@ -123,6 +131,30 @@ def list_existing_s3_files(bucket_name=extract_bucket(), client=boto3.client("s3 return existing_files +def get_latest_timestamp(existing_files): + all_datetimes = [] + for file_name in existing_files.keys(): + match = re.search(r"\/(.+/).+_(.+)\.csv", file_name) + if match: + datetime_str = "".join(match.group(1, 2)) + all_datetimes.append(datetime.strptime(datetime_str, "%Y/%m/%d/%H:%M:%S")) + return max(all_datetimes) if all_datetimes else datetime.min + + +def stream_to_s3(table_name, rows, column_names, s3_client, bucket_name, s3_key): + csv_buffer = StringIO() + csv_writer = csv.writer(csv_buffer) + + csv_writer.writerow(column_names) + + for row in rows: + csv_writer.writerow(row) + + csv_buffer.seek(0) + + s3_client.upload_fileobj(csv_buffer, bucket_name, s3_key) + + 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 @@ -131,53 +163,42 @@ def process_and_upload_tables(db, existing_files, client=boto3.client("s3")): to files, or new tables/files it uploads them to the s3 bucket """ load_status = {"updated": [], "no change": []} - # Retrieving the latest file timestamp from S3 extract bucket - 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) + latest_timestamp = get_latest_timestamp(existing_files) - # Iterating through tables on the database and retrieving only latest changes vs previous file load tables = db.run( """ - SELECT table_name - FROM information_schema.tables - WHERE table_schema='public' AND table_type='BASE TABLE';""" + SELECT table_name + FROM information_schema.tables + WHERE table_schema='public' + AND table_type='BASE TABLE'; + """ ) + for table in tables: - print(tables) table_name = table[0] rows = db.run( f"SELECT * FROM {identifier(table_name)} WHERE last_updated >= :latest;", latest={datetime.strftime(latest_timestamp, "%Y-%m-%d %H:%M:%S")}, ) - print("rows", rows) - # Creating a temporary file path and writing the column name to it followed by each row of data 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( - """SELECT column_name FROM INFORMATION_SCHEMA.COLUMNS - WHERE table_name = :table ;""", - table=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" + column_names = [ + col_name[0] + for col_name in db.run( + """SELECT column_name FROM INFORMATION_SCHEMA.COLUMNS + WHERE table_name = :table ;""", + table=table_name, + ) + ] + + s3_key = ( + f"{table_name}/{datetime.now().strftime('%Y/%m/%d')}/" + f"{table_name}_{datetime.now().strftime('%H:%M:%S')}.csv" ) - # Writing the new file to S3 extract bucket: try: - client.upload_file(csv_file_path, extract_bucket(), s3_key) + stream_to_s3( + table_name, rows, column_names, client, extract_bucket(), s3_key + ) load_status["updated"].append(table_name) logger.info(f"Uploaded {s3_key} to S3.") except ClientError as e: |