def get_args():
""" This function gets settings based on arg_specs.csv
'schema' file and input file as specified in CLI.
"""
# should probably read system configuration settings here
# get CLI arguments
argspecs_df = DB.read_local_csv_to_df(file_path=ARG_SPECS_PATH, user_format=True, silent_error=False)
argspecs_dod = utils.df_to_dod(argspecs_df, field='name')
cli_argsdict = get_cli_args_per_argspecs_dod(argspecs_dod, description=DESCRIPTION)
# job configuration settings
# input file can be from CLI OR might be provided per API in job folder.
settings_file_name = cli_argsdict.get('input')
if settings_file_name:
# read the settings file and set the value according to the type specified in argspecs_dod.
inputdict = read_settings_csv_file(
dirname='input_files',
name=settings_file_name,
argspecs_dod=argspecs_dod,
name_field='argument',
value_field='value'
)
# at this point, inputdict contains arguments passed in input file.
# cli_argsdict will overwrite those in input file.
argsdict = {**inputdict, **cli_argsdict}
else:
argsdict = cli_argsdict
# now review argspecs to make sure all required records exist and are valid.
if (not check_args(argsdict, argspecs_dod) or
not custom_argsdict_checks(argsdict)):
sys.exit(1)
return argsdict
def read_argspecs_dod(file_path, field='name', user_format=False, silent_error=False):
""" read csv file and return dod with primary key being field.
"""
df = DB.read_local_csv_to_df(file_path, user_format=False, silent_error=False)
dod = utils.df_to_dod(df, field)
return dod
sns.publish(TopicArn=topic_arn, Message=msg, Subject=sub)
def lambda_handler(event, context):
updated_klayers = get_updated_klayer()
message = 'Hi, \n\n There is new version available for following kLayer:\n\n'
for updated_klayer in updated_klayers:
update_msg = f"KLayer Name: {updated_klayer['LayerName']}\nNew Version ARN: {updated_klayer['latest_klayer_arn']}\n\n"
message = message + update_msg
message = message + '\n\n\n\nYou may consider upgrading them\n\n'
instructions = "Instructions:\nTo create a layer or update with a new version you can add/update list of packages " \
"on a csv file at path 'input_files/layers_manager_input.csv' and run script from directory 'utilities/layers_manager.py' " \
"on your local machine. It will scan through the all listed layers and will deploy new if required.\n\n\n\n"
message = message + instructions
if len(updated_klayers) > 0:
publish_to_sns('KLayer New Version Available', message)
if __name__ == "__main__":
lambda_client = boto3.client('lambda')
file_path = '../input_files/layers_manager_input.csv'
input_df = DB.read_local_csv_to_df(file_path,
user_format=True,
silent_error=False)
for index, row in input_df.iterrows():
create_update_klayer(lambda_client, row['klayer-arn'], row['package'])
