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debora.benedetto@hpe.com authoreddebora.benedetto@hpe.com authored
main.py 3.57 KiB
# Copyright 2022 Hewlett Packard Enterprise Development LP
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#-------------------------------------------------------------------------
#-------------------------------------------------------------------------
# PIACERE ICG Main
#
# This module has been tested with Python v3.9.7
# To use it you must first install PyEcore, PyYAML, Jinja2
# $ pip install pyecore~=0.12.2
# $ pip install PyYAML==6.0
# $ pip install Jinja2==3.0.3
#
# Usage: python main.py [-h] [-d dir] [-v] [--single] model
# -h prints usage
# -d dir loads metamodel from <dir>
# --single / --single_mmodel use the single (non-split) metamodel
# model the input model to be translated into the ICG intermediate representation
#
#-------------------------------------------------------------------------
import logging
import sys
from fastapi import FastAPI
import api.InfrastructureTemplateController
from controller import Orchestrator
from icgparser import ModelPrinter
fast_api = FastAPI()
fast_api.include_router(api.InfrastructureTemplateController.api_router)
logging.getLogger().setLevel(logging.INFO)
# -------------------------------------------------------------------------
# Parse parameters
# -------------------------------------------------------------------------
skip_next = False
doml_directory = "./icgparser/doml"
model_filename = "icgparser/doml/v1/nginx-aws_v1.domlx"
load_split_model = False
output_file_name = "iac_files.tar.gz"
# get metamodel directory from command line
def param_dir(pos, list):
global doml_directory
global skip_next
doml_directory = list[pos + 1]
print(f" doml_directory = {doml_directory} model_filename = {model_filename}")
skip_next = True
def param_help(pos, list):
print(f"\nUsage: {sys.argv[0]} [-h] [-d <doml_directory>] [--single] <model_filename>\n")
sys.exit()
# indicate to load the single-file metamodel (doml.ecore) instead of the split one
def param_single(pos, list):
global load_split_model
print(f"--> param_single({pos},{list}")
load_split_model = False
options = {'-d': param_dir, '-h': param_help, '--single_mmodel': param_single, '--single': param_single,
'--output': output_file_name}
argc = len(sys.argv)
paramlist = sys.argv[1:]
for i, param in enumerate(paramlist):
print(f"i={i} param={param} skip_next={skip_next}")
if param in options:
options[param](i, paramlist)
continue
if skip_next:
skip_next = False
continue
else:
model_filename = param
if __name__ == '__main__':
ModelPrinter.print_model(model_path=model_filename, is_multiecore_metamodel=load_split_model,
metamodel_directory=doml_directory)
compress_folder_info = Orchestrator.create_iac_from_doml_path(model_path=model_filename,
is_multiecore_metamodel=load_split_model,
metamodel_directory=doml_directory)