| #!/usr/bin/env python3 |
| |
| # Copyright 2019-present Open Networking Foundation |
| # |
| # 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. |
| |
| """ |
| Workflow Essence Extractor |
| |
| This module extracts essence of airflow workflows |
| Following information will be extracted from workflow code |
| - DAG info |
| - Operator info |
| - CORD-related operators |
| - Airflow operators |
| - Dependency info |
| """ |
| |
| import ast |
| import json |
| import os.path |
| import argparse |
| import pyfiglet |
| |
| from multistructlog import create_logger |
| |
| |
| progargs = { |
| 'logging': None |
| } |
| |
| DEFAULT_CONFIG_FILE_PATH = '/etc/cord_workflow_airflow_extensions/config.json' |
| |
| |
| class NoopLogger(object): |
| def __init__(self): |
| pass |
| |
| def info(self, *args): |
| pass |
| |
| def debug(self, *args): |
| pass |
| |
| def error(self, *args): |
| pass |
| |
| def warn(self, *args): |
| pass |
| |
| |
| class EssenceExtractor(object): |
| def __init__(self, logger=None): |
| if logger: |
| self.logger = logger |
| else: |
| self.logger = NoopLogger() |
| |
| self.tree = None |
| |
| def set_logger(self, logger): |
| self.logger = logger |
| |
| def get_logger(self): |
| return self.logger |
| |
| def get_ast(self): |
| return self.tree |
| |
| def parse_code(self, code): |
| tree = ast.parse(code) |
| self.tree = self.__jsonify_ast(tree) |
| |
| def parse_codefile(self, filepath): |
| code = None |
| with open(filepath, "r") as f: |
| code = f.read() |
| tree = ast.parse(code, filepath) |
| self.tree = self.__jsonify_ast(tree) |
| |
| def __classname(self, cls): |
| return cls.__class__.__name__ |
| |
| def __jsonify_ast(self, node, level=0): |
| fields = {} |
| for k in node._fields: |
| fields[k] = '...' |
| v = getattr(node, k) |
| if isinstance(v, ast.AST): |
| if v._fields: |
| fields[k] = self.__jsonify_ast(v) |
| else: |
| fields[k] = self.__classname(v) |
| |
| elif isinstance(v, list): |
| fields[k] = [] |
| for e in v: |
| fields[k].append(self.__jsonify_ast(e)) |
| |
| elif isinstance(v, str): |
| fields[k] = v |
| |
| elif isinstance(v, int) or isinstance(v, float): |
| fields[k] = v |
| |
| elif v is None: |
| fields[k] = None |
| |
| else: |
| fields[k] = 'unrecognized' |
| |
| ret = { |
| self.__classname(node): fields |
| } |
| return ret |
| |
| def __recursively_find_elements(self, tree, elem): |
| """ |
| traverse AST and find elements |
| """ |
| for e in tree: |
| obj = None |
| if isinstance(tree, list): |
| obj = e |
| elif isinstance(tree, dict): |
| obj = tree[e] |
| |
| if e == elem: |
| yield obj |
| |
| if obj and (isinstance(obj, list) or isinstance(obj, dict)): |
| for y in self.__recursively_find_elements(obj, elem): |
| yield y |
| |
| def __extract_func_calls(self, tree, func_name): |
| """ |
| extract function calls with assignment |
| """ |
| assigns = self.__recursively_find_elements(tree, "Assign") |
| if assigns: |
| for assign in assigns: |
| found = False |
| |
| calls = self.__recursively_find_elements(assign, "Call") |
| if calls: |
| for call in calls: |
| funcs = self.__recursively_find_elements(call, "func") |
| if funcs: |
| for func in funcs: |
| if "Name" in func: |
| name = func["Name"] |
| if "ctx" in name and "id" in name: |
| # found function |
| if name["id"] == func_name: |
| found = True |
| |
| if found: |
| yield assign |
| |
| def __extract_func_calls_airflow_operators(self, tree): |
| """ |
| extract only airflow operators which end with "*Operator" or "*Sensor" |
| """ |
| assigns = self.__recursively_find_elements(tree, "Assign") |
| if assigns: |
| for assign in assigns: |
| found = False |
| |
| calls = self.__recursively_find_elements(assign, "Call") |
| if calls: |
| for call in calls: |
| funcs = self.__recursively_find_elements(call, "func") |
| if funcs: |
| for func in funcs: |
| if "Name" in func: |
| name = func["Name"] |
| if "ctx" in name and "id" in name: |
| # found function |
| if name["id"].endswith(("Operator", "Sensor")): |
| found = True |
| |
| if found: |
| yield assign |
| |
| def __extract_bin_op(self, tree, op_name): |
| """ |
| extract binary operation such as >>, << |
| """ |
| ops = self.__recursively_find_elements(tree, "BinOp") |
| if ops: |
| for op in ops: |
| if op["op"] == op_name: |
| yield op |
| |
| def __take_string_or_tree(self, tree): |
| if "Str" in tree: |
| return tree["Str"]["s"] |
| return tree |
| |
| def __take_num_or_tree(self, tree): |
| if "Num" in tree: |
| return tree["Num"]["n"] |
| return tree |
| |
| def __take_id_or_tree(self, tree): |
| if "Name" in tree: |
| return tree["Name"]["id"] |
| return tree |
| |
| def __take_name_constant_or_tree(self, tree): |
| if "NameConstant" in tree: |
| return tree["NameConstant"]["value"] |
| return tree |
| |
| def __take_value_or_tree(self, tree): |
| if "Str" in tree: |
| return tree["Str"]["s"] |
| elif "Num" in tree: |
| return tree["Num"]["n"] |
| elif "Name" in tree: |
| val = tree["Name"]["id"] |
| if val in ["True", "False"]: |
| return bool(val) |
| elif val == "None": |
| return None |
| return val |
| elif "NameConstant" in tree: |
| val = tree["NameConstant"]["value"] |
| if val in ["True", "False"]: |
| return bool(val) |
| elif val == "None": |
| return None |
| return val |
| elif "List" in tree: |
| vals = [] |
| if "elts" in tree["List"]: |
| elts = tree["List"]["elts"] |
| for elt in elts: |
| val = self.__take_value_or_tree(elt) |
| vals.append(val) |
| return vals |
| return tree |
| |
| def __make_dag(self, tree): |
| loc_val = None |
| dag_id = None |
| |
| if "targets" in tree: |
| targets = tree["targets"] |
| loc_val = self.__take_id_or_tree(targets[0]) |
| |
| if "value" in tree: |
| value = tree["value"] |
| if "Call" in value: |
| call = value["Call"] |
| if "keywords" in call: |
| keywords = call["keywords"] |
| for keyword in keywords: |
| if "keyword" in keyword: |
| k = keyword["keyword"] |
| if k["arg"] == "dag_id": |
| dag_id = self.__take_string_or_tree(k["value"]) |
| |
| return { |
| 'local_variable': loc_val, |
| 'dag_id': dag_id |
| } |
| |
| def __make_airflow_operator(self, tree): |
| airflow_operator = {} |
| |
| if "targets" in tree: |
| targets = tree["targets"] |
| loc_val = self.__take_id_or_tree(targets[0]) |
| airflow_operator["local_variable"] = loc_val |
| |
| if "value" in tree: |
| value = tree["value"] |
| if "Call" in value: |
| call = value["Call"] |
| if "func" in call: |
| class_name = self.__take_id_or_tree(call["func"]) |
| airflow_operator["class"] = class_name |
| |
| if "keywords" in call: |
| keywords = call["keywords"] |
| for keyword in keywords: |
| if "keyword" in keyword: |
| k = keyword["keyword"] |
| arg = k["arg"] |
| airflow_operator[arg] = self.__take_value_or_tree(k["value"]) |
| |
| return airflow_operator |
| |
| def __make_dependencies_bin_op(self, tree, dependencies): |
| children = [] |
| parents = [] |
| child = None |
| parent = None |
| |
| if tree["op"] == "RShift": |
| child = self.__take_id_or_tree(tree["right"]) |
| parent = self.__take_id_or_tree(tree["left"]) |
| elif tree["op"] == "LShift": |
| child = self.__take_id_or_tree(tree["left"]) |
| parent = self.__take_id_or_tree(tree["right"]) |
| |
| if child: |
| if isinstance(child, dict): |
| if "List" in child: |
| for c in child["List"]["elts"]: |
| children.append(self.__take_id_or_tree(c)) |
| elif "BinOp" in child: |
| deps = self.__make_dependencies_bin_op(child["BinOp"], dependencies) |
| for dep in deps: |
| children.append(dep) |
| else: |
| children.append(self.__take_id_or_tree(child)) |
| else: |
| children.append(child) |
| |
| if parent: |
| if isinstance(parent, dict): |
| if "List" in parent: |
| for p in parent["List"]["elts"]: |
| parents.append(self.__take_id_or_tree(p)) |
| elif "BinOp" in parent: |
| deps = self.__make_dependencies_bin_op(parent["BinOp"], dependencies) |
| for dep in deps: |
| parents.append(dep) |
| else: |
| parents.append(self.__take_id_or_tree(parent)) |
| else: |
| parents.append(parent) |
| |
| if len(parents) > 0 and len(children) > 0: |
| # make all-vs-all combinations |
| for p in parents: |
| for c in children: |
| dep = { |
| 'parent': p, |
| 'child': c |
| } |
| dependencies.append(dep) |
| |
| if tree["op"] == "RShift": |
| return children |
| elif tree["op"] == "LShift": |
| return parents |
| return children |
| |
| def __extract_dep_operations(self, tree): |
| # extract dependency definition using ">>" |
| ops = self.__extract_bin_op(tree, "RShift") |
| if ops: |
| for op in ops: |
| deps = [] |
| self.__make_dependencies_bin_op(op, deps) |
| for dep in deps: |
| yield dep |
| |
| # extract dependency definition using "<<" |
| ops = self.__extract_bin_op(tree, "LShift") |
| if ops: |
| for op in ops: |
| deps = [] |
| self.__make_dependencies_bin_op(op, deps) |
| for dep in deps: |
| yield dep |
| |
| def __extract_dags(self, tree): |
| dags = {} |
| calls = self.__extract_func_calls(tree, "DAG") |
| if calls: |
| for call in calls: |
| dag = self.__make_dag(call) |
| dagid = dag["dag_id"] |
| dags[dagid] = dag |
| return dags |
| |
| def __extract_CORD_event_sensors(self, tree): |
| operators = {} |
| calls = self.__extract_func_calls(tree, "CORDEventSensor") |
| if calls: |
| for call in calls: |
| operator = self.__make_airflow_operator(call) |
| operatorid = operator["task_id"] |
| operators[operatorid] = operator |
| return operators |
| |
| def __extract_CORD_model_sensors(self, tree): |
| operators = {} |
| calls = self.__extract_func_calls(tree, "CORDModelSensor") |
| if calls: |
| for call in calls: |
| operator = self.__make_airflow_operator(call) |
| operatorid = operator["task_id"] |
| operators[operatorid] = operator |
| return operators |
| |
| def __extract_CORD_model_operators(self, tree): |
| operators = {} |
| calls = self.__extract_func_calls(tree, "CORDModelOperator") |
| if calls: |
| for call in calls: |
| operator = self.__make_airflow_operator(call) |
| operatorid = operator["task_id"] |
| operators[operatorid] = operator |
| return operators |
| |
| def __extract_airflow_operators(self, tree): |
| operators = {} |
| calls = self.__extract_func_calls_airflow_operators(tree) |
| if calls: |
| for call in calls: |
| operator = self.__make_airflow_operator(call) |
| operatorid = operator["task_id"] |
| operators[operatorid] = operator |
| return operators |
| |
| def __extract_all_operators(self, tree): |
| operators = {} |
| event_sensors = self.__extract_CORD_event_sensors(tree) |
| if event_sensors: |
| for task_id in event_sensors: |
| operators[task_id] = event_sensors[task_id] |
| |
| model_sensors = self.__extract_CORD_model_sensors(tree) |
| if model_sensors: |
| for task_id in model_sensors: |
| operators[task_id] = model_sensors[task_id] |
| |
| model_operators = self.__extract_CORD_model_operators(tree) |
| if model_operators: |
| for task_id in model_operators: |
| operators[task_id] = model_operators[task_id] |
| |
| airflow_operators = self.__extract_airflow_operators(tree) |
| if airflow_operators: |
| for task_id in airflow_operators: |
| # add operators that are not already handled above |
| if task_id not in operators: |
| operators[task_id] = airflow_operators[task_id] |
| |
| return operators |
| |
| def __extract_dependencies(self, tree): |
| """ |
| Build N-N dependencies from fragmented parent-child relations |
| A node can have multiple parents and multiple children |
| """ |
| dependencies = {} |
| ops = self.__extract_dep_operations(tree) |
| if ops: |
| for op in ops: |
| p = op["parent"] |
| c = op["child"] |
| |
| if p in dependencies: |
| # append to an existing list |
| node_p = dependencies[p] |
| if "children" in node_p: |
| # prevent duplicates |
| if c not in node_p["children"]: |
| node_p["children"].append(c) |
| else: |
| node_p["children"] = [c] |
| else: |
| # create a new |
| node_p = { |
| 'children': [c] |
| } |
| dependencies[p] = node_p |
| |
| if c in dependencies: |
| # append to an existing list |
| node_c = dependencies[c] |
| if "parents" in node_c: |
| # prevent duplicates |
| if p not in node_c["parents"]: |
| node_c["parents"].append(p) |
| else: |
| node_c["parents"] = [p] |
| else: |
| # create a new |
| node_c = { |
| 'parents': [p] |
| } |
| dependencies[c] = node_c |
| |
| return dependencies |
| |
| def extract(self): |
| """ |
| Build highlevel information of workflows dag, operators and dependencies refers to each other |
| """ |
| if self.tree: |
| dags = self.__extract_dags(self.tree) |
| operators = self.__extract_all_operators(self.tree) |
| dependencies = self.__extract_dependencies(self.tree) |
| |
| dag_dict = {} |
| for dag_id in dags: |
| dag = dags[dag_id] |
| dag_var = dag["local_variable"] |
| |
| # filter operators that do not belong to the dag |
| my_operators = {} |
| my_operators_var = {} |
| for task_id in operators: |
| operator = operators[task_id] |
| if operator["dag"] == dag_var: |
| # set dag_id |
| operator["dag_id"] = dag_id |
| my_operators[task_id] = operator |
| |
| # this is to help fast search while working with dependencies |
| operator_local_var = operator["local_variable"] |
| my_operators_var[operator_local_var] = operator |
| |
| # filter dependencies that do not belong to the dag |
| my_dependencies = {} |
| for task_var in dependencies: |
| if task_var in my_operators_var: |
| dependency = dependencies[task_var] |
| task_id = my_operators_var[task_var]["task_id"] |
| |
| # convert dependency task_var to task_id |
| dep = {} |
| if "children" in dependency: |
| dep["children"] = [] |
| for child in dependency["children"]: |
| if child in my_operators_var: |
| child_task_id = my_operators_var[child]["task_id"] |
| dep["children"].append(child_task_id) |
| |
| if "parents" in dependency: |
| dep["parents"] = [] |
| for parent in dependency["parents"]: |
| if parent in my_operators_var: |
| parent_task_id = my_operators_var[parent]["task_id"] |
| dep["parents"].append(parent_task_id) |
| |
| my_dependencies[task_id] = dep |
| |
| d = { |
| 'dag': dag, |
| 'tasks': my_operators, |
| 'dependencies': my_dependencies |
| } |
| dag_dict[dag_id] = d |
| |
| return dag_dict |
| else: |
| return None |
| |
| |
| """ |
| Command-line tool |
| """ |
| |
| |
| def print_graffiti(): |
| result = pyfiglet.figlet_format("CORD\nWorkflow\nEssence\nExtractor", font="graffiti") |
| print(result) |
| |
| |
| def get_arg_parser(): |
| parser = argparse.ArgumentParser(description='CORD Workflow Essence Extractor.', prog='essence_extractor') |
| parser.add_argument('--config', help='locate a configuration file') |
| parser.add_argument('-o', '--output', help='output file path') |
| parser.add_argument('-c', '--stdout', action='store_true', help='output to console (STDOUT)') |
| parser.add_argument('input_file', help='input airflow dag source file') |
| return parser |
| |
| |
| def read_config(path): |
| if os.path.exists(path): |
| with open(path) as json_config_file: |
| data = json.load(json_config_file) |
| return data |
| return {} |
| |
| |
| def pretty_format_json(j): |
| dumps = json.dumps(j, sort_keys=True, indent=4, separators=(',', ': ')) |
| return dumps |
| |
| |
| # for command-line execution |
| def main(args): |
| # check if config path is set |
| config_file_path = DEFAULT_CONFIG_FILE_PATH |
| if args.config: |
| config_file_path = args.config |
| |
| if os.path.exists(config_file_path): |
| # read config |
| config = read_config(config_file_path) |
| if config: |
| global progargs |
| for k in progargs: |
| # overwrite |
| if k in config: |
| progargs[k] = config[k] |
| |
| log = create_logger(progargs["logging"]) |
| |
| code_filepath = args.input_file |
| if not os.path.exists(code_filepath): |
| raise IOError('cannot find an input file - %s' % code_filepath) |
| |
| output_filepath = './essence.json' |
| if args.output: |
| output_filepath = args.output |
| |
| print_console = False |
| if args.stdout or output_filepath == '-': |
| print_console = True |
| |
| extractor = EssenceExtractor(logger=log) |
| extractor.parse_codefile(code_filepath) |
| essence = extractor.extract() |
| json_string = pretty_format_json(essence) |
| if print_console: |
| print(json_string) |
| else: |
| print_graffiti() |
| with open(output_filepath, 'w') as f: |
| f.write(json_string) |
| |
| |
| if __name__ == "__main__": |
| parser = get_arg_parser() |
| args = parser.parse_args() |
| main(args) |