| #!/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 |
| - XOS-related operators |
| - Airflow operators |
| - Dependency info |
| """ |
| |
| import ast |
| import sys |
| import json |
| import os.path |
| |
| |
| def classname(cls): |
| return cls.__class__.__name__ |
| |
| |
| def jsonify_ast(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] = jsonify_ast(v) |
| else: |
| fields[k] = classname(v) |
| |
| elif isinstance(v, list): |
| fields[k] = [] |
| for e in v: |
| fields[k].append(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 = { |
| classname(node): fields |
| } |
| return ret |
| |
| |
| def parse(code): |
| lines = code.split("\n") |
| if len(lines) == 1: |
| if code.endswith(".py") and os.path.exists(code): |
| return parse_codefile(code) |
| return parse_code(code) |
| |
| |
| def parse_code(code): |
| tree = ast.parse(code) |
| return jsonify_ast(tree) |
| |
| |
| def parse_codefile(code_filepath): |
| code = None |
| with open(code_filepath, "r") as f: |
| code = f.read() |
| tree = ast.parse(code, code_filepath) |
| return jsonify_ast(tree) |
| |
| |
| def pretty_print_json(j): |
| dumps = json.dumps(j, sort_keys=True, indent=4, separators=(',', ': ')) |
| print(dumps) |
| |
| |
| def recursively_find_elements(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 recursively_find_elements(obj, elem): |
| yield y |
| |
| |
| def extract_func_calls(tree, func_name): |
| """ |
| extract function calls with assignment |
| """ |
| assigns = recursively_find_elements(tree, "Assign") |
| if assigns: |
| for assign in assigns: |
| found = False |
| |
| calls = recursively_find_elements(assign, "Call") |
| if calls: |
| for call in calls: |
| funcs = 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(tree): |
| """ |
| extract only airflow operators which end with "*Operator" or "*Sensor" |
| """ |
| assigns = recursively_find_elements(tree, "Assign") |
| if assigns: |
| for assign in assigns: |
| found = False |
| |
| calls = recursively_find_elements(assign, "Call") |
| if calls: |
| for call in calls: |
| funcs = 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(tree, op_name): |
| """ |
| extract binary operation such as >>, << |
| """ |
| ops = recursively_find_elements(tree, "BinOp") |
| if ops: |
| for op in ops: |
| if op["op"] == op_name: |
| yield op |
| |
| |
| def take_string_or_tree(tree): |
| if "Str" in tree: |
| return tree["Str"]["s"] |
| return tree |
| |
| |
| def take_num_or_tree(tree): |
| if "Num" in tree: |
| return tree["Num"]["n"] |
| return tree |
| |
| |
| def take_id_or_tree(tree): |
| if "Name" in tree: |
| return tree["Name"]["id"] |
| return tree |
| |
| |
| def take_name_constant_or_tree(tree): |
| if "NameConstant" in tree: |
| return tree["NameConstant"]["value"] |
| return tree |
| |
| |
| def take_value_or_tree(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 = take_value_or_tree(elt) |
| vals.append(val) |
| return vals |
| return tree |
| |
| |
| def make_dag(tree): |
| loc_val = None |
| dag_id = None |
| |
| if "targets" in tree: |
| targets = tree["targets"] |
| loc_val = 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 = take_string_or_tree(k["value"]) |
| |
| return { |
| 'local_variable': loc_val, |
| 'dag_id': dag_id |
| } |
| |
| |
| def make_airflow_operator(tree): |
| airflow_operator = {} |
| |
| if "targets" in tree: |
| targets = tree["targets"] |
| loc_val = 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 = 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] = take_value_or_tree(k["value"]) |
| |
| return airflow_operator |
| |
| |
| def make_dependencies_bin_op(tree, dependencies): |
| children = [] |
| parents = [] |
| child = None |
| parent = None |
| |
| if tree["op"] == "RShift": |
| child = take_id_or_tree(tree["right"]) |
| parent = take_id_or_tree(tree["left"]) |
| elif tree["op"] == "LShift": |
| child = take_id_or_tree(tree["left"]) |
| parent = take_id_or_tree(tree["right"]) |
| |
| if child: |
| if isinstance(child, dict): |
| if "List" in child: |
| for c in child["List"]["elts"]: |
| children.append(take_id_or_tree(c)) |
| elif "BinOp" in child: |
| deps = make_dependencies_bin_op(child["BinOp"], dependencies) |
| for dep in deps: |
| children.append(dep) |
| else: |
| children.append(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(take_id_or_tree(p)) |
| elif "BinOp" in parent: |
| deps = make_dependencies_bin_op(parent["BinOp"], dependencies) |
| for dep in deps: |
| parents.append(dep) |
| else: |
| parents.append(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(tree): |
| # extract dependency definition using ">>" |
| ops = extract_bin_op(tree, "RShift") |
| if ops: |
| for op in ops: |
| deps = [] |
| make_dependencies_bin_op(op, deps) |
| for dep in deps: |
| yield dep |
| |
| # extract dependency definition using "<<" |
| ops = extract_bin_op(tree, "LShift") |
| if ops: |
| for op in ops: |
| deps = [] |
| make_dependencies_bin_op(op, deps) |
| for dep in deps: |
| yield dep |
| |
| |
| def extract_dags(tree): |
| dags = {} |
| calls = extract_func_calls(tree, "DAG") |
| if calls: |
| for call in calls: |
| dag = make_dag(call) |
| dagid = dag["dag_id"] |
| dags[dagid] = dag |
| return dags |
| |
| |
| def extract_XOS_event_sensors(tree): |
| operators = {} |
| calls = extract_func_calls(tree, "XOSEventSensor") |
| if calls: |
| for call in calls: |
| operator = make_airflow_operator(call) |
| operatorid = operator["task_id"] |
| operators[operatorid] = operator |
| return operators |
| |
| |
| def extract_XOS_model_sensors(tree): |
| operators = {} |
| calls = extract_func_calls(tree, "XOSModelSensor") |
| if calls: |
| for call in calls: |
| operator = make_airflow_operator(call) |
| operatorid = operator["task_id"] |
| operators[operatorid] = operator |
| return operators |
| |
| |
| def extract_airflow_operators(tree): |
| operators = {} |
| calls = extract_func_calls_airflow_operators(tree) |
| if calls: |
| for call in calls: |
| operator = make_airflow_operator(call) |
| operatorid = operator["task_id"] |
| operators[operatorid] = operator |
| return operators |
| |
| |
| def extract_all_operators(tree): |
| operators = {} |
| event_sensors = extract_XOS_event_sensors(tree) |
| if event_sensors: |
| for event_sensor in event_sensors: |
| operators[event_sensor] = event_sensors[event_sensor] |
| |
| model_sensors = extract_XOS_model_sensors(tree) |
| if model_sensors: |
| for model_sensor in model_sensors: |
| operators[model_sensor] = model_sensors[model_sensor] |
| |
| airflow_operators = extract_airflow_operators(tree) |
| if airflow_operators: |
| for airflow_operator in airflow_operators: |
| operators[airflow_operator] = airflow_operators[airflow_operator] |
| |
| return operators |
| |
| |
| def extract_dependencies(tree): |
| """ |
| Build N-N dependencies from fragmented parent-child relations |
| A node can have multiple parents and multiple children |
| """ |
| dependencies = {} |
| ops = 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_all(tree): |
| """ |
| Build highlevel information of workflows dag, operators and dependencies refers to each other |
| """ |
| dags = extract_dags(tree) |
| operators = extract_all_operators(tree) |
| dependencies = extract_dependencies(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 |
| |
| |
| # for command-line execution |
| def main(argv): |
| if len(argv) < 1: |
| sys.exit("Error: Need a filepath") |
| |
| code_filepath = argv[0] |
| |
| tree = parse_codefile(code_filepath) |
| all = extract_all(tree) |
| pretty_print_json(all) |
| |
| |
| if __name__ == "__main__": |
| main(sys.argv[1:]) |