mobuchowski commented on code in PR #29940: URL: https://github.com/apache/airflow/pull/29940#discussion_r1157621916
########## airflow/providers/openlineage/utils/utils.py: ########## @@ -0,0 +1,482 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. + +from __future__ import annotations + +import datetime +import importlib +import json +import logging +import os +import subprocess +from contextlib import suppress +from functools import wraps +from typing import TYPE_CHECKING, Any +from urllib.parse import parse_qsl, urlencode, urlparse, urlunparse + +import attrs +from attrs import asdict + +from airflow.models import DAG as AIRFLOW_DAG +from airflow.providers.openlineage.plugins.facets import ( + AirflowMappedTaskRunFacet, + AirflowRunArgsRunFacet, + AirflowRunFacet, + AirflowVersionRunFacet, +) + +# TODO: move this maybe to Airflow's logic? +from openlineage.client.utils import RedactMixin + +if TYPE_CHECKING: + from airflow.models import DAG, BaseOperator, Connection, DagRun, TaskInstance + + +log = logging.getLogger(__name__) +_NOMINAL_TIME_FORMAT = "%Y-%m-%dT%H:%M:%S.%fZ" + + +def openlineage_job_name(dag_id: str, task_id: str) -> str: + return f"{dag_id}.{task_id}" + + +def get_operator_class(task: BaseOperator) -> type: + if task.__class__.__name__ in ("DecoratedMappedOperator", "MappedOperator"): + return task.operator_class + return task.__class__ + + +def to_json_encodable(task: BaseOperator) -> dict[str, object]: + def _task_encoder(obj): + if isinstance(obj, datetime.datetime): + return obj.isoformat() + elif isinstance(obj, AIRFLOW_DAG): + return { + "dag_id": obj.dag_id, + "tags": obj.tags, + "schedule_interval": obj.schedule_interval, + } + else: + return str(obj) + + return json.loads(json.dumps(task.__dict__, default=_task_encoder)) + + +def url_to_https(url) -> str | None: + # Ensure URL exists + if not url: + return None + + base_url = None + if url.startswith("git@"): + part = url.split("git@")[1:2] + if part: + base_url = f'https://{part[0].replace(":", "/", 1)}' + elif url.startswith("https://";): + base_url = url + + if not base_url: + raise ValueError(f"Unable to extract location from: {url}") + + if base_url.endswith(".git"): + base_url = base_url[:-4] + return base_url + + +def get_location(file_path) -> str | None: + # Ensure file path exists + if not file_path: + return None + + # move to the file directory + abs_path = os.path.abspath(file_path) + file_name = os.path.basename(file_path) + cwd = os.path.dirname(abs_path) + + # get the repo url + repo_url = execute_git(cwd, ["config", "--get", "remote.origin.url"]) + + # get the repo relative path + repo_relative_path = execute_git(cwd, ["rev-parse", "--show-prefix"]) + + # get the commitId for the particular file + commit_id = execute_git(cwd, ["rev-list", "HEAD", "-1", "--", file_name]) + + # build the URL + base_url = url_to_https(repo_url) + if not base_url: + return None + + return f"{base_url}/blob/{commit_id}/{repo_relative_path}{file_name}" + + +def get_task_location(task): + try: + if hasattr(task, "file_path") and task.file_path: + return get_location(task.file_path) + else: + return get_location(task.dag.fileloc) + except Exception: + return None + + +def execute_git(cwd, params): + p = subprocess.Popen(["git"] + params, cwd=cwd, stdout=subprocess.PIPE, stderr=None) + p.wait(timeout=0.5) + out, err = p.communicate() + return out.decode("utf8").strip() + + +def redacted_connection_uri(conn: Connection, filtered_params=None, filtered_prefixes=None): + """ + Return the connection URI for the given Connection. + This method additionally filters URI by removing query parameters that are known to carry sensitive data + like username, password, access key. + """ + if filtered_prefixes is None: + filtered_prefixes = [] + if filtered_params is None: + filtered_params = [] + + def filter_key_params(k: str): + return k not in filtered_params and any(substr in k for substr in filtered_prefixes) + + conn_uri = conn.get_uri() + parsed = urlparse(conn_uri) + + # Remove username and password + netloc = f"{parsed.hostname}" + (f":{parsed.port}" if parsed.port else "") + parsed = parsed._replace(netloc=netloc) + if parsed.query: + query_dict = dict(parse_qsl(parsed.query)) + if conn.EXTRA_KEY in query_dict: + query_dict = json.loads(query_dict[conn.EXTRA_KEY]) + filtered_qs = {k: v for k, v in query_dict.items() if not filter_key_params(k)} + parsed = parsed._replace(query=urlencode(filtered_qs)) + return urlunparse(parsed) + + +def get_normalized_postgres_connection_uri(conn): + """ + URIs starting with postgresql:// and postgres:// are both valid + PostgreSQL connection strings. This function normalizes it to + postgres:// as canonical name according to OpenLineage spec. + """ + uri = redacted_connection_uri(conn) + if uri.startswith("postgresql"): + uri = uri.replace("postgresql", "postgres", 1) + return uri + + +def get_connection(conn_id) -> Connection | None: + from airflow.hooks.base import BaseHook + + with suppress(Exception): + return BaseHook.get_connection(conn_id=conn_id) + return None + + +def get_job_name(task): + return f"{task.dag_id}.{task.task_id}" + + +def get_custom_facets( + dagrun, task, is_external_trigger: bool, task_instance: TaskInstance | None = None +) -> dict[str, Any]: + custom_facets = { + "airflow_runArgs": AirflowRunArgsRunFacet(is_external_trigger), + "airflow_version": AirflowVersionRunFacet.from_dagrun_and_task(dagrun, task), + } + # check for -1 comes from SmartSensor compatibility with dynamic task mapping + # this comes from Airflow code + if hasattr(task_instance, "map_index") and getattr(task_instance, "map_index") != -1: + custom_facets["airflow_mappedTask"] = AirflowMappedTaskRunFacet.from_task_instance(task_instance) + return custom_facets + + +class InfoJsonEncodable(dict): + """ + Airflow objects might not be json-encodable overall. + + The class provides additional attributes to control + what and how is encoded: + * renames: a dictionary of attribute name changes + * casts: a dictionary consisting of attribute names + and corresponding methods that should change + object value + * includes: list of attributes to be included in encoding + * excludes: list of attributes to be excluded from encoding + + Don't use both includes and excludes. + """ + + renames: dict[str, str] = {} + casts: dict[str, Any] = {} + includes: list[str] = [] + excludes: list[str] = [] + + def __init__(self, obj): + self.obj = obj + self._fields = [] + + self._cast_fields() + self._rename_fields() + self._include_fields() + dict.__init__( + self, + **{field: InfoJsonEncodable._cast_basic_types(getattr(self, field)) for field in self._fields}, + ) + + @staticmethod + def _cast_basic_types(value): + if isinstance(value, datetime.datetime): + return value.isoformat() + if isinstance(value, (set, list, tuple)): + return str(list(value)) + return value + + def _rename_fields(self): + for field, renamed in self.renames.items(): + if hasattr(self.obj, field): + setattr(self, renamed, getattr(self.obj, field)) + self._fields.append(renamed) + + def _cast_fields(self): + for field, func in self.casts.items(): + setattr(self, field, func(self.obj)) + self._fields.append(field) + + def _include_fields(self): + if self.includes and self.excludes: + raise Exception("Don't use both includes and excludes.") + if self.includes: + for field in self.includes: + if field in self._fields or not hasattr(self.obj, field): + continue + setattr(self, field, getattr(self.obj, field)) + self._fields.append(field) + else: + for field, val in self.obj.__dict__.items(): + if field in self._fields or field in self.excludes or field in self.renames: + continue + setattr(self, field, val) + self._fields.append(field) + + +class DagInfo(InfoJsonEncodable): + """Defines encoding DAG object to JSON.""" + + includes = ["dag_id", "schedule_interval", "tags", "start_date"] + casts = {"timetable": lambda dag: dag.timetable.serialize() if getattr(dag, "timetable", None) else None} + renames = {"_dag_id": "dag_id"} + + +class DagRunInfo(InfoJsonEncodable): + """Defines encoding DagRun object to JSON.""" + + includes = [ + "conf", + "dag_id", + "data_interval_start", + "data_interval_end", + "external_trigger", + "run_id", + "run_type", + "start_date", + ] + + +class TaskInstanceInfo(InfoJsonEncodable): + """Defines encoding TaskInstance object to JSON.""" + + includes = ["duration", "try_number", "pool"] + casts = { + "map_index": lambda ti: ti.map_index + if hasattr(ti, "map_index") and getattr(ti, "map_index") != -1 + else None + } + + +class TaskInfo(InfoJsonEncodable): + """Defines encoding BaseOperator/AbstractOperator object to JSON.""" + + renames = { + "_BaseOperator__init_kwargs": "args", + "_BaseOperator__from_mapped": "mapped", + "_downstream_task_ids": "downstream_task_ids", + "_upstream_task_ids": "upstream_task_ids", + } + excludes = [ + "_BaseOperator__instantiated", + "_dag", + "_hook", + "_log", + "_outlets", + "_inlets", + "_lock_for_execution", + "handler", + "params", + "python_callable", + "retry_delay", + ] + casts = { + "operator_class": lambda task: f"{get_operator_class(task).__module__}.{get_operator_class(task).__name__}", # noqa + "task_group": lambda task: TaskGroupInfo(task.task_group) + if hasattr(task, "task_group") and getattr(task.task_group, "_group_id", None) + else None, + } + + +class TaskGroupInfo(InfoJsonEncodable): + """Defines encoding TaskGroup object to JSON.""" + + renames = { + "_group_id": "group_id", + } + includes = [ + "downstream_group_ids", + "downstream_task_ids", + "prefix_group_id", + "tooltip", + "upstream_group_ids", + "upstream_task_ids", + ] + + +def get_airflow_run_facet( + dag_run: DagRun, + dag: DAG, + task_instance: TaskInstance, + task: BaseOperator, + task_uuid: str, +): + return { + "airflow": json.loads( + json.dumps( + asdict( + AirflowRunFacet( + dag=DagInfo(dag), + dagRun=DagRunInfo(dag_run), + taskInstance=TaskInstanceInfo(task_instance), + task=TaskInfo(task), + taskUuid=task_uuid, + ) + ), + default=str, + ) + ) + } + + +def import_from_string(path: str): + try: + module_path, target = path.rsplit(".", 1) + module = importlib.import_module(module_path) + return getattr(module, target) + except Exception as e: + log.warning(e) + raise ImportError(f"Failed to import {path}") from e + + +def try_import_from_string(path: str): + with suppress(ImportError): + return import_from_string(path) + + +def redact_with_exclusions(source: Any): + """This function redacts sensitive data similar to SecretsMasker in Airflow logs. + The difference is that MAX_RECURSION_DEPTH is way higher - due to the structure of OL events + we need more depth. + Also, we allow data structures to specify data that needs not to be redacted by specifying + _skip_redact list. + """ + try: + from airflow.utils.log.secrets_masker import ( + _secrets_masker, + should_hide_value_for_key, + ) + except ImportError: + return source + + sm = _secrets_masker() + MAX_RECURSION_DEPTH = 20 + + def _redact(item, name: str | None, depth: int): + if depth > MAX_RECURSION_DEPTH: + return item + try: + if name and should_hide_value_for_key(name): + return sm._redact_all(item, depth) + if isinstance(item, dict): + return { + dict_key: _redact(subval, name=dict_key, depth=(depth + 1)) + for dict_key, subval in item.items() + } + elif attrs.has(item.__class__) or (is_json_serializable(item) and hasattr(item, "__dict__")): + for dict_key, subval in item.__dict__.items(): Review Comment: For slotted classes, we can use `attrs.asdict(obj, recurse=False)`. -- This is an automated message from the Apache Git Service. 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