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views.py
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views.py
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#
# 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 collections
import copy
import datetime
import itertools
import json
import logging
import math
import re
import sys
import traceback
import warnings
from bisect import insort_left
from collections import defaultdict
from functools import wraps
from json import JSONDecodeError
from typing import Any, Callable, Collection, Iterator, Mapping, MutableMapping, Sequence
from urllib.parse import unquote, urljoin, urlsplit
import configupdater
import flask.json
import lazy_object_proxy
import markupsafe
import nvd3
import sqlalchemy as sqla
from croniter import croniter
from flask import (
Response,
abort,
before_render_template,
flash,
g,
has_request_context,
make_response,
redirect,
render_template,
request,
send_from_directory,
session as flask_session,
url_for,
)
from flask_appbuilder import BaseView, ModelView, expose
from flask_appbuilder.actions import action
from flask_appbuilder.models.sqla.filters import BaseFilter
from flask_appbuilder.security.decorators import has_access
from flask_appbuilder.urltools import get_order_args, get_page_args, get_page_size_args
from flask_appbuilder.widgets import FormWidget
from flask_babel import lazy_gettext
from jinja2.utils import htmlsafe_json_dumps, pformat # type: ignore
from markupsafe import Markup, escape
from pendulum.datetime import DateTime
from pendulum.parsing.exceptions import ParserError
from pygments import highlight, lexers
from pygments.formatters import HtmlFormatter
from sqlalchemy import Date, and_, case, desc, func, inspect, union_all
from sqlalchemy.exc import IntegrityError
from sqlalchemy.orm import Session, joinedload
from wtforms import SelectField, validators
import airflow
from airflow import models, plugins_manager, settings
from airflow.api.common.airflow_health import get_airflow_health
from airflow.api.common.mark_tasks import (
set_dag_run_state_to_failed,
set_dag_run_state_to_queued,
set_dag_run_state_to_success,
set_state,
)
from airflow.compat.functools import cached_property
from airflow.configuration import AIRFLOW_CONFIG, conf
from airflow.datasets import Dataset
from airflow.exceptions import AirflowException, ParamValidationError, RemovedInAirflow3Warning
from airflow.executors.executor_loader import ExecutorLoader
from airflow.jobs.job import Job
from airflow.jobs.scheduler_job_runner import SchedulerJobRunner
from airflow.jobs.triggerer_job_runner import TriggererJobRunner
from airflow.models import Connection, DagModel, DagTag, Log, SlaMiss, TaskFail, XCom, errors
from airflow.models.abstractoperator import AbstractOperator
from airflow.models.dag import DAG, get_dataset_triggered_next_run_info
from airflow.models.dagcode import DagCode
from airflow.models.dagrun import RUN_ID_REGEX, DagRun, DagRunType
from airflow.models.dataset import DagScheduleDatasetReference, DatasetDagRunQueue, DatasetEvent, DatasetModel
from airflow.models.mappedoperator import MappedOperator
from airflow.models.operator import Operator
from airflow.models.serialized_dag import SerializedDagModel
from airflow.models.taskinstance import TaskInstance, TaskInstanceNote
from airflow.providers_manager import ProvidersManager
from airflow.security import permissions
from airflow.ti_deps.dep_context import DepContext
from airflow.ti_deps.dependencies_deps import SCHEDULER_QUEUED_DEPS
from airflow.timetables._cron import CronMixin
from airflow.timetables.base import DataInterval, TimeRestriction
from airflow.utils import json as utils_json, timezone, yaml
from airflow.utils.airflow_flask_app import get_airflow_app
from airflow.utils.dag_edges import dag_edges
from airflow.utils.dates import infer_time_unit, scale_time_units
from airflow.utils.docs import get_doc_url_for_provider, get_docs_url
from airflow.utils.helpers import alchemy_to_dict
from airflow.utils.log import secrets_masker
from airflow.utils.log.log_reader import TaskLogReader
from airflow.utils.net import get_hostname
from airflow.utils.session import NEW_SESSION, create_session, provide_session
from airflow.utils.state import DagRunState, State, TaskInstanceState
from airflow.utils.strings import to_boolean
from airflow.utils.task_group import MappedTaskGroup, TaskGroup, task_group_to_dict
from airflow.utils.timezone import td_format, utcnow
from airflow.version import version
from airflow.www import auth, utils as wwwutils
from airflow.www.decorators import action_logging, gzipped
from airflow.www.forms import (
DagRunEditForm,
DateTimeForm,
DateTimeWithNumRunsForm,
DateTimeWithNumRunsWithDagRunsForm,
TaskInstanceEditForm,
create_connection_form_class,
)
from airflow.www.widgets import AirflowModelListWidget, AirflowVariableShowWidget
PAGE_SIZE = conf.getint("webserver", "page_size")
FILTER_TAGS_COOKIE = "tags_filter"
FILTER_STATUS_COOKIE = "dag_status_filter"
LINECHART_X_AXIS_TICKFORMAT = (
"function (d, i) { let xLabel;"
"if (i === undefined) {xLabel = d3.time.format('%H:%M, %d %b %Y')(new Date(parseInt(d)));"
"} else {xLabel = d3.time.format('%H:%M, %d %b')(new Date(parseInt(d)));} return xLabel;}"
)
def truncate_task_duration(task_duration):
"""
Cast the task_duration to an int was for optimization for large/huge dags if task_duration > 10s
otherwise we keep it as a float with 3dp
"""
return int(task_duration) if task_duration > 10.0 else round(task_duration, 3)
def sanitize_args(args: dict[str, str]) -> dict[str, str]:
"""
Remove all parameters starting with `_`
:param args: arguments of request
:return: copy of the dictionary passed as input with args starting with `_` removed.
"""
return {key: value for key, value in args.items() if not key.startswith("_")}
# Following the release of https://github.com/python/cpython/issues/102153 in Python 3.8.17 and 3.9.17 on
# June 6, 2023, we are adding extra sanitization of the urls passed to get_safe_url method to make it works
# the same way regardless if the user uses latest Python patchlevel versions or not. This also follows
# a recommended solution by the Python core team.
#
# From: https://github.com/python/cpython/commit/d28bafa2d3e424b6fdcfd7ae7cde8e71d7177369
#
# We recommend that users of these APIs where the values may be used anywhere
# with security implications code defensively. Do some verification within your
# code before trusting a returned component part. Does that ``scheme`` make
# sense? Is that a sensible ``path``? Is there anything strange about that
# ``hostname``? etc.
#
# C0 control and space to be stripped per WHATWG spec.
# == "".join([chr(i) for i in range(0, 0x20 + 1)])
_WHATWG_C0_CONTROL_OR_SPACE = (
"\x00\x01\x02\x03\x04\x05\x06\x07\x08\t\n\x0b\x0c"
"\r\x0e\x0f\x10\x11\x12\x13\x14\x15\x16\x17\x18\x19\x1a\x1b\x1c\x1d\x1e\x1f "
)
def get_safe_url(url):
"""Given a user-supplied URL, ensure it points to our web server"""
if not url:
return url_for("Airflow.index")
# If the url contains semicolon, redirect it to homepage to avoid
# potential XSS. (Similar to https://github.com/python/cpython/pull/24297/files (bpo-42967))
if ";" in unquote(url):
return url_for("Airflow.index")
url = url.lstrip(_WHATWG_C0_CONTROL_OR_SPACE)
host_url = urlsplit(request.host_url)
redirect_url = urlsplit(urljoin(request.host_url, url))
if not (redirect_url.scheme in ("http", "https") and host_url.netloc == redirect_url.netloc):
return url_for("Airflow.index")
# This will ensure we only redirect to the right scheme/netloc
return redirect_url.geturl()
def get_date_time_num_runs_dag_runs_form_data(www_request, session, dag):
"""Get Execution Data, Base Date & Number of runs from a Request"""
date_time = www_request.args.get("execution_date")
run_id = www_request.args.get("run_id")
# First check run id, then check execution date, if not fall back on the latest dagrun
if run_id:
dagrun = dag.get_dagrun(run_id=run_id, session=session)
date_time = dagrun.execution_date
elif date_time:
date_time = _safe_parse_datetime(date_time)
else:
date_time = dag.get_latest_execution_date(session=session) or timezone.utcnow()
base_date = www_request.args.get("base_date")
if base_date:
base_date = _safe_parse_datetime(base_date)
else:
# The DateTimeField widget truncates milliseconds and would loose
# the first dag run. Round to next second.
base_date = (date_time + datetime.timedelta(seconds=1)).replace(microsecond=0)
default_dag_run = conf.getint("webserver", "default_dag_run_display_number")
num_runs = www_request.args.get("num_runs", default=default_dag_run, type=int)
# When base_date has been rounded up because of the DateTimeField widget, we want
# to use the execution_date as the starting point for our query just to ensure a
# link targeting a specific dag run actually loads that dag run. If there are
# more than num_runs dag runs in the "rounded period" then those dagruns would get
# loaded and the actual requested run would be excluded by the limit(). Once
# the user has changed base date to be anything else we want to use that instead.
query_date = base_date
if date_time < base_date and date_time + datetime.timedelta(seconds=1) >= base_date:
query_date = date_time
drs = (
session.query(DagRun)
.filter(DagRun.dag_id == dag.dag_id, DagRun.execution_date <= query_date)
.order_by(desc(DagRun.execution_date))
.limit(num_runs)
.all()
)
dr_choices = []
dr_state = None
for dr in drs:
dr_choices.append((dr.execution_date.isoformat(), dr.run_id))
if date_time == dr.execution_date:
dr_state = dr.state
# Happens if base_date was changed and the selected dag run is not in result
if not dr_state and drs:
dr = drs[0]
date_time = dr.execution_date
dr_state = dr.state
return {
"dttm": date_time,
"base_date": base_date,
"num_runs": num_runs,
"execution_date": date_time.isoformat(),
"dr_choices": dr_choices,
"dr_state": dr_state,
}
def _safe_parse_datetime(v, allow_empty=False) -> datetime.datetime | None:
"""
Parse datetime and return error message for invalid dates
:param v: the string value to be parsed
:param allow_empty: Set True to return none if empty str or None
"""
if allow_empty is True and not v:
return None
try:
return timezone.parse(v)
except (TypeError, ParserError):
abort(400, f"Invalid datetime: {v!r}")
def node_dict(node_id, label, node_class):
return {
"id": node_id,
"value": {"label": label, "rx": 5, "ry": 5, "class": node_class},
}
def dag_to_grid(dag: DagModel, dag_runs: Sequence[DagRun], session: Session):
"""
Create a nested dict representation of the DAG's TaskGroup and its children
used to construct the Graph and Grid views.
"""
query = (
session.query(
TaskInstance.task_id,
TaskInstance.run_id,
TaskInstance.state,
TaskInstance._try_number,
func.min(TaskInstanceNote.content).label("note"),
func.count(func.coalesce(TaskInstance.state, sqla.literal("no_status"))).label("state_count"),
func.min(TaskInstance.start_date).label("start_date"),
func.max(TaskInstance.end_date).label("end_date"),
)
.join(TaskInstance.task_instance_note, isouter=True)
.filter(
TaskInstance.dag_id == dag.dag_id,
TaskInstance.run_id.in_([dag_run.run_id for dag_run in dag_runs]),
)
.group_by(TaskInstance.task_id, TaskInstance.run_id, TaskInstance.state, TaskInstance._try_number)
.order_by(TaskInstance.task_id, TaskInstance.run_id)
)
grouped_tis = {task_id: list(tis) for task_id, tis in itertools.groupby(query, key=lambda ti: ti.task_id)}
def task_group_to_grid(item, grouped_tis, *, is_parent_mapped: bool):
if not isinstance(item, TaskGroup):
def _get_summary(task_instance):
return {
"task_id": task_instance.task_id,
"run_id": task_instance.run_id,
"state": task_instance.state,
"start_date": task_instance.start_date,
"end_date": task_instance.end_date,
"try_number": wwwutils.get_try_count(task_instance._try_number, task_instance.state),
"note": task_instance.note,
}
def _mapped_summary(ti_summaries):
run_id = None
record = None
def set_overall_state(record):
for state in wwwutils.priority:
if state in record["mapped_states"]:
record["state"] = state
break
if None in record["mapped_states"]:
# When turning the dict into JSON we can't have None as a key,
# so use the string that the UI does.
record["mapped_states"]["no_status"] = record["mapped_states"].pop(None)
for ti_summary in ti_summaries:
if run_id != ti_summary.run_id:
run_id = ti_summary.run_id
if record:
set_overall_state(record)
yield record
record = {
"task_id": ti_summary.task_id,
"run_id": run_id,
"start_date": ti_summary.start_date,
"end_date": ti_summary.end_date,
"mapped_states": {ti_summary.state: ti_summary.state_count},
"state": None, # We change this before yielding
}
continue
record["start_date"] = min(
filter(None, [record["start_date"], ti_summary.start_date]), default=None
)
record["end_date"] = max(
filter(None, [record["end_date"], ti_summary.end_date]), default=None
)
record["mapped_states"][ti_summary.state] = ti_summary.state_count
if record:
set_overall_state(record)
yield record
if isinstance(item, MappedOperator) or is_parent_mapped:
instances = list(_mapped_summary(grouped_tis.get(item.task_id, [])))
else:
instances = list(map(_get_summary, grouped_tis.get(item.task_id, [])))
return {
"id": item.task_id,
"instances": instances,
"label": item.label,
"extra_links": item.extra_links,
"is_mapped": isinstance(item, MappedOperator) or is_parent_mapped,
"has_outlet_datasets": any(isinstance(i, Dataset) for i in (item.outlets or [])),
"operator": item.operator_name,
"trigger_rule": item.trigger_rule,
}
# Task Group
task_group = item
group_is_mapped = isinstance(task_group, MappedTaskGroup)
children = [
task_group_to_grid(child, grouped_tis, is_parent_mapped=group_is_mapped)
for child in task_group.topological_sort()
]
def get_summary(dag_run: DagRun):
child_instances = [
item
for sublist in (child["instances"] for child in children if "instances" in child)
for item in sublist
if item["run_id"] == dag_run.run_id
if item
]
children_start_dates = (item["start_date"] for item in child_instances)
children_end_dates = (item["end_date"] for item in child_instances)
children_states = {item["state"] for item in child_instances}
group_state = next((state for state in wwwutils.priority if state in children_states), None)
group_start_date = min(filter(None, children_start_dates), default=None)
group_end_date = max(filter(None, children_end_dates), default=None)
return {
"task_id": task_group.group_id,
"run_id": dag_run.run_id,
"state": group_state,
"start_date": group_start_date,
"end_date": group_end_date,
}
def get_mapped_group_summaries():
mapped_ti_query = (
session.query(
TaskInstance.task_id, TaskInstance.state, TaskInstance.run_id, TaskInstance.map_index
)
.filter(
TaskInstance.dag_id == dag.dag_id,
TaskInstance.task_id.in_(child["id"] for child in children),
TaskInstance.run_id.in_(r.run_id for r in dag_runs),
)
.order_by(TaskInstance.task_id, TaskInstance.run_id)
)
# Group tis by run_id, and then map_index.
mapped_tis: Mapping[str, Mapping[int, list[TaskInstance]]] = collections.defaultdict(
lambda: collections.defaultdict(list),
)
for ti in mapped_ti_query:
mapped_tis[ti.run_id][ti.map_index].append(ti)
def get_mapped_group_summary(run_id: str, mapped_instances: Mapping[int, list[TaskInstance]]):
child_instances = [
item
for sublist in (child["instances"] for child in children if "instances" in child)
for item in sublist
if item and item["run_id"] == run_id
]
children_start_dates = (item["start_date"] for item in child_instances)
children_end_dates = (item["end_date"] for item in child_instances)
children_states = {item["state"] for item in child_instances}
# TODO: This assumes TI map index has a one-to-one mapping to
# its parent mapped task group, which will not be true when we
# allow nested mapping in the future.
mapped_states: MutableMapping[str, int] = collections.defaultdict(int)
for mis in mapped_instances.values():
child_states = {mi.state for mi in mis}
state = next(s for s in wwwutils.priority if s in child_states)
value = state.value if state is not None else "no_status"
mapped_states[value] += 1
group_state = next((state for state in wwwutils.priority if state in children_states), None)
group_start_date = min(filter(None, children_start_dates), default=None)
group_end_date = max(filter(None, children_end_dates), default=None)
return {
"task_id": task_group.group_id,
"run_id": run_id,
"state": group_state,
"start_date": group_start_date,
"end_date": group_end_date,
"mapped_states": mapped_states,
}
return [get_mapped_group_summary(run_id, tis) for run_id, tis in mapped_tis.items()]
# We don't need to calculate summaries for the root
if task_group.group_id is None:
return {
"id": task_group.group_id,
"label": task_group.label,
"children": children,
"instances": [],
}
if group_is_mapped:
mapped_group_summaries = get_mapped_group_summaries()
return {
"id": task_group.group_id,
"label": task_group.label,
"children": children,
"tooltip": task_group.tooltip,
"instances": mapped_group_summaries,
"is_mapped": group_is_mapped,
}
group_summaries = [get_summary(dr) for dr in dag_runs]
return {
"id": task_group.group_id,
"label": task_group.label,
"children": children,
"tooltip": task_group.tooltip,
"instances": group_summaries,
}
return task_group_to_grid(dag.task_group, grouped_tis, is_parent_mapped=False)
def get_key_paths(input_dict):
"""Return a list of dot-separated dictionary paths"""
for key, value in input_dict.items():
if isinstance(value, dict):
for sub_key in get_key_paths(value):
yield ".".join((key, sub_key))
else:
yield key
def get_value_from_path(key_path, content):
"""Return the value from a dictionary based on dot-separated path of keys"""
elem = content
for x in key_path.strip(".").split("."):
try:
x = int(x)
elem = elem[x]
except ValueError:
elem = elem.get(x)
return elem
def get_task_stats_from_query(qry):
"""
Return a dict of the task quantity, grouped by dag id and task status.
:param qry: The data in the format (<dag id>, <task state>, <is dag running>, <task count>),
ordered by <dag id> and <is dag running>
"""
data = {}
last_dag_id = None
has_running_dags = False
for dag_id, state, is_dag_running, count in qry:
if last_dag_id != dag_id:
last_dag_id = dag_id
has_running_dags = False
elif not is_dag_running and has_running_dags:
continue
if is_dag_running:
has_running_dags = True
if dag_id not in data:
data[dag_id] = {}
data[dag_id][state] = count
return data
def redirect_or_json(origin, msg, status="", status_code=200):
"""
Some endpoints are called by javascript,
returning json will allow us to more elegantly handle side-effects in-page
"""
if request.headers.get("Accept") == "application/json":
if status == "error" and status_code == 200:
status_code = 500
return Response(response=msg, status=status_code, mimetype="application/json")
else:
if status:
flash(msg, status)
else:
flash(msg)
return redirect(origin)
######################################################################################
# Error handlers
######################################################################################
def not_found(error):
"""Show Not Found on screen for any error in the Webserver"""
return (
render_template(
"airflow/error.html",
hostname=get_hostname() if conf.getboolean("webserver", "EXPOSE_HOSTNAME") else "redact",
status_code=404,
error_message="Page cannot be found.",
),
404,
)
def method_not_allowed(error):
"""Show Method Not Allowed on screen for any error in the Webserver"""
return (
render_template(
"airflow/error.html",
hostname=get_hostname() if conf.getboolean("webserver", "EXPOSE_HOSTNAME") else "redact",
status_code=405,
error_message="Received an invalid request.",
),
405,
)
def show_traceback(error):
"""Show Traceback for a given error"""
return (
render_template(
"airflow/traceback.html",
python_version=sys.version.split(" ")[0] if g.user.is_authenticated else "redact",
airflow_version=version if g.user.is_authenticated else "redact",
hostname=get_hostname()
if conf.getboolean("webserver", "EXPOSE_HOSTNAME") and g.user.is_authenticated
else "redact",
info=traceback.format_exc()
if conf.getboolean("webserver", "EXPOSE_STACKTRACE") and g.user.is_authenticated
else "Error! Please contact server admin.",
),
500,
)
######################################################################################
# BaseViews
######################################################################################
class AirflowBaseView(BaseView):
"""Base View to set Airflow related properties"""
from airflow import macros
route_base = ""
extra_args = {
# Make our macros available to our UI templates too.
"macros": macros,
"get_docs_url": get_docs_url,
}
if not conf.getboolean("core", "unit_test_mode"):
executor, _ = ExecutorLoader.import_default_executor_cls()
extra_args["sqlite_warning"] = settings.engine.dialect.name == "sqlite"
if not executor.is_production:
extra_args["production_executor_warning"] = executor.__name__
extra_args["otel_on"] = conf.getboolean("metrics", "otel_on")
line_chart_attr = {
"legend.maxKeyLength": 200,
}
def render_template(self, *args, **kwargs):
# Add triggerer_job only if we need it
if TriggererJobRunner.is_needed():
kwargs["triggerer_job"] = lazy_object_proxy.Proxy(TriggererJobRunner.most_recent_job)
return super().render_template(
*args,
# Cache this at most once per request, not for the lifetime of the view instance
scheduler_job=lazy_object_proxy.Proxy(SchedulerJobRunner.most_recent_job),
**kwargs,
)
class Airflow(AirflowBaseView):
"""Main Airflow application."""
@expose("/health")
def health(self):
"""
An endpoint helping check the health status of the Airflow instance,
including metadatabase, scheduler and triggerer.
"""
airflow_health_status = get_airflow_health()
return flask.json.jsonify(airflow_health_status)
@expose("/home")
@auth.has_access(
[
(permissions.ACTION_CAN_READ, permissions.RESOURCE_WEBSITE),
]
)
def index(self):
"""Home view."""
from airflow.models.dag import DagOwnerAttributes
hide_paused_dags_by_default = conf.getboolean("webserver", "hide_paused_dags_by_default")
default_dag_run = conf.getint("webserver", "default_dag_run_display_number")
num_runs = request.args.get("num_runs", default=default_dag_run, type=int)
current_page = request.args.get("page", default=0, type=int)
arg_search_query = request.args.get("search")
arg_tags_filter = request.args.getlist("tags")
arg_status_filter = request.args.get("status")
arg_sorting_key = request.args.get("sorting_key", "dag_id")
arg_sorting_direction = request.args.get("sorting_direction", default="asc")
if request.args.get("reset_tags") is not None:
flask_session[FILTER_TAGS_COOKIE] = None
# Remove the reset_tags=reset from the URL
return redirect(url_for("Airflow.index"))
cookie_val = flask_session.get(FILTER_TAGS_COOKIE)
if arg_tags_filter:
flask_session[FILTER_TAGS_COOKIE] = ",".join(arg_tags_filter)
elif cookie_val:
# If tags exist in cookie, but not URL, add them to the URL
return redirect(url_for("Airflow.index", tags=cookie_val.split(",")))
if arg_status_filter is None:
cookie_val = flask_session.get(FILTER_STATUS_COOKIE)
if cookie_val:
arg_status_filter = cookie_val
else:
arg_status_filter = "active" if hide_paused_dags_by_default else "all"
flask_session[FILTER_STATUS_COOKIE] = arg_status_filter
else:
status = arg_status_filter.strip().lower()
flask_session[FILTER_STATUS_COOKIE] = status
arg_status_filter = status
dags_per_page = PAGE_SIZE
start = current_page * dags_per_page
end = start + dags_per_page
# Get all the dag id the user could access
filter_dag_ids = get_airflow_app().appbuilder.sm.get_accessible_dag_ids(g.user)
with create_session() as session:
# read orm_dags from the db
dags_query = session.query(DagModel).filter(~DagModel.is_subdag, DagModel.is_active)
if arg_search_query:
escaped_arg_search_query = arg_search_query.replace("_", r"\_")
dags_query = dags_query.filter(
DagModel.dag_id.ilike("%" + escaped_arg_search_query + "%", escape="\\")
| DagModel.owners.ilike("%" + escaped_arg_search_query + "%", escape="\\")
)
if arg_tags_filter:
dags_query = dags_query.filter(DagModel.tags.any(DagTag.name.in_(arg_tags_filter)))
dags_query = dags_query.filter(DagModel.dag_id.in_(filter_dag_ids))
filtered_dag_count = dags_query.count()
if filtered_dag_count == 0 and len(arg_tags_filter):
flash(
"No matching DAG tags found.",
"warning",
)
flask_session[FILTER_TAGS_COOKIE] = None
return redirect(url_for("Airflow.index"))
all_dags = dags_query
active_dags = dags_query.filter(~DagModel.is_paused)
paused_dags = dags_query.filter(DagModel.is_paused)
is_paused_count = dict(
all_dags.with_entities(DagModel.is_paused, func.count(DagModel.dag_id))
.group_by(DagModel.is_paused)
.all()
)
status_count_active = is_paused_count.get(False, 0)
status_count_paused = is_paused_count.get(True, 0)
all_dags_count = status_count_active + status_count_paused
if arg_status_filter == "active":
current_dags = active_dags
num_of_all_dags = status_count_active
elif arg_status_filter == "paused":
current_dags = paused_dags
num_of_all_dags = status_count_paused
else:
current_dags = all_dags
num_of_all_dags = all_dags_count
sort_column = DagModel.__table__.c.get(arg_sorting_key)
if sort_column is not None:
if arg_sorting_direction == "desc":
sort_column = sort_column.desc()
current_dags = current_dags.order_by(sort_column)
dags = current_dags.options(joinedload(DagModel.tags)).offset(start).limit(dags_per_page).all()
user_permissions = g.user.perms
can_create_dag_run = (
permissions.ACTION_CAN_CREATE,
permissions.RESOURCE_DAG_RUN,
) in user_permissions
dataset_triggered_dag_ids = {dag.dag_id for dag in dags if dag.schedule_interval == "Dataset"}
if dataset_triggered_dag_ids:
dataset_triggered_next_run_info = get_dataset_triggered_next_run_info(
dataset_triggered_dag_ids, session=session
)
else:
dataset_triggered_next_run_info = {}
for dag in dags:
dag.can_edit = get_airflow_app().appbuilder.sm.can_edit_dag(dag.dag_id, g.user)
dag.can_trigger = dag.can_edit and can_create_dag_run
dag.can_delete = get_airflow_app().appbuilder.sm.can_delete_dag(dag.dag_id, g.user)
dagtags = session.query(func.distinct(DagTag.name)).order_by(DagTag.name).all()
tags = [
{"name": name, "selected": bool(arg_tags_filter and name in arg_tags_filter)}
for name, in dagtags
]
owner_links_dict = DagOwnerAttributes.get_all(session)
import_errors = session.query(errors.ImportError).order_by(errors.ImportError.id)
if (permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG) not in user_permissions:
# if the user doesn't have access to all DAGs, only display errors from visible DAGs
import_errors = import_errors.join(
DagModel, DagModel.fileloc == errors.ImportError.filename
).filter(DagModel.dag_id.in_(filter_dag_ids))
for import_error in import_errors:
flash(
"Broken DAG: [{ie.filename}] {ie.stacktrace}".format(ie=import_error),
"dag_import_error",
)
from airflow.plugins_manager import import_errors as plugin_import_errors
for filename, stacktrace in plugin_import_errors.items():
flash(
f"Broken plugin: [{filename}] {stacktrace}",
"error",
)
num_of_pages = int(math.ceil(num_of_all_dags / float(dags_per_page)))
state_color_mapping = State.state_color.copy()
state_color_mapping["null"] = state_color_mapping.pop(None)
page_title = conf.get(section="webserver", key="instance_name", fallback="DAGs")
page_title_has_markup = conf.getboolean(
section="webserver", key="instance_name_has_markup", fallback=False
)
dashboard_alerts = [
fm for fm in settings.DASHBOARD_UIALERTS if fm.should_show(get_airflow_app().appbuilder.sm)
]
def _iter_parsed_moved_data_table_names():
for table_name in inspect(session.get_bind()).get_table_names():
segments = table_name.split("__", 3)
if len(segments) < 3:
continue
if segments[0] != settings.AIRFLOW_MOVED_TABLE_PREFIX:
continue
# Second segment is a version marker that we don't need to show.
yield segments[-1], table_name
if (
permissions.ACTION_CAN_ACCESS_MENU,
permissions.RESOURCE_ADMIN_MENU,
) in user_permissions and conf.getboolean("webserver", "warn_deployment_exposure"):
robots_file_access_count = (
session.query(Log)
.filter(Log.event == "robots")
.filter(Log.dttm > (utcnow() - datetime.timedelta(days=7)))
.count()
)
if robots_file_access_count > 0:
flash(
Markup(
"Recent requests have been made to /robots.txt. "
"This indicates that this deployment may be accessible to the public internet. "
"This warning can be disabled by setting webserver.warn_deployment_exposure=False in "
"airflow.cfg. Read more about web deployment security <a href="
f'"{get_docs_url("security/webserver.html")}">'
"here</a>"
),
"warning",
)
return self.render_template(
"airflow/dags.html",
dags=dags,
dashboard_alerts=dashboard_alerts,
migration_moved_data_alerts=sorted(set(_iter_parsed_moved_data_table_names())),
current_page=current_page,
search_query=arg_search_query if arg_search_query else "",
page_title=Markup(page_title) if page_title_has_markup else page_title,
page_size=dags_per_page,
num_of_pages=num_of_pages,
num_dag_from=min(start + 1, num_of_all_dags),
num_dag_to=min(end, num_of_all_dags),
num_of_all_dags=num_of_all_dags,
paging=wwwutils.generate_pages(
current_page,
num_of_pages,
search=escape(arg_search_query) if arg_search_query else None,
status=arg_status_filter if arg_status_filter else None,
tags=arg_tags_filter if arg_tags_filter else None,
sorting_key=arg_sorting_key if arg_sorting_key else None,
sorting_direction=arg_sorting_direction if arg_sorting_direction else None,
),
num_runs=num_runs,
tags=tags,
owner_links=owner_links_dict,
state_color=state_color_mapping,
status_filter=arg_status_filter,
status_count_all=all_dags_count,
status_count_active=status_count_active,
status_count_paused=status_count_paused,
tags_filter=arg_tags_filter,
sorting_key=arg_sorting_key,
sorting_direction=arg_sorting_direction,
auto_refresh_interval=conf.getint("webserver", "auto_refresh_interval"),
dataset_triggered_next_run_info=dataset_triggered_next_run_info,
)
@expose("/datasets")
@auth.has_access([(permissions.ACTION_CAN_READ, permissions.RESOURCE_DATASET)])
def datasets(self):
"""Datasets view."""
state_color_mapping = State.state_color.copy()
state_color_mapping["null"] = state_color_mapping.pop(None)
return self.render_template(
"airflow/datasets.html",
state_color_mapping=state_color_mapping,
)
@expose("/next_run_datasets_summary", methods=["POST"])
@auth.has_access([(permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG)])
@provide_session
def next_run_datasets_summary(self, session: Session = NEW_SESSION):
"""Next run info for dataset triggered DAGs."""
allowed_dag_ids = get_airflow_app().appbuilder.sm.get_accessible_dag_ids(g.user)
if not allowed_dag_ids:
return flask.json.jsonify({})
# Filter by post parameters
selected_dag_ids = {unquote(dag_id) for dag_id in request.form.getlist("dag_ids") if dag_id}
if selected_dag_ids:
filter_dag_ids = selected_dag_ids.intersection(allowed_dag_ids)
else:
filter_dag_ids = allowed_dag_ids
dataset_triggered_dag_ids = [
dag.dag_id
for dag in session.query(DagModel.dag_id)
.filter(DagModel.dag_id.in_(filter_dag_ids))
.filter(DagModel.schedule_interval == "Dataset")
]
dataset_triggered_next_run_info = get_dataset_triggered_next_run_info(
dataset_triggered_dag_ids, session=session
)
return flask.json.jsonify(dataset_triggered_next_run_info)
@expose("/dag_stats", methods=["POST"])
@auth.has_access(
[
(permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG),
(permissions.ACTION_CAN_READ, permissions.RESOURCE_DAG_RUN),
]
)
@provide_session
def dag_stats(self, session: Session = NEW_SESSION):
"""Dag statistics."""
dr = models.DagRun
allowed_dag_ids = get_airflow_app().appbuilder.sm.get_accessible_dag_ids(g.user)
dag_state_stats = session.query(dr.dag_id, dr.state, sqla.func.count(dr.state)).group_by(
dr.dag_id, dr.state
)
# Filter by post parameters
selected_dag_ids = {unquote(dag_id) for dag_id in request.form.getlist("dag_ids") if dag_id}
if selected_dag_ids:
filter_dag_ids = selected_dag_ids.intersection(allowed_dag_ids)
else:
filter_dag_ids = allowed_dag_ids
if not filter_dag_ids:
return flask.json.jsonify({})
dag_state_stats = dag_state_stats.filter(dr.dag_id.in_(filter_dag_ids))
data: dict[str, dict[str, int]] = collections.defaultdict(dict)
payload: dict[str, list[dict[str, Any]]] = collections.defaultdict(list)
for dag_id, state, count in dag_state_stats:
data[dag_id][state] = count