1702 lines
67 KiB
Python
1702 lines
67 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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"""The main config file for Superset
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All configuration in this file can be overridden by providing a superset_config
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in your PYTHONPATH as there is a ``from superset_config import *``
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at the end of this file.
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"""
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# pylint: disable=too-many-lines
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from __future__ import annotations
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import imp # pylint: disable=deprecated-module
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import importlib.util
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import json
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import logging
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import os
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import re
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import sys
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from collections import OrderedDict
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from datetime import timedelta
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from email.mime.multipart import MIMEMultipart
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from importlib.resources import files
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from typing import Any, Callable, Literal, TYPE_CHECKING, TypedDict
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import pkg_resources
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from celery.schedules import crontab
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from flask import Blueprint
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from flask_appbuilder.security.manager import AUTH_DB
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from flask_caching.backends.base import BaseCache
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from pandas import Series
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from pandas._libs.parsers import STR_NA_VALUES # pylint: disable=no-name-in-module
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from sqlalchemy.orm.query import Query
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from superset.advanced_data_type.plugins.internet_address import internet_address
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from superset.advanced_data_type.plugins.internet_port import internet_port
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from superset.advanced_data_type.types import AdvancedDataType
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from superset.constants import CHANGE_ME_SECRET_KEY
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from superset.jinja_context import BaseTemplateProcessor
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from superset.key_value.types import JsonKeyValueCodec
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from superset.stats_logger import DummyStatsLogger
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from superset.superset_typing import CacheConfig
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from superset.tasks.types import ExecutorType
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from superset.utils import core as utils
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from superset.utils.core import is_test, NO_TIME_RANGE, parse_boolean_string
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from superset.utils.encrypt import SQLAlchemyUtilsAdapter
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from superset.utils.log import DBEventLogger
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from superset.utils.logging_configurator import DefaultLoggingConfigurator
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logger = logging.getLogger(__name__)
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if TYPE_CHECKING:
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from flask_appbuilder.security.sqla import models
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from superset.connectors.sqla.models import SqlaTable
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from superset.models.core import Database
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from superset.models.dashboard import Dashboard
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from superset.models.slice import Slice
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# Realtime stats logger, a StatsD implementation exists
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STATS_LOGGER = DummyStatsLogger()
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EVENT_LOGGER = DBEventLogger()
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SUPERSET_LOG_VIEW = True
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BASE_DIR = pkg_resources.resource_filename("superset", "")
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if "SUPERSET_HOME" in os.environ:
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DATA_DIR = os.environ["SUPERSET_HOME"]
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else:
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DATA_DIR = os.path.expanduser("~/.superset")
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# ---------------------------------------------------------
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# Superset specific config
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# ---------------------------------------------------------
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VERSION_INFO_FILE = str(files("superset") / "static/version_info.json")
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PACKAGE_JSON_FILE = str(files("superset") / "static/assets/package.json")
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# Multiple favicons can be specified here. The "href" property
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# is mandatory, but "sizes," "type," and "rel" are optional.
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# For example:
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# {
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# "href":path/to/image.png",
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# "sizes": "16x16",
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# "type": "image/png"
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# "rel": "icon"
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# },
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FAVICONS = [{"href": "/static/assets/images/favicon.png"}]
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def _try_json_readversion(filepath: str) -> str | None:
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try:
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with open(filepath) as f:
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return json.load(f).get("version")
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except Exception: # pylint: disable=broad-except
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return None
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def _try_json_readsha(filepath: str, length: int) -> str | None:
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try:
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with open(filepath) as f:
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return json.load(f).get("GIT_SHA")[:length]
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except Exception: # pylint: disable=broad-except
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return None
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#
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# If True, we will skip the call to load the logger config found in alembic.init
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#
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ALEMBIC_SKIP_LOG_CONFIG = False
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# Depending on the context in which this config is loaded, the
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# version_info.json file may or may not be available, as it is
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# generated on install via setup.py. In the event that we're
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# actually running Superset, we will have already installed,
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# therefore it WILL exist. When unit tests are running, however,
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# it WILL NOT exist, so we fall back to reading package.json
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VERSION_STRING = _try_json_readversion(VERSION_INFO_FILE) or _try_json_readversion(
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PACKAGE_JSON_FILE
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)
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VERSION_SHA_LENGTH = 8
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VERSION_SHA = _try_json_readsha(VERSION_INFO_FILE, VERSION_SHA_LENGTH)
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# Build number is shown in the About section if available. This
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# can be replaced at build time to expose build information.
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BUILD_NUMBER = None
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# default viz used in chart explorer & SQL Lab explore
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DEFAULT_VIZ_TYPE = "table"
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# default row limit when requesting chart data
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ROW_LIMIT = 50000
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# default row limit when requesting samples from datasource in explore view
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SAMPLES_ROW_LIMIT = 1000
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# default row limit for native filters
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NATIVE_FILTER_DEFAULT_ROW_LIMIT = 1000
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# max rows retrieved by filter select auto complete
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FILTER_SELECT_ROW_LIMIT = 10000
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# default time filter in explore
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# values may be "Last day", "Last week", "<ISO date> : now", etc.
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DEFAULT_TIME_FILTER = NO_TIME_RANGE
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SUPERSET_WEBSERVER_PROTOCOL = "http"
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SUPERSET_WEBSERVER_ADDRESS = "0.0.0.0"
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SUPERSET_WEBSERVER_PORT = 8088
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# This is an important setting, and should be lower than your
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# [load balancer / proxy / envoy / kong / ...] timeout settings.
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# You should also make sure to configure your WSGI server
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# (gunicorn, nginx, apache, ...) timeout setting to be <= to this setting
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SUPERSET_WEBSERVER_TIMEOUT = int(timedelta(minutes=1).total_seconds())
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# this 2 settings are used by dashboard period force refresh feature
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# When user choose auto force refresh frequency
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# < SUPERSET_DASHBOARD_PERIODICAL_REFRESH_LIMIT
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# they will see warning message in the Refresh Interval Modal.
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# please check PR #9886
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SUPERSET_DASHBOARD_PERIODICAL_REFRESH_LIMIT = 0
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SUPERSET_DASHBOARD_PERIODICAL_REFRESH_WARNING_MESSAGE = None
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SUPERSET_DASHBOARD_POSITION_DATA_LIMIT = 65535
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CUSTOM_SECURITY_MANAGER = None
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SQLALCHEMY_TRACK_MODIFICATIONS = False
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# ---------------------------------------------------------
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# Your App secret key. Make sure you override it on superset_config.py
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# or use `SUPERSET_SECRET_KEY` environment variable.
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# Use a strong complex alphanumeric string and use a tool to help you generate
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# a sufficiently random sequence, ex: openssl rand -base64 42"
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SECRET_KEY = os.environ.get("SUPERSET_SECRET_KEY") or CHANGE_ME_SECRET_KEY
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# The SQLAlchemy connection string.
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SQLALCHEMY_DATABASE_URI = "sqlite:///" + os.path.join(DATA_DIR, "superset.db")
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# SQLALCHEMY_DATABASE_URI = 'mysql://myapp@localhost/myapp'
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# SQLALCHEMY_DATABASE_URI = 'postgresql://root:password@localhost/myapp'
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# In order to hook up a custom password store for all SQLALCHEMY connections
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# implement a function that takes a single argument of type 'sqla.engine.url',
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# returns a password and set SQLALCHEMY_CUSTOM_PASSWORD_STORE.
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#
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# e.g.:
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# def lookup_password(url):
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# return 'secret'
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# SQLALCHEMY_CUSTOM_PASSWORD_STORE = lookup_password
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SQLALCHEMY_CUSTOM_PASSWORD_STORE = None
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#
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# The EncryptedFieldTypeAdapter is used whenever we're building SqlAlchemy models
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# which include sensitive fields that should be app-encrypted BEFORE sending
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# to the DB.
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#
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# Note: the default impl leverages SqlAlchemyUtils' EncryptedType, which defaults
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# to AesEngine that uses AES-128 under the covers using the app's SECRET_KEY
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# as key material. Do note that AesEngine allows for queryability over the
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# encrypted fields.
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#
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# To change the default engine you need to define your own adapter:
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#
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# e.g.:
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#
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# class AesGcmEncryptedAdapter(
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# AbstractEncryptedFieldAdapter
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# ):
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# def create(
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# self,
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# app_config: Optional[Dict[str, Any]],
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# *args: List[Any],
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# **kwargs: Optional[Dict[str, Any]],
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# ) -> TypeDecorator:
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# if app_config:
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# return EncryptedType(
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# *args, app_config["SECRET_KEY"], engine=AesGcmEngine, **kwargs
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# )
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# raise Exception("Missing app_config kwarg")
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#
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#
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# SQLALCHEMY_ENCRYPTED_FIELD_TYPE_ADAPTER = AesGcmEncryptedAdapter
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SQLALCHEMY_ENCRYPTED_FIELD_TYPE_ADAPTER = ( # pylint: disable=invalid-name
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SQLAlchemyUtilsAdapter
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)
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# The limit of queries fetched for query search
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QUERY_SEARCH_LIMIT = 1000
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# Flask-WTF flag for CSRF
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WTF_CSRF_ENABLED = True
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# Add endpoints that need to be exempt from CSRF protection
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WTF_CSRF_EXEMPT_LIST = [
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"superset.views.core.log",
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"superset.views.core.explore_json",
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"superset.charts.data.api.data",
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]
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# Whether to run the web server in debug mode or not
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DEBUG = os.environ.get("FLASK_DEBUG")
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FLASK_USE_RELOAD = True
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# Enable profiling of Python calls. Turn this on and append ``?_instrument=1``
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# to the page to see the call stack.
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PROFILING = False
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# Superset allows server-side python stacktraces to be surfaced to the
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# user when this feature is on. This may have security implications
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# and it's more secure to turn it off in production settings.
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SHOW_STACKTRACE = False
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# Use all X-Forwarded headers when ENABLE_PROXY_FIX is True.
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# When proxying to a different port, set "x_port" to 0 to avoid downstream issues.
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ENABLE_PROXY_FIX = False
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PROXY_FIX_CONFIG = {"x_for": 1, "x_proto": 1, "x_host": 1, "x_port": 1, "x_prefix": 1}
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# Configuration for scheduling queries from SQL Lab.
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SCHEDULED_QUERIES: dict[str, Any] = {}
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# FAB Rate limiting: this is a security feature for preventing DDOS attacks. The
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# feature is on by default to make Superset secure by default, but you should
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# fine tune the limits to your needs. You can read more about the different
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# parameters here: https://flask-limiter.readthedocs.io/en/stable/configuration.html
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RATELIMIT_ENABLED = True
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RATELIMIT_APPLICATION = "50 per second"
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AUTH_RATE_LIMITED = True
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AUTH_RATE_LIMIT = "5 per second"
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# A storage location conforming to the scheme in storage-scheme. See the limits
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# library for allowed values: https://limits.readthedocs.io/en/stable/storage.html
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# RATELIMIT_STORAGE_URI = "redis://host:port"
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# A callable that returns the unique identity of the current request.
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# RATELIMIT_REQUEST_IDENTIFIER = flask.Request.endpoint
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# ------------------------------
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# GLOBALS FOR APP Builder
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# ------------------------------
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# Uncomment to setup Your App name
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APP_NAME = "Superset"
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# Specify the App icon
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APP_ICON = "/static/assets/images/superset-logo-horiz.png"
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# Specify where clicking the logo would take the user
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# e.g. setting it to '/' would take the user to '/superset/welcome/'
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LOGO_TARGET_PATH = None
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# Specify tooltip that should appear when hovering over the App Icon/Logo
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LOGO_TOOLTIP = ""
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# Specify any text that should appear to the right of the logo
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LOGO_RIGHT_TEXT: Callable[[], str] | str = ""
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# Enables SWAGGER UI for superset openapi spec
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# ex: http://localhost:8080/swagger/v1
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FAB_API_SWAGGER_UI = True
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# ----------------------------------------------------
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# AUTHENTICATION CONFIG
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# ----------------------------------------------------
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# The authentication type
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# AUTH_OID : Is for OpenID
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# AUTH_DB : Is for database (username/password)
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# AUTH_LDAP : Is for LDAP
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# AUTH_REMOTE_USER : Is for using REMOTE_USER from web server
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AUTH_TYPE = AUTH_DB
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# Uncomment to setup Full admin role name
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# AUTH_ROLE_ADMIN = 'Admin'
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# Uncomment to setup Public role name, no authentication needed
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# AUTH_ROLE_PUBLIC = 'Public'
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# Will allow user self registration
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# AUTH_USER_REGISTRATION = True
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# The default user self registration role
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# AUTH_USER_REGISTRATION_ROLE = "Public"
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# When using LDAP Auth, setup the LDAP server
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# AUTH_LDAP_SERVER = "ldap://ldapserver.new"
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# Uncomment to setup OpenID providers example for OpenID authentication
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# OPENID_PROVIDERS = [
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# { 'name': 'Yahoo', 'url': 'https://open.login.yahoo.com/' },
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# { 'name': 'Flickr', 'url': 'https://www.flickr.com/<username>' },
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# ---------------------------------------------------
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# Roles config
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# ---------------------------------------------------
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# Grant public role the same set of permissions as for a selected builtin role.
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# This is useful if one wants to enable anonymous users to view
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# dashboards. Explicit grant on specific datasets is still required.
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PUBLIC_ROLE_LIKE: str | None = None
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# ---------------------------------------------------
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# Babel config for translations
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# ---------------------------------------------------
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# Setup default language
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BABEL_DEFAULT_LOCALE = "en"
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# Your application default translation path
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BABEL_DEFAULT_FOLDER = "superset/translations"
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# The allowed translation for your app
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LANGUAGES = {
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"en": {"flag": "us", "name": "English"},
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"es": {"flag": "es", "name": "Spanish"},
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"it": {"flag": "it", "name": "Italian"},
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"fr": {"flag": "fr", "name": "French"},
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"zh": {"flag": "cn", "name": "Chinese"},
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"ja": {"flag": "jp", "name": "Japanese"},
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"de": {"flag": "de", "name": "German"},
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"pt": {"flag": "pt", "name": "Portuguese"},
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"pt_BR": {"flag": "br", "name": "Brazilian Portuguese"},
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"ru": {"flag": "ru", "name": "Russian"},
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"ko": {"flag": "kr", "name": "Korean"},
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"sk": {"flag": "sk", "name": "Slovak"},
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"sl": {"flag": "si", "name": "Slovenian"},
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"nl": {"flag": "nl", "name": "Dutch"},
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}
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# Turning off i18n by default as translation in most languages are
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# incomplete and not well maintained.
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LANGUAGES = {}
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# Override the default d3 locale format
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# Default values are equivalent to
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# D3_FORMAT = {
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# "decimal": ".", # - decimal place string (e.g., ".").
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# "thousands": ",", # - group separator string (e.g., ",").
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# "grouping": [3], # - array of group sizes (e.g., [3]), cycled as needed.
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# "currency": ["$", ""] # - currency prefix/suffix strings (e.g., ["$", ""])
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# }
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# https://github.com/d3/d3-format/blob/main/README.md#formatLocale
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class D3Format(TypedDict, total=False):
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decimal: str
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thousands: str
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grouping: list[int]
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currency: list[str]
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D3_FORMAT: D3Format = {}
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CURRENCIES = ["USD", "EUR", "GBP", "INR", "MXN", "JPY", "CNY"]
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# ---------------------------------------------------
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# Feature flags
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# ---------------------------------------------------
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# Feature flags that are set by default go here. Their values can be
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# overwritten by those specified under FEATURE_FLAGS in superset_config.py
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# For example, DEFAULT_FEATURE_FLAGS = { 'FOO': True, 'BAR': False } here
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# and FEATURE_FLAGS = { 'BAR': True, 'BAZ': True } in superset_config.py
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# will result in combined feature flags of { 'FOO': True, 'BAR': True, 'BAZ': True }
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DEFAULT_FEATURE_FLAGS: dict[str, bool] = {
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# Experimental feature introducing a client (browser) cache
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"CLIENT_CACHE": False, # deprecated
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"DISABLE_DATASET_SOURCE_EDIT": False, # deprecated
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# When using a recent version of Druid that supports JOINs turn this on
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"DRUID_JOINS": False,
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"DYNAMIC_PLUGINS": False,
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# With Superset 2.0, we are updating the default so that the legacy datasource
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# editor no longer shows. Currently this is set to false so that the editor
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# option does show, but we will be depreciating it.
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"DISABLE_LEGACY_DATASOURCE_EDITOR": True,
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# For some security concerns, you may need to enforce CSRF protection on
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# all query request to explore_json endpoint. In Superset, we use
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# `flask-csrf <https://sjl.bitbucket.io/flask-csrf/>`_ add csrf protection
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# for all POST requests, but this protection doesn't apply to GET method.
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# When ENABLE_EXPLORE_JSON_CSRF_PROTECTION is set to true, your users cannot
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# make GET request to explore_json. explore_json accepts both GET and POST request.
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# See `PR 7935 <https://github.com/apache/superset/pull/7935>`_ for more details.
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"ENABLE_EXPLORE_JSON_CSRF_PROTECTION": False, # deprecated
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"ENABLE_TEMPLATE_PROCESSING": False,
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"ENABLE_TEMPLATE_REMOVE_FILTERS": True, # deprecated
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# Allow for javascript controls components
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# this enables programmers to customize certain charts (like the
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# geospatial ones) by inputting javascript in controls. This exposes
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# an XSS security vulnerability
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"ENABLE_JAVASCRIPT_CONTROLS": False,
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"KV_STORE": False,
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# When this feature is enabled, nested types in Presto will be
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# expanded into extra columns and/or arrays. This is experimental,
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# and doesn't work with all nested types.
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"PRESTO_EXPAND_DATA": False,
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# Exposes API endpoint to compute thumbnails
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"THUMBNAILS": False,
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"DASHBOARD_CACHE": False, # deprecated
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"REMOVE_SLICE_LEVEL_LABEL_COLORS": False, # deprecated
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"SHARE_QUERIES_VIA_KV_STORE": False,
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"TAGGING_SYSTEM": False,
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"SQLLAB_BACKEND_PERSISTENCE": True,
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"LISTVIEWS_DEFAULT_CARD_VIEW": False,
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# When True, this escapes HTML (rather than rendering it) in Markdown components
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"ESCAPE_MARKDOWN_HTML": False,
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"DASHBOARD_NATIVE_FILTERS": True, # deprecated
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"DASHBOARD_CROSS_FILTERS": True,
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# Feature is under active development and breaking changes are expected
|
|
"DASHBOARD_NATIVE_FILTERS_SET": False, # deprecated
|
|
"DASHBOARD_FILTERS_EXPERIMENTAL": False, # deprecated
|
|
"DASHBOARD_VIRTUALIZATION": False,
|
|
"GLOBAL_ASYNC_QUERIES": False,
|
|
"VERSIONED_EXPORT": True, # deprecated
|
|
"EMBEDDED_SUPERSET": False,
|
|
# Enables Alerts and reports new implementation
|
|
"ALERT_REPORTS": False,
|
|
"DASHBOARD_RBAC": False,
|
|
"ENABLE_EXPLORE_DRAG_AND_DROP": True, # deprecated
|
|
"ENABLE_ADVANCED_DATA_TYPES": False,
|
|
# Enabling ALERTS_ATTACH_REPORTS, the system sends email and slack message
|
|
# with screenshot and link
|
|
# Disables ALERTS_ATTACH_REPORTS, the system DOES NOT generate screenshot
|
|
# for report with type 'alert' and sends email and slack message with only link;
|
|
# for report with type 'report' still send with email and slack message with
|
|
# screenshot and link
|
|
"ALERTS_ATTACH_REPORTS": True,
|
|
# Allow users to export full CSV of table viz type.
|
|
# This could cause the server to run out of memory or compute.
|
|
"ALLOW_FULL_CSV_EXPORT": False,
|
|
"GENERIC_CHART_AXES": True, # deprecated
|
|
"ALLOW_ADHOC_SUBQUERY": False,
|
|
"USE_ANALAGOUS_COLORS": False,
|
|
# Apply RLS rules to SQL Lab queries. This requires parsing and manipulating the
|
|
# query, and might break queries and/or allow users to bypass RLS. Use with care!
|
|
"RLS_IN_SQLLAB": False,
|
|
# Enable caching per impersonation key (e.g username) in a datasource where user
|
|
# impersonation is enabled
|
|
"CACHE_IMPERSONATION": False,
|
|
# Enable caching per user key for Superset cache (not database cache impersonation)
|
|
"CACHE_QUERY_BY_USER": False,
|
|
# Enable sharing charts with embedding
|
|
"EMBEDDABLE_CHARTS": True,
|
|
"DRILL_TO_DETAIL": True,
|
|
"DRILL_BY": False,
|
|
"DATAPANEL_CLOSED_BY_DEFAULT": False,
|
|
"HORIZONTAL_FILTER_BAR": False,
|
|
# The feature is off by default, and currently only supported in Presto and Postgres,
|
|
# and Bigquery.
|
|
# It also needs to be enabled on a per-database basis, by adding the key/value pair
|
|
# `cost_estimate_enabled: true` to the database `extra` attribute.
|
|
"ESTIMATE_QUERY_COST": False,
|
|
# Allow users to enable ssh tunneling when creating a DB.
|
|
# Users must check whether the DB engine supports SSH Tunnels
|
|
# otherwise enabling this flag won't have any effect on the DB.
|
|
"SSH_TUNNELING": False,
|
|
"AVOID_COLORS_COLLISION": True,
|
|
# Set to False to only allow viewing own recent activity
|
|
# or to disallow users from viewing other users profile page
|
|
# Do not show user info or profile in the menu
|
|
"MENU_HIDE_USER_INFO": False,
|
|
# Allows users to add a ``superset://`` DB that can query across databases. This is
|
|
# an experimental feature with potential security and performance risks, so use with
|
|
# caution. If the feature is enabled you can also set a limit for how much data is
|
|
# returned from each database in the ``SUPERSET_META_DB_LIMIT`` configuration value
|
|
# in this file.
|
|
"ENABLE_SUPERSET_META_DB": False,
|
|
# Set to True to replace Selenium with Playwright to execute reports and thumbnails.
|
|
# Unlike Selenium, Playwright reports support deck.gl visualizations
|
|
# Enabling this feature flag requires installing "playwright" pip package
|
|
"PLAYWRIGHT_REPORTS_AND_THUMBNAILS": False,
|
|
}
|
|
|
|
# ------------------------------
|
|
# SSH Tunnel
|
|
# ------------------------------
|
|
# Allow users to set the host used when connecting to the SSH Tunnel
|
|
# as localhost and any other alias (0.0.0.0)
|
|
# ----------------------------------------------------------------------
|
|
# |
|
|
# -------------+ | +----------+
|
|
# LOCAL | | | REMOTE | :22 SSH
|
|
# CLIENT | <== SSH ========> | SERVER | :8080 web service
|
|
# -------------+ | +----------+
|
|
# |
|
|
# FIREWALL (only port 22 is open)
|
|
|
|
# ----------------------------------------------------------------------
|
|
SSH_TUNNEL_MANAGER_CLASS = "superset.extensions.ssh.SSHManager"
|
|
SSH_TUNNEL_LOCAL_BIND_ADDRESS = "127.0.0.1"
|
|
#: Timeout (seconds) for tunnel connection (open_channel timeout)
|
|
SSH_TUNNEL_TIMEOUT_SEC = 10.0
|
|
#: Timeout (seconds) for transport socket (``socket.settimeout``)
|
|
SSH_TUNNEL_PACKET_TIMEOUT_SEC = 1.0
|
|
|
|
|
|
# Feature flags may also be set via 'SUPERSET_FEATURE_' prefixed environment vars.
|
|
DEFAULT_FEATURE_FLAGS.update(
|
|
{
|
|
k[len("SUPERSET_FEATURE_") :]: parse_boolean_string(v)
|
|
for k, v in os.environ.items()
|
|
if re.search(r"^SUPERSET_FEATURE_\w+", k)
|
|
}
|
|
)
|
|
|
|
# This is merely a default.
|
|
FEATURE_FLAGS: dict[str, bool] = {}
|
|
|
|
# A function that receives a dict of all feature flags
|
|
# (DEFAULT_FEATURE_FLAGS merged with FEATURE_FLAGS)
|
|
# can alter it, and returns a similar dict. Note the dict of feature
|
|
# flags passed to the function is a deepcopy of the dict in the config,
|
|
# and can therefore be mutated without side-effect
|
|
#
|
|
# GET_FEATURE_FLAGS_FUNC can be used to implement progressive rollouts,
|
|
# role-based features, or a full on A/B testing framework.
|
|
#
|
|
# from flask import g, request
|
|
# def GET_FEATURE_FLAGS_FUNC(feature_flags_dict: Dict[str, bool]) -> Dict[str, bool]:
|
|
# if hasattr(g, "user") and g.user.is_active:
|
|
# feature_flags_dict['some_feature'] = g.user and g.user.get_id() == 5
|
|
# return feature_flags_dict
|
|
GET_FEATURE_FLAGS_FUNC: Callable[[dict[str, bool]], dict[str, bool]] | None = None
|
|
# A function that receives a feature flag name and an optional default value.
|
|
# Has a similar utility to GET_FEATURE_FLAGS_FUNC but it's useful to not force the
|
|
# evaluation of all feature flags when just evaluating a single one.
|
|
#
|
|
# Note that the default `get_feature_flags` will evaluate each feature with this
|
|
# callable when the config key is set, so don't use both GET_FEATURE_FLAGS_FUNC
|
|
# and IS_FEATURE_ENABLED_FUNC in conjunction.
|
|
IS_FEATURE_ENABLED_FUNC: Callable[[str, bool | None], bool] | None = None
|
|
# A function that expands/overrides the frontend `bootstrap_data.common` object.
|
|
# Can be used to implement custom frontend functionality,
|
|
# or dynamically change certain configs.
|
|
#
|
|
# Values in `bootstrap_data.common` should have these characteristics:
|
|
# - They are not specific to a page the user is visiting
|
|
# - They do not contain secrets
|
|
#
|
|
# Takes as a parameter the common bootstrap payload before transformations.
|
|
# Returns a dict containing data that should be added or overridden to the payload.
|
|
COMMON_BOOTSTRAP_OVERRIDES_FUNC: Callable[
|
|
[dict[str, Any]], dict[str, Any]
|
|
] = lambda data: {} # default: empty dict
|
|
|
|
# EXTRA_CATEGORICAL_COLOR_SCHEMES is used for adding custom categorical color schemes
|
|
# example code for "My custom warm to hot" color scheme
|
|
# EXTRA_CATEGORICAL_COLOR_SCHEMES = [
|
|
# {
|
|
# "id": 'myVisualizationColors',
|
|
# "description": '',
|
|
# "label": 'My Visualization Colors',
|
|
# "isDefault": True,
|
|
# "colors":
|
|
# ['#006699', '#009DD9', '#5AAA46', '#44AAAA', '#DDAA77', '#7799BB', '#88AA77',
|
|
# '#552288', '#5AAA46', '#CC7788', '#EEDD55', '#9977BB', '#BBAA44', '#DDCCDD']
|
|
# }]
|
|
|
|
# This is merely a default
|
|
EXTRA_CATEGORICAL_COLOR_SCHEMES: list[dict[str, Any]] = []
|
|
|
|
# THEME_OVERRIDES is used for adding custom theme to superset
|
|
# example code for "My theme" custom scheme
|
|
# THEME_OVERRIDES = {
|
|
# "borderRadius": 4,
|
|
# "colors": {
|
|
# "primary": {
|
|
# "base": 'red',
|
|
# },
|
|
# "secondary": {
|
|
# "base": 'green',
|
|
# },
|
|
# "grayscale": {
|
|
# "base": 'orange',
|
|
# }
|
|
# }
|
|
# }
|
|
|
|
THEME_OVERRIDES: dict[str, Any] = {}
|
|
|
|
# EXTRA_SEQUENTIAL_COLOR_SCHEMES is used for adding custom sequential color schemes
|
|
# EXTRA_SEQUENTIAL_COLOR_SCHEMES = [
|
|
# {
|
|
# "id": 'warmToHot',
|
|
# "description": '',
|
|
# "isDiverging": True,
|
|
# "label": 'My custom warm to hot',
|
|
# "isDefault": True,
|
|
# "colors":
|
|
# ['#552288', '#5AAA46', '#CC7788', '#EEDD55', '#9977BB', '#BBAA44', '#DDCCDD',
|
|
# '#006699', '#009DD9', '#5AAA46', '#44AAAA', '#DDAA77', '#7799BB', '#88AA77']
|
|
# }]
|
|
|
|
# This is merely a default
|
|
EXTRA_SEQUENTIAL_COLOR_SCHEMES: list[dict[str, Any]] = []
|
|
|
|
# ---------------------------------------------------
|
|
# Thumbnail config (behind feature flag)
|
|
# ---------------------------------------------------
|
|
# By default, thumbnails are rendered per user, and will fall back to the Selenium
|
|
# user for anonymous users. Similar to Alerts & Reports, thumbnails
|
|
# can be configured to always be rendered as a fixed user. See
|
|
# `superset.tasks.types.ExecutorType` for a full list of executor options.
|
|
# To always use a fixed user account, use the following configuration:
|
|
# THUMBNAIL_EXECUTE_AS = [ExecutorType.SELENIUM]
|
|
THUMBNAIL_SELENIUM_USER: str | None = "admin"
|
|
THUMBNAIL_EXECUTE_AS = [ExecutorType.CURRENT_USER, ExecutorType.SELENIUM]
|
|
|
|
# By default, thumbnail digests are calculated based on various parameters in the
|
|
# chart/dashboard metadata, and in the case of user-specific thumbnails, the
|
|
# username. To specify a custom digest function, use the following config parameters
|
|
# to define callbacks that receive
|
|
# 1. the model (dashboard or chart)
|
|
# 2. the executor type (e.g. ExecutorType.SELENIUM)
|
|
# 3. the executor's username (note, this is the executor as defined by
|
|
# `THUMBNAIL_EXECUTE_AS`; the executor is only equal to the currently logged in
|
|
# user if the executor type is equal to `ExecutorType.CURRENT_USER`)
|
|
# and return the final digest string:
|
|
THUMBNAIL_DASHBOARD_DIGEST_FUNC: None | (
|
|
Callable[[Dashboard, ExecutorType, str], str]
|
|
) = None
|
|
THUMBNAIL_CHART_DIGEST_FUNC: Callable[[Slice, ExecutorType, str], str] | None = None
|
|
|
|
THUMBNAIL_CACHE_CONFIG: CacheConfig = {
|
|
"CACHE_TYPE": "NullCache",
|
|
"CACHE_NO_NULL_WARNING": True,
|
|
}
|
|
|
|
# Time before selenium times out after trying to locate an element on the page and wait
|
|
# for that element to load for a screenshot.
|
|
SCREENSHOT_LOCATE_WAIT = int(timedelta(seconds=10).total_seconds())
|
|
# Time before selenium times out after waiting for all DOM class elements named
|
|
# "loading" are gone.
|
|
SCREENSHOT_LOAD_WAIT = int(timedelta(minutes=1).total_seconds())
|
|
# Selenium destroy retries
|
|
SCREENSHOT_SELENIUM_RETRIES = 5
|
|
# Give selenium an headstart, in seconds
|
|
SCREENSHOT_SELENIUM_HEADSTART = 3
|
|
# Wait for the chart animation, in seconds
|
|
SCREENSHOT_SELENIUM_ANIMATION_WAIT = 5
|
|
# Replace unexpected errors in screenshots with real error messages
|
|
SCREENSHOT_REPLACE_UNEXPECTED_ERRORS = False
|
|
# Max time to wait for error message modal to show up, in seconds
|
|
SCREENSHOT_WAIT_FOR_ERROR_MODAL_VISIBLE = 5
|
|
# Max time to wait for error message modal to close, in seconds
|
|
SCREENSHOT_WAIT_FOR_ERROR_MODAL_INVISIBLE = 5
|
|
|
|
# ---------------------------------------------------
|
|
# Image and file configuration
|
|
# ---------------------------------------------------
|
|
# The file upload folder, when using models with files
|
|
UPLOAD_FOLDER = BASE_DIR + "/app/static/uploads/"
|
|
UPLOAD_CHUNK_SIZE = 4096
|
|
|
|
# The image upload folder, when using models with images
|
|
IMG_UPLOAD_FOLDER = BASE_DIR + "/app/static/uploads/"
|
|
|
|
# The image upload url, when using models with images
|
|
IMG_UPLOAD_URL = "/static/uploads/"
|
|
# Setup image size default is (300, 200, True)
|
|
# IMG_SIZE = (300, 200, True)
|
|
|
|
# Default cache timeout, applies to all cache backends unless specifically overridden in
|
|
# each cache config.
|
|
CACHE_DEFAULT_TIMEOUT = int(timedelta(days=1).total_seconds())
|
|
|
|
# Default cache for Superset objects
|
|
CACHE_CONFIG: CacheConfig = {"CACHE_TYPE": "NullCache"}
|
|
|
|
# Cache for datasource metadata and query results
|
|
DATA_CACHE_CONFIG: CacheConfig = {"CACHE_TYPE": "NullCache"}
|
|
|
|
# Cache for dashboard filter state. `CACHE_TYPE` defaults to `SupersetMetastoreCache`
|
|
# that stores the values in the key-value table in the Superset metastore, as it's
|
|
# required for Superset to operate correctly, but can be replaced by any
|
|
# `Flask-Caching` backend.
|
|
FILTER_STATE_CACHE_CONFIG: CacheConfig = {
|
|
"CACHE_TYPE": "SupersetMetastoreCache",
|
|
"CACHE_DEFAULT_TIMEOUT": int(timedelta(days=90).total_seconds()),
|
|
# Should the timeout be reset when retrieving a cached value?
|
|
"REFRESH_TIMEOUT_ON_RETRIEVAL": True,
|
|
# The following parameter only applies to `MetastoreCache`:
|
|
# How should entries be serialized/deserialized?
|
|
"CODEC": JsonKeyValueCodec(),
|
|
}
|
|
|
|
# Cache for explore form data state. `CACHE_TYPE` defaults to `SupersetMetastoreCache`
|
|
# that stores the values in the key-value table in the Superset metastore, as it's
|
|
# required for Superset to operate correctly, but can be replaced by any
|
|
# `Flask-Caching` backend.
|
|
EXPLORE_FORM_DATA_CACHE_CONFIG: CacheConfig = {
|
|
"CACHE_TYPE": "SupersetMetastoreCache",
|
|
"CACHE_DEFAULT_TIMEOUT": int(timedelta(days=7).total_seconds()),
|
|
# Should the timeout be reset when retrieving a cached value?
|
|
"REFRESH_TIMEOUT_ON_RETRIEVAL": True,
|
|
# The following parameter only applies to `MetastoreCache`:
|
|
# How should entries be serialized/deserialized?
|
|
"CODEC": JsonKeyValueCodec(),
|
|
}
|
|
|
|
# store cache keys by datasource UID (via CacheKey) for custom processing/invalidation
|
|
STORE_CACHE_KEYS_IN_METADATA_DB = False
|
|
|
|
# CORS Options
|
|
ENABLE_CORS = False
|
|
CORS_OPTIONS: dict[Any, Any] = {}
|
|
|
|
# Sanitizes the HTML content used in markdowns to allow its rendering in a safe manner.
|
|
# Disabling this option is not recommended for security reasons. If you wish to allow
|
|
# valid safe elements that are not included in the default sanitization schema, use the
|
|
# HTML_SANITIZATION_SCHEMA_EXTENSIONS configuration.
|
|
HTML_SANITIZATION = True
|
|
|
|
# Use this configuration to extend the HTML sanitization schema.
|
|
# By default we use the GitHub schema defined in
|
|
# https://github.com/syntax-tree/hast-util-sanitize/blob/main/lib/schema.js
|
|
# For example, the following configuration would allow the rendering of the
|
|
# style attribute for div elements and the ftp protocol in hrefs:
|
|
# HTML_SANITIZATION_SCHEMA_EXTENSIONS = {
|
|
# "attributes": {
|
|
# "div": ["style"],
|
|
# },
|
|
# "protocols": {
|
|
# "href": ["ftp"],
|
|
# }
|
|
# }
|
|
# Be careful when extending the default schema to avoid XSS attacks.
|
|
HTML_SANITIZATION_SCHEMA_EXTENSIONS: dict[str, Any] = {}
|
|
|
|
# Chrome allows up to 6 open connections per domain at a time. When there are more
|
|
# than 6 slices in dashboard, a lot of time fetch requests are queued up and wait for
|
|
# next available socket. PR #5039 is trying to allow domain sharding for Superset,
|
|
# and this feature will be enabled by configuration only (by default Superset
|
|
# doesn't allow cross-domain request).
|
|
SUPERSET_WEBSERVER_DOMAINS = None
|
|
|
|
# Allowed format types for upload on Database view
|
|
EXCEL_EXTENSIONS = {"xlsx", "xls"}
|
|
CSV_EXTENSIONS = {"csv", "tsv", "txt"}
|
|
COLUMNAR_EXTENSIONS = {"parquet", "zip"}
|
|
ALLOWED_EXTENSIONS = {*EXCEL_EXTENSIONS, *CSV_EXTENSIONS, *COLUMNAR_EXTENSIONS}
|
|
|
|
# Optional maximum file size in bytes when uploading a CSV
|
|
CSV_UPLOAD_MAX_SIZE = None
|
|
|
|
# CSV Options: key/value pairs that will be passed as argument to DataFrame.to_csv
|
|
# method.
|
|
# note: index option should not be overridden
|
|
CSV_EXPORT = {"encoding": "utf-8"}
|
|
|
|
# Excel Options: key/value pairs that will be passed as argument to DataFrame.to_excel
|
|
# method.
|
|
# note: index option should not be overridden
|
|
EXCEL_EXPORT: dict[str, Any] = {}
|
|
|
|
# ---------------------------------------------------
|
|
# Time grain configurations
|
|
# ---------------------------------------------------
|
|
# List of time grains to disable in the application (see list of builtin
|
|
# time grains in superset/db_engine_specs/base.py).
|
|
# For example: to disable 1 second time grain:
|
|
# TIME_GRAIN_DENYLIST = ['PT1S']
|
|
TIME_GRAIN_DENYLIST: list[str] = []
|
|
|
|
# Additional time grains to be supported using similar definitions as in
|
|
# superset/db_engine_specs/base.py.
|
|
# For example: To add a new 2 second time grain:
|
|
# TIME_GRAIN_ADDONS = {'PT2S': '2 second'}
|
|
TIME_GRAIN_ADDONS: dict[str, str] = {}
|
|
|
|
# Implementation of additional time grains per engine.
|
|
# The column to be truncated is denoted `{col}` in the expression.
|
|
# For example: To implement 2 second time grain on clickhouse engine:
|
|
# TIME_GRAIN_ADDON_EXPRESSIONS = {
|
|
# 'clickhouse': {
|
|
# 'PT2S': 'toDateTime(intDiv(toUInt32(toDateTime({col})), 2)*2)'
|
|
# }
|
|
# }
|
|
TIME_GRAIN_ADDON_EXPRESSIONS: dict[str, dict[str, str]] = {}
|
|
|
|
# Map of custom time grains and artificial join column producers used
|
|
# when generating the join key between results and time shifts.
|
|
# See superset/common/query_context_processor.get_aggregated_join_column
|
|
#
|
|
# Example of a join column producer that aggregates by fiscal year
|
|
# def join_producer(row: Series, column_index: int) -> str:
|
|
# return row[index].strftime("%F")
|
|
#
|
|
# TIME_GRAIN_JOIN_COLUMN_PRODUCERS = {"P1F": join_producer}
|
|
TIME_GRAIN_JOIN_COLUMN_PRODUCERS: dict[str, Callable[[Series, int], str]] = {}
|
|
|
|
# ---------------------------------------------------
|
|
# List of viz_types not allowed in your environment
|
|
# For example: Disable pivot table and treemap:
|
|
# VIZ_TYPE_DENYLIST = ['pivot_table', 'treemap']
|
|
# ---------------------------------------------------
|
|
|
|
VIZ_TYPE_DENYLIST: list[str] = []
|
|
|
|
# --------------------------------------------------
|
|
# Modules, datasources and middleware to be registered
|
|
# --------------------------------------------------
|
|
DEFAULT_MODULE_DS_MAP = OrderedDict(
|
|
[
|
|
("superset.connectors.sqla.models", ["SqlaTable"]),
|
|
]
|
|
)
|
|
ADDITIONAL_MODULE_DS_MAP: dict[str, list[str]] = {}
|
|
ADDITIONAL_MIDDLEWARE: list[Callable[..., Any]] = []
|
|
|
|
# 1) https://docs.python-guide.org/writing/logging/
|
|
# 2) https://docs.python.org/2/library/logging.config.html
|
|
|
|
# Default configurator will consume the LOG_* settings below
|
|
LOGGING_CONFIGURATOR = DefaultLoggingConfigurator()
|
|
|
|
# Console Log Settings
|
|
|
|
LOG_FORMAT = "%(asctime)s:%(levelname)s:%(name)s:%(message)s"
|
|
LOG_LEVEL = "DEBUG"
|
|
|
|
# ---------------------------------------------------
|
|
# Enable Time Rotate Log Handler
|
|
# ---------------------------------------------------
|
|
# LOG_LEVEL = DEBUG, INFO, WARNING, ERROR, CRITICAL
|
|
|
|
ENABLE_TIME_ROTATE = False
|
|
TIME_ROTATE_LOG_LEVEL = "DEBUG"
|
|
FILENAME = os.path.join(DATA_DIR, "superset.log")
|
|
ROLLOVER = "midnight"
|
|
INTERVAL = 1
|
|
BACKUP_COUNT = 30
|
|
|
|
# Custom logger for auditing queries. This can be used to send ran queries to a
|
|
# structured immutable store for auditing purposes. The function is called for
|
|
# every query ran, in both SQL Lab and charts/dashboards.
|
|
# def QUERY_LOGGER(
|
|
# database,
|
|
# query,
|
|
# schema=None,
|
|
# client=None,
|
|
# security_manager=None,
|
|
# log_params=None,
|
|
# ):
|
|
# pass
|
|
QUERY_LOGGER = None
|
|
|
|
# Set this API key to enable Mapbox visualizations
|
|
MAPBOX_API_KEY = os.environ.get("MAPBOX_API_KEY", "")
|
|
|
|
# Maximum number of rows returned for any analytical database query
|
|
SQL_MAX_ROW = 100000
|
|
|
|
# Maximum number of rows displayed in SQL Lab UI
|
|
# Is set to avoid out of memory/localstorage issues in browsers. Does not affect
|
|
# exported CSVs
|
|
DISPLAY_MAX_ROW = 10000
|
|
|
|
# Default row limit for SQL Lab queries. Is overridden by setting a new limit in
|
|
# the SQL Lab UI
|
|
DEFAULT_SQLLAB_LIMIT = 1000
|
|
|
|
# The limit for the Superset Meta DB when the feature flag ENABLE_SUPERSET_META_DB is on
|
|
SUPERSET_META_DB_LIMIT: int | None = 1000
|
|
|
|
# Adds a warning message on sqllab save query and schedule query modals.
|
|
SQLLAB_SAVE_WARNING_MESSAGE = None
|
|
SQLLAB_SCHEDULE_WARNING_MESSAGE = None
|
|
|
|
# Force refresh while auto-refresh in dashboard
|
|
DASHBOARD_AUTO_REFRESH_MODE: Literal["fetch", "force"] = "force"
|
|
# Dashboard auto refresh intervals
|
|
DASHBOARD_AUTO_REFRESH_INTERVALS = [
|
|
[0, "Don't refresh"],
|
|
[10, "10 seconds"],
|
|
[30, "30 seconds"],
|
|
[60, "1 minute"],
|
|
[300, "5 minutes"],
|
|
[1800, "30 minutes"],
|
|
[3600, "1 hour"],
|
|
[21600, "6 hours"],
|
|
[43200, "12 hours"],
|
|
[86400, "24 hours"],
|
|
]
|
|
|
|
# This is used as a workaround for the alerts & reports scheduler task to get the time
|
|
# celery beat triggered it, see https://github.com/celery/celery/issues/6974 for details
|
|
CELERY_BEAT_SCHEDULER_EXPIRES = timedelta(weeks=1)
|
|
|
|
# Default celery config is to use SQLA as a broker, in a production setting
|
|
# you'll want to use a proper broker as specified here:
|
|
# https://docs.celeryq.dev/en/stable/getting-started/backends-and-brokers/index.html
|
|
|
|
|
|
class CeleryConfig: # pylint: disable=too-few-public-methods
|
|
broker_url = "sqla+sqlite:///celerydb.sqlite"
|
|
imports = ("superset.sql_lab",)
|
|
result_backend = "db+sqlite:///celery_results.sqlite"
|
|
worker_prefetch_multiplier = 1
|
|
task_acks_late = False
|
|
task_annotations = {
|
|
"sql_lab.get_sql_results": {"rate_limit": "100/s"},
|
|
"email_reports.send": {
|
|
"rate_limit": "1/s",
|
|
"time_limit": int(timedelta(seconds=120).total_seconds()),
|
|
"soft_time_limit": int(timedelta(seconds=150).total_seconds()),
|
|
"ignore_result": True,
|
|
},
|
|
}
|
|
beat_schedule = {
|
|
"email_reports.schedule_hourly": {
|
|
"task": "email_reports.schedule_hourly",
|
|
"schedule": crontab(minute=1, hour="*"),
|
|
},
|
|
"reports.scheduler": {
|
|
"task": "reports.scheduler",
|
|
"schedule": crontab(minute="*", hour="*"),
|
|
"options": {"expires": int(CELERY_BEAT_SCHEDULER_EXPIRES.total_seconds())},
|
|
},
|
|
"reports.prune_log": {
|
|
"task": "reports.prune_log",
|
|
"schedule": crontab(minute=0, hour=0),
|
|
},
|
|
}
|
|
|
|
|
|
CELERY_CONFIG = CeleryConfig # pylint: disable=invalid-name
|
|
|
|
# Set celery config to None to disable all the above configuration
|
|
# CELERY_CONFIG = None
|
|
|
|
# Additional static HTTP headers to be served by your Superset server. Note
|
|
# Flask-Talisman applies the relevant security HTTP headers.
|
|
#
|
|
# DEFAULT_HTTP_HEADERS: sets default values for HTTP headers. These may be overridden
|
|
# within the app
|
|
# OVERRIDE_HTTP_HEADERS: sets override values for HTTP headers. These values will
|
|
# override anything set within the app
|
|
DEFAULT_HTTP_HEADERS: dict[str, Any] = {}
|
|
OVERRIDE_HTTP_HEADERS: dict[str, Any] = {}
|
|
HTTP_HEADERS: dict[str, Any] = {}
|
|
|
|
# The db id here results in selecting this one as a default in SQL Lab
|
|
DEFAULT_DB_ID = None
|
|
|
|
# Timeout duration for SQL Lab synchronous queries
|
|
SQLLAB_TIMEOUT = int(timedelta(seconds=30).total_seconds())
|
|
|
|
# Timeout duration for SQL Lab query validation
|
|
SQLLAB_VALIDATION_TIMEOUT = int(timedelta(seconds=10).total_seconds())
|
|
|
|
# SQLLAB_DEFAULT_DBID
|
|
SQLLAB_DEFAULT_DBID = None
|
|
|
|
# The MAX duration a query can run for before being killed by celery.
|
|
SQLLAB_ASYNC_TIME_LIMIT_SEC = int(timedelta(hours=6).total_seconds())
|
|
|
|
# Some databases support running EXPLAIN queries that allow users to estimate
|
|
# query costs before they run. These EXPLAIN queries should have a small
|
|
# timeout.
|
|
SQLLAB_QUERY_COST_ESTIMATE_TIMEOUT = int(timedelta(seconds=10).total_seconds())
|
|
|
|
# The cost returned by the databases is a relative value; in order to map the cost to
|
|
# a tangible value you need to define a custom formatter that takes into consideration
|
|
# your specific infrastructure. For example, you could analyze queries a posteriori by
|
|
# running EXPLAIN on them, and compute a histogram of relative costs to present the
|
|
# cost as a percentile, this step is optional as every db engine spec has its own
|
|
# query cost formatter, but it you wanna customize it you can define it inside the config:
|
|
|
|
# def postgres_query_cost_formatter(
|
|
# result: List[Dict[str, Any]]
|
|
# ) -> List[Dict[str, str]]:
|
|
# # 25, 50, 75% percentiles
|
|
# percentile_costs = [100.0, 1000.0, 10000.0]
|
|
#
|
|
# out = []
|
|
# for row in result:
|
|
# relative_cost = row["Total cost"]
|
|
# percentile = bisect.bisect_left(percentile_costs, relative_cost) + 1
|
|
# out.append({
|
|
# "Relative cost": relative_cost,
|
|
# "Percentile": str(percentile * 25) + "%",
|
|
# })
|
|
#
|
|
# return out
|
|
#
|
|
# QUERY_COST_FORMATTERS_BY_ENGINE: {"postgresql": postgres_query_cost_formatter}
|
|
QUERY_COST_FORMATTERS_BY_ENGINE: dict[
|
|
str, Callable[[list[dict[str, Any]]], list[dict[str, Any]]]
|
|
] = {}
|
|
|
|
# Flag that controls if limit should be enforced on the CTA (create table as queries).
|
|
SQLLAB_CTAS_NO_LIMIT = False
|
|
|
|
# This allows you to define custom logic around the "CREATE TABLE AS" or CTAS feature
|
|
# in SQL Lab that defines where the target schema should be for a given user.
|
|
# Database `CTAS Schema` has a precedence over this setting.
|
|
# Example below returns a username and CTA queries will write tables into the schema
|
|
# name `username`
|
|
# SQLLAB_CTAS_SCHEMA_NAME_FUNC = lambda database, user, schema, sql: user.username
|
|
# This is move involved example where depending on the database you can leverage data
|
|
# available to assign schema for the CTA query:
|
|
# def compute_schema_name(database: Database, user: User, schema: str, sql: str) -> str:
|
|
# if database.name == 'mysql_payments_slave':
|
|
# return 'tmp_superset_schema'
|
|
# if database.name == 'presto_gold':
|
|
# return user.username
|
|
# if database.name == 'analytics':
|
|
# if 'analytics' in [r.name for r in user.roles]:
|
|
# return 'analytics_cta'
|
|
# else:
|
|
# return f'tmp_{schema}'
|
|
# Function accepts database object, user object, schema name and sql that will be run.
|
|
SQLLAB_CTAS_SCHEMA_NAME_FUNC: None | (
|
|
Callable[[Database, models.User, str, str], str]
|
|
) = None
|
|
|
|
# If enabled, it can be used to store the results of long-running queries
|
|
# in SQL Lab by using the "Run Async" button/feature
|
|
RESULTS_BACKEND: BaseCache | None = None
|
|
|
|
# Use PyArrow and MessagePack for async query results serialization,
|
|
# rather than JSON. This feature requires additional testing from the
|
|
# community before it is fully adopted, so this config option is provided
|
|
# in order to disable should breaking issues be discovered.
|
|
RESULTS_BACKEND_USE_MSGPACK = True
|
|
|
|
# The S3 bucket where you want to store your external hive tables created
|
|
# from CSV files. For example, 'companyname-superset'
|
|
CSV_TO_HIVE_UPLOAD_S3_BUCKET = None
|
|
|
|
# The directory within the bucket specified above that will
|
|
# contain all the external tables
|
|
CSV_TO_HIVE_UPLOAD_DIRECTORY = "EXTERNAL_HIVE_TABLES/"
|
|
|
|
|
|
# Function that creates upload directory dynamically based on the
|
|
# database used, user and schema provided.
|
|
def CSV_TO_HIVE_UPLOAD_DIRECTORY_FUNC( # pylint: disable=invalid-name
|
|
database: Database,
|
|
user: models.User, # pylint: disable=unused-argument
|
|
schema: str | None,
|
|
) -> str:
|
|
# Note the final empty path enforces a trailing slash.
|
|
return os.path.join(
|
|
CSV_TO_HIVE_UPLOAD_DIRECTORY, str(database.id), schema or "", ""
|
|
)
|
|
|
|
|
|
# The namespace within hive where the tables created from
|
|
# uploading CSVs will be stored.
|
|
UPLOADED_CSV_HIVE_NAMESPACE: str | None = None
|
|
|
|
# Function that computes the allowed schemas for the CSV uploads.
|
|
# Allowed schemas will be a union of schemas_allowed_for_file_upload
|
|
# db configuration and a result of this function.
|
|
|
|
# mypy doesn't catch that if case ensures list content being always str
|
|
ALLOWED_USER_CSV_SCHEMA_FUNC: Callable[[Database, models.User], list[str]] = (
|
|
lambda database, user: [UPLOADED_CSV_HIVE_NAMESPACE]
|
|
if UPLOADED_CSV_HIVE_NAMESPACE
|
|
else []
|
|
)
|
|
|
|
# Values that should be treated as nulls for the csv uploads.
|
|
CSV_DEFAULT_NA_NAMES = list(STR_NA_VALUES)
|
|
|
|
# A dictionary of items that gets merged into the Jinja context for
|
|
# SQL Lab. The existing context gets updated with this dictionary,
|
|
# meaning values for existing keys get overwritten by the content of this
|
|
# dictionary. Exposing functionality through JINJA_CONTEXT_ADDONS has security
|
|
# implications as it opens a window for a user to execute untrusted code.
|
|
# It's important to make sure that the objects exposed (as well as objects attached
|
|
# to those objects) are harmless. We recommend only exposing simple/pure functions that
|
|
# return native types.
|
|
JINJA_CONTEXT_ADDONS: dict[str, Callable[..., Any]] = {}
|
|
|
|
# A dictionary of macro template processors (by engine) that gets merged into global
|
|
# template processors. The existing template processors get updated with this
|
|
# dictionary, which means the existing keys get overwritten by the content of this
|
|
# dictionary. The customized addons don't necessarily need to use Jinja templating
|
|
# language. This allows you to define custom logic to process templates on a per-engine
|
|
# basis. Example value = `{"presto": CustomPrestoTemplateProcessor}`
|
|
CUSTOM_TEMPLATE_PROCESSORS: dict[str, type[BaseTemplateProcessor]] = {}
|
|
|
|
# Roles that are controlled by the API / Superset and should not be changed
|
|
# by humans.
|
|
ROBOT_PERMISSION_ROLES = ["Public", "Gamma", "Alpha", "Admin", "sql_lab"]
|
|
|
|
CONFIG_PATH_ENV_VAR = "SUPERSET_CONFIG_PATH"
|
|
|
|
# If a callable is specified, it will be called at app startup while passing
|
|
# a reference to the Flask app. This can be used to alter the Flask app
|
|
# in whatever way.
|
|
# example: FLASK_APP_MUTATOR = lambda x: x.before_request = f
|
|
FLASK_APP_MUTATOR = None
|
|
|
|
# smtp server configuration
|
|
EMAIL_NOTIFICATIONS = False # all the emails are sent using dryrun
|
|
SMTP_HOST = "localhost"
|
|
SMTP_STARTTLS = True
|
|
SMTP_SSL = False
|
|
SMTP_USER = "superset"
|
|
SMTP_PORT = 25
|
|
SMTP_PASSWORD = "superset"
|
|
SMTP_MAIL_FROM = "superset@superset.com"
|
|
# If True creates a default SSL context with ssl.Purpose.CLIENT_AUTH using the
|
|
# default system root CA certificates.
|
|
SMTP_SSL_SERVER_AUTH = False
|
|
ENABLE_CHUNK_ENCODING = False
|
|
|
|
# Whether to bump the logging level to ERROR on the flask_appbuilder package
|
|
# Set to False if/when debugging FAB related issues like
|
|
# permission management
|
|
SILENCE_FAB = True
|
|
|
|
FAB_ADD_SECURITY_VIEWS = True
|
|
FAB_ADD_SECURITY_PERMISSION_VIEW = False
|
|
FAB_ADD_SECURITY_VIEW_MENU_VIEW = False
|
|
FAB_ADD_SECURITY_PERMISSION_VIEWS_VIEW = False
|
|
|
|
# The link to a page containing common errors and their resolutions
|
|
# It will be appended at the bottom of sql_lab errors.
|
|
TROUBLESHOOTING_LINK = ""
|
|
|
|
# CSRF token timeout, set to None for a token that never expires
|
|
WTF_CSRF_TIME_LIMIT = int(timedelta(weeks=1).total_seconds())
|
|
|
|
# This link should lead to a page with instructions on how to gain access to a
|
|
# Datasource. It will be placed at the bottom of permissions errors.
|
|
PERMISSION_INSTRUCTIONS_LINK = ""
|
|
|
|
# Integrate external Blueprints to the app by passing them to your
|
|
# configuration. These blueprints will get integrated in the app
|
|
BLUEPRINTS: list[Blueprint] = []
|
|
|
|
# Provide a callable that receives a tracking_url and returns another
|
|
# URL. This is used to translate internal Hadoop job tracker URL
|
|
# into a proxied one
|
|
|
|
|
|
# Transform SQL query tracking url for Hive and Presto engines. You may also
|
|
# access information about the query itself by adding a second parameter
|
|
# to your transformer function, e.g.:
|
|
# TRACKING_URL_TRANSFORMER = (
|
|
# lambda url, query: url if is_fresh(query) else None
|
|
# )
|
|
# pylint: disable-next=unnecessary-lambda-assignment
|
|
TRACKING_URL_TRANSFORMER = lambda url: url
|
|
|
|
|
|
# customize the polling time of each engine
|
|
DB_POLL_INTERVAL_SECONDS: dict[str, int] = {}
|
|
|
|
# Interval between consecutive polls when using Presto Engine
|
|
# See here: https://github.com/dropbox/PyHive/blob/8eb0aeab8ca300f3024655419b93dad926c1a351/pyhive/presto.py#L93 # pylint: disable=line-too-long,useless-suppression
|
|
PRESTO_POLL_INTERVAL = int(timedelta(seconds=1).total_seconds())
|
|
|
|
# Allow list of custom authentications for each DB engine.
|
|
# Example:
|
|
# from your.module import AuthClass
|
|
# from another.extra import auth_method
|
|
#
|
|
# ALLOWED_EXTRA_AUTHENTICATIONS: Dict[str, Dict[str, Callable[..., Any]]] = {
|
|
# "trino": {
|
|
# "custom_auth": AuthClass,
|
|
# "another_auth_method": auth_method,
|
|
# },
|
|
# }
|
|
ALLOWED_EXTRA_AUTHENTICATIONS: dict[str, dict[str, Callable[..., Any]]] = {}
|
|
|
|
# The id of a template dashboard that should be copied to every new user
|
|
DASHBOARD_TEMPLATE_ID = None
|
|
|
|
# A callable that allows altering the database connection URL and params
|
|
# on the fly, at runtime. This allows for things like impersonation or
|
|
# arbitrary logic. For instance you can wire different users to
|
|
# use different connection parameters, or pass their email address as the
|
|
# username. The function receives the connection uri object, connection
|
|
# params, the username, and returns the mutated uri and params objects.
|
|
# Example:
|
|
# def DB_CONNECTION_MUTATOR(uri, params, username, security_manager, source):
|
|
# user = security_manager.find_user(username=username)
|
|
# if user and user.email:
|
|
# uri.username = user.email
|
|
# return uri, params
|
|
#
|
|
# Note that the returned uri and params are passed directly to sqlalchemy's
|
|
# as such `create_engine(url, **params)`
|
|
DB_CONNECTION_MUTATOR = None
|
|
|
|
|
|
# A function that intercepts the SQL to be executed and can alter it.
|
|
# The use case is can be around adding some sort of comment header
|
|
# with information such as the username and worker node information
|
|
#
|
|
# def SQL_QUERY_MUTATOR(
|
|
# sql,
|
|
# security_manager=security_manager,
|
|
# database=database,
|
|
# ):
|
|
# dttm = datetime.now().isoformat()
|
|
# return f"-- [SQL LAB] {user_name} {dttm}\n{sql}"
|
|
# For backward compatibility, you can unpack any of the above arguments in your
|
|
# function definition, but keep the **kwargs as the last argument to allow new args
|
|
# to be added later without any errors.
|
|
def SQL_QUERY_MUTATOR( # pylint: disable=invalid-name,unused-argument
|
|
sql: str, **kwargs: Any
|
|
) -> str:
|
|
return sql
|
|
|
|
|
|
# A variable that chooses whether to apply the SQL_QUERY_MUTATOR before or after splitting the input query
|
|
# It allows for using the SQL_QUERY_MUTATOR function for more than comments
|
|
# Usage: If you want to apply a change to every statement to a given query, set MUTATE_AFTER_SPLIT = True
|
|
# An example use case is if data has role based access controls, and you want to apply
|
|
# a SET ROLE statement alongside every user query. Changing this variable maintains
|
|
# functionality for both the SQL_Lab and Charts.
|
|
MUTATE_AFTER_SPLIT = False
|
|
|
|
|
|
# This allows for a user to add header data to any outgoing emails. For example,
|
|
# if you need to include metadata in the header or you want to change the specifications
|
|
# of the email title, header, or sender.
|
|
def EMAIL_HEADER_MUTATOR( # pylint: disable=invalid-name,unused-argument
|
|
msg: MIMEMultipart, **kwargs: Any
|
|
) -> MIMEMultipart:
|
|
return msg
|
|
|
|
|
|
# Define a list of usernames to be excluded from all dropdown lists of users
|
|
# Owners, filters for created_by, etc.
|
|
# The users can also be excluded by overriding the get_exclude_users_from_lists method
|
|
# in security manager
|
|
EXCLUDE_USERS_FROM_LISTS: list[str] | None = None
|
|
|
|
# For database connections, this dictionary will remove engines from the available
|
|
# list/dropdown if you do not want these dbs to show as available.
|
|
# The available list is generated by driver installed, and some engines have multiple
|
|
# drivers.
|
|
# e.g., DBS_AVAILABLE_DENYLIST: Dict[str, Set[str]] = {"databricks": {"pyhive", "pyodbc"}}
|
|
DBS_AVAILABLE_DENYLIST: dict[str, set[str]] = {}
|
|
|
|
# This auth provider is used by background (offline) tasks that need to access
|
|
# protected resources. Can be overridden by end users in order to support
|
|
# custom auth mechanisms
|
|
MACHINE_AUTH_PROVIDER_CLASS = "superset.utils.machine_auth.MachineAuthProvider"
|
|
|
|
# ---------------------------------------------------
|
|
# Alerts & Reports
|
|
# ---------------------------------------------------
|
|
# Used for Alerts/Reports (Feature flask ALERT_REPORTS) to set the size for the
|
|
# sliding cron window size, should be synced with the celery beat config minus 1 second
|
|
ALERT_REPORTS_CRON_WINDOW_SIZE = 59
|
|
ALERT_REPORTS_WORKING_TIME_OUT_KILL = True
|
|
# Which user to attempt to execute Alerts/Reports as. By default,
|
|
# execute as the primary owner of the alert/report (giving priority to the last
|
|
# modifier and then the creator if either is contained within the list of owners,
|
|
# otherwise the first owner will be used).
|
|
#
|
|
# To first try to execute as the creator in the owners list (if present), then fall
|
|
# back to the creator, then the last modifier in the owners list (if present), then the
|
|
# last modifier, then an owner and finally `THUMBNAIL_SELENIUM_USER`, set as follows:
|
|
# ALERT_REPORTS_EXECUTE_AS = [
|
|
# ExecutorType.CREATOR_OWNER,
|
|
# ExecutorType.CREATOR,
|
|
# ExecutorType.MODIFIER_OWNER,
|
|
# ExecutorType.MODIFIER,
|
|
# ExecutorType.OWNER,
|
|
# ExecutorType.SELENIUM,
|
|
# ]
|
|
ALERT_REPORTS_EXECUTE_AS: list[ExecutorType] = [ExecutorType.OWNER]
|
|
# if ALERT_REPORTS_WORKING_TIME_OUT_KILL is True, set a celery hard timeout
|
|
# Equal to working timeout + ALERT_REPORTS_WORKING_TIME_OUT_LAG
|
|
ALERT_REPORTS_WORKING_TIME_OUT_LAG = int(timedelta(seconds=10).total_seconds())
|
|
# if ALERT_REPORTS_WORKING_TIME_OUT_KILL is True, set a celery hard timeout
|
|
# Equal to working timeout + ALERT_REPORTS_WORKING_SOFT_TIME_OUT_LAG
|
|
ALERT_REPORTS_WORKING_SOFT_TIME_OUT_LAG = int(timedelta(seconds=1).total_seconds())
|
|
# Default values that user using when creating alert
|
|
ALERT_REPORTS_DEFAULT_WORKING_TIMEOUT = 3600
|
|
ALERT_REPORTS_DEFAULT_RETENTION = 90
|
|
ALERT_REPORTS_DEFAULT_CRON_VALUE = "0 * * * *" # every hour
|
|
# If set to true no notification is sent, the worker will just log a message.
|
|
# Useful for debugging
|
|
ALERT_REPORTS_NOTIFICATION_DRY_RUN = False
|
|
# Max tries to run queries to prevent false errors caused by transient errors
|
|
# being returned to users. Set to a value >1 to enable retries.
|
|
ALERT_REPORTS_QUERY_EXECUTION_MAX_TRIES = 1
|
|
# Custom width for screenshots
|
|
ALERT_REPORTS_MIN_CUSTOM_SCREENSHOT_WIDTH = 600
|
|
ALERT_REPORTS_MAX_CUSTOM_SCREENSHOT_WIDTH = 2400
|
|
|
|
# A custom prefix to use on all Alerts & Reports emails
|
|
EMAIL_REPORTS_SUBJECT_PREFIX = "[Report] "
|
|
|
|
# The text for call-to-action link in Alerts & Reports emails
|
|
EMAIL_REPORTS_CTA = "Explore in Superset"
|
|
|
|
# Slack API token for the superset reports, either string or callable
|
|
SLACK_API_TOKEN: Callable[[], str] | str | None = None
|
|
SLACK_PROXY = None
|
|
|
|
# The webdriver to use for generating reports. Use one of the following
|
|
# firefox
|
|
# Requires: geckodriver and firefox installations
|
|
# Limitations: can be buggy at times
|
|
# chrome:
|
|
# Requires: headless chrome
|
|
# Limitations: unable to generate screenshots of elements
|
|
WEBDRIVER_TYPE = "firefox"
|
|
|
|
# Window size - this will impact the rendering of the data
|
|
WEBDRIVER_WINDOW = {
|
|
"dashboard": (1600, 2000),
|
|
"slice": (3000, 1200),
|
|
"pixel_density": 1,
|
|
}
|
|
|
|
# An optional override to the default auth hook used to provide auth to the offline
|
|
# webdriver (when using Selenium) or browser context (when using Playwright - see
|
|
# PLAYWRIGHT_REPORTS_AND_THUMBNAILS feature flag)
|
|
WEBDRIVER_AUTH_FUNC = None
|
|
BROWSER_CONTEXT_AUTH_FUNC = None
|
|
|
|
# Any config options to be passed as-is to the webdriver
|
|
WEBDRIVER_CONFIGURATION: dict[Any, Any] = {"service_log_path": "/dev/null"}
|
|
|
|
# Additional args to be passed as arguments to the config object
|
|
# Note: If using Chrome, you'll want to add the "--marionette" arg.
|
|
WEBDRIVER_OPTION_ARGS = ["--headless"]
|
|
|
|
# The base URL to query for accessing the user interface
|
|
WEBDRIVER_BASEURL = "http://0.0.0.0:8080/"
|
|
# The base URL for the email report hyperlinks.
|
|
WEBDRIVER_BASEURL_USER_FRIENDLY = WEBDRIVER_BASEURL
|
|
# Time selenium will wait for the page to load and render for the email report.
|
|
EMAIL_PAGE_RENDER_WAIT = int(timedelta(seconds=30).total_seconds())
|
|
|
|
# Send user to a link where they can report bugs
|
|
BUG_REPORT_URL = None
|
|
BUG_REPORT_TEXT = "Report a bug"
|
|
BUG_REPORT_ICON = None # Recommended size: 16x16
|
|
|
|
# Send user to a link where they can read more about Superset
|
|
DOCUMENTATION_URL = None
|
|
DOCUMENTATION_TEXT = "Documentation"
|
|
DOCUMENTATION_ICON = None # Recommended size: 16x16
|
|
|
|
# What is the Last N days relative in the time selector to:
|
|
# 'today' means it is midnight (00:00:00) in the local timezone
|
|
# 'now' means it is relative to the query issue time
|
|
# If both start and end time is set to now, this will make the time
|
|
# filter a moving window. By only setting the end time to now,
|
|
# start time will be set to midnight, while end will be relative to
|
|
# the query issue time.
|
|
DEFAULT_RELATIVE_START_TIME = "today"
|
|
DEFAULT_RELATIVE_END_TIME = "today"
|
|
|
|
# Configure which SQL validator to use for each engine
|
|
SQL_VALIDATORS_BY_ENGINE = {
|
|
"presto": "PrestoDBSQLValidator",
|
|
"postgresql": "PostgreSQLValidator",
|
|
}
|
|
|
|
# A list of preferred databases, in order. These databases will be
|
|
# displayed prominently in the "Add Database" dialog. You should
|
|
# use the "engine_name" attribute of the corresponding DB engine spec
|
|
# in `superset/db_engine_specs/`.
|
|
PREFERRED_DATABASES: list[str] = [
|
|
"PostgreSQL",
|
|
"Presto",
|
|
"MySQL",
|
|
"SQLite",
|
|
# etc.
|
|
]
|
|
# When adding a new database we try to connect to it. Depending on which parameters are
|
|
# incorrect this could take a couple minutes, until the SQLAlchemy driver pinging the
|
|
# database times out. Instead of relying on the driver timeout we can specify a shorter
|
|
# one here.
|
|
TEST_DATABASE_CONNECTION_TIMEOUT = timedelta(seconds=30)
|
|
|
|
# Enable/disable CSP warning
|
|
CONTENT_SECURITY_POLICY_WARNING = True
|
|
|
|
# Do you want Talisman enabled?
|
|
TALISMAN_ENABLED = utils.cast_to_boolean(os.environ.get("TALISMAN_ENABLED", True))
|
|
|
|
# If you want Talisman, how do you want it configured??
|
|
TALISMAN_CONFIG = {
|
|
"content_security_policy": {
|
|
"default-src": ["'self'"],
|
|
"img-src": ["'self'", "data:"],
|
|
"worker-src": ["'self'", "blob:"],
|
|
"connect-src": [
|
|
"'self'",
|
|
"https://api.mapbox.com",
|
|
"https://events.mapbox.com",
|
|
],
|
|
"object-src": "'none'",
|
|
"style-src": [
|
|
"'self'",
|
|
"'unsafe-inline'",
|
|
"https://cdn.jsdelivr.net/npm/swagger-ui-dist@5/swagger-ui.css",
|
|
],
|
|
"script-src": ["'self'", "'strict-dynamic'"],
|
|
},
|
|
"content_security_policy_nonce_in": ["script-src"],
|
|
"force_https": False,
|
|
}
|
|
# React requires `eval` to work correctly in dev mode
|
|
TALISMAN_DEV_CONFIG = {
|
|
"content_security_policy": {
|
|
"default-src": ["'self'"],
|
|
"img-src": ["'self'", "data:"],
|
|
"worker-src": ["'self'", "blob:"],
|
|
"connect-src": [
|
|
"'self'",
|
|
"https://api.mapbox.com",
|
|
"https://events.mapbox.com",
|
|
],
|
|
"object-src": "'none'",
|
|
"style-src": [
|
|
"'self'",
|
|
"'unsafe-inline'",
|
|
"https://cdn.jsdelivr.net/npm/swagger-ui-dist@5/swagger-ui.css",
|
|
],
|
|
"script-src": ["'self'", "'unsafe-inline'", "'unsafe-eval'"],
|
|
},
|
|
"content_security_policy_nonce_in": ["script-src"],
|
|
"force_https": False,
|
|
}
|
|
|
|
#
|
|
# Flask session cookie options
|
|
#
|
|
# See https://flask.palletsprojects.com/en/1.1.x/security/#set-cookie-options
|
|
# for details
|
|
#
|
|
SESSION_COOKIE_HTTPONLY = True # Prevent cookie from being read by frontend JS?
|
|
SESSION_COOKIE_SECURE = False # Prevent cookie from being transmitted over non-tls?
|
|
SESSION_COOKIE_SAMESITE: Literal["None", "Lax", "Strict"] | None = "Lax"
|
|
|
|
# Cache static resources.
|
|
SEND_FILE_MAX_AGE_DEFAULT = int(timedelta(days=365).total_seconds())
|
|
|
|
# URI to database storing the example data, points to
|
|
# SQLALCHEMY_DATABASE_URI by default if set to `None`
|
|
SQLALCHEMY_EXAMPLES_URI = "sqlite:///" + os.path.join(DATA_DIR, "examples.db")
|
|
|
|
# Optional prefix to be added to all static asset paths when rendering the UI.
|
|
# This is useful for hosting assets in an external CDN, for example
|
|
STATIC_ASSETS_PREFIX = ""
|
|
|
|
# Some sqlalchemy connection strings can open Superset to security risks.
|
|
# Typically these should not be allowed.
|
|
PREVENT_UNSAFE_DB_CONNECTIONS = True
|
|
|
|
# If true all default urls on datasets will be handled as relative URLs by the frontend
|
|
PREVENT_UNSAFE_DEFAULT_URLS_ON_DATASET = True
|
|
|
|
# Define a list of allowed URLs for dataset data imports (v1).
|
|
# Simple example to only allow URLs that belong to certain domains:
|
|
# ALLOWED_IMPORT_URL_DOMAINS = [
|
|
# r"^https://.+\.domain1\.com\/?.*", r"^https://.+\.domain2\.com\/?.*"
|
|
# ]
|
|
DATASET_IMPORT_ALLOWED_DATA_URLS = [r".*"]
|
|
|
|
# Path used to store SSL certificates that are generated when using custom certs.
|
|
# Defaults to temporary directory.
|
|
# Example: SSL_CERT_PATH = "/certs"
|
|
SSL_CERT_PATH: str | None = None
|
|
|
|
# SQLA table mutator, every time we fetch the metadata for a certain table
|
|
# (superset.connectors.sqla.models.SqlaTable), we call this hook
|
|
# to allow mutating the object with this callback.
|
|
# This can be used to set any properties of the object based on naming
|
|
# conventions and such. You can find examples in the tests.
|
|
|
|
# pylint: disable-next=unnecessary-lambda-assignment
|
|
SQLA_TABLE_MUTATOR = lambda table: table
|
|
|
|
|
|
# Global async query config options.
|
|
# Requires GLOBAL_ASYNC_QUERIES feature flag to be enabled.
|
|
GLOBAL_ASYNC_QUERY_MANAGER_CLASS = (
|
|
"superset.async_events.async_query_manager.AsyncQueryManager"
|
|
)
|
|
GLOBAL_ASYNC_QUERIES_REDIS_CONFIG = {
|
|
"port": 6379,
|
|
"host": "127.0.0.1",
|
|
"password": "",
|
|
"db": 0,
|
|
"ssl": False,
|
|
}
|
|
GLOBAL_ASYNC_QUERIES_REDIS_STREAM_PREFIX = "async-events-"
|
|
GLOBAL_ASYNC_QUERIES_REDIS_STREAM_LIMIT = 1000
|
|
GLOBAL_ASYNC_QUERIES_REDIS_STREAM_LIMIT_FIREHOSE = 1000000
|
|
GLOBAL_ASYNC_QUERIES_REGISTER_REQUEST_HANDLERS = True
|
|
GLOBAL_ASYNC_QUERIES_JWT_COOKIE_NAME = "async-token"
|
|
GLOBAL_ASYNC_QUERIES_JWT_COOKIE_SECURE = False
|
|
GLOBAL_ASYNC_QUERIES_JWT_COOKIE_SAMESITE: None | (
|
|
Literal["None", "Lax", "Strict"]
|
|
) = None
|
|
GLOBAL_ASYNC_QUERIES_JWT_COOKIE_DOMAIN = None
|
|
GLOBAL_ASYNC_QUERIES_JWT_SECRET = "test-secret-change-me"
|
|
GLOBAL_ASYNC_QUERIES_TRANSPORT = "polling"
|
|
GLOBAL_ASYNC_QUERIES_POLLING_DELAY = int(
|
|
timedelta(milliseconds=500).total_seconds() * 1000
|
|
)
|
|
GLOBAL_ASYNC_QUERIES_WEBSOCKET_URL = "ws://127.0.0.1:8080/"
|
|
|
|
# Embedded config options
|
|
GUEST_ROLE_NAME = "Public"
|
|
GUEST_TOKEN_JWT_SECRET = "test-guest-secret-change-me"
|
|
GUEST_TOKEN_JWT_ALGO = "HS256"
|
|
GUEST_TOKEN_HEADER_NAME = "X-GuestToken"
|
|
GUEST_TOKEN_JWT_EXP_SECONDS = 300 # 5 minutes
|
|
# Guest token audience for the embedded superset, either string or callable
|
|
GUEST_TOKEN_JWT_AUDIENCE: Callable[[], str] | str | None = None
|
|
|
|
# A SQL dataset health check. Note if enabled it is strongly advised that the callable
|
|
# be memoized to aid with performance, i.e.,
|
|
#
|
|
# @cache_manager.cache.memoize(timeout=0)
|
|
# def DATASET_HEALTH_CHECK(datasource: SqlaTable) -> Optional[str]:
|
|
# if (
|
|
# datasource.sql and
|
|
# len(sql_parse.ParsedQuery(datasource.sql, strip_comments=True).tables) == 1
|
|
# ):
|
|
# return (
|
|
# "This virtual dataset queries only one table and therefore could be "
|
|
# "replaced by querying the table directly."
|
|
# )
|
|
#
|
|
# return None
|
|
#
|
|
# Within the FLASK_APP_MUTATOR callable, i.e., once the application and thus cache have
|
|
# been initialized it is also necessary to add the following logic to blow the cache for
|
|
# all datasources if the callback function changed.
|
|
#
|
|
# def FLASK_APP_MUTATOR(app: Flask) -> None:
|
|
# name = "DATASET_HEALTH_CHECK"
|
|
# func = app.config[name]
|
|
# code = func.uncached.__code__.co_code
|
|
#
|
|
# if cache_manager.cache.get(name) != code:
|
|
# cache_manager.cache.delete_memoized(func)
|
|
# cache_manager.cache.set(name, code, timeout=0)
|
|
#
|
|
DATASET_HEALTH_CHECK: Callable[[SqlaTable], str] | None = None
|
|
|
|
# the advanced data type key should correspond to that set in the column metadata
|
|
ADVANCED_DATA_TYPES: dict[str, AdvancedDataType] = {
|
|
"internet_address": internet_address,
|
|
"port": internet_port,
|
|
}
|
|
|
|
# By default, the Welcome page features all charts and dashboards the user has access
|
|
# to. This can be changed to show only examples, or a custom view
|
|
# by providing the title and a FAB filter:
|
|
# WELCOME_PAGE_LAST_TAB = (
|
|
# "Xyz",
|
|
# [{"col": 'created_by', "opr": 'rel_o_m', "value": 10}],
|
|
# )
|
|
WELCOME_PAGE_LAST_TAB: (
|
|
Literal["examples", "all"] | tuple[str, list[dict[str, Any]]]
|
|
) = "all"
|
|
|
|
# Configuration for environment tag shown on the navbar. Setting 'text' to '' will hide the tag.
|
|
# 'color' can either be a hex color code, or a dot-indexed theme color (e.g. error.base)
|
|
ENVIRONMENT_TAG_CONFIG = {
|
|
"variable": "SUPERSET_ENV",
|
|
"values": {
|
|
"debug": {
|
|
"color": "error.base",
|
|
"text": "flask-debug",
|
|
},
|
|
"development": {
|
|
"color": "error.base",
|
|
"text": "Development",
|
|
},
|
|
"production": {
|
|
"color": "",
|
|
"text": "",
|
|
},
|
|
},
|
|
}
|
|
|
|
|
|
# Extra related query filters make it possible to limit which objects are shown
|
|
# in the UI. For examples, to only show "admin" or users starting with the letter "b" in
|
|
# the "Owners" dropdowns, you could add the following in your config:
|
|
# def user_filter(query: Query, *args, *kwargs):
|
|
# from superset import security_manager
|
|
#
|
|
# user_model = security_manager.user_model
|
|
# filters = [
|
|
# user_model.username == "admin",
|
|
# user_model.username.ilike("b%"),
|
|
# ]
|
|
# return query.filter(or_(*filters))
|
|
#
|
|
# EXTRA_RELATED_QUERY_FILTERS = {"user": user_filter}
|
|
#
|
|
# Similarly, to restrict the roles in the "Roles" dropdown you can provide a custom
|
|
# filter callback for the "role" key.
|
|
class ExtraRelatedQueryFilters(TypedDict, total=False):
|
|
role: Callable[[Query], Query]
|
|
user: Callable[[Query], Query]
|
|
|
|
|
|
EXTRA_RELATED_QUERY_FILTERS: ExtraRelatedQueryFilters = {}
|
|
|
|
|
|
# Extra dynamic query filters make it possible to limit which objects are shown
|
|
# in the UI before any other filtering is applied. Useful for example when
|
|
# considering to filter using Feature Flags along with regular role filters
|
|
# that get applied by default in our base_filters.
|
|
# For example, to only show a database starting with the letter "b"
|
|
# in the "Database Connections" list, you could add the following in your config:
|
|
# def initial_database_filter(query: Query, *args, *kwargs):
|
|
# from superset.models.core import Database
|
|
#
|
|
# filter = Database.database_name.startswith('b')
|
|
# return query.filter(filter)
|
|
#
|
|
# EXTRA_DYNAMIC_QUERY_FILTERS = {"database": initial_database_filter}
|
|
class ExtraDynamicQueryFilters(TypedDict, total=False):
|
|
databases: Callable[[Query], Query]
|
|
|
|
|
|
EXTRA_DYNAMIC_QUERY_FILTERS: ExtraDynamicQueryFilters = {}
|
|
|
|
|
|
# -------------------------------------------------------------------
|
|
# * WARNING: STOP EDITING HERE *
|
|
# -------------------------------------------------------------------
|
|
# Don't add config values below this line since local configs won't be
|
|
# able to override them.
|
|
if CONFIG_PATH_ENV_VAR in os.environ:
|
|
# Explicitly import config module that is not necessarily in pythonpath; useful
|
|
# for case where app is being executed via pex.
|
|
cfg_path = os.environ[CONFIG_PATH_ENV_VAR]
|
|
try:
|
|
module = sys.modules[__name__]
|
|
override_conf = imp.load_source("superset_config", cfg_path)
|
|
for key in dir(override_conf):
|
|
if key.isupper():
|
|
setattr(module, key, getattr(override_conf, key))
|
|
|
|
print(f"Loaded your LOCAL configuration at [{cfg_path}]")
|
|
except Exception:
|
|
logger.exception(
|
|
"Failed to import config for %s=%s", CONFIG_PATH_ENV_VAR, cfg_path
|
|
)
|
|
raise
|
|
elif importlib.util.find_spec("superset_config") and not is_test():
|
|
try:
|
|
# pylint: disable=import-error,wildcard-import,unused-wildcard-import
|
|
import superset_config
|
|
from superset_config import * # type: ignore
|
|
|
|
print(f"Loaded your LOCAL configuration at [{superset_config.__file__}]")
|
|
except Exception:
|
|
logger.exception("Found but failed to import local superset_config")
|
|
raise
|