iop
/
superset
4
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
superset/superset/utils/core.py

1909 lines
59 KiB
Python
Raw Blame History

# 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.
"""Utility functions used across Superset"""
# pylint: disable=too-many-lines
import _thread
import collections
import decimal
import errno
import json
import logging
import os
import platform
import re
import signal
import smtplib
import tempfile
import threading
import traceback
import uuid
import zlib
from contextlib import contextmanager
from datetime import date, datetime, time, timedelta
from distutils.util import strtobool
from email.mime.application import MIMEApplication
from email.mime.image import MIMEImage
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.utils import formatdate
from enum import Enum, IntEnum
from io import BytesIO
from timeit import default_timer
from types import TracebackType
from typing import (
Any,
Callable,
cast,
Dict,
Iterable,
Iterator,
List,
NamedTuple,
Optional,
Sequence,
Set,
Tuple,
Type,
TYPE_CHECKING,
TypeVar,
Union,
)
from urllib.parse import unquote_plus
from zipfile import ZipFile
import bleach
import markdown as md
import numpy as np
import pandas as pd
import sqlalchemy as sa
from cryptography import x509
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.backends.openssl.x509 import _Certificate
from flask import current_app, flash, g, Markup, render_template, request
from flask_appbuilder import SQLA
from flask_appbuilder.security.sqla.models import Role, User
from flask_babel import gettext as __
from flask_babel.speaklater import LazyString
from pandas.api.types import infer_dtype
from pandas.core.dtypes.common import is_numeric_dtype
from sqlalchemy import event, exc, inspect, select, Text
from sqlalchemy.dialects.mysql import MEDIUMTEXT
from sqlalchemy.engine import Connection, Engine
from sqlalchemy.engine.reflection import Inspector
from sqlalchemy.sql.type_api import Variant
from sqlalchemy.types import TEXT, TypeDecorator, TypeEngine
from typing_extensions import TypedDict, TypeGuard
from superset.constants import (
EXTRA_FORM_DATA_APPEND_KEYS,
EXTRA_FORM_DATA_OVERRIDE_EXTRA_KEYS,
EXTRA_FORM_DATA_OVERRIDE_REGULAR_MAPPINGS,
)
from superset.errors import ErrorLevel, SupersetErrorType
from superset.exceptions import (
CertificateException,
SupersetException,
SupersetTimeoutException,
)
from superset.sql_parse import sanitize_clause
from superset.superset_typing import (
AdhocColumn,
AdhocMetric,
AdhocMetricColumn,
Column,
FilterValues,
FlaskResponse,
FormData,
Metric,
)
from superset.utils.database import get_example_database
from superset.utils.dates import datetime_to_epoch, EPOCH
from superset.utils.hashing import md5_sha_from_dict, md5_sha_from_str
try:
from pydruid.utils.having import Having
except ImportError:
pass
if TYPE_CHECKING:
from superset.connectors.base.models import BaseColumn, BaseDatasource
logging.getLogger("MARKDOWN").setLevel(logging.INFO)
logger = logging.getLogger(__name__)
DTTM_ALIAS = "__timestamp"
NO_TIME_RANGE = "No filter"
TIME_COMPARISON = "__"
JS_MAX_INTEGER = 9007199254740991 # Largest int Java Script can handle 2^53-1
InputType = TypeVar("InputType")
class LenientEnum(Enum):
"""Enums with a `get` method that convert a enum value to `Enum` if it is a
valid value."""
@classmethod
def get(cls, value: Any) -> Any:
try:
return super().__new__(cls, value)
except ValueError:
return None
class AdhocMetricExpressionType(str, Enum):
SIMPLE = "SIMPLE"
SQL = "SQL"
class AnnotationType(str, Enum):
FORMULA = "FORMULA"
INTERVAL = "INTERVAL"
EVENT = "EVENT"
TIME_SERIES = "TIME_SERIES"
class GenericDataType(IntEnum):
"""
Generic database column type that fits both frontend and backend.
"""
NUMERIC = 0
STRING = 1
TEMPORAL = 2
BOOLEAN = 3
# ARRAY = 4 # Mapping all the complex data types to STRING for now
# JSON = 5 # and leaving these as a reminder.
# MAP = 6
# ROW = 7
class DatasourceType(str, Enum):
SLTABLE = "sl_table"
TABLE = "table"
DATASET = "dataset"
QUERY = "query"
SAVEDQUERY = "saved_query"
VIEW = "view"
class DatasourceDict(TypedDict):
type: str # todo(hugh): update this to be DatasourceType
id: int
class AdhocFilterClause(TypedDict, total=False):
clause: str
expressionType: str
filterOptionName: Optional[str]
comparator: Optional[FilterValues]
operator: str
subject: str
isExtra: Optional[bool]
sqlExpression: Optional[str]
class QueryObjectFilterClause(TypedDict, total=False):
col: str
op: str # pylint: disable=invalid-name
val: Optional[FilterValues]
grain: Optional[str]
isExtra: Optional[bool]
class ExtraFiltersTimeColumnType(str, Enum):
GRANULARITY = "__granularity"
TIME_COL = "__time_col"
TIME_GRAIN = "__time_grain"
TIME_ORIGIN = "__time_origin"
TIME_RANGE = "__time_range"
class ExtraFiltersReasonType(str, Enum):
NO_TEMPORAL_COLUMN = "no_temporal_column"
COL_NOT_IN_DATASOURCE = "not_in_datasource"
class FilterOperator(str, Enum):
"""
Operators used filter controls
"""
EQUALS = "=="
NOT_EQUALS = "!="
GREATER_THAN = ">"
LESS_THAN = "<"
GREATER_THAN_OR_EQUALS = ">="
LESS_THAN_OR_EQUALS = "<="
LIKE = "LIKE"
ILIKE = "ILIKE"
IS_NULL = "IS NULL"
IS_NOT_NULL = "IS NOT NULL"
IN = "IN"
NOT_IN = "NOT IN"
REGEX = "REGEX"
IS_TRUE = "IS TRUE"
IS_FALSE = "IS FALSE"
class FilterStringOperators(str, Enum):
EQUALS = ("EQUALS",)
NOT_EQUALS = ("NOT_EQUALS",)
LESS_THAN = ("LESS_THAN",)
GREATER_THAN = ("GREATER_THAN",)
LESS_THAN_OR_EQUAL = ("LESS_THAN_OR_EQUAL",)
GREATER_THAN_OR_EQUAL = ("GREATER_THAN_OR_EQUAL",)
IN = ("IN",)
NOT_IN = ("NOT_IN",)
ILIKE = ("ILIKE",)
LIKE = ("LIKE",)
REGEX = ("REGEX",)
IS_NOT_NULL = ("IS_NOT_NULL",)
IS_NULL = ("IS_NULL",)
LATEST_PARTITION = ("LATEST_PARTITION",)
IS_TRUE = ("IS_TRUE",)
IS_FALSE = ("IS_FALSE",)
class PostProcessingBoxplotWhiskerType(str, Enum):
"""
Calculate cell contribution to row/column total
"""
TUKEY = "tukey"
MINMAX = "min/max"
PERCENTILE = "percentile"
class PostProcessingContributionOrientation(str, Enum):
"""
Calculate cell contribution to row/column total
"""
ROW = "row"
COLUMN = "column"
class QueryMode(str, LenientEnum):
"""
Whether the query runs on aggregate or returns raw records
"""
RAW = "raw"
AGGREGATE = "aggregate"
class QuerySource(Enum):
"""
The source of a SQL query.
"""
CHART = 0
DASHBOARD = 1
SQL_LAB = 2
class QueryStatus(str, Enum):
"""Enum-type class for query statuses"""
STOPPED: str = "stopped"
FAILED: str = "failed"
PENDING: str = "pending"
RUNNING: str = "running"
SCHEDULED: str = "scheduled"
SUCCESS: str = "success"
FETCHING: str = "fetching"
TIMED_OUT: str = "timed_out"
class DashboardStatus(str, Enum):
"""Dashboard status used for frontend filters"""
PUBLISHED = "published"
DRAFT = "draft"
class ReservedUrlParameters(str, Enum):
"""
Reserved URL parameters that are used internally by Superset. These will not be
passed to chart queries, as they control the behavior of the UI.
"""
STANDALONE = "standalone"
EDIT_MODE = "edit"
@staticmethod
def is_standalone_mode() -> Optional[bool]:
standalone_param = request.args.get(ReservedUrlParameters.STANDALONE.value)
standalone: Optional[bool] = bool(
standalone_param and standalone_param != "false" and standalone_param != "0"
)
return standalone
class RowLevelSecurityFilterType(str, Enum):
REGULAR = "Regular"
BASE = "Base"
class TemporalType(str, Enum):
"""
Supported temporal types
"""
DATE = "DATE"
DATETIME = "DATETIME"
SMALLDATETIME = "SMALLDATETIME"
TEXT = "TEXT"
TIME = "TIME"
TIME_WITH_TIME_ZONE = "TIME WITH TIME ZONE"
TIMESTAMP = "TIMESTAMP"
TIMESTAMP_WITH_TIME_ZONE = "TIMESTAMP WITH TIME ZONE"
class ColumnTypeSource(Enum):
GET_TABLE = 1
CURSOR_DESCRIPION = 2
class ColumnSpec(NamedTuple):
sqla_type: Union[TypeEngine, str]
generic_type: GenericDataType
is_dttm: bool
python_date_format: Optional[str] = None
try:
# Having might not have been imported.
class DimSelector(Having):
def __init__(self, **args: Any) -> None:
# Just a hack to prevent any exceptions
Having.__init__(self, type="equalTo", aggregation=None, value=None)
self.having = {
"having": {
"type": "dimSelector",
"dimension": args["dimension"],
"value": args["value"],
}
}
except NameError:
pass
def flasher(msg: str, severity: str = "message") -> None:
"""Flask's flash if available, logging call if not"""
try:
flash(msg, severity)
except RuntimeError:
if severity == "danger":
logger.error(msg, exc_info=True)
else:
logger.info(msg)
def parse_js_uri_path_item(
item: Optional[str], unquote: bool = True, eval_undefined: bool = False
) -> Optional[str]:
"""Parse a uri path item made with js.
:param item: a uri path component
:param unquote: Perform unquoting of string using urllib.parse.unquote_plus()
:param eval_undefined: When set to True and item is either 'null' or 'undefined',
assume item is undefined and return None.
:return: Either None, the original item or unquoted item
"""
item = None if eval_undefined and item in ("null", "undefined") else item
return unquote_plus(item) if unquote and item else item
def cast_to_num(value: Optional[Union[float, int, str]]) -> Optional[Union[float, int]]:
"""Casts a value to an int/float
>>> cast_to_num('1 ')
1.0
>>> cast_to_num(' 2')
2.0
>>> cast_to_num('5')
5
>>> cast_to_num('5.2')
5.2
>>> cast_to_num(10)
10
>>> cast_to_num(10.1)
10.1
>>> cast_to_num(None) is None
True
>>> cast_to_num('this is not a string') is None
True
:param value: value to be converted to numeric representation
:returns: value cast to `int` if value is all digits, `float` if `value` is
decimal value and `None`` if it can't be converted
"""
if value is None:
return None
if isinstance(value, (int, float)):
return value
if value.isdigit():
return int(value)
try:
return float(value)
except ValueError:
return None
def cast_to_boolean(value: Any) -> Optional[bool]:
"""Casts a value to an int/float
>>> cast_to_boolean(1)
True
>>> cast_to_boolean(0)
False
>>> cast_to_boolean(0.5)
True
>>> cast_to_boolean('true')
True
>>> cast_to_boolean('false')
False
>>> cast_to_boolean('False')
False
>>> cast_to_boolean(None)
:param value: value to be converted to boolean representation
:returns: value cast to `bool`. when value is 'true' or value that are not 0
converted into True. Return `None` if value is `None`
"""
if value is None:
return None
if isinstance(value, (int, float)):
return value != 0
if isinstance(value, str):
return value.strip().lower() == "true"
return False
def list_minus(l: List[Any], minus: List[Any]) -> List[Any]:
"""Returns l without what is in minus
>>> list_minus([1, 2, 3], [2])
[1, 3]
"""
return [o for o in l if o not in minus]
class DashboardEncoder(json.JSONEncoder):
def __init__(self, *args: Any, **kwargs: Any) -> None:
super().__init__(*args, **kwargs)
self.sort_keys = True
def default(self, o: Any) -> Union[Dict[Any, Any], str]:
if isinstance(o, uuid.UUID):
return str(o)
try:
vals = {k: v for k, v in o.__dict__.items() if k != "_sa_instance_state"}
return {"__{}__".format(o.__class__.__name__): vals}
except Exception: # pylint: disable=broad-except
if isinstance(o, datetime):
return {"__datetime__": o.replace(microsecond=0).isoformat()}
return json.JSONEncoder(sort_keys=True).default(o)
class JSONEncodedDict(TypeDecorator): # pylint: disable=abstract-method
"""Represents an immutable structure as a json-encoded string."""
impl = TEXT
def process_bind_param(
self, value: Optional[Dict[Any, Any]], dialect: str
) -> Optional[str]:
return json.dumps(value) if value is not None else None
def process_result_value(
self, value: Optional[str], dialect: str
) -> Optional[Dict[Any, Any]]:
return json.loads(value) if value is not None else None
def format_timedelta(time_delta: timedelta) -> str:
"""
Ensures negative time deltas are easily interpreted by humans
>>> td = timedelta(0) - timedelta(days=1, hours=5,minutes=6)
>>> str(td)
'-2 days, 18:54:00'
>>> format_timedelta(td)
'-1 day, 5:06:00'
"""
if time_delta < timedelta(0):
return "-" + str(abs(time_delta))
# Change this to format positive time deltas the way you want
return str(time_delta)
def base_json_conv( # pylint: disable=inconsistent-return-statements
obj: Any,
) -> Any:
if isinstance(obj, memoryview):
obj = obj.tobytes()
if isinstance(obj, np.int64):
return int(obj)
if isinstance(obj, np.bool_):
return bool(obj)
if isinstance(obj, np.ndarray):
return obj.tolist()
if isinstance(obj, set):
return list(obj)
if isinstance(obj, decimal.Decimal):
return float(obj)
if isinstance(obj, (uuid.UUID, time, LazyString)):
return str(obj)
if isinstance(obj, timedelta):
return format_timedelta(obj)
if isinstance(obj, bytes):
try:
return obj.decode("utf-8")
except Exception: # pylint: disable=broad-except
return "[bytes]"
def json_iso_dttm_ser(obj: Any, pessimistic: bool = False) -> str:
"""
json serializer that deals with dates
>>> dttm = datetime(1970, 1, 1)
>>> json.dumps({'dttm': dttm}, default=json_iso_dttm_ser)
'{"dttm": "1970-01-01T00:00:00"}'
"""
val = base_json_conv(obj)
if val is not None:
return val
if isinstance(obj, (datetime, date, pd.Timestamp)):
obj = obj.isoformat()
else:
if pessimistic:
return "Unserializable [{}]".format(type(obj))
raise TypeError("Unserializable object {} of type {}".format(obj, type(obj)))
return obj
def pessimistic_json_iso_dttm_ser(obj: Any) -> str:
"""Proxy to call json_iso_dttm_ser in a pessimistic way
If one of object is not serializable to json, it will still succeed"""
return json_iso_dttm_ser(obj, pessimistic=True)
def json_int_dttm_ser(obj: Any) -> float:
"""json serializer that deals with dates"""
val = base_json_conv(obj)
if val is not None:
return val
if isinstance(obj, (datetime, pd.Timestamp)):
obj = datetime_to_epoch(obj)
elif isinstance(obj, date):
obj = (obj - EPOCH.date()).total_seconds() * 1000
else:
raise TypeError("Unserializable object {} of type {}".format(obj, type(obj)))
return obj
def json_dumps_w_dates(payload: Dict[Any, Any], sort_keys: bool = False) -> str:
"""Dumps payload to JSON with Datetime objects properly converted"""
return json.dumps(payload, default=json_int_dttm_ser, sort_keys=sort_keys)
def error_msg_from_exception(ex: Exception) -> str:
"""Translate exception into error message
Database have different ways to handle exception. This function attempts
to make sense of the exception object and construct a human readable
sentence.
TODO(bkyryliuk): parse the Presto error message from the connection
created via create_engine.
engine = create_engine('presto://localhost:3506/silver') -
gives an e.message as the str(dict)
presto.connect('localhost', port=3506, catalog='silver') - as a dict.
The latter version is parsed correctly by this function.
"""
msg = ""
if hasattr(ex, "message"):
if isinstance(ex.message, dict): # type: ignore
msg = ex.message.get("message") # type: ignore
elif ex.message: # type: ignore
msg = ex.message # type: ignore
return msg or str(ex)
def markdown(raw: str, markup_wrap: Optional[bool] = False) -> str:
safe_markdown_tags = [
"h1",
"h2",
"h3",
"h4",
"h5",
"h6",
"b",
"i",
"strong",
"em",
"tt",
"p",
"br",
"span",
"div",
"blockquote",
"code",
"hr",
"ul",
"ol",
"li",
"dd",
"dt",
"img",
"a",
]
safe_markdown_attrs = {
"img": ["src", "alt", "title"],
"a": ["href", "alt", "title"],
}
safe = md.markdown(
raw or "",
extensions=[
"markdown.extensions.tables",
"markdown.extensions.fenced_code",
"markdown.extensions.codehilite",
],
)
safe = bleach.clean(safe, safe_markdown_tags, safe_markdown_attrs)
if markup_wrap:
safe = Markup(safe)
return safe
def readfile(file_path: str) -> Optional[str]:
with open(file_path) as f:
content = f.read()
return content
def generic_find_constraint_name(
table: str, columns: Set[str], referenced: str, database: SQLA
) -> Optional[str]:
"""Utility to find a constraint name in alembic migrations"""
tbl = sa.Table(
table, database.metadata, autoload=True, autoload_with=database.engine
)
for fk in tbl.foreign_key_constraints:
if fk.referred_table.name == referenced and set(fk.column_keys) == columns:
return fk.name
return None
def generic_find_fk_constraint_name(
table: str, columns: Set[str], referenced: str, insp: Inspector
) -> Optional[str]:
"""Utility to find a foreign-key constraint name in alembic migrations"""
for fk in insp.get_foreign_keys(table):
if (
fk["referred_table"] == referenced
and set(fk["referred_columns"]) == columns
):
return fk["name"]
return None
def generic_find_fk_constraint_names( # pylint: disable=invalid-name
table: str, columns: Set[str], referenced: str, insp: Inspector
) -> Set[str]:
"""Utility to find foreign-key constraint names in alembic migrations"""
names = set()
for fk in insp.get_foreign_keys(table):
if (
fk["referred_table"] == referenced
and set(fk["referred_columns"]) == columns
):
names.add(fk["name"])
return names
def generic_find_uq_constraint_name(
table: str, columns: Set[str], insp: Inspector
) -> Optional[str]:
"""Utility to find a unique constraint name in alembic migrations"""
for uq in insp.get_unique_constraints(table):
if columns == set(uq["column_names"]):
return uq["name"]
return None
def get_datasource_full_name(
database_name: str, datasource_name: str, schema: Optional[str] = None
) -> str:
if not schema:
return "[{}].[{}]".format(database_name, datasource_name)
return "[{}].[{}].[{}]".format(database_name, schema, datasource_name)
def validate_json(obj: Union[bytes, bytearray, str]) -> None:
if obj:
try:
json.loads(obj)
except Exception as ex:
logger.error("JSON is not valid %s", str(ex), exc_info=True)
raise SupersetException("JSON is not valid") from ex
class SigalrmTimeout:
"""
To be used in a ``with`` block and timeout its content.
"""
def __init__(self, seconds: int = 1, error_message: str = "Timeout") -> None:
self.seconds = seconds
self.error_message = error_message
def handle_timeout( # pylint: disable=unused-argument
self, signum: int, frame: Any
) -> None:
logger.error("Process timed out", exc_info=True)
raise SupersetTimeoutException(
error_type=SupersetErrorType.BACKEND_TIMEOUT_ERROR,
message=self.error_message,
level=ErrorLevel.ERROR,
extra={"timeout": self.seconds},
)
def __enter__(self) -> None:
try:
if threading.current_thread() == threading.main_thread():
signal.signal(signal.SIGALRM, self.handle_timeout)
signal.alarm(self.seconds)
except ValueError as ex:
logger.warning("timeout can't be used in the current context")
logger.exception(ex)
def __exit__( # pylint: disable=redefined-outer-name,redefined-builtin
self, type: Any, value: Any, traceback: TracebackType
) -> None:
try:
signal.alarm(0)
except ValueError as ex:
logger.warning("timeout can't be used in the current context")
logger.exception(ex)
class TimerTimeout:
def __init__(self, seconds: int = 1, error_message: str = "Timeout") -> None:
self.seconds = seconds
self.error_message = error_message
self.timer = threading.Timer(seconds, _thread.interrupt_main)
def __enter__(self) -> None:
self.timer.start()
def __exit__( # pylint: disable=redefined-outer-name,redefined-builtin
self, type: Any, value: Any, traceback: TracebackType
) -> None:
self.timer.cancel()
if type is KeyboardInterrupt: # raised by _thread.interrupt_main
raise SupersetTimeoutException(
error_type=SupersetErrorType.BACKEND_TIMEOUT_ERROR,
message=self.error_message,
level=ErrorLevel.ERROR,
extra={"timeout": self.seconds},
)
# Windows has no support for SIGALRM, so we use the timer based timeout
timeout: Union[Type[TimerTimeout], Type[SigalrmTimeout]] = (
TimerTimeout if platform.system() == "Windows" else SigalrmTimeout
)
def pessimistic_connection_handling(some_engine: Engine) -> None:
@event.listens_for(some_engine, "engine_connect")
def ping_connection(connection: Connection, branch: bool) -> None:
if branch:
# 'branch' refers to a sub-connection of a connection,
# we don't want to bother pinging on these.
return
# turn off 'close with result'. This flag is only used with
# 'connectionless' execution, otherwise will be False in any case
save_should_close_with_result = connection.should_close_with_result
connection.should_close_with_result = False
try:
# run a SELECT 1. use a core select() so that
# the SELECT of a scalar value without a table is
# appropriately formatted for the backend
connection.scalar(select([1]))
except exc.DBAPIError as err:
# catch SQLAlchemy's DBAPIError, which is a wrapper
# for the DBAPI's exception. It includes a .connection_invalidated
# attribute which specifies if this connection is a 'disconnect'
# condition, which is based on inspection of the original exception
# by the dialect in use.
if err.connection_invalidated:
# run the same SELECT again - the connection will re-validate
# itself and establish a new connection. The disconnect detection
# here also causes the whole connection pool to be invalidated
# so that all stale connections are discarded.
connection.scalar(select([1]))
else:
raise
finally:
# restore 'close with result'
connection.should_close_with_result = save_should_close_with_result
def notify_user_about_perm_udate( # pylint: disable=too-many-arguments
granter: User,
user: User,
role: Role,
datasource: "BaseDatasource",
tpl_name: str,
config: Dict[str, Any],
) -> None:
msg = render_template(
tpl_name, granter=granter, user=user, role=role, datasource=datasource
)
logger.info(msg)
subject = __(
"[Superset] Access to the datasource %(name)s was granted",
name=datasource.full_name,
)
send_email_smtp(
user.email,
subject,
msg,
config,
bcc=granter.email,
dryrun=not config["EMAIL_NOTIFICATIONS"],
)
def send_email_smtp( # pylint: disable=invalid-name,too-many-arguments,too-many-locals
to: str,
subject: str,
html_content: str,
config: Dict[str, Any],
files: Optional[List[str]] = None,
data: Optional[Dict[str, str]] = None,
images: Optional[Dict[str, bytes]] = None,
dryrun: bool = False,
cc: Optional[str] = None,
bcc: Optional[str] = None,
mime_subtype: str = "mixed",
) -> None:
"""
Send an email with html content, eg:
send_email_smtp(
'test@example.com', 'foo', '<b>Foo</b> bar',['/dev/null'], dryrun=True)
"""
smtp_mail_from = config["SMTP_MAIL_FROM"]
smtp_mail_to = get_email_address_list(to)
msg = MIMEMultipart(mime_subtype)
msg["Subject"] = subject
msg["From"] = smtp_mail_from
msg["To"] = ", ".join(smtp_mail_to)
msg.preamble = "This is a multi-part message in MIME format."
recipients = smtp_mail_to
if cc:
smtp_mail_cc = get_email_address_list(cc)
msg["CC"] = ", ".join(smtp_mail_cc)
recipients = recipients + smtp_mail_cc
if bcc:
# don't add bcc in header
smtp_mail_bcc = get_email_address_list(bcc)
recipients = recipients + smtp_mail_bcc
msg["Date"] = formatdate(localtime=True)
mime_text = MIMEText(html_content, "html")
msg.attach(mime_text)
# Attach files by reading them from disk
for fname in files or []:
basename = os.path.basename(fname)
with open(fname, "rb") as f:
msg.attach(
MIMEApplication(
f.read(),
Content_Disposition="attachment; filename='%s'" % basename,
Name=basename,
)
)
# Attach any files passed directly
for name, body in (data or {}).items():
msg.attach(
MIMEApplication(
body, Content_Disposition="attachment; filename='%s'" % name, Name=name
)
)
# Attach any inline images, which may be required for display in
# HTML content (inline)
for msgid, imgdata in (images or {}).items():
formatted_time = formatdate(localtime=True)
file_name = f"{subject} {formatted_time}"
image = MIMEImage(imgdata, name=file_name)
image.add_header("Content-ID", "<%s>" % msgid)
image.add_header("Content-Disposition", "inline")
msg.attach(image)
send_mime_email(smtp_mail_from, recipients, msg, config, dryrun=dryrun)
def send_mime_email(
e_from: str,
e_to: List[str],
mime_msg: MIMEMultipart,
config: Dict[str, Any],
dryrun: bool = False,
) -> None:
smtp_host = config["SMTP_HOST"]
smtp_port = config["SMTP_PORT"]
smtp_user = config["SMTP_USER"]
smtp_password = config["SMTP_PASSWORD"]
smtp_starttls = config["SMTP_STARTTLS"]
smtp_ssl = config["SMTP_SSL"]
if not dryrun:
smtp = (
smtplib.SMTP_SSL(smtp_host, smtp_port)
if smtp_ssl
else smtplib.SMTP(smtp_host, smtp_port)
)
if smtp_starttls:
smtp.starttls()
if smtp_user and smtp_password:
smtp.login(smtp_user, smtp_password)
logger.debug("Sent an email to %s", str(e_to))
smtp.sendmail(e_from, e_to, mime_msg.as_string())
smtp.quit()
else:
logger.info("Dryrun enabled, email notification content is below:")
logger.info(mime_msg.as_string())
def get_email_address_list(address_string: str) -> List[str]:
address_string_list: List[str] = []
if isinstance(address_string, str):
address_string_list = re.split(r",|\s|;", address_string)
return [x.strip() for x in address_string_list if x.strip()]
def get_email_address_str(address_string: str) -> str:
address_list = get_email_address_list(address_string)
address_list_str = ", ".join(address_list)
return address_list_str
def choicify(values: Iterable[Any]) -> List[Tuple[Any, Any]]:
"""Takes an iterable and makes an iterable of tuples with it"""
return [(v, v) for v in values]
def zlib_compress(data: Union[bytes, str]) -> bytes:
"""
Compress things in a py2/3 safe fashion
>>> json_str = '{"test": 1}'
>>> blob = zlib_compress(json_str)
"""
if isinstance(data, str):
return zlib.compress(bytes(data, "utf-8"))
return zlib.compress(data)
def zlib_decompress(blob: bytes, decode: Optional[bool] = True) -> Union[bytes, str]:
"""
Decompress things to a string in a py2/3 safe fashion
>>> json_str = '{"test": 1}'
>>> blob = zlib_compress(json_str)
>>> got_str = zlib_decompress(blob)
>>> got_str == json_str
True
"""
if isinstance(blob, bytes):
decompressed = zlib.decompress(blob)
else:
decompressed = zlib.decompress(bytes(blob, "utf-8"))
return decompressed.decode("utf-8") if decode else decompressed
def simple_filter_to_adhoc(
filter_clause: QueryObjectFilterClause,
clause: str = "where",
) -> AdhocFilterClause:
result: AdhocFilterClause = {
"clause": clause.upper(),
"expressionType": "SIMPLE",
"comparator": filter_clause.get("val"),
"operator": filter_clause["op"],
"subject": filter_clause["col"],
}
if filter_clause.get("isExtra"):
result["isExtra"] = True
result["filterOptionName"] = md5_sha_from_dict(cast(Dict[Any, Any], result))
return result
def form_data_to_adhoc(form_data: Dict[str, Any], clause: str) -> AdhocFilterClause:
if clause not in ("where", "having"):
raise ValueError(__("Unsupported clause type: %(clause)s", clause=clause))
result: AdhocFilterClause = {
"clause": clause.upper(),
"expressionType": "SQL",
"sqlExpression": form_data.get(clause),
}
result["filterOptionName"] = md5_sha_from_dict(cast(Dict[Any, Any], result))
return result
def merge_extra_form_data(form_data: Dict[str, Any]) -> None:
"""
Merge extra form data (appends and overrides) into the main payload
and add applied time extras to the payload.
"""
filter_keys = ["filters", "adhoc_filters"]
extra_form_data = form_data.pop("extra_form_data", {})
append_filters: List[QueryObjectFilterClause] = extra_form_data.get("filters", None)
# merge append extras
for key in [key for key in EXTRA_FORM_DATA_APPEND_KEYS if key not in filter_keys]:
extra_value = getattr(extra_form_data, key, {})
form_value = getattr(form_data, key, {})
form_value.update(extra_value)
if form_value:
form_data["key"] = extra_value
# map regular extras that apply to form data properties
for src_key, target_key in EXTRA_FORM_DATA_OVERRIDE_REGULAR_MAPPINGS.items():
value = extra_form_data.get(src_key)
if value is not None:
form_data[target_key] = value
# map extras that apply to form data extra properties
extras = form_data.get("extras", {})
for key in EXTRA_FORM_DATA_OVERRIDE_EXTRA_KEYS:
value = extra_form_data.get(key)
if value is not None:
extras[key] = value
if extras:
form_data["extras"] = extras
adhoc_filters: List[AdhocFilterClause] = form_data.get("adhoc_filters", [])
form_data["adhoc_filters"] = adhoc_filters
append_adhoc_filters: List[AdhocFilterClause] = extra_form_data.get(
"adhoc_filters", []
)
adhoc_filters.extend(
{"isExtra": True, **fltr} for fltr in append_adhoc_filters # type: ignore
)
if append_filters:
for key, value in form_data.items():
if re.match("adhoc_filter.*", key):
value.extend(
simple_filter_to_adhoc({"isExtra": True, **fltr}) # type: ignore
for fltr in append_filters
if fltr
)
def merge_extra_filters(form_data: Dict[str, Any]) -> None:
# extra_filters are temporary/contextual filters (using the legacy constructs)
# that are external to the slice definition. We use those for dynamic
# interactive filters like the ones emitted by the "Filter Box" visualization.
# Note extra_filters only support simple filters.
applied_time_extras: Dict[str, str] = {}
form_data["applied_time_extras"] = applied_time_extras
adhoc_filters = form_data.get("adhoc_filters", [])
form_data["adhoc_filters"] = adhoc_filters
merge_extra_form_data(form_data)
if "extra_filters" in form_data:
# __form and __to are special extra_filters that target time
# boundaries. The rest of extra_filters are simple
# [column_name in list_of_values]. `__` prefix is there to avoid
# potential conflicts with column that would be named `from` or `to`
date_options = {
"__time_range": "time_range",
"__time_col": "granularity_sqla",
"__time_grain": "time_grain_sqla",
"__granularity": "granularity",
}
# Grab list of existing filters 'keyed' on the column and operator
def get_filter_key(f: Dict[str, Any]) -> str:
if "expressionType" in f:
return "{}__{}".format(f["subject"], f["operator"])
return "{}__{}".format(f["col"], f["op"])
existing_filters = {}
for existing in adhoc_filters:
if (
existing["expressionType"] == "SIMPLE"
and existing.get("comparator") is not None
and existing.get("subject") is not None
):
existing_filters[get_filter_key(existing)] = existing["comparator"]
for filtr in form_data[ # pylint: disable=too-many-nested-blocks
"extra_filters"
]:
filtr["isExtra"] = True
# Pull out time filters/options and merge into form data
filter_column = filtr["col"]
time_extra = date_options.get(filter_column)
if time_extra:
time_extra_value = filtr.get("val")
if time_extra_value and time_extra_value != NO_TIME_RANGE:
form_data[time_extra] = time_extra_value
applied_time_extras[filter_column] = time_extra_value
elif filtr["val"]:
# Merge column filters
filter_key = get_filter_key(filtr)
if filter_key in existing_filters:
# Check if the filter already exists
if isinstance(filtr["val"], list):
if isinstance(existing_filters[filter_key], list):
# Add filters for unequal lists
# order doesn't matter
if set(existing_filters[filter_key]) != set(filtr["val"]):
adhoc_filters.append(simple_filter_to_adhoc(filtr))
else:
adhoc_filters.append(simple_filter_to_adhoc(filtr))
else:
# Do not add filter if same value already exists
if filtr["val"] != existing_filters[filter_key]:
adhoc_filters.append(simple_filter_to_adhoc(filtr))
else:
# Filter not found, add it
adhoc_filters.append(simple_filter_to_adhoc(filtr))
# Remove extra filters from the form data since no longer needed
del form_data["extra_filters"]
def merge_request_params(form_data: Dict[str, Any], params: Dict[str, Any]) -> None:
"""
Merge request parameters to the key `url_params` in form_data. Only updates
or appends parameters to `form_data` that are defined in `params; pre-existing
parameters not defined in params are left unchanged.
:param form_data: object to be updated
:param params: request parameters received via query string
"""
url_params = form_data.get("url_params", {})
for key, value in params.items():
if key in ("form_data", "r"):
continue
url_params[key] = value
form_data["url_params"] = url_params
def user_label(user: User) -> Optional[str]:
"""Given a user ORM FAB object, returns a label"""
if user:
if user.first_name and user.last_name:
return user.first_name + " " + user.last_name
return user.username
return None
def get_example_default_schema() -> Optional[str]:
"""
Return the default schema of the examples database, if any.
"""
database = get_example_database()
engine = database.get_sqla_engine()
return inspect(engine).default_schema_name
def backend() -> str:
return get_example_database().backend
def is_adhoc_metric(metric: Metric) -> TypeGuard[AdhocMetric]:
return isinstance(metric, dict) and "expressionType" in metric
def is_adhoc_column(column: Column) -> TypeGuard[AdhocColumn]:
return isinstance(column, dict)
def get_column_name(
column: Column, verbose_map: Optional[Dict[str, Any]] = None
) -> str:
"""
Extract label from column
:param column: object to extract label from
:param verbose_map: verbose_map from dataset for optional mapping from
raw name to verbose name
:return: String representation of column
:raises ValueError: if metric object is invalid
"""
if isinstance(column, dict):
label = column.get("label")
if label:
return label
expr = column.get("sqlExpression")
if expr:
return expr
raise ValueError("Missing label")
verbose_map = verbose_map or {}
return verbose_map.get(column, column)
def get_metric_name(
metric: Metric, verbose_map: Optional[Dict[str, Any]] = None
) -> str:
"""
Extract label from metric
:param metric: object to extract label from
:param verbose_map: verbose_map from dataset for optional mapping from
raw name to verbose name
:return: String representation of metric
:raises ValueError: if metric object is invalid
"""
if is_adhoc_metric(metric):
label = metric.get("label")
if label:
return label
expression_type = metric.get("expressionType")
if expression_type == "SQL":
sql_expression = metric.get("sqlExpression")
if sql_expression:
return sql_expression
if expression_type == "SIMPLE":
column: AdhocMetricColumn = metric.get("column") or {}
column_name = column.get("column_name")
aggregate = metric.get("aggregate")
if column and aggregate:
return f"{aggregate}({column_name})"
if column_name:
return column_name
if isinstance(metric, str):
verbose_map = verbose_map or {}
return verbose_map.get(metric, metric)
raise ValueError(__("Invalid metric object: %(metric)s", metric=str(metric)))
def get_column_names(
columns: Optional[Sequence[Column]],
verbose_map: Optional[Dict[str, Any]] = None,
) -> List[str]:
return [
column
for column in [get_column_name(column, verbose_map) for column in columns or []]
if column
]
def get_metric_names(
metrics: Optional[Sequence[Metric]],
verbose_map: Optional[Dict[str, Any]] = None,
) -> List[str]:
return [
metric
for metric in [get_metric_name(metric, verbose_map) for metric in metrics or []]
if metric
]
def get_first_metric_name(
metrics: Optional[Sequence[Metric]],
verbose_map: Optional[Dict[str, Any]] = None,
) -> Optional[str]:
metric_labels = get_metric_names(metrics, verbose_map)
return metric_labels[0] if metric_labels else None
def ensure_path_exists(path: str) -> None:
try:
os.makedirs(path)
except OSError as ex:
if not (os.path.isdir(path) and ex.errno == errno.EEXIST):
raise
def convert_legacy_filters_into_adhoc( # pylint: disable=invalid-name
form_data: FormData,
) -> None:
mapping = {"having": "having_filters", "where": "filters"}
if not form_data.get("adhoc_filters"):
adhoc_filters: List[AdhocFilterClause] = []
form_data["adhoc_filters"] = adhoc_filters
for clause, filters in mapping.items():
if clause in form_data and form_data[clause] != "":
adhoc_filters.append(form_data_to_adhoc(form_data, clause))
if filters in form_data:
for filt in filter(lambda x: x is not None, form_data[filters]):
adhoc_filters.append(simple_filter_to_adhoc(filt, clause))
for key in ("filters", "having", "having_filters", "where"):
if key in form_data:
del form_data[key]
def split_adhoc_filters_into_base_filters( # pylint: disable=invalid-name
form_data: FormData,
) -> None:
"""
Mutates form data to restructure the adhoc filters in the form of the four base
filters, `where`, `having`, `filters`, and `having_filters` which represent
free form where sql, free form having sql, structured where clauses and structured
having clauses.
"""
adhoc_filters = form_data.get("adhoc_filters")
if isinstance(adhoc_filters, list):
simple_where_filters = []
simple_having_filters = []
sql_where_filters = []
sql_having_filters = []
for adhoc_filter in adhoc_filters:
expression_type = adhoc_filter.get("expressionType")
clause = adhoc_filter.get("clause")
if expression_type == "SIMPLE":
if clause == "WHERE":
simple_where_filters.append(
{
"col": adhoc_filter.get("subject"),
"op": adhoc_filter.get("operator"),
"val": adhoc_filter.get("comparator"),
}
)
elif clause == "HAVING":
simple_having_filters.append(
{
"col": adhoc_filter.get("subject"),
"op": adhoc_filter.get("operator"),
"val": adhoc_filter.get("comparator"),
}
)
elif expression_type == "SQL":
sql_expression = adhoc_filter.get("sqlExpression")
sql_expression = sanitize_clause(sql_expression)
if clause == "WHERE":
sql_where_filters.append(sql_expression)
elif clause == "HAVING":
sql_having_filters.append(sql_expression)
form_data["where"] = " AND ".join(
["({})".format(sql) for sql in sql_where_filters]
)
form_data["having"] = " AND ".join(
["({})".format(sql) for sql in sql_having_filters]
)
form_data["having_filters"] = simple_having_filters
form_data["filters"] = simple_where_filters
def get_username() -> Optional[str]:
"""
Get username (if defined) associated with the current user.
:returns: The username
"""
try:
return g.user.username
except Exception: # pylint: disable=broad-except
return None
def get_user_id() -> Optional[int]:
"""
Get the user identifier (if defined) associated with the current user.
Though the Flask-AppBuilder `User` and Flask-Login `AnonymousUserMixin` and
`UserMixin` models provide a convenience `get_id` method, for generality, the
identifier is encoded as a `str` whereas in Superset all identifiers are encoded as
an `int`.
returns: The user identifier
"""
try:
return g.user.id
except Exception: # pylint: disable=broad-except
return None
@contextmanager
def override_user(user: Optional[User], force: bool = True) -> Iterator[Any]:
"""
Temporarily override the current user per `flask.g` with the specified user.
Sometimes, often in the context of async Celery tasks, it is useful to switch the
current user (which may be undefined) to different one, execute some SQLAlchemy
tasks et al. and then revert back to the original one.
:param user: The override user
:param force: Whether to override the current user if set
"""
# pylint: disable=assigning-non-slot
if hasattr(g, "user"):
if force or g.user is None:
current = g.user
g.user = user
yield
g.user = current
else:
yield
else:
g.user = user
yield
delattr(g, "user")
def parse_ssl_cert(certificate: str) -> _Certificate:
"""
Parses the contents of a certificate and returns a valid certificate object
if valid.
:param certificate: Contents of certificate file
:return: Valid certificate instance
:raises CertificateException: If certificate is not valid/unparseable
"""
try:
return x509.load_pem_x509_certificate(
certificate.encode("utf-8"), default_backend()
)
except ValueError as ex:
raise CertificateException("Invalid certificate") from ex
def create_ssl_cert_file(certificate: str) -> str:
"""
This creates a certificate file that can be used to validate HTTPS
sessions. A certificate is only written to disk once; on subsequent calls,
only the path of the existing certificate is returned.
:param certificate: The contents of the certificate
:return: The path to the certificate file
:raises CertificateException: If certificate is not valid/unparseable
"""
filename = f"{md5_sha_from_str(certificate)}.crt"
cert_dir = current_app.config["SSL_CERT_PATH"]
path = cert_dir if cert_dir else tempfile.gettempdir()
path = os.path.join(path, filename)
if not os.path.exists(path):
# Validate certificate prior to persisting to temporary directory
parse_ssl_cert(certificate)
with open(path, "w") as cert_file:
cert_file.write(certificate)
return path
def time_function(
func: Callable[..., FlaskResponse], *args: Any, **kwargs: Any
) -> Tuple[float, Any]:
"""
Measures the amount of time a function takes to execute in ms
:param func: The function execution time to measure
:param args: args to be passed to the function
:param kwargs: kwargs to be passed to the function
:return: A tuple with the duration and response from the function
"""
start = default_timer()
response = func(*args, **kwargs)
stop = default_timer()
return (stop - start) * 1000.0, response
def MediumText() -> Variant: # pylint:disable=invalid-name
return Text().with_variant(MEDIUMTEXT(), "mysql")
def shortid() -> str:
return "{}".format(uuid.uuid4())[-12:]
class DatasourceName(NamedTuple):
table: str
schema: str
def get_stacktrace() -> Optional[str]:
if current_app.config["SHOW_STACKTRACE"]:
return traceback.format_exc()
return None
def split(
string: str, delimiter: str = " ", quote: str = '"', escaped_quote: str = r"\""
) -> Iterator[str]:
"""
A split function that is aware of quotes and parentheses.
:param string: string to split
:param delimiter: string defining where to split, usually a comma or space
:param quote: string, either a single or a double quote
:param escaped_quote: string representing an escaped quote
:return: list of strings
"""
parens = 0
quotes = False
i = 0
for j, character in enumerate(string):
complete = parens == 0 and not quotes
if complete and character == delimiter:
yield string[i:j]
i = j + len(delimiter)
elif character == "(":
parens += 1
elif character == ")":
parens -= 1
elif character == quote:
if quotes and string[j - len(escaped_quote) + 1 : j + 1] != escaped_quote:
quotes = False
elif not quotes:
quotes = True
yield string[i:]
def get_iterable(x: Any) -> List[Any]:
"""
Get an iterable (list) representation of the object.
:param x: The object
:returns: An iterable representation
"""
return x if isinstance(x, list) else [x]
def get_form_data_token(form_data: Dict[str, Any]) -> str:
"""
Return the token contained within form data or generate a new one.
:param form_data: chart form data
:return: original token if predefined, otherwise new uuid4 based token
"""
return form_data.get("token") or "token_" + uuid.uuid4().hex[:8]
def get_column_name_from_column(column: Column) -> Optional[str]:
"""
Extract the physical column that a column is referencing. If the column is
an adhoc column, always returns `None`.
:param column: Physical and ad-hoc column
:return: column name if physical column, otherwise None
"""
if is_adhoc_column(column):
return None
return column # type: ignore
def get_column_names_from_columns(columns: List[Column]) -> List[str]:
"""
Extract the physical columns that a list of columns are referencing. Ignore
adhoc columns
:param columns: Physical and adhoc columns
:return: column names of all physical columns
"""
return [col for col in map(get_column_name_from_column, columns) if col]
def get_column_name_from_metric(metric: Metric) -> Optional[str]:
"""
Extract the column that a metric is referencing. If the metric isn't
a simple metric, always returns `None`.
:param metric: Ad-hoc metric
:return: column name if simple metric, otherwise None
"""
if is_adhoc_metric(metric):
metric = cast(AdhocMetric, metric)
if metric["expressionType"] == AdhocMetricExpressionType.SIMPLE:
return cast(Dict[str, Any], metric["column"])["column_name"]
return None
def get_column_names_from_metrics(metrics: List[Metric]) -> List[str]:
"""
Extract the columns that a list of metrics are referencing. Expcludes all
SQL metrics.
:param metrics: Ad-hoc metric
:return: column name if simple metric, otherwise None
"""
return [col for col in map(get_column_name_from_metric, metrics) if col]
def extract_dataframe_dtypes(
df: pd.DataFrame,
datasource: Optional["BaseDatasource"] = None,
) -> List[GenericDataType]:
"""Serialize pandas/numpy dtypes to generic types"""
# omitting string types as those will be the default type
inferred_type_map: Dict[str, GenericDataType] = {
"floating": GenericDataType.NUMERIC,
"integer": GenericDataType.NUMERIC,
"mixed-integer-float": GenericDataType.NUMERIC,
"decimal": GenericDataType.NUMERIC,
"boolean": GenericDataType.BOOLEAN,
"datetime64": GenericDataType.TEMPORAL,
"datetime": GenericDataType.TEMPORAL,
"date": GenericDataType.TEMPORAL,
}
columns_by_name: Dict[str, Any] = {}
if datasource:
for column in datasource.columns:
if isinstance(column, dict):
columns_by_name[column.get("column_name")] = column
else:
columns_by_name[column.column_name] = column
generic_types: List[GenericDataType] = []
for column in df.columns:
column_object = columns_by_name.get(column)
series = df[column]
inferred_type = infer_dtype(series)
if isinstance(column_object, dict): # type: ignore
generic_type = (
GenericDataType.TEMPORAL
if column_object and column_object.get("is_dttm")
else inferred_type_map.get(inferred_type, GenericDataType.STRING)
)
else:
generic_type = (
GenericDataType.TEMPORAL
if column_object and column_object.is_dttm
else inferred_type_map.get(inferred_type, GenericDataType.STRING)
)
generic_types.append(generic_type)
return generic_types
def extract_column_dtype(col: "BaseColumn") -> GenericDataType:
if col.is_temporal:
return GenericDataType.TEMPORAL
if col.is_numeric:
return GenericDataType.NUMERIC
# TODO: add check for boolean data type when proper support is added
return GenericDataType.STRING
def indexed(
items: List[Any], key: Union[str, Callable[[Any], Any]]
) -> Dict[Any, List[Any]]:
"""Build an index for a list of objects"""
idx: Dict[Any, Any] = {}
for item in items:
key_ = getattr(item, key) if isinstance(key, str) else key(item)
idx.setdefault(key_, []).append(item)
return idx
def is_test() -> bool:
return strtobool(os.environ.get("SUPERSET_TESTENV", "false"))
def get_time_filter_status(
datasource: "BaseDatasource",
applied_time_extras: Dict[str, str],
) -> Tuple[List[Dict[str, str]], List[Dict[str, str]]]:
temporal_columns: Set[Any]
if datasource.type == "query":
temporal_columns = {
col.get("column_name") for col in datasource.columns if col.get("is_dttm")
}
else:
temporal_columns = {
col.column_name for col in datasource.columns if col.is_dttm
}
applied: List[Dict[str, str]] = []
rejected: List[Dict[str, str]] = []
time_column = applied_time_extras.get(ExtraFiltersTimeColumnType.TIME_COL)
if time_column:
if time_column in temporal_columns:
applied.append({"column": ExtraFiltersTimeColumnType.TIME_COL})
else:
rejected.append(
{
"reason": ExtraFiltersReasonType.COL_NOT_IN_DATASOURCE,
"column": ExtraFiltersTimeColumnType.TIME_COL,
}
)
if ExtraFiltersTimeColumnType.TIME_GRAIN in applied_time_extras:
# are there any temporal columns to assign the time grain to?
if temporal_columns:
applied.append({"column": ExtraFiltersTimeColumnType.TIME_GRAIN})
else:
rejected.append(
{
"reason": ExtraFiltersReasonType.NO_TEMPORAL_COLUMN,
"column": ExtraFiltersTimeColumnType.TIME_GRAIN,
}
)
time_range = applied_time_extras.get(ExtraFiltersTimeColumnType.TIME_RANGE)
if time_range:
# are there any temporal columns to assign the time grain to?
if temporal_columns:
applied.append({"column": ExtraFiltersTimeColumnType.TIME_RANGE})
else:
rejected.append(
{
"reason": ExtraFiltersReasonType.NO_TEMPORAL_COLUMN,
"column": ExtraFiltersTimeColumnType.TIME_RANGE,
}
)
return applied, rejected
def format_list(items: Sequence[str], sep: str = ", ", quote: str = '"') -> str:
quote_escaped = "\\" + quote
return sep.join(f"{quote}{x.replace(quote, quote_escaped)}{quote}" for x in items)
def find_duplicates(items: Iterable[InputType]) -> List[InputType]:
"""Find duplicate items in an iterable."""
return [item for item, count in collections.Counter(items).items() if count > 1]
def remove_duplicates(
items: Iterable[InputType], key: Optional[Callable[[InputType], Any]] = None
) -> List[InputType]:
"""Remove duplicate items in an iterable."""
if not key:
return list(dict.fromkeys(items).keys())
seen = set()
result = []
for item in items:
item_key = key(item)
if item_key not in seen:
seen.add(item_key)
result.append(item)
return result
def normalize_dttm_col(
df: pd.DataFrame,
timestamp_format: Optional[str],
offset: int,
time_shift: Optional[timedelta],
) -> None:
if DTTM_ALIAS not in df.columns:
return
if timestamp_format in ("epoch_s", "epoch_ms"):
dttm_col = df[DTTM_ALIAS]
if is_numeric_dtype(dttm_col):
# Column is formatted as a numeric value
unit = timestamp_format.replace("epoch_", "")
df[DTTM_ALIAS] = pd.to_datetime(
dttm_col, utc=False, unit=unit, origin="unix", errors="coerce"
)
else:
# Column has already been formatted as a timestamp.
df[DTTM_ALIAS] = dttm_col.apply(pd.Timestamp)
else:
df[DTTM_ALIAS] = pd.to_datetime(
df[DTTM_ALIAS], utc=False, format=timestamp_format, errors="coerce"
)
if offset:
df[DTTM_ALIAS] += timedelta(hours=offset)
if time_shift is not None:
df[DTTM_ALIAS] += time_shift
def parse_boolean_string(bool_str: Optional[str]) -> bool:
"""
Convert a string representation of a true/false value into a boolean
>>> parse_boolean_string(None)
False
>>> parse_boolean_string('false')
False
>>> parse_boolean_string('true')
True
>>> parse_boolean_string('False')
False
>>> parse_boolean_string('True')
True
>>> parse_boolean_string('foo')
False
>>> parse_boolean_string('0')
False
>>> parse_boolean_string('1')
True
:param bool_str: string representation of a value that is assumed to be boolean
:return: parsed boolean value
"""
if bool_str is None:
return False
try:
return bool(strtobool(bool_str.lower()))
except ValueError:
return False
def apply_max_row_limit(
limit: int,
max_limit: Optional[int] = None,
) -> int:
"""
Override row limit if max global limit is defined
:param limit: requested row limit
:param max_limit: Maximum allowed row limit
:return: Capped row limit
>>> apply_max_row_limit(100000, 10)
10
>>> apply_max_row_limit(10, 100000)
10
>>> apply_max_row_limit(0, 10000)
10000
"""
if max_limit is None:
max_limit = current_app.config["SQL_MAX_ROW"]
if limit != 0:
return min(max_limit, limit)
return max_limit
def create_zip(files: Dict[str, Any]) -> BytesIO:
buf = BytesIO()
with ZipFile(buf, "w") as bundle:
for filename, contents in files.items():
with bundle.open(filename, "w") as fp:
fp.write(contents)
buf.seek(0)
return buf
Reference in New Issue View Git Blame Copy Permalink