# 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. """Defines the templating context for SQL Lab""" import json import re from functools import partial from typing import ( Any, Callable, cast, Dict, List, Optional, Tuple, TYPE_CHECKING, Union, ) from flask import current_app, g, has_request_context, request from flask_babel import gettext as _ from jinja2 import DebugUndefined from jinja2.sandbox import SandboxedEnvironment from sqlalchemy.engine.interfaces import Dialect from sqlalchemy.types import String from typing_extensions import TypedDict from superset.datasets.commands.exceptions import DatasetNotFoundError from superset.exceptions import SupersetTemplateException from superset.extensions import feature_flag_manager from superset.utils.core import ( convert_legacy_filters_into_adhoc, get_user_id, merge_extra_filters, ) from superset.utils.memoized import memoized if TYPE_CHECKING: from superset.connectors.sqla.models import SqlaTable from superset.models.core import Database from superset.models.sql_lab import Query NONE_TYPE = type(None).__name__ ALLOWED_TYPES = ( NONE_TYPE, "bool", "str", "unicode", "int", "long", "float", "list", "dict", "tuple", "set", ) COLLECTION_TYPES = ("list", "dict", "tuple", "set") @memoized def context_addons() -> Dict[str, Any]: return current_app.config.get("JINJA_CONTEXT_ADDONS", {}) class Filter(TypedDict): op: str # pylint: disable=C0103 col: str val: Union[None, Any, List[Any]] class ExtraCache: """ Dummy class that exposes a method used to store additional values used in calculation of query object cache keys. """ # Regular expression for detecting the presence of templated methods which could # be added to the cache key. regex = re.compile( r"\{\{.*(" r"current_user_id\(.*\)|" r"current_username\(.*\)|" r"cache_key_wrapper\(.*\)|" r"url_param\(.*\)" r").*\}\}" ) def __init__( self, extra_cache_keys: Optional[List[Any]] = None, applied_filters: Optional[List[str]] = None, removed_filters: Optional[List[str]] = None, dialect: Optional[Dialect] = None, ): self.extra_cache_keys = extra_cache_keys self.applied_filters = applied_filters if applied_filters is not None else [] self.removed_filters = removed_filters if removed_filters is not None else [] self.dialect = dialect def current_user_id(self, add_to_cache_keys: bool = True) -> Optional[int]: """ Return the user ID of the user who is currently logged in. :param add_to_cache_keys: Whether the value should be included in the cache key :returns: The user ID """ if hasattr(g, "user") and g.user: id_ = get_user_id() if add_to_cache_keys: self.cache_key_wrapper(id_) return id_ return None def current_username(self, add_to_cache_keys: bool = True) -> Optional[str]: """ Return the username of the user who is currently logged in. :param add_to_cache_keys: Whether the value should be included in the cache key :returns: The username """ if g.user and hasattr(g.user, "username"): if add_to_cache_keys: self.cache_key_wrapper(g.user.username) return g.user.username return None def cache_key_wrapper(self, key: Any) -> Any: """ Adds values to a list that is added to the query object used for calculating a cache key. This is needed if the following applies: - Caching is enabled - The query is dynamically generated using a jinja template - A `JINJA_CONTEXT_ADDONS` or similar is used as a filter in the query :param key: Any value that should be considered when calculating the cache key :return: the original value ``key`` passed to the function """ if self.extra_cache_keys is not None: self.extra_cache_keys.append(key) return key def url_param( self, param: str, default: Optional[str] = None, add_to_cache_keys: bool = True, escape_result: bool = True, ) -> Optional[str]: """ Read a url or post parameter and use it in your SQL Lab query. When in SQL Lab, it's possible to add arbitrary URL "query string" parameters, and use those in your SQL code. For instance you can alter your url and add `?foo=bar`, as in `{domain}/superset/sqllab?foo=bar`. Then if your query is something like SELECT * FROM foo = '{{ url_param('foo') }}', it will be parsed at runtime and replaced by the value in the URL. As you create a visualization form this SQL Lab query, you can pass parameters in the explore view as well as from the dashboard, and it should carry through to your queries. Default values for URL parameters can be defined in chart metadata by adding the key-value pair `url_params: {'foo': 'bar'}` :param param: the parameter to lookup :param default: the value to return in the absence of the parameter :param add_to_cache_keys: Whether the value should be included in the cache key :param escape_result: Should special characters in the result be escaped :returns: The URL parameters """ # pylint: disable=import-outside-toplevel from superset.views.utils import get_form_data if has_request_context() and request.args.get(param): # type: ignore return request.args.get(param, default) form_data, _ = get_form_data() url_params = form_data.get("url_params") or {} result = url_params.get(param, default) if result and escape_result and self.dialect: # use the dialect specific quoting logic to escape string result = String().literal_processor(dialect=self.dialect)(value=result)[ 1:-1 ] if add_to_cache_keys: self.cache_key_wrapper(result) return result def filter_values( self, column: str, default: Optional[str] = None, remove_filter: bool = False ) -> List[Any]: """Gets a values for a particular filter as a list This is useful if: - you want to use a filter component to filter a query where the name of filter component column doesn't match the one in the select statement - you want to have the ability for filter inside the main query for speed purposes Usage example:: SELECT action, count(*) as times FROM logs WHERE action in ({{ "'" + "','".join(filter_values('action_type')) + "'" }}) GROUP BY action :param column: column/filter name to lookup :param default: default value to return if there's no matching columns :param remove_filter: When set to true, mark the filter as processed, removing it from the outer query. Useful when a filter should only apply to the inner query :return: returns a list of filter values """ return_val: List[Any] = [] filters = self.get_filters(column, remove_filter) for flt in filters: val = flt.get("val") if isinstance(val, list): return_val.extend(val) elif val: return_val.append(val) if (not return_val) and default: # If no values are found, return the default provided. return_val = [default] return return_val def get_filters(self, column: str, remove_filter: bool = False) -> List[Filter]: """Get the filters applied to the given column. In addition to returning values like the filter_values function the get_filters function returns the operator specified in the explorer UI. This is useful if: - you want to handle more than the IN operator in your SQL clause - you want to handle generating custom SQL conditions for a filter - you want to have the ability for filter inside the main query for speed purposes Usage example:: WITH RECURSIVE superiors(employee_id, manager_id, full_name, level, lineage) AS ( SELECT employee_id, manager_id, full_name, 1 as level, employee_id as lineage FROM employees WHERE 1=1 {# Render a blank line #} {%- for filter in get_filters('full_name', remove_filter=True) -%} {%- if filter.get('op') == 'IN' -%} AND full_name IN ( {{ "'" + "', '".join(filter.get('val')) + "'" }} ) {%- endif -%} {%- if filter.get('op') == 'LIKE' -%} AND full_name LIKE {{ "'" + filter.get('val') + "'" }} {%- endif -%} {%- endfor -%} UNION ALL SELECT e.employee_id, e.manager_id, e.full_name, s.level + 1 as level, s.lineage FROM employees e, superiors s WHERE s.manager_id = e.employee_id ) SELECT employee_id, manager_id, full_name, level, lineage FROM superiors order by lineage, level :param column: column/filter name to lookup :param remove_filter: When set to true, mark the filter as processed, removing it from the outer query. Useful when a filter should only apply to the inner query :return: returns a list of filters """ # pylint: disable=import-outside-toplevel from superset.utils.core import FilterOperator from superset.views.utils import get_form_data form_data, _ = get_form_data() convert_legacy_filters_into_adhoc(form_data) merge_extra_filters(form_data) filters: List[Filter] = [] for flt in form_data.get("adhoc_filters", []): val: Union[Any, List[Any]] = flt.get("comparator") op: str = flt["operator"].upper() if flt.get("operator") else None # fltOpName: str = flt.get("filterOptionName") if ( flt.get("expressionType") == "SIMPLE" and flt.get("clause") == "WHERE" and flt.get("subject") == column and val ): if remove_filter: if column not in self.removed_filters: self.removed_filters.append(column) if column not in self.applied_filters: self.applied_filters.append(column) if op in ( FilterOperator.IN.value, FilterOperator.NOT_IN.value, ) and not isinstance(val, list): val = [val] filters.append({"op": op, "col": column, "val": val}) return filters def safe_proxy(func: Callable[..., Any], *args: Any, **kwargs: Any) -> Any: return_value = func(*args, **kwargs) value_type = type(return_value).__name__ if value_type not in ALLOWED_TYPES: raise SupersetTemplateException( _( "Unsafe return type for function %(func)s: %(value_type)s", func=func.__name__, value_type=value_type, ) ) if value_type in COLLECTION_TYPES: try: return_value = json.loads(json.dumps(return_value)) except TypeError as ex: raise SupersetTemplateException( _( "Unsupported return value for method %(name)s", name=func.__name__, ) ) from ex return return_value def validate_context_types(context: Dict[str, Any]) -> Dict[str, Any]: for key in context: arg_type = type(context[key]).__name__ if arg_type not in ALLOWED_TYPES and key not in context_addons(): if arg_type == "partial" and context[key].func.__name__ == "safe_proxy": continue raise SupersetTemplateException( _( "Unsafe template value for key %(key)s: %(value_type)s", key=key, value_type=arg_type, ) ) if arg_type in COLLECTION_TYPES: try: context[key] = json.loads(json.dumps(context[key])) except TypeError as ex: raise SupersetTemplateException( _("Unsupported template value for key %(key)s", key=key) ) from ex return context def validate_template_context( engine: Optional[str], context: Dict[str, Any] ) -> Dict[str, Any]: if engine and engine in context: # validate engine context separately to allow for engine-specific methods engine_context = validate_context_types(context.pop(engine)) valid_context = validate_context_types(context) valid_context[engine] = engine_context return valid_context return validate_context_types(context) def where_in(values: List[Any], mark: str = "'") -> str: """ Given a list of values, build a parenthesis list suitable for an IN expression. >>> where_in([1, "b", 3]) (1, 'b', 3) """ def quote(value: Any) -> str: if isinstance(value, str): value = value.replace(mark, mark * 2) return f"{mark}{value}{mark}" return str(value) joined_values = ", ".join(quote(value) for value in values) return f"({joined_values})" class BaseTemplateProcessor: """ Base class for database-specific jinja context """ engine: Optional[str] = None # pylint: disable=too-many-arguments def __init__( self, database: "Database", query: Optional["Query"] = None, table: Optional["SqlaTable"] = None, extra_cache_keys: Optional[List[Any]] = None, removed_filters: Optional[List[str]] = None, applied_filters: Optional[List[str]] = None, **kwargs: Any, ) -> None: self._database = database self._query = query self._schema = None if query and query.schema: self._schema = query.schema elif table: self._schema = table.schema self._extra_cache_keys = extra_cache_keys self._applied_filters = applied_filters self._removed_filters = removed_filters self._context: Dict[str, Any] = {} self._env = SandboxedEnvironment(undefined=DebugUndefined) self.set_context(**kwargs) # custom filters self._env.filters["where_in"] = where_in def set_context(self, **kwargs: Any) -> None: self._context.update(kwargs) self._context.update(context_addons()) def process_template(self, sql: str, **kwargs: Any) -> str: """Processes a sql template >>> sql = "SELECT '{{ datetime(2017, 1, 1).isoformat() }}'" >>> process_template(sql) "SELECT '2017-01-01T00:00:00'" """ template = self._env.from_string(sql) kwargs.update(self._context) context = validate_template_context(self.engine, kwargs) return template.render(context) class JinjaTemplateProcessor(BaseTemplateProcessor): def set_context(self, **kwargs: Any) -> None: super().set_context(**kwargs) extra_cache = ExtraCache( extra_cache_keys=self._extra_cache_keys, applied_filters=self._applied_filters, removed_filters=self._removed_filters, dialect=self._database.get_dialect(), ) self._context.update( { "url_param": partial(safe_proxy, extra_cache.url_param), "current_user_id": partial(safe_proxy, extra_cache.current_user_id), "current_username": partial(safe_proxy, extra_cache.current_username), "cache_key_wrapper": partial(safe_proxy, extra_cache.cache_key_wrapper), "filter_values": partial(safe_proxy, extra_cache.filter_values), "get_filters": partial(safe_proxy, extra_cache.get_filters), "dataset": partial(safe_proxy, dataset_macro), } ) class NoOpTemplateProcessor(BaseTemplateProcessor): def process_template(self, sql: str, **kwargs: Any) -> str: """ Makes processing a template a noop """ return sql class PrestoTemplateProcessor(JinjaTemplateProcessor): """Presto Jinja context The methods described here are namespaced under ``presto`` in the jinja context as in ``SELECT '{{ presto.some_macro_call() }}'`` """ engine = "presto" def set_context(self, **kwargs: Any) -> None: super().set_context(**kwargs) self._context[self.engine] = { "first_latest_partition": partial(safe_proxy, self.first_latest_partition), "latest_partitions": partial(safe_proxy, self.latest_partitions), "latest_sub_partition": partial(safe_proxy, self.latest_sub_partition), "latest_partition": partial(safe_proxy, self.latest_partition), } @staticmethod def _schema_table( table_name: str, schema: Optional[str] ) -> Tuple[str, Optional[str]]: if "." in table_name: schema, table_name = table_name.split(".") return table_name, schema def first_latest_partition(self, table_name: str) -> Optional[str]: """ Gets the first value in the array of all latest partitions :param table_name: table name in the format `schema.table` :return: the first (or only) value in the latest partition array :raises IndexError: If no partition exists """ latest_partitions = self.latest_partitions(table_name) return latest_partitions[0] if latest_partitions else None def latest_partitions(self, table_name: str) -> Optional[List[str]]: """ Gets the array of all latest partitions :param table_name: table name in the format `schema.table` :return: the latest partition array """ # pylint: disable=import-outside-toplevel from superset.db_engine_specs.presto import PrestoEngineSpec table_name, schema = self._schema_table(table_name, self._schema) return cast(PrestoEngineSpec, self._database.db_engine_spec).latest_partition( table_name, schema, self._database )[1] def latest_sub_partition(self, table_name: str, **kwargs: Any) -> Any: table_name, schema = self._schema_table(table_name, self._schema) # pylint: disable=import-outside-toplevel from superset.db_engine_specs.presto import PrestoEngineSpec return cast( PrestoEngineSpec, self._database.db_engine_spec ).latest_sub_partition( table_name=table_name, schema=schema, database=self._database, **kwargs ) latest_partition = first_latest_partition class HiveTemplateProcessor(PrestoTemplateProcessor): engine = "hive" class TrinoTemplateProcessor(PrestoTemplateProcessor): engine = "trino" def process_template(self, sql: str, **kwargs: Any) -> str: template = self._env.from_string(sql) kwargs.update(self._context) # Backwards compatibility if migrating from Presto. context = validate_template_context(self.engine, kwargs) context["presto"] = context["trino"] return template.render(context) DEFAULT_PROCESSORS = { "presto": PrestoTemplateProcessor, "hive": HiveTemplateProcessor, "trino": TrinoTemplateProcessor, } @memoized def get_template_processors() -> Dict[str, Any]: processors = current_app.config.get("CUSTOM_TEMPLATE_PROCESSORS", {}) for engine, processor in DEFAULT_PROCESSORS.items(): # do not overwrite engine-specific CUSTOM_TEMPLATE_PROCESSORS if not engine in processors: processors[engine] = processor return processors def get_template_processor( database: "Database", table: Optional["SqlaTable"] = None, query: Optional["Query"] = None, **kwargs: Any, ) -> BaseTemplateProcessor: if feature_flag_manager.is_feature_enabled("ENABLE_TEMPLATE_PROCESSING"): template_processor = get_template_processors().get( database.backend, JinjaTemplateProcessor ) else: template_processor = NoOpTemplateProcessor return template_processor(database=database, table=table, query=query, **kwargs) def dataset_macro( dataset_id: int, include_metrics: bool = False, columns: Optional[List[str]] = None, ) -> str: """ Given a dataset ID, return the SQL that represents it. The generated SQL includes all columns (including computed) by default. Optionally the user can also request metrics to be included, and columns to group by. """ # pylint: disable=import-outside-toplevel from superset.datasets.dao import DatasetDAO dataset = DatasetDAO.find_by_id(dataset_id) if not dataset: raise DatasetNotFoundError(f"Dataset {dataset_id} not found!") columns = columns or [column.column_name for column in dataset.columns] metrics = [metric.metric_name for metric in dataset.metrics] query_obj = { "is_timeseries": False, "filter": [], "metrics": metrics if include_metrics else None, "columns": columns, } sqla_query = dataset.get_query_str_extended(query_obj) sql = sqla_query.sql return f"({sql}) AS dataset_{dataset_id}"