(superset) branch master updated: feat(explore): dataset macro: dttm filter context (#25950)

[jo...@apache.org]

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johnbodley pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/superset.git


The following commit(s) were added to refs/heads/master by this push:
     new f6ba75a185 feat(explore): dataset macro: dttm filter context (#25950)
f6ba75a185 is described below

commit f6ba75a1859b89b196bb09970d0b6f8cafd6ee99
Author: Rob Moore <gi...@users.noreply.github.com>
AuthorDate: Tue Nov 14 17:16:42 2023 +0000

    feat(explore): dataset macro: dttm filter context (#25950)
---
 superset/jinja_context.py | 42 +++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 41 insertions(+), 1 deletion(-)

diff --git a/superset/jinja_context.py b/superset/jinja_context.py
index c159a667ee..13a639df7b 100644
--- a/superset/jinja_context.py
+++ b/superset/jinja_context.py
@@ -17,9 +17,11 @@
 """Defines the templating context for SQL Lab"""
 import json
 import re
+from datetime import datetime
 from functools import lru_cache, partial
 from typing import Any, Callable, cast, Optional, TYPE_CHECKING, TypedDict, Union
 
+import dateutil
 from flask import current_app, g, has_request_context, request
 from flask_babel import gettext as _
 from jinja2 import DebugUndefined
@@ -486,6 +488,19 @@ class BaseTemplateProcessor:
 
 
 class JinjaTemplateProcessor(BaseTemplateProcessor):
+    def _parse_datetime(self, dttm: str) -> Optional[datetime]:
+        """
+        Try to parse a datetime and default to None in the worst case.
+
+        Since this may have been rendered by different engines, the datetime may
+        vary slightly in format. We try to make it consistent, and if all else
+        fails, just return None.
+        """
+        try:
+            return dateutil.parser.parse(dttm)
+        except dateutil.parser.ParserError:
+            return None
+
     def set_context(self, **kwargs: Any) -> None:
         super().set_context(**kwargs)
         extra_cache = ExtraCache(
@@ -494,6 +509,23 @@ class JinjaTemplateProcessor(BaseTemplateProcessor):
             removed_filters=self._removed_filters,
             dialect=self._database.get_dialect(),
         )
+
+        from_dttm = (
+            self._parse_datetime(dttm)
+            if (dttm := self._context.get("from_dttm"))
+            else None
+        )
+        to_dttm = (
+            self._parse_datetime(dttm)
+            if (dttm := self._context.get("to_dttm"))
+            else None
+        )
+
+        dataset_macro_with_context = partial(
+            dataset_macro,
+            from_dttm=from_dttm,
+            to_dttm=to_dttm,
+        )
         self._context.update(
             {
                 "url_param": partial(safe_proxy, extra_cache.url_param),
@@ -502,7 +534,7 @@ class JinjaTemplateProcessor(BaseTemplateProcessor):
                 "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),
+                "dataset": partial(safe_proxy, dataset_macro_with_context),
             }
         )
 
@@ -638,12 +670,18 @@ def dataset_macro(
     dataset_id: int,
     include_metrics: bool = False,
     columns: Optional[list[str]] = None,
+    from_dttm: Optional[datetime] = None,
+    to_dttm: Optional[datetime] = 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.
+
+    The from_dttm and to_dttm parameters are filled in from filter values in explore
+    views, and we take them to make those properties available to jinja templates in
+    the underlying dataset.
     """
     # pylint: disable=import-outside-toplevel
     from superset.daos.dataset import DatasetDAO
@@ -659,6 +697,8 @@ def dataset_macro(
         "filter": [],
         "metrics": metrics if include_metrics else None,
         "columns": columns,
+        "from_dttm": from_dttm,
+        "to_dttm": to_dttm,
     }
     sqla_query = dataset.get_query_str_extended(query_obj, mutate=False)
     sql = sqla_query.sql