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Update datetime filter #396

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1 change: 1 addition & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.

### Changed

- Improved datetime query handling to only check start and end datetime values when datetime is None [#396](https://github.com/stac-utils/stac-fastapi-elasticsearch-opensearch/pull/396)
- Optimize data_loader.py script [#395](https://github.com/stac-utils/stac-fastapi-elasticsearch-opensearch/pull/395)

### Removed
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186 changes: 81 additions & 105 deletions stac_fastapi/elasticsearch/stac_fastapi/elasticsearch/database_logic.py
Original file line number Diff line number Diff line change
Expand Up @@ -245,121 +245,97 @@ def apply_collections_filter(search: Search, collection_ids: List[str]):
@staticmethod
def apply_datetime_filter(
search: Search, interval: Optional[Union[DateTimeType, str]]
):
) -> Search:
"""Apply a filter to search on datetime, start_datetime, and end_datetime fields.

Args:
search (Search): The search object to filter.
interval: Optional[Union[DateTimeType, str]]
search: The search object to filter.
interval: Optional datetime interval to filter by. Can be:
- A single datetime string (e.g., "2023-01-01T12:00:00")
- A datetime range string (e.g., "2023-01-01/2023-12-31")
- A datetime object
- A tuple of (start_datetime, end_datetime)

Returns:
Search: The filtered search object.
The filtered search object.
"""
if not interval:
return search

should = []
datetime_search = return_date(interval)
try:
datetime_search = return_date(interval)
except (ValueError, TypeError) as e:
# Handle invalid interval formats if return_date fails
logger.error(f"Invalid interval format: {interval}, error: {e}")
return search

# If the request is a single datetime return
# items with datetimes equal to the requested datetime OR
# the requested datetime is between their start and end datetimes
if "eq" in datetime_search:
should.extend(
[
Q(
"bool",
filter=[
Q(
"term",
properties__datetime=datetime_search["eq"],
),
],
),
Q(
"bool",
filter=[
Q(
"range",
properties__start_datetime={
"lte": datetime_search["eq"],
},
),
Q(
"range",
properties__end_datetime={
"gte": datetime_search["eq"],
},
),
],
),
]
)

# If the request is a date range return
# items with datetimes within the requested date range OR
# their startdatetime ithin the requested date range OR
# their enddatetime ithin the requested date range OR
# the requested daterange within their start and end datetimes
# For exact matches, include:
# 1. Items with matching exact datetime
# 2. Items with datetime:null where the time falls within their range
should = [
Q(
"bool",
filter=[
Q("exists", field="properties.datetime"),
Q("term", **{"properties__datetime": datetime_search["eq"]}),
],
),
Q(
"bool",
must_not=[Q("exists", field="properties.datetime")],
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The current best practices recommends that you populate datetime even if you have a date range.

"The specification does allow one to set the datetime field to null, but it is strongly recommended to populate the single datetime field, as that is what many clients will search on. If it is at all possible to pick a nominal or representative datetime then that should be used."

So we should probably loosen the search (remove this line?) or update the recommended practice.

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I don't know. I think the best practices are recommended but may not always be relevant for all types of data.

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@rhysrevans3 Can you look at this issue #396? I am not 100% sure on what the right approach should be.

filter=[
Q("exists", field="properties.start_datetime"),
Q("exists", field="properties.end_datetime"),
Q(
"range",
properties__start_datetime={"lte": datetime_search["eq"]},
),
Q(
"range",
properties__end_datetime={"gte": datetime_search["eq"]},
),
],
),
]
else:
should.extend(
[
Q(
"bool",
filter=[
Q(
"range",
properties__datetime={
"gte": datetime_search["gte"],
"lte": datetime_search["lte"],
},
),
],
),
Q(
"bool",
filter=[
Q(
"range",
properties__start_datetime={
"gte": datetime_search["gte"],
"lte": datetime_search["lte"],
},
),
],
),
Q(
"bool",
filter=[
Q(
"range",
properties__end_datetime={
"gte": datetime_search["gte"],
"lte": datetime_search["lte"],
},
),
],
),
Q(
"bool",
filter=[
Q(
"range",
properties__start_datetime={
"lte": datetime_search["gte"]
},
),
Q(
"range",
properties__end_datetime={
"gte": datetime_search["lte"]
},
),
],
),
]
)

search = search.query(Q("bool", filter=[Q("bool", should=should)]))

return search
# For date ranges, include:
# 1. Items with datetime in the range
# 2. Items with datetime:null that overlap the search range
should = [
Q(
"bool",
filter=[
Q("exists", field="properties.datetime"),
Q(
"range",
properties__datetime={
"gte": datetime_search["gte"],
"lte": datetime_search["lte"],
},
),
],
),
Q(
"bool",
must_not=[Q("exists", field="properties.datetime")],
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@rhysrevans3 rhysrevans3 Jun 9, 2025

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Same as below.

filter=[
Q("exists", field="properties.start_datetime"),
Q("exists", field="properties.end_datetime"),
Q(
"range",
properties__start_datetime={"lte": datetime_search["lte"]},
),
Q(
"range",
properties__end_datetime={"gte": datetime_search["gte"]},
),
],
Comment on lines +323 to +334
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Is this enough to give all possible combinations of datetime overlap? This looks like it will only return items whose date range entirely encapsulates the searched for date range.

),
]

return search.query(Q("bool", should=should, minimum_should_match=1))

@staticmethod
def apply_bbox_filter(search: Search, bbox: List):
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