Files
2026-10-15 20:36:59 +08:00

262 lines
7.1 KiB
Python

from typing import Iterable, Union
from .aggregation import Asc, Desc, Reducer, SortDirection
def _ensure_at_prefix(name: str) -> str:
"""Return ``name`` with a single leading ``@`` prefix."""
return name if name.startswith("@") else "@" + name
class FieldOnlyReducer(Reducer):
"""See https://redis.io/docs/interact/search-and-query/search/aggregations/"""
def __init__(self, field: str) -> None:
super().__init__(field)
self._field = field
class count(Reducer):
"""
Counts the number of results in the group
"""
NAME = "COUNT"
def __init__(self) -> None:
super().__init__()
class sum(FieldOnlyReducer):
"""
Calculates the sum of all the values in the given fields within the group
"""
NAME = "SUM"
def __init__(self, field: str) -> None:
super().__init__(field)
class min(FieldOnlyReducer):
"""
Calculates the smallest value in the given field within the group
"""
NAME = "MIN"
def __init__(self, field: str) -> None:
super().__init__(field)
class max(FieldOnlyReducer):
"""
Calculates the largest value in the given field within the group
"""
NAME = "MAX"
def __init__(self, field: str) -> None:
super().__init__(field)
class avg(FieldOnlyReducer):
"""
Calculates the mean value in the given field within the group
"""
NAME = "AVG"
def __init__(self, field: str) -> None:
super().__init__(field)
class tolist(FieldOnlyReducer):
"""
Returns all the matched properties in a list
"""
NAME = "TOLIST"
def __init__(self, field: str) -> None:
super().__init__(field)
class count_distinct(FieldOnlyReducer):
"""
Calculate the number of distinct values contained in all the results in
the group for the given field
"""
NAME = "COUNT_DISTINCT"
def __init__(self, field: str) -> None:
super().__init__(field)
class count_distinctish(FieldOnlyReducer):
"""
Calculate the number of distinct values contained in all the results in the
group for the given field. This uses a faster algorithm than
`count_distinct` but is less accurate
"""
NAME = "COUNT_DISTINCTISH"
class quantile(Reducer):
"""
Return the value for the nth percentile within the range of values for the
field within the group.
"""
NAME = "QUANTILE"
def __init__(self, field: str, pct: float) -> None:
super().__init__(field, str(pct))
self._field = field
class stddev(FieldOnlyReducer):
"""
Return the standard deviation for the values within the group
"""
NAME = "STDDEV"
def __init__(self, field: str) -> None:
super().__init__(field)
class first_value(Reducer):
"""
Selects the first value within the group according to sorting parameters
"""
NAME = "FIRST_VALUE"
def __init__(self, field: str, *byfields: Union[Asc, Desc]) -> None:
"""
Selects the first value of the given field within the group.
### Parameter
- **field**: Source field used for the value
- **byfields**: How to sort the results. This can be either the
*class* of `aggregation.Asc` or `aggregation.Desc` in which
case the field `field` is also used as the sort input.
`byfields` can also be one or more *instances* of `Asc` or `Desc`
indicating the sort order for these fields
"""
fieldstrs = []
if (
len(byfields) == 1
and isinstance(byfields[0], type)
and issubclass(byfields[0], SortDirection)
):
byfields = [byfields[0](field)]
for f in byfields:
fieldstrs += [f.field, f.DIRSTRING]
args = [field]
if fieldstrs:
args += ["BY"] + fieldstrs
super().__init__(*args)
self._field = field
class random_sample(Reducer):
"""
Returns a random sample of items from the dataset, from the given property
"""
NAME = "RANDOM_SAMPLE"
def __init__(self, field: str, size: int) -> None:
"""
### Parameter
**field**: Field to sample from
**size**: Return this many items (can be less)
"""
args = [field, str(size)]
super().__init__(*args)
self._field = field
class collect(Reducer):
"""
Gathers the rows of each ``GROUPBY`` group, projects a chosen set of
fields from every row, optionally deduplicates, sorts, and limits them,
and returns them as an array of per-entry maps under the reducer alias.
``COLLECT`` is a preview feature gated behind
``search-enable-unstable-features``. See
`FT.AGGREGATE <https://redis.io/commands/ft.aggregate>`_.
"""
NAME = "COLLECT"
def __init__(
self,
fields: str | Iterable[str] = "*",
distinct: bool = False,
sort_by: Asc | Desc | Iterable[Asc | Desc] | None = None,
limit: tuple[int, int] | None = None,
) -> None:
"""
### Parameters
- **fields**: The fields to project from each collected row. Either the
literal ``"*"`` (project every field present in the pipeline at this
stage) or a field name / iterable of field names. Names are
normalized to a single leading ``@`` on the wire; output map keys
are the bare names.
- **distinct**: When ``True``, emit ``DISTINCT`` to deduplicate entries
with identical projected fields. Forward-compatible: this option is
not yet implemented by the server and currently produces a server
error when sent.
- **sort_by**: An ``Asc``/``Desc`` instance or an iterable of them, used
to order the collected entries within each group.
- **limit**: An ``(offset, count)`` pair. Returns at most ``count``
entries per group after skipping ``offset``. With ``sort_by`` this
acts as a top-N selection.
"""
args: list[str] = []
# FIELDS (required)
if fields == "*":
args += ["FIELDS", "*"]
else:
names = [fields] if isinstance(fields, str) else list(fields)
if not names or any(not n.strip() for n in names):
raise ValueError(
"collect fields must be '*' or a non-empty list of names"
)
names = [_ensure_at_prefix(n) for n in names]
args += ["FIELDS", str(len(names))] + names
# DISTINCT (optional)
if distinct:
args += ["DISTINCT"]
# SORTBY (optional)
if sort_by is not None:
sort_fields = [sort_by] if isinstance(sort_by, (Asc, Desc)) else sort_by
sort_args: list[str] = []
for f in sort_fields:
sort_args += [_ensure_at_prefix(f.field), f.DIRSTRING]
if not sort_args:
raise ValueError("collect sort_by must contain at least one field")
args += ["SORTBY", str(len(sort_args))] + sort_args
# LIMIT (optional)
if limit is not None:
offset, count = limit
args += ["LIMIT", str(offset), str(count)]
super().__init__(*args)