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