67 lines
1.7 KiB
Python
67 lines
1.7 KiB
Python
from pypika.functions import *
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from pypika.terms import Function, CustomFunction, ArithmeticExpression, Arithmetic
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from frappe.query_builder.utils import ImportMapper, db_type_is
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from frappe.query_builder.custom import GROUP_CONCAT, STRING_AGG, MATCH, TO_TSVECTOR
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from frappe.database.query import Query
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from .utils import Column
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class Concat_ws(Function):
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def __init__(self, *terms, **kwargs):
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super(Concat_ws, self).__init__("CONCAT_WS", *terms, **kwargs)
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GroupConcat = ImportMapper(
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{
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db_type_is.MARIADB: GROUP_CONCAT,
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db_type_is.POSTGRES: STRING_AGG
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}
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)
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Match = ImportMapper(
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{
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db_type_is.MARIADB: MATCH,
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db_type_is.POSTGRES: TO_TSVECTOR
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}
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)
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class _PostgresTimestamp(ArithmeticExpression):
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def __init__(self, datepart, timepart, alias=None):
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if isinstance(datepart, str):
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datepart = Cast(datepart, "date")
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if isinstance(timepart, str):
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timepart = Cast(timepart, "time")
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super().__init__(operator=Arithmetic.add,
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left=datepart, right=timepart, alias=alias)
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CombineDatetime = ImportMapper(
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{
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db_type_is.MARIADB: CustomFunction("TIMESTAMP", ["date", "time"]),
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db_type_is.POSTGRES: _PostgresTimestamp,
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}
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)
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def _aggregate(function, dt, fieldname, filters, **kwargs):
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return (
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Query()
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.build_conditions(dt, filters)
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.select(function(Column(fieldname)))
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.run(**kwargs)[0][0]
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or 0
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)
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def _max(dt, fieldname, filters=None, **kwargs):
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return _aggregate(Max, dt, fieldname, filters, **kwargs)
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def _min(dt, fieldname, filters=None, **kwargs):
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return _aggregate(Min, dt, fieldname, filters, **kwargs)
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def _avg(dt, fieldname, filters=None, **kwargs):
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return _aggregate(Avg, dt, fieldname, filters, **kwargs)
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def _sum(dt, fieldname, filters=None, **kwargs):
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return _aggregate(Sum, dt, fieldname, filters, **kwargs)
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