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128 lines (98 loc) · 4.11 KB
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# Copyright 2025 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import dataclasses
import typing
import pandas as pd
import pyarrow as pa
from bigframes import dtypes
from bigframes.operations import base_ops
import bigframes.operations.type as op_typing
date_op = base_ops.create_unary_op(
name="date",
type_signature=op_typing.FixedOutputType(
dtypes.is_date_like, dtypes.DATE_DTYPE, description="date-like"
),
)
time_op = base_ops.create_unary_op(
name="time",
type_signature=op_typing.FixedOutputType(
dtypes.is_time_like, dtypes.TIME_DTYPE, description="time-like"
),
)
@dataclasses.dataclass(frozen=True)
class ToDatetimeOp(base_ops.UnaryOp):
name: typing.ClassVar[str] = "to_datetime"
format: typing.Optional[str] = None
unit: typing.Optional[str] = None
def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionType:
if input_types[0] not in (
dtypes.FLOAT_DTYPE,
dtypes.INT_DTYPE,
dtypes.STRING_DTYPE,
):
raise TypeError("expected string or numeric input")
return pd.ArrowDtype(pa.timestamp("us", tz=None))
@dataclasses.dataclass(frozen=True)
class ToTimestampOp(base_ops.UnaryOp):
name: typing.ClassVar[str] = "to_timestamp"
format: typing.Optional[str] = None
unit: typing.Optional[str] = None
def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionType:
# Must be numeric or string
if input_types[0] not in (
dtypes.FLOAT_DTYPE,
dtypes.INT_DTYPE,
dtypes.STRING_DTYPE,
):
raise TypeError("expected string or numeric input")
return pd.ArrowDtype(pa.timestamp("us", tz="UTC"))
@dataclasses.dataclass(frozen=True)
class StrftimeOp(base_ops.UnaryOp):
name: typing.ClassVar[str] = "strftime"
date_format: str
def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionType:
return dtypes.STRING_DTYPE
@dataclasses.dataclass(frozen=True)
class UnixSeconds(base_ops.UnaryOp):
name: typing.ClassVar[str] = "unix_seconds"
def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionType:
if input_types[0] is not dtypes.TIMESTAMP_DTYPE:
raise TypeError("expected timestamp input")
return dtypes.INT_DTYPE
@dataclasses.dataclass(frozen=True)
class UnixMillis(base_ops.UnaryOp):
name: typing.ClassVar[str] = "unix_millis"
def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionType:
if input_types[0] is not dtypes.TIMESTAMP_DTYPE:
raise TypeError("expected timestamp input")
return dtypes.INT_DTYPE
@dataclasses.dataclass(frozen=True)
class UnixMicros(base_ops.UnaryOp):
name: typing.ClassVar[str] = "unix_micros"
def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionType:
if input_types[0] is not dtypes.TIMESTAMP_DTYPE:
raise TypeError("expected timestamp input")
return dtypes.INT_DTYPE
@dataclasses.dataclass(frozen=True)
class TimestampDiff(base_ops.BinaryOp):
name: typing.ClassVar[str] = "timestamp_diff"
def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionType:
if input_types[0] is not input_types[1]:
raise TypeError(
f"two inputs have different types. left: {input_types[0]}, right: {input_types[1]}"
)
if not dtypes.is_datetime_like(input_types[0]):
raise TypeError("expected timestamp input")
return dtypes.TIMEDELTA_DTYPE
timestamp_diff_op = TimestampDiff()