googleapis · sycai · Jan 21, 2025 · Jan 16, 2025 · Jan 16, 2025 · Jan 17, 2025
@@ -22,6 +22,11 @@
     array_length,
     array_to_string,
 )
+from bigframes.bigquery._operations.datetime import (
+    unix_micros,
+    unix_millis,
+    unix_seconds,
+)
 from bigframes.bigquery._operations.json import (
     json_extract,
     json_extract_array,
@@ -53,4 +58,8 @@
     "sql_scalar",
     # struct ops
     "struct",
+    # datetime ops
+    "unix_micros",
+    "unix_millis",
+    "unix_seconds",
 ]
@@ -0,0 +1,97 @@
+# 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.
+
+from bigframes import operations as ops
+from bigframes import series
+
+
+def unix_seconds(input: series.Series) -> series.Series:
+    """Converts a timestmap series to unix epoch seconds
+
+    **Examples:**
+
+        >>> import pandas as pd
+        >>> import bigframes.pandas as bpd
+        >>> import bigframes.bigquery as bbq
+        >>> bpd.options.display.progress_bar = None
+
+        >>> s = bpd.Series([pd.Timestamp("1970-01-02", tz="UTC"), pd.Timestamp("1970-01-03", tz="UTC")])
+        >>> bbq.unix_seconds(s)
+        0     86400
+        1    172800
+        dtype: Int64
+
+    Args:
+        input (bigframes.pandas.Series):
+            A timestamp series.
+
+    Returns:
+        bigframes.pandas.Series: A new series of unix epoch in seconds.
+
+    """
+    return input._apply_unary_op(ops.UnixSeconds())
+
+
+def unix_millis(input: series.Series) -> series.Series:
+    """Converts a timestmap series to unix epoch milliseconds
+
+    **Examples:**
+
+        >>> import pandas as pd
+        >>> import bigframes.pandas as bpd
+        >>> import bigframes.bigquery as bbq
+        >>> bpd.options.display.progress_bar = None
+
+        >>> s = bpd.Series([pd.Timestamp("1970-01-02", tz="UTC"), pd.Timestamp("1970-01-03", tz="UTC")])
+        >>> bbq.unix_millis(s)
+        0     86400000
+        1    172800000
+        dtype: Int64
+
+    Args:
+        input (bigframes.pandas.Series):
+            A timestamp series.
+
+    Returns:
+        bigframes.pandas.Series: A new series of unix epoch in milliseconds.
+
+    """
+    return input._apply_unary_op(ops.UnixMillis())
+
+
+def unix_micros(input: series.Series) -> series.Series:
+    """Converts a timestmap series to unix epoch microseconds
+
+    **Examples:**
+
+        >>> import pandas as pd
+        >>> import bigframes.pandas as bpd
+        >>> import bigframes.bigquery as bbq
+        >>> bpd.options.display.progress_bar = None
+
+        >>> s = bpd.Series([pd.Timestamp("1970-01-02", tz="UTC"), pd.Timestamp("1970-01-03", tz="UTC")])
+        >>> bbq.unix_micros(s)
+        0     86400000000
+        1    172800000000
+        dtype: Int64
+
+    Args:
+        input (bigframes.pandas.Series):
+            A timestamp series.
+
+    Returns:
+        bigframes.pandas.Series: A new series of unix epoch in microseconds.
+
+    """
+    return input._apply_unary_op(ops.UnixMicros())
@@ -722,6 +722,21 @@ def strftime_op_impl(x: ibis_types.Value, op: ops.StrftimeOp):
     )
 
 
+@scalar_op_compiler.register_unary_op(ops.UnixSeconds)
+def unix_seconds_op_impl(x: ibis_types.TimestampValue):
+    return x.epoch_seconds()
+
+
+@scalar_op_compiler.register_unary_op(ops.UnixMicros)
+def unix_micros_op_impl(x: ibis_types.TimestampValue):
+    return unix_micros(x)
+
+
+@scalar_op_compiler.register_unary_op(ops.UnixMillis)
+def unix_millis_op_impl(x: ibis_types.TimestampValue):
+    return unix_millis(x)
+
+
 @scalar_op_compiler.register_unary_op(ops.FloorDtOp, pass_op=True)
 def floor_dt_op_impl(x: ibis_types.Value, op: ops.FloorDtOp):
     supported_freqs = ["Y", "Q", "M", "W", "D", "h", "min", "s", "ms", "us", "ns"]
@@ -1887,6 +1902,16 @@ def timestamp(a: str) -> ibis_dtypes.timestamp:  # type: ignore
     """Convert string to timestamp."""
 
 
+@ibis_udf.scalar.builtin
+def unix_millis(a: ibis_dtypes.timestamp) -> int:  # type: ignore
+    """Convert a timestamp to milliseconds"""
+
+
+@ibis_udf.scalar.builtin
+def unix_micros(a: ibis_dtypes.timestamp) -> int:  # type: ignore
+    """Convert a timestamp to microseconds"""
+
+
 # Need these because ibis otherwise tries to do casts to int that can fail
 @ibis_udf.scalar.builtin(name="floor")
 def float_floor(a: float) -> float:

@@ -51,6 +51,9 @@
     time_op,
     ToDatetimeOp,
     ToTimestampOp,
+    UnixMicros,
+    UnixMillis,
+    UnixSeconds,
 )
 from bigframes.operations.distance_ops import (
     cosine_distance_op,
@@ -243,6 +246,9 @@
     "ToDatetimeOp",
     "ToTimestampOp",
     "StrftimeOp",
+    "UnixMicros",
+    "UnixMillis",
+    "UnixSeconds",
     # Numeric ops
     "abs_op",
     "add_op",

@@ -77,3 +77,27 @@ class StrftimeOp(base_ops.UnaryOp):
 
     def output_type(self, *input_types):
         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):
+        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):
+        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):
+        return dtypes.INT_DTYPE
@@ -0,0 +1,66 @@
+# 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 typing
+
+import pandas as pd
+
+from bigframes import bigquery
+
+
+def test_unix_seconds(scalars_dfs):
+    bigframes_df, pandas_df = scalars_dfs
+
+    actual_res = bigquery.unix_seconds(bigframes_df["timestamp_col"]).to_pandas()
+
+    expected_res = (
+        pandas_df["timestamp_col"]
+        .apply(lambda ts: _to_unix_epoch(ts, "s"))
+        .astype("Int64")
+    )
+    pd.testing.assert_series_equal(actual_res, expected_res)
+
+
+def test_unix_millis(scalars_dfs):
+    bigframes_df, pandas_df = scalars_dfs
+
+    actual_res = bigquery.unix_millis(bigframes_df["timestamp_col"]).to_pandas()
+
+    expected_res = (
+        pandas_df["timestamp_col"]
+        .apply(lambda ts: _to_unix_epoch(ts, "ms"))
+        .astype("Int64")
+    )
+    pd.testing.assert_series_equal(actual_res, expected_res)
+
+
+def test_unix_micros(scalars_dfs):
+    bigframes_df, pandas_df = scalars_dfs
+
+    actual_res = bigquery.unix_micros(bigframes_df["timestamp_col"]).to_pandas()
+
+    expected_res = (
+        pandas_df["timestamp_col"]
+        .apply(lambda ts: _to_unix_epoch(ts, "us"))
+        .astype("Int64")
+    )
+    pd.testing.assert_series_equal(actual_res, expected_res)
+
+
+def _to_unix_epoch(
+    ts: pd.Timestamp, unit: typing.Literal["s", "ms", "us"]
+) -> typing.Optional[int]:
+    if pd.isna(ts):
+        return None
+    return (ts - pd.Timestamp("1970-01-01", tz="UTC")) // pd.Timedelta(1, unit)