# Copyright 2024 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

from typing import Mapping, Optional, Union

import weakref

import polars

import bigframes

import bigframes.clients

import bigframes.core.blocks

import bigframes.core.compile.polars

import bigframes.core.ordering

import bigframes.dataframe

import bigframes.session.clients

import bigframes.session.executor

import bigframes.session.metrics

# Does not support to_sql, export_gbq, export_gcs, dry_run, peek, head, get_row_count, cached

@dataclasses.dataclass

class TestExecutor(bigframes.session.executor.Executor):

compiler = bigframes.core.compile.polars.PolarsCompiler()

def execute(

self,

array_value: bigframes.core.ArrayValue,

*,

ordered: bool = True,

col_id_overrides: Mapping[str, str] = {},

use_explicit_destination: bool = False,

get_size_bytes: bool = False,

page_size: Optional[int] = None,

max_results: Optional[int] = None,

):

"""

Execute the ArrayValue, storing the result to a temporary session-owned table.

"""

lazy_frame: polars.LazyFrame = self.compiler.compile(array_value)

pa_table = lazy_frame.collect().to_arrow()

# Currently, pyarrow types might not quite be exactly the ones in the bigframes schema.

# Nullability may be different, and might use large versions of list, string datatypes.

return bigframes.session.executor.ExecuteResult(

arrow_batches=lambda: pa_table.to_batches(),

schema=array_value.schema,

total_bytes=pa_table.nbytes,

total_rows=pa_table.num_rows,

)

class TestSession(bigframes.session.Session):

def __init__(self):

self._location = None # type: ignore

self._bq_kms_key_name = None # type: ignore

self._clients_provider = None # type: ignore

self.ibis_client = None # type: ignore

self._bq_connection = None # type: ignore

self._skip_bq_connection_check = True

self._session_id: str = "test_session"

self._objects: list[

weakref.ReferenceType[

Union[

bigframes.core.indexes.Index,

bigframes.series.Series,

bigframes.dataframe.DataFrame,

]

]

] = []

self._strictly_ordered: bool = True

self._allow_ambiguity = False # type: ignore

self._default_index_type = bigframes.enums.DefaultIndexKind.SEQUENTIAL_INT64

self._metrics = bigframes.session.metrics.ExecutionMetrics()

self._remote_function_session = None # type: ignore

self._temp_storage_manager = None # type: ignore

self._executor = TestExecutor()

self._loader = None # type: ignore

def read_pandas(self, pandas_dataframe):

# override read_pandas to always keep data local-only

local_block = bigframes.core.blocks.Block.from_local(pandas_dataframe, self)

return bigframes.dataframe.DataFrame(local_block)