slyons commented on code in PR #750: URL: https://github.com/apache/datafusion-python/pull/750#discussion_r1671038077
########## python/datafusion/context.py: ########## @@ -0,0 +1,1167 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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 __future__ import annotations + +from ._internal import SessionConfig as SessionConfigInternal +from ._internal import RuntimeConfig as RuntimeConfigInternal +from ._internal import SQLOptions as SQLOptionsInternal +from ._internal import SessionContext as SessionContextInternal +from ._internal import LogicalPlan, ExecutionPlan # TODO MAKE THIS A DEFINED CLASS + +from datafusion._internal import AggregateUDF +from datafusion.catalog import Catalog, Table +from datafusion.dataframe import DataFrame +from datafusion.expr import Expr +from datafusion.record_batch import RecordBatchStream +from datafusion.udf import ScalarUDF + +from typing import Any, TYPE_CHECKING +from typing_extensions import deprecated + +if TYPE_CHECKING: + import pyarrow + import pandas + import polars + + +class SessionConfig: + def __init__(self, config_options: dict[str, str] = {}) -> None: + """Create a new `SessionConfig` with the given configuration options. + + Parameters + ---------- + config_options : dict[str, str] + Configuration options. + """ + self.config_internal = SessionConfigInternal(config_options) + + def with_create_default_catalog_and_schema( + self, enabled: bool = True + ) -> SessionConfig: + """Control whether the default catalog and schema will be automatically created. + + Parameters + ---------- + enabled : bool + Whether the default catalog and schema will be automatically created. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = ( + self.config_internal.with_create_default_catalog_and_schema(enabled) + ) + return self + + def with_default_catalog_and_schema( + self, catalog: str, schema: str + ) -> SessionConfig: + """Select a name for the default catalog and shcema. + + Parameters + ---------- + catalog : str + Catalog name. + schema : str + Schema name. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_default_catalog_and_schema( + catalog, schema + ) + return self + + def with_information_schema(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the inclusion of `information_schema` virtual tables. + + Parameters + ---------- + enabled : bool + Whether to include `information_schema` virtual tables. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_information_schema(enabled) + return self + + def with_batch_size(self, batch_size: int) -> SessionConfig: + """Customize batch size. + + Parameters + ---------- + batch_size : int + Batch size. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_batch_size(batch_size) + return self + + def with_target_partitions(self, target_partitions: int) -> SessionConfig: + """Customize the number of target partitions for query execution. + + Increasing partitions can increase concurrency. + + Parameters + ---------- + target_partitions : int + Number of target partitions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_target_partitions( + target_partitions + ) + return self + + def with_repartition_aggregations(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for aggregations. + + Enabling this improves parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for aggregations. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_aggregations( + enabled + ) + return self + + def with_repartition_joins(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for joins to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for joins. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_joins(enabled) + return self + + def with_repartition_windows(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for window functions to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for window functions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_windows(enabled) + return self + + def with_repartition_sorts(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for window functions to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for window functions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_sorts(enabled) + return self + + def with_repartition_file_scans(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for file scans. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for file scans. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_file_scans(enabled) + return self + + def with_repartition_file_min_size(self, size: int) -> SessionConfig: + """Set minimum file range size for repartitioning scans. + + Parameters + ---------- + size : int + Minimum file range size. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_file_min_size(size) + return self + + def with_parquet_pruning(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of pruning predicate for parquet readers to skip row groups. + + Parameters + ---------- + enabled : bool + Whether to use pruning predicate for parquet readers. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_parquet_pruning(enabled) + return self + + def set(self, key: str, value: str) -> SessionConfig: + """Set a configuration option. + + Parameters + ---------- + key : str + Option key. + value : str + Option value. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.set(key, value) + return self + + +class RuntimeConfig: + def __init__(self) -> None: + """Create a new `RuntimeConfig` with default values.""" + self.config_internal = RuntimeConfigInternal() + + def with_disk_manager_disabled(self) -> RuntimeConfig: + """Disable the disk manager, attempts to create temporary files will error. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_disabled() + """ + self.config_internal = self.config_internal.with_disk_manager_disabled() + return self + + def with_disk_manager_os(self) -> RuntimeConfig: + """Use the operating system's temporary directory for disk manager. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_os() + """ + self.config_internal = self.config_internal.with_disk_manager_os() + return self + + def with_disk_manager_specified(self, paths: list[str]) -> RuntimeConfig: + """Use the specified paths for the disk manager's temporary files. + + Parameters + ---------- + paths : list[str] + Paths to use for the disk manager's temporary files. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_specified(["/tmp"]) + """ + self.config_internal = self.config_internal.with_disk_manager_specified(paths) + return self + + def with_unbounded_memory_pool(self) -> RuntimeConfig: + """Use an unbounded memory pool. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_unbounded_memory_pool() + """ + self.config_internal = self.config_internal.with_unbounded_memory_pool() + return self + + def with_fair_spill_pool(self, size: int) -> RuntimeConfig: + """Use a fair spill pool with the specified size. + + This pool works best when you know beforehand the query has multiple spillable + operators that will likely all need to spill. Sometimes it will cause spills + even when there was sufficient memory (reserved for other operators) to avoid + doing so. + + ```text + ┌───────────────────────z──────────────────────z───────────────┐ + │ z z │ + │ z z │ + │ Spillable z Unspillable z Free │ + │ Memory z Memory z Memory │ + │ z z │ + │ z z │ + └───────────────────────z──────────────────────z───────────────┘ + ``` + + Parameters + ---------- + size : int + Size of the memory pool in bytes. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + ```python + >>> config = RuntimeConfig().with_fair_spill_pool(1024) + ``` + """ + self.config_internal = self.config_internal.with_fair_spill_pool(size) + return self + + def with_greedy_memory_pool(self, size: int) -> RuntimeConfig: + """Use a greedy memory pool with the specified size. + + This pool works well for queries that do not need to spill or have a single + spillable operator. See `RuntimeConfig.with_fair_spill_pool` if there are + multiple spillable operators that all will spill. + + Parameters + ---------- + size : int + Size of the memory pool in bytes. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_greedy_memory_pool(1024) + """ + self.config_internal = self.config_internal.with_greedy_memory_pool(size) + return self + + def with_temp_file_path(self, path: str) -> RuntimeConfig: Review Comment: Can we support `pathlib.Path` for this? ########## python/datafusion/context.py: ########## @@ -0,0 +1,1167 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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 __future__ import annotations + +from ._internal import SessionConfig as SessionConfigInternal +from ._internal import RuntimeConfig as RuntimeConfigInternal +from ._internal import SQLOptions as SQLOptionsInternal +from ._internal import SessionContext as SessionContextInternal +from ._internal import LogicalPlan, ExecutionPlan # TODO MAKE THIS A DEFINED CLASS + +from datafusion._internal import AggregateUDF +from datafusion.catalog import Catalog, Table +from datafusion.dataframe import DataFrame +from datafusion.expr import Expr +from datafusion.record_batch import RecordBatchStream +from datafusion.udf import ScalarUDF + +from typing import Any, TYPE_CHECKING +from typing_extensions import deprecated + +if TYPE_CHECKING: + import pyarrow + import pandas + import polars + + +class SessionConfig: + def __init__(self, config_options: dict[str, str] = {}) -> None: + """Create a new `SessionConfig` with the given configuration options. + + Parameters + ---------- + config_options : dict[str, str] + Configuration options. + """ + self.config_internal = SessionConfigInternal(config_options) + + def with_create_default_catalog_and_schema( + self, enabled: bool = True + ) -> SessionConfig: + """Control whether the default catalog and schema will be automatically created. + + Parameters + ---------- + enabled : bool + Whether the default catalog and schema will be automatically created. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = ( + self.config_internal.with_create_default_catalog_and_schema(enabled) + ) + return self + + def with_default_catalog_and_schema( + self, catalog: str, schema: str + ) -> SessionConfig: + """Select a name for the default catalog and shcema. + + Parameters + ---------- + catalog : str + Catalog name. + schema : str + Schema name. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_default_catalog_and_schema( + catalog, schema + ) + return self + + def with_information_schema(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the inclusion of `information_schema` virtual tables. + + Parameters + ---------- + enabled : bool + Whether to include `information_schema` virtual tables. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_information_schema(enabled) + return self + + def with_batch_size(self, batch_size: int) -> SessionConfig: + """Customize batch size. + + Parameters + ---------- + batch_size : int + Batch size. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_batch_size(batch_size) + return self + + def with_target_partitions(self, target_partitions: int) -> SessionConfig: + """Customize the number of target partitions for query execution. + + Increasing partitions can increase concurrency. + + Parameters + ---------- + target_partitions : int + Number of target partitions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_target_partitions( + target_partitions + ) + return self + + def with_repartition_aggregations(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for aggregations. + + Enabling this improves parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for aggregations. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_aggregations( + enabled + ) + return self + + def with_repartition_joins(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for joins to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for joins. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_joins(enabled) + return self + + def with_repartition_windows(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for window functions to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for window functions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_windows(enabled) + return self + + def with_repartition_sorts(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for window functions to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for window functions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_sorts(enabled) + return self + + def with_repartition_file_scans(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for file scans. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for file scans. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_file_scans(enabled) + return self + + def with_repartition_file_min_size(self, size: int) -> SessionConfig: + """Set minimum file range size for repartitioning scans. + + Parameters + ---------- + size : int + Minimum file range size. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_file_min_size(size) + return self + + def with_parquet_pruning(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of pruning predicate for parquet readers to skip row groups. + + Parameters + ---------- + enabled : bool + Whether to use pruning predicate for parquet readers. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_parquet_pruning(enabled) + return self + + def set(self, key: str, value: str) -> SessionConfig: + """Set a configuration option. + + Parameters + ---------- + key : str + Option key. + value : str + Option value. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.set(key, value) + return self + + +class RuntimeConfig: + def __init__(self) -> None: + """Create a new `RuntimeConfig` with default values.""" + self.config_internal = RuntimeConfigInternal() + + def with_disk_manager_disabled(self) -> RuntimeConfig: + """Disable the disk manager, attempts to create temporary files will error. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_disabled() + """ + self.config_internal = self.config_internal.with_disk_manager_disabled() + return self + + def with_disk_manager_os(self) -> RuntimeConfig: + """Use the operating system's temporary directory for disk manager. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_os() + """ + self.config_internal = self.config_internal.with_disk_manager_os() + return self + + def with_disk_manager_specified(self, paths: list[str]) -> RuntimeConfig: + """Use the specified paths for the disk manager's temporary files. + + Parameters + ---------- + paths : list[str] + Paths to use for the disk manager's temporary files. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_specified(["/tmp"]) + """ + self.config_internal = self.config_internal.with_disk_manager_specified(paths) + return self + + def with_unbounded_memory_pool(self) -> RuntimeConfig: + """Use an unbounded memory pool. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_unbounded_memory_pool() + """ + self.config_internal = self.config_internal.with_unbounded_memory_pool() + return self + + def with_fair_spill_pool(self, size: int) -> RuntimeConfig: + """Use a fair spill pool with the specified size. + + This pool works best when you know beforehand the query has multiple spillable + operators that will likely all need to spill. Sometimes it will cause spills + even when there was sufficient memory (reserved for other operators) to avoid + doing so. + + ```text + ┌───────────────────────z──────────────────────z───────────────┐ + │ z z │ + │ z z │ + │ Spillable z Unspillable z Free │ + │ Memory z Memory z Memory │ + │ z z │ + │ z z │ + └───────────────────────z──────────────────────z───────────────┘ + ``` + + Parameters + ---------- + size : int + Size of the memory pool in bytes. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + ```python + >>> config = RuntimeConfig().with_fair_spill_pool(1024) + ``` + """ + self.config_internal = self.config_internal.with_fair_spill_pool(size) + return self + + def with_greedy_memory_pool(self, size: int) -> RuntimeConfig: + """Use a greedy memory pool with the specified size. + + This pool works well for queries that do not need to spill or have a single + spillable operator. See `RuntimeConfig.with_fair_spill_pool` if there are + multiple spillable operators that all will spill. + + Parameters + ---------- + size : int + Size of the memory pool in bytes. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_greedy_memory_pool(1024) + """ + self.config_internal = self.config_internal.with_greedy_memory_pool(size) + return self + + def with_temp_file_path(self, path: str) -> RuntimeConfig: + """Use the specified path to create any needed temporary files. + + Parameters + ---------- + path : str + Path to use for temporary files. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_temp_file_path("/tmp") + """ + self.config_internal = self.config_internal.with_temp_file_path(path) + return self + + +class SQLOptions: + def __init__(self) -> None: + """Create a new `SQLOptions` with default values. + + The default values are: + - DDL commands are allowed + - DML commands are allowed + - Statements are allowed + """ + self.options_internal = SQLOptionsInternal() + + def with_allow_ddl(self, allow: bool = True) -> SQLOptions: + """Should DDL (Data Definition Language) commands be run? + + Examples of DDL commands include `CREATE TABLE` and `DROP TABLE`. + + Parameters + ---------- + allow : bool + Allow DDL commands to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + + Examples + -------- + >>> options = SQLOptions().with_allow_ddl(True) + """ + self.options_internal = self.options_internal.with_allow_ddl(allow) + return self + + def with_allow_dml(self, allow: bool = True) -> SQLOptions: + """Should DML (Data Manipulation Language) commands be run? + + Examples of DML commands include `INSERT INTO` and `DELETE`. + + Parameters + ---------- + allow : bool + Allow DML commands to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + + Examples + -------- + >>> options = SQLOptions().with_allow_dml(True) + """ + self.options_internal = self.options_internal.with_allow_dml(allow) + return self + + def with_allow_statements(self, allow: bool = True) -> SQLOptions: + """Should statements such as `SET VARIABLE` and `BEGIN TRANSACTION` be run? + + Parameters + ---------- + allow : bool + Allow statements to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + Examples + -------- + >>> options = SQLOptions().with_allow_statements(True) + """ + self.options_internal = self.options_internal.with_allow_statements(allow) + return self + + +class SessionContext: + def __init__( + self, config: SessionConfig | None = None, runtime: RuntimeConfig | None = None + ) -> None: + """Main interface for executing queries with DataFusion. + + Maintains the state of the connection between a user and an instance + of the connection between a user and an instance of the DataFusion + engine. + + Parameters + ---------- + config : SessionConfig | None + Session configuration options. + runtime : RuntimeConfig | None + Runtime configuration options. + + Examples + -------- + The following example demostrates how to use the context to execute + a query against a CSV data source using the `DataFrame` API: + + ```python + from datafusion import SessionContext + + ctx = SessionContext() + df = ctx.read_csv("data.csv") + ``` + """ + config = config.config_internal if config is not None else None + runtime = runtime.config_internal if config is not None else None + + self.ctx = SessionContextInternal(config, runtime) + + def register_object_store(self, schema: str, store: Any, host: str | None) -> None: + self.ctx.register_object_store(schema, store, host) + + def register_listing_table( + self, + name: str, + path: str, + table_partition_cols: list[tuple[str, str]] = [], + file_extension: str = ".parquet", + schema: pyarrow.Schema | None = None, + file_sort_order: list[list[Expr]] | None = None, + ) -> None: + if file_sort_order is not None: + file_sort_order = [[x.expr for x in xs] for xs in file_sort_order] + self.ctx.register_listing_table( + name, path, table_partition_cols, file_extension, schema, file_sort_order + ) + + def sql(self, query: str) -> DataFrame: + """Create a `DataFrame` from SQL query text. + + Note: This API implements DDL statements such as `CREATE TABLE` and + `CREATE VIEW` and DML statements such as `INSERT INTO` with in-memory + default implementation. See `SessionContext.sql_with_options`. + + Parameters + ---------- + query : str + SQL query text. + + Returns + ------- + DataFrame + DataFrame representation of the SQL query. + """ + return DataFrame(self.ctx.sql(query)) + + def sql_with_options(self, query: str, options: SQLOptions) -> DataFrame: + """Create a `DataFrame` from SQL query text, first validating that + the query is allowed by the provided options. + + Parameters + ---------- + query : str + SQL query text. + options : SQLOptions + SQL options. + + Returns + ------- + DataFrame + DataFrame representation of the SQL query. + """ + return DataFrame(self.ctx.sql_with_options(query, options.options_internal)) + + def create_dataframe( + self, + partitions: list[list[pyarrow.RecordBatch]], + name: str | None = None, + schema: pyarrow.Schema | None = None, + ) -> DataFrame: + return DataFrame(self.ctx.create_dataframe(partitions, name, schema)) + + def create_dataframe_from_logical_plan(self, plan: LogicalPlan) -> DataFrame: + """Create a `DataFrame` from an existing logical plan. + + Parameters + ---------- + plan : LogicalPlan + Logical plan. + + Returns + ------- + DataFrame + DataFrame representation of the logical plan. + """ + return DataFrame(self.ctx.create_dataframe_from_logical_plan(plan)) + + def from_pylist( + self, data: list[dict[str, Any]], name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from a list of dictionaries. + + Parameters + ---------- + data : list[dict[str, Any]] + List of dictionaries. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the list of dictionaries. + """ + return DataFrame(self.ctx.from_pylist(data, name)) + + def from_pydict( + self, data: dict[str, list[Any]], name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from a dictionary of lists. + + Parameters + ---------- + data : dict[str, list[Any]] + Dictionary of lists. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the dictionary of lists. + """ + return DataFrame(self.ctx.from_pydict(data, name)) + + def from_arrow_table( + self, data: pyarrow.Table, name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from an Arrow table. + + Parameters + ---------- + data : pyarrow.Table + Arrow table. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Arrow table. + """ + return DataFrame(self.ctx.from_arrow_table(data, name)) + + def from_pandas(self, data: pandas.DataFrame, name: str | None = None) -> DataFrame: + """Create a `DataFrame` from a Pandas DataFrame. + + Parameters + ---------- + data : pandas.DataFrame + Pandas DataFrame. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Pandas DataFrame. + """ + return DataFrame(self.ctx.from_pandas(data, name)) + + def from_polars(self, data: polars.DataFrame, name: str | None = None) -> DataFrame: + """Create a `DataFrame` from a Polars DataFrame. + + Parameters + ---------- + data : polars.DataFrame + Polars DataFrame. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Polars DataFrame. + """ + return DataFrame(self.ctx.from_polars(data, name)) + + def register_table(self, name: str, table: pyarrow.Table) -> None: + self.ctx.register_table(name, table) + + def deregister_table(self, name: str) -> None: + self.ctx.deregister_table(name) + + def register_record_batches( + self, name: str, partitions: list[list[pyarrow.RecordBatch]] + ) -> None: + self.ctx.register_record_batches(name, partitions) + + def register_parquet( + self, + name: str, + path: str, Review Comment: Same comment about `pathlib.Path` ########## python/datafusion/context.py: ########## @@ -0,0 +1,1167 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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 __future__ import annotations + +from ._internal import SessionConfig as SessionConfigInternal +from ._internal import RuntimeConfig as RuntimeConfigInternal +from ._internal import SQLOptions as SQLOptionsInternal +from ._internal import SessionContext as SessionContextInternal +from ._internal import LogicalPlan, ExecutionPlan # TODO MAKE THIS A DEFINED CLASS + +from datafusion._internal import AggregateUDF +from datafusion.catalog import Catalog, Table +from datafusion.dataframe import DataFrame +from datafusion.expr import Expr +from datafusion.record_batch import RecordBatchStream +from datafusion.udf import ScalarUDF + +from typing import Any, TYPE_CHECKING +from typing_extensions import deprecated + +if TYPE_CHECKING: + import pyarrow + import pandas + import polars + + +class SessionConfig: + def __init__(self, config_options: dict[str, str] = {}) -> None: + """Create a new `SessionConfig` with the given configuration options. + + Parameters + ---------- + config_options : dict[str, str] + Configuration options. + """ + self.config_internal = SessionConfigInternal(config_options) + + def with_create_default_catalog_and_schema( + self, enabled: bool = True + ) -> SessionConfig: + """Control whether the default catalog and schema will be automatically created. + + Parameters + ---------- + enabled : bool + Whether the default catalog and schema will be automatically created. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = ( + self.config_internal.with_create_default_catalog_and_schema(enabled) + ) + return self + + def with_default_catalog_and_schema( + self, catalog: str, schema: str + ) -> SessionConfig: + """Select a name for the default catalog and shcema. + + Parameters + ---------- + catalog : str + Catalog name. + schema : str + Schema name. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_default_catalog_and_schema( + catalog, schema + ) + return self + + def with_information_schema(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the inclusion of `information_schema` virtual tables. + + Parameters + ---------- + enabled : bool + Whether to include `information_schema` virtual tables. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_information_schema(enabled) + return self + + def with_batch_size(self, batch_size: int) -> SessionConfig: + """Customize batch size. + + Parameters + ---------- + batch_size : int + Batch size. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_batch_size(batch_size) + return self + + def with_target_partitions(self, target_partitions: int) -> SessionConfig: + """Customize the number of target partitions for query execution. + + Increasing partitions can increase concurrency. + + Parameters + ---------- + target_partitions : int + Number of target partitions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_target_partitions( + target_partitions + ) + return self + + def with_repartition_aggregations(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for aggregations. + + Enabling this improves parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for aggregations. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_aggregations( + enabled + ) + return self + + def with_repartition_joins(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for joins to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for joins. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_joins(enabled) + return self + + def with_repartition_windows(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for window functions to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for window functions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_windows(enabled) + return self + + def with_repartition_sorts(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for window functions to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for window functions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_sorts(enabled) + return self + + def with_repartition_file_scans(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for file scans. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for file scans. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_file_scans(enabled) + return self + + def with_repartition_file_min_size(self, size: int) -> SessionConfig: + """Set minimum file range size for repartitioning scans. + + Parameters + ---------- + size : int + Minimum file range size. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_file_min_size(size) + return self + + def with_parquet_pruning(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of pruning predicate for parquet readers to skip row groups. + + Parameters + ---------- + enabled : bool + Whether to use pruning predicate for parquet readers. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_parquet_pruning(enabled) + return self + + def set(self, key: str, value: str) -> SessionConfig: + """Set a configuration option. + + Parameters + ---------- + key : str + Option key. + value : str + Option value. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.set(key, value) + return self + + +class RuntimeConfig: + def __init__(self) -> None: + """Create a new `RuntimeConfig` with default values.""" + self.config_internal = RuntimeConfigInternal() + + def with_disk_manager_disabled(self) -> RuntimeConfig: + """Disable the disk manager, attempts to create temporary files will error. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_disabled() + """ + self.config_internal = self.config_internal.with_disk_manager_disabled() + return self + + def with_disk_manager_os(self) -> RuntimeConfig: + """Use the operating system's temporary directory for disk manager. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_os() + """ + self.config_internal = self.config_internal.with_disk_manager_os() + return self + + def with_disk_manager_specified(self, paths: list[str]) -> RuntimeConfig: + """Use the specified paths for the disk manager's temporary files. + + Parameters + ---------- + paths : list[str] + Paths to use for the disk manager's temporary files. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_specified(["/tmp"]) + """ + self.config_internal = self.config_internal.with_disk_manager_specified(paths) + return self + + def with_unbounded_memory_pool(self) -> RuntimeConfig: + """Use an unbounded memory pool. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_unbounded_memory_pool() + """ + self.config_internal = self.config_internal.with_unbounded_memory_pool() + return self + + def with_fair_spill_pool(self, size: int) -> RuntimeConfig: + """Use a fair spill pool with the specified size. + + This pool works best when you know beforehand the query has multiple spillable + operators that will likely all need to spill. Sometimes it will cause spills + even when there was sufficient memory (reserved for other operators) to avoid + doing so. + + ```text + ┌───────────────────────z──────────────────────z───────────────┐ + │ z z │ + │ z z │ + │ Spillable z Unspillable z Free │ + │ Memory z Memory z Memory │ + │ z z │ + │ z z │ + └───────────────────────z──────────────────────z───────────────┘ + ``` + + Parameters + ---------- + size : int + Size of the memory pool in bytes. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + ```python + >>> config = RuntimeConfig().with_fair_spill_pool(1024) + ``` + """ + self.config_internal = self.config_internal.with_fair_spill_pool(size) + return self + + def with_greedy_memory_pool(self, size: int) -> RuntimeConfig: + """Use a greedy memory pool with the specified size. + + This pool works well for queries that do not need to spill or have a single + spillable operator. See `RuntimeConfig.with_fair_spill_pool` if there are + multiple spillable operators that all will spill. + + Parameters + ---------- + size : int + Size of the memory pool in bytes. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_greedy_memory_pool(1024) + """ + self.config_internal = self.config_internal.with_greedy_memory_pool(size) + return self + + def with_temp_file_path(self, path: str) -> RuntimeConfig: + """Use the specified path to create any needed temporary files. + + Parameters + ---------- + path : str + Path to use for temporary files. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_temp_file_path("/tmp") + """ + self.config_internal = self.config_internal.with_temp_file_path(path) + return self + + +class SQLOptions: + def __init__(self) -> None: + """Create a new `SQLOptions` with default values. + + The default values are: + - DDL commands are allowed + - DML commands are allowed + - Statements are allowed + """ + self.options_internal = SQLOptionsInternal() + + def with_allow_ddl(self, allow: bool = True) -> SQLOptions: + """Should DDL (Data Definition Language) commands be run? + + Examples of DDL commands include `CREATE TABLE` and `DROP TABLE`. + + Parameters + ---------- + allow : bool + Allow DDL commands to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + + Examples + -------- + >>> options = SQLOptions().with_allow_ddl(True) + """ + self.options_internal = self.options_internal.with_allow_ddl(allow) + return self + + def with_allow_dml(self, allow: bool = True) -> SQLOptions: + """Should DML (Data Manipulation Language) commands be run? + + Examples of DML commands include `INSERT INTO` and `DELETE`. + + Parameters + ---------- + allow : bool + Allow DML commands to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + + Examples + -------- + >>> options = SQLOptions().with_allow_dml(True) + """ + self.options_internal = self.options_internal.with_allow_dml(allow) + return self + + def with_allow_statements(self, allow: bool = True) -> SQLOptions: + """Should statements such as `SET VARIABLE` and `BEGIN TRANSACTION` be run? + + Parameters + ---------- + allow : bool + Allow statements to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + Examples + -------- + >>> options = SQLOptions().with_allow_statements(True) + """ + self.options_internal = self.options_internal.with_allow_statements(allow) + return self + + +class SessionContext: + def __init__( + self, config: SessionConfig | None = None, runtime: RuntimeConfig | None = None + ) -> None: + """Main interface for executing queries with DataFusion. + + Maintains the state of the connection between a user and an instance + of the connection between a user and an instance of the DataFusion + engine. + + Parameters + ---------- + config : SessionConfig | None + Session configuration options. + runtime : RuntimeConfig | None + Runtime configuration options. + + Examples + -------- + The following example demostrates how to use the context to execute + a query against a CSV data source using the `DataFrame` API: + + ```python + from datafusion import SessionContext + + ctx = SessionContext() + df = ctx.read_csv("data.csv") + ``` + """ + config = config.config_internal if config is not None else None + runtime = runtime.config_internal if config is not None else None + + self.ctx = SessionContextInternal(config, runtime) + + def register_object_store(self, schema: str, store: Any, host: str | None) -> None: + self.ctx.register_object_store(schema, store, host) + + def register_listing_table( + self, + name: str, + path: str, + table_partition_cols: list[tuple[str, str]] = [], + file_extension: str = ".parquet", + schema: pyarrow.Schema | None = None, + file_sort_order: list[list[Expr]] | None = None, + ) -> None: + if file_sort_order is not None: + file_sort_order = [[x.expr for x in xs] for xs in file_sort_order] + self.ctx.register_listing_table( + name, path, table_partition_cols, file_extension, schema, file_sort_order + ) + + def sql(self, query: str) -> DataFrame: + """Create a `DataFrame` from SQL query text. + + Note: This API implements DDL statements such as `CREATE TABLE` and + `CREATE VIEW` and DML statements such as `INSERT INTO` with in-memory + default implementation. See `SessionContext.sql_with_options`. + + Parameters + ---------- + query : str + SQL query text. + + Returns + ------- + DataFrame + DataFrame representation of the SQL query. + """ + return DataFrame(self.ctx.sql(query)) + + def sql_with_options(self, query: str, options: SQLOptions) -> DataFrame: + """Create a `DataFrame` from SQL query text, first validating that + the query is allowed by the provided options. + + Parameters + ---------- + query : str + SQL query text. + options : SQLOptions + SQL options. + + Returns + ------- + DataFrame + DataFrame representation of the SQL query. + """ + return DataFrame(self.ctx.sql_with_options(query, options.options_internal)) + + def create_dataframe( + self, + partitions: list[list[pyarrow.RecordBatch]], + name: str | None = None, + schema: pyarrow.Schema | None = None, + ) -> DataFrame: + return DataFrame(self.ctx.create_dataframe(partitions, name, schema)) + + def create_dataframe_from_logical_plan(self, plan: LogicalPlan) -> DataFrame: + """Create a `DataFrame` from an existing logical plan. + + Parameters + ---------- + plan : LogicalPlan + Logical plan. + + Returns + ------- + DataFrame + DataFrame representation of the logical plan. + """ + return DataFrame(self.ctx.create_dataframe_from_logical_plan(plan)) + + def from_pylist( + self, data: list[dict[str, Any]], name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from a list of dictionaries. + + Parameters + ---------- + data : list[dict[str, Any]] + List of dictionaries. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the list of dictionaries. + """ + return DataFrame(self.ctx.from_pylist(data, name)) + + def from_pydict( + self, data: dict[str, list[Any]], name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from a dictionary of lists. + + Parameters + ---------- + data : dict[str, list[Any]] + Dictionary of lists. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the dictionary of lists. + """ + return DataFrame(self.ctx.from_pydict(data, name)) + + def from_arrow_table( + self, data: pyarrow.Table, name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from an Arrow table. + + Parameters + ---------- + data : pyarrow.Table + Arrow table. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Arrow table. + """ + return DataFrame(self.ctx.from_arrow_table(data, name)) + + def from_pandas(self, data: pandas.DataFrame, name: str | None = None) -> DataFrame: + """Create a `DataFrame` from a Pandas DataFrame. + + Parameters + ---------- + data : pandas.DataFrame + Pandas DataFrame. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Pandas DataFrame. + """ + return DataFrame(self.ctx.from_pandas(data, name)) + + def from_polars(self, data: polars.DataFrame, name: str | None = None) -> DataFrame: + """Create a `DataFrame` from a Polars DataFrame. + + Parameters + ---------- + data : polars.DataFrame + Polars DataFrame. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Polars DataFrame. + """ + return DataFrame(self.ctx.from_polars(data, name)) + + def register_table(self, name: str, table: pyarrow.Table) -> None: + self.ctx.register_table(name, table) + + def deregister_table(self, name: str) -> None: + self.ctx.deregister_table(name) + + def register_record_batches( + self, name: str, partitions: list[list[pyarrow.RecordBatch]] + ) -> None: + self.ctx.register_record_batches(name, partitions) + + def register_parquet( + self, + name: str, + path: str, + table_partition_cols: list[tuple[str, str]] = [], + parquet_pruning: bool = True, + file_extension: str = ".parquet", + skip_metadata: bool = True, + schema: pyarrow.Schema | None = None, + file_sort_order: list[list[Expr]] | None = None, + ) -> None: + """Register a Parquet file as a table. + + The registered table can be referenced from SQL statement executed against + this context. + + Parameters + ---------- + name : str + Name of the table to register. + path : str + Path to the Parquet file. + table_partition_cols : list[tuple[str, str]], optional + Partition columns, by default [] + parquet_pruning : bool, optional + Whether the parquet reader should use the predicate to prune row groups, by default True + file_extension : str, optional + File extension; only files with this extension are selected for data input, by default ".parquet" + skip_metadata : bool, optional + Whether the parquet reader should skip any metadata that may be in the file + schema. This can help avoid schema conflicts due to metadata. by default True + schema : pyarrow.Schema | None, optional + The data source schema, by default None + file_sort_order : list[list[Expr]] | None, optional + Sort order for the file, by default None + """ + self.ctx.register_parquet( + name, + path, + table_partition_cols, + parquet_pruning, + file_extension, + skip_metadata, + schema, + file_sort_order, + ) + + def register_csv( + self, + name: str, + path: str, + schema: pyarrow.Schema | None = None, + has_header: bool = True, + delimiter: str = ",", + schema_infer_max_records: int = 1000, + file_extension: str = ".csv", + file_compression_type: str | None = None, + ) -> None: + """Register a CSV file as a table. + + The registered table can be referenced from SQL statement executed against. + + Parameters + ---------- + name : str + Name of the table to register. + path : str + Path to the CSV file. + schema : pyarrow.Schema | None, optional + An optional schema representing the CSV file. If None, the CSV reader will try to infer it based on data in file, by default None + has_header : bool, optional + Whether the CSV file have a header. If schema inference is run on a file with no headers, default column names are created, by default True + delimiter : str, optional + An optional column delimiter, by default "," + schema_infer_max_records : int, optional + Maximum number of rows to read from CSV files for schema inference if needed, by default 1000 + file_extension : str, optional + File extension; only files with this extension are selected for data input, by default ".csv" + file_compression_type : str | None, optional + File compression type, by default None + """ + self.ctx.register_csv( + name, + path, + schema, + has_header, + delimiter, + schema_infer_max_records, + file_extension, + file_compression_type, + ) + + def register_json( + self, + name: str, + path: str, + schema: pyarrow.Schema | None = None, + schema_infer_max_records: int = 1000, + file_extension: str = ".json", + table_partition_cols: list[tuple[str, str]] = [], + file_compression_type: str | None = None, + ) -> None: + """Register a JSON file as a table. + + The registered table can be referenced from SQL statement executed against + this context. + + Parameters + ---------- + name : str + Name of the table to register. + path : str + Path to the JSON file. + schema : pyarrow.Schema | None, optional + The data source schema, by default None + schema_infer_max_records : int, optional + Maximum number of rows to read from JSON files for schema inference if needed, by default 1000 + file_extension : str, optional + File extension; only files with this extension are selected for data input, by default ".json" + table_partition_cols : list[tuple[str, str]], optional + Partition columns, by default [] + file_compression_type : str | None, optional + File compression type, by default None + """ + self.ctx.register_json( + name, + path, + schema, + schema_infer_max_records, + file_extension, + table_partition_cols, + file_compression_type, + ) + + def register_avro( + self, + name: str, + path: str, + schema: pyarrow.Schema | None = None, + file_extension: str = ".avro", + table_partition_cols: list[tuple[str, str]] = [], + ) -> None: + """Register an Avro file as a table. + + The registered table can be referenced from SQL statement executed against + this context. + + Parameters + ---------- + name : str + Name of the table to register. + path : str + Path to the Avro file. + schema : pyarrow.Schema | None, optional + The data source schema, by default None + file_extension : str, optional + File extension to select, by default ".avro" + table_partition_cols : list[tuple[str, str]], optional + Partition columns, by default [] + """ + self.ctx.register_avro(name, path, schema, file_extension, table_partition_cols) + + def register_dataset(self, name: str, dataset: pyarrow.dataset.Dataset) -> None: + """ + Register a `pyarrow.dataset.Dataset` as a table. + + Parameters + ---------- + name : str + Name of the table to register. + dataset : dataset.Dataset + PyArrow dataset. + """ + self.ctx.register_dataset(name, dataset) + + def register_udf(self, udf: ScalarUDF) -> None: + """Register a user-defined function (UDF) with the context. + + Parameters + ---------- + udf : ScalarUDF + User-defined function. + """ + self.ctx.register_udf(udf.udf) + + def register_udaf(self, udaf: AggregateUDF) -> None: + """Register a user-defined aggregation function (UDAF) with the context. + + Parameters + ---------- + udaf : AggregateUDF + User-defined aggregation function. + """ + self.ctx.register_udaf(udaf) + + def catalog(self, name: str = "datafusion") -> Catalog: + """Retrieve a catalog by name. + + Parameters + ---------- + name : str, optional + Name of the catalog to retrieve, by default "datafusion". + + Returns + ------- + Catalog + Catalog representation. + """ + return self.ctx.catalog(name) + + @deprecated( + "Use the catalog provider interface `SessionContext.catalog` to " + "examine available catalogs, schemas and tables" + ) + def tables(self) -> set[str]: + return self.ctx.tables() + + def table(self, name: str) -> DataFrame: + """Retrieve a `DataFrame` representing a previously registered table. + + Parameters + ---------- + name : str + Name of the table to retrieve. + + Returns + ------- + DataFrame + DataFrame representation of the table. + """ + return DataFrame(self.ctx.table(name)) + + def table_exist(self, name: str) -> bool: + """Return whether a table with the given name exists. + + Parameters + ---------- + name : str + Name of the table to check. + + Returns + ------- + bool + Whether a table with the given name exists. + """ + return self.ctx.table_exist(name) + + def empty_table(self) -> DataFrame: + """Create an empty `DataFrame`. + + Returns + ------- + DataFrame + An empty DataFrame. + """ + return DataFrame(self.ctx.empty_table()) + + def session_id(self) -> str: + """Retrun an id that uniquely identifies this `SessionContext`. + + Returns + ------- + str + Unique session identifier + """ + return self.ctx.session_id() + + def read_json( + self, + path: str, Review Comment: Same comment as above re `pathlib.Path` ########## python/datafusion/substrait.py: ########## @@ -15,9 +15,156 @@ # specific language governing permissions and limitations # under the License. +from __future__ import annotations -from ._internal import substrait +from ._internal import substrait as substrait_internal +from typing import TYPE_CHECKING -def __getattr__(name): - return getattr(substrait, name) +if TYPE_CHECKING: + from datafusion.context import SessionContext + from datafusion._internal import LogicalPlan + + +class plan: Review Comment: According to PEP8: > According to PEP8: Class names must follow CamelCase naming (Each new word is capitalized without underscore) ########## python/datafusion/context.py: ########## @@ -0,0 +1,1167 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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 __future__ import annotations + +from ._internal import SessionConfig as SessionConfigInternal +from ._internal import RuntimeConfig as RuntimeConfigInternal +from ._internal import SQLOptions as SQLOptionsInternal +from ._internal import SessionContext as SessionContextInternal +from ._internal import LogicalPlan, ExecutionPlan # TODO MAKE THIS A DEFINED CLASS + +from datafusion._internal import AggregateUDF +from datafusion.catalog import Catalog, Table +from datafusion.dataframe import DataFrame +from datafusion.expr import Expr +from datafusion.record_batch import RecordBatchStream +from datafusion.udf import ScalarUDF + +from typing import Any, TYPE_CHECKING +from typing_extensions import deprecated + +if TYPE_CHECKING: + import pyarrow + import pandas + import polars + + +class SessionConfig: + def __init__(self, config_options: dict[str, str] = {}) -> None: + """Create a new `SessionConfig` with the given configuration options. + + Parameters + ---------- + config_options : dict[str, str] + Configuration options. + """ + self.config_internal = SessionConfigInternal(config_options) + + def with_create_default_catalog_and_schema( + self, enabled: bool = True + ) -> SessionConfig: + """Control whether the default catalog and schema will be automatically created. + + Parameters + ---------- + enabled : bool + Whether the default catalog and schema will be automatically created. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = ( + self.config_internal.with_create_default_catalog_and_schema(enabled) + ) + return self + + def with_default_catalog_and_schema( + self, catalog: str, schema: str + ) -> SessionConfig: + """Select a name for the default catalog and shcema. + + Parameters + ---------- + catalog : str + Catalog name. + schema : str + Schema name. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_default_catalog_and_schema( + catalog, schema + ) + return self + + def with_information_schema(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the inclusion of `information_schema` virtual tables. + + Parameters + ---------- + enabled : bool + Whether to include `information_schema` virtual tables. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_information_schema(enabled) + return self + + def with_batch_size(self, batch_size: int) -> SessionConfig: + """Customize batch size. + + Parameters + ---------- + batch_size : int + Batch size. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_batch_size(batch_size) + return self + + def with_target_partitions(self, target_partitions: int) -> SessionConfig: + """Customize the number of target partitions for query execution. + + Increasing partitions can increase concurrency. + + Parameters + ---------- + target_partitions : int + Number of target partitions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_target_partitions( + target_partitions + ) + return self + + def with_repartition_aggregations(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for aggregations. + + Enabling this improves parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for aggregations. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_aggregations( + enabled + ) + return self + + def with_repartition_joins(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for joins to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for joins. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_joins(enabled) + return self + + def with_repartition_windows(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for window functions to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for window functions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_windows(enabled) + return self + + def with_repartition_sorts(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for window functions to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for window functions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_sorts(enabled) + return self + + def with_repartition_file_scans(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for file scans. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for file scans. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_file_scans(enabled) + return self + + def with_repartition_file_min_size(self, size: int) -> SessionConfig: + """Set minimum file range size for repartitioning scans. + + Parameters + ---------- + size : int + Minimum file range size. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_file_min_size(size) + return self + + def with_parquet_pruning(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of pruning predicate for parquet readers to skip row groups. + + Parameters + ---------- + enabled : bool + Whether to use pruning predicate for parquet readers. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_parquet_pruning(enabled) + return self + + def set(self, key: str, value: str) -> SessionConfig: + """Set a configuration option. + + Parameters + ---------- + key : str + Option key. + value : str + Option value. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.set(key, value) + return self + + +class RuntimeConfig: + def __init__(self) -> None: + """Create a new `RuntimeConfig` with default values.""" + self.config_internal = RuntimeConfigInternal() + + def with_disk_manager_disabled(self) -> RuntimeConfig: + """Disable the disk manager, attempts to create temporary files will error. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_disabled() + """ + self.config_internal = self.config_internal.with_disk_manager_disabled() + return self + + def with_disk_manager_os(self) -> RuntimeConfig: + """Use the operating system's temporary directory for disk manager. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_os() + """ + self.config_internal = self.config_internal.with_disk_manager_os() + return self + + def with_disk_manager_specified(self, paths: list[str]) -> RuntimeConfig: + """Use the specified paths for the disk manager's temporary files. + + Parameters + ---------- + paths : list[str] + Paths to use for the disk manager's temporary files. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_specified(["/tmp"]) + """ + self.config_internal = self.config_internal.with_disk_manager_specified(paths) + return self + + def with_unbounded_memory_pool(self) -> RuntimeConfig: + """Use an unbounded memory pool. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_unbounded_memory_pool() + """ + self.config_internal = self.config_internal.with_unbounded_memory_pool() + return self + + def with_fair_spill_pool(self, size: int) -> RuntimeConfig: + """Use a fair spill pool with the specified size. + + This pool works best when you know beforehand the query has multiple spillable + operators that will likely all need to spill. Sometimes it will cause spills + even when there was sufficient memory (reserved for other operators) to avoid + doing so. + + ```text + ┌───────────────────────z──────────────────────z───────────────┐ + │ z z │ + │ z z │ + │ Spillable z Unspillable z Free │ + │ Memory z Memory z Memory │ + │ z z │ + │ z z │ + └───────────────────────z──────────────────────z───────────────┘ + ``` + + Parameters + ---------- + size : int + Size of the memory pool in bytes. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + ```python + >>> config = RuntimeConfig().with_fair_spill_pool(1024) + ``` + """ + self.config_internal = self.config_internal.with_fair_spill_pool(size) + return self + + def with_greedy_memory_pool(self, size: int) -> RuntimeConfig: + """Use a greedy memory pool with the specified size. + + This pool works well for queries that do not need to spill or have a single + spillable operator. See `RuntimeConfig.with_fair_spill_pool` if there are + multiple spillable operators that all will spill. + + Parameters + ---------- + size : int + Size of the memory pool in bytes. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_greedy_memory_pool(1024) + """ + self.config_internal = self.config_internal.with_greedy_memory_pool(size) + return self + + def with_temp_file_path(self, path: str) -> RuntimeConfig: + """Use the specified path to create any needed temporary files. + + Parameters + ---------- + path : str + Path to use for temporary files. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_temp_file_path("/tmp") + """ + self.config_internal = self.config_internal.with_temp_file_path(path) + return self + + +class SQLOptions: + def __init__(self) -> None: + """Create a new `SQLOptions` with default values. + + The default values are: + - DDL commands are allowed + - DML commands are allowed + - Statements are allowed + """ + self.options_internal = SQLOptionsInternal() + + def with_allow_ddl(self, allow: bool = True) -> SQLOptions: + """Should DDL (Data Definition Language) commands be run? + + Examples of DDL commands include `CREATE TABLE` and `DROP TABLE`. + + Parameters + ---------- + allow : bool + Allow DDL commands to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + + Examples + -------- + >>> options = SQLOptions().with_allow_ddl(True) + """ + self.options_internal = self.options_internal.with_allow_ddl(allow) + return self + + def with_allow_dml(self, allow: bool = True) -> SQLOptions: + """Should DML (Data Manipulation Language) commands be run? + + Examples of DML commands include `INSERT INTO` and `DELETE`. + + Parameters + ---------- + allow : bool + Allow DML commands to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + + Examples + -------- + >>> options = SQLOptions().with_allow_dml(True) + """ + self.options_internal = self.options_internal.with_allow_dml(allow) + return self + + def with_allow_statements(self, allow: bool = True) -> SQLOptions: + """Should statements such as `SET VARIABLE` and `BEGIN TRANSACTION` be run? + + Parameters + ---------- + allow : bool + Allow statements to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + Examples + -------- + >>> options = SQLOptions().with_allow_statements(True) + """ + self.options_internal = self.options_internal.with_allow_statements(allow) + return self + + +class SessionContext: + def __init__( + self, config: SessionConfig | None = None, runtime: RuntimeConfig | None = None + ) -> None: + """Main interface for executing queries with DataFusion. + + Maintains the state of the connection between a user and an instance + of the connection between a user and an instance of the DataFusion + engine. + + Parameters + ---------- + config : SessionConfig | None + Session configuration options. + runtime : RuntimeConfig | None + Runtime configuration options. + + Examples + -------- + The following example demostrates how to use the context to execute + a query against a CSV data source using the `DataFrame` API: + + ```python + from datafusion import SessionContext + + ctx = SessionContext() + df = ctx.read_csv("data.csv") + ``` + """ + config = config.config_internal if config is not None else None + runtime = runtime.config_internal if config is not None else None + + self.ctx = SessionContextInternal(config, runtime) + + def register_object_store(self, schema: str, store: Any, host: str | None) -> None: + self.ctx.register_object_store(schema, store, host) + + def register_listing_table( + self, + name: str, + path: str, + table_partition_cols: list[tuple[str, str]] = [], + file_extension: str = ".parquet", + schema: pyarrow.Schema | None = None, + file_sort_order: list[list[Expr]] | None = None, + ) -> None: + if file_sort_order is not None: + file_sort_order = [[x.expr for x in xs] for xs in file_sort_order] + self.ctx.register_listing_table( + name, path, table_partition_cols, file_extension, schema, file_sort_order + ) + + def sql(self, query: str) -> DataFrame: + """Create a `DataFrame` from SQL query text. + + Note: This API implements DDL statements such as `CREATE TABLE` and + `CREATE VIEW` and DML statements such as `INSERT INTO` with in-memory + default implementation. See `SessionContext.sql_with_options`. + + Parameters + ---------- + query : str + SQL query text. + + Returns + ------- + DataFrame + DataFrame representation of the SQL query. + """ + return DataFrame(self.ctx.sql(query)) + + def sql_with_options(self, query: str, options: SQLOptions) -> DataFrame: + """Create a `DataFrame` from SQL query text, first validating that + the query is allowed by the provided options. + + Parameters + ---------- + query : str + SQL query text. + options : SQLOptions + SQL options. + + Returns + ------- + DataFrame + DataFrame representation of the SQL query. + """ + return DataFrame(self.ctx.sql_with_options(query, options.options_internal)) + + def create_dataframe( + self, + partitions: list[list[pyarrow.RecordBatch]], + name: str | None = None, + schema: pyarrow.Schema | None = None, + ) -> DataFrame: + return DataFrame(self.ctx.create_dataframe(partitions, name, schema)) + + def create_dataframe_from_logical_plan(self, plan: LogicalPlan) -> DataFrame: + """Create a `DataFrame` from an existing logical plan. + + Parameters + ---------- + plan : LogicalPlan + Logical plan. + + Returns + ------- + DataFrame + DataFrame representation of the logical plan. + """ + return DataFrame(self.ctx.create_dataframe_from_logical_plan(plan)) + + def from_pylist( + self, data: list[dict[str, Any]], name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from a list of dictionaries. + + Parameters + ---------- + data : list[dict[str, Any]] + List of dictionaries. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the list of dictionaries. + """ + return DataFrame(self.ctx.from_pylist(data, name)) + + def from_pydict( + self, data: dict[str, list[Any]], name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from a dictionary of lists. + + Parameters + ---------- + data : dict[str, list[Any]] + Dictionary of lists. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the dictionary of lists. + """ + return DataFrame(self.ctx.from_pydict(data, name)) + + def from_arrow_table( + self, data: pyarrow.Table, name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from an Arrow table. + + Parameters + ---------- + data : pyarrow.Table + Arrow table. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Arrow table. + """ + return DataFrame(self.ctx.from_arrow_table(data, name)) + + def from_pandas(self, data: pandas.DataFrame, name: str | None = None) -> DataFrame: + """Create a `DataFrame` from a Pandas DataFrame. + + Parameters + ---------- + data : pandas.DataFrame + Pandas DataFrame. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Pandas DataFrame. + """ + return DataFrame(self.ctx.from_pandas(data, name)) + + def from_polars(self, data: polars.DataFrame, name: str | None = None) -> DataFrame: + """Create a `DataFrame` from a Polars DataFrame. + + Parameters + ---------- + data : polars.DataFrame + Polars DataFrame. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Polars DataFrame. + """ + return DataFrame(self.ctx.from_polars(data, name)) + + def register_table(self, name: str, table: pyarrow.Table) -> None: + self.ctx.register_table(name, table) + + def deregister_table(self, name: str) -> None: + self.ctx.deregister_table(name) + + def register_record_batches( + self, name: str, partitions: list[list[pyarrow.RecordBatch]] + ) -> None: + self.ctx.register_record_batches(name, partitions) + + def register_parquet( + self, + name: str, + path: str, + table_partition_cols: list[tuple[str, str]] = [], + parquet_pruning: bool = True, + file_extension: str = ".parquet", + skip_metadata: bool = True, + schema: pyarrow.Schema | None = None, + file_sort_order: list[list[Expr]] | None = None, + ) -> None: + """Register a Parquet file as a table. + + The registered table can be referenced from SQL statement executed against + this context. + + Parameters + ---------- + name : str + Name of the table to register. + path : str + Path to the Parquet file. + table_partition_cols : list[tuple[str, str]], optional + Partition columns, by default [] + parquet_pruning : bool, optional + Whether the parquet reader should use the predicate to prune row groups, by default True + file_extension : str, optional + File extension; only files with this extension are selected for data input, by default ".parquet" + skip_metadata : bool, optional + Whether the parquet reader should skip any metadata that may be in the file + schema. This can help avoid schema conflicts due to metadata. by default True + schema : pyarrow.Schema | None, optional + The data source schema, by default None + file_sort_order : list[list[Expr]] | None, optional + Sort order for the file, by default None + """ + self.ctx.register_parquet( + name, + path, + table_partition_cols, + parquet_pruning, + file_extension, + skip_metadata, + schema, + file_sort_order, + ) + + def register_csv( + self, + name: str, + path: str, Review Comment: Same comment as above about `pathlib.Path` ########## python/datafusion/context.py: ########## @@ -0,0 +1,1167 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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 __future__ import annotations + +from ._internal import SessionConfig as SessionConfigInternal +from ._internal import RuntimeConfig as RuntimeConfigInternal +from ._internal import SQLOptions as SQLOptionsInternal +from ._internal import SessionContext as SessionContextInternal +from ._internal import LogicalPlan, ExecutionPlan # TODO MAKE THIS A DEFINED CLASS + +from datafusion._internal import AggregateUDF +from datafusion.catalog import Catalog, Table +from datafusion.dataframe import DataFrame +from datafusion.expr import Expr +from datafusion.record_batch import RecordBatchStream +from datafusion.udf import ScalarUDF + +from typing import Any, TYPE_CHECKING +from typing_extensions import deprecated + +if TYPE_CHECKING: + import pyarrow + import pandas + import polars + + +class SessionConfig: + def __init__(self, config_options: dict[str, str] = {}) -> None: + """Create a new `SessionConfig` with the given configuration options. + + Parameters + ---------- + config_options : dict[str, str] + Configuration options. + """ + self.config_internal = SessionConfigInternal(config_options) + + def with_create_default_catalog_and_schema( + self, enabled: bool = True + ) -> SessionConfig: + """Control whether the default catalog and schema will be automatically created. + + Parameters + ---------- + enabled : bool + Whether the default catalog and schema will be automatically created. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = ( + self.config_internal.with_create_default_catalog_and_schema(enabled) + ) + return self + + def with_default_catalog_and_schema( + self, catalog: str, schema: str + ) -> SessionConfig: + """Select a name for the default catalog and shcema. + + Parameters + ---------- + catalog : str + Catalog name. + schema : str + Schema name. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_default_catalog_and_schema( + catalog, schema + ) + return self + + def with_information_schema(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the inclusion of `information_schema` virtual tables. + + Parameters + ---------- + enabled : bool + Whether to include `information_schema` virtual tables. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_information_schema(enabled) + return self + + def with_batch_size(self, batch_size: int) -> SessionConfig: + """Customize batch size. + + Parameters + ---------- + batch_size : int + Batch size. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_batch_size(batch_size) + return self + + def with_target_partitions(self, target_partitions: int) -> SessionConfig: + """Customize the number of target partitions for query execution. + + Increasing partitions can increase concurrency. + + Parameters + ---------- + target_partitions : int + Number of target partitions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_target_partitions( + target_partitions + ) + return self + + def with_repartition_aggregations(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for aggregations. + + Enabling this improves parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for aggregations. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_aggregations( + enabled + ) + return self + + def with_repartition_joins(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for joins to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for joins. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_joins(enabled) + return self + + def with_repartition_windows(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for window functions to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for window functions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_windows(enabled) + return self + + def with_repartition_sorts(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for window functions to improve parallelism. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for window functions. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_sorts(enabled) + return self + + def with_repartition_file_scans(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of repartitioning for file scans. + + Parameters + ---------- + enabled : bool + Whether to use repartitioning for file scans. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_file_scans(enabled) + return self + + def with_repartition_file_min_size(self, size: int) -> SessionConfig: + """Set minimum file range size for repartitioning scans. + + Parameters + ---------- + size : int + Minimum file range size. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_repartition_file_min_size(size) + return self + + def with_parquet_pruning(self, enabled: bool = True) -> SessionConfig: + """Enable or disable the use of pruning predicate for parquet readers to skip row groups. + + Parameters + ---------- + enabled : bool + Whether to use pruning predicate for parquet readers. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.with_parquet_pruning(enabled) + return self + + def set(self, key: str, value: str) -> SessionConfig: + """Set a configuration option. + + Parameters + ---------- + key : str + Option key. + value : str + Option value. + + Returns + ------- + SessionConfig + A new `SessionConfig` object with the updated setting. + """ + self.config_internal = self.config_internal.set(key, value) + return self + + +class RuntimeConfig: + def __init__(self) -> None: + """Create a new `RuntimeConfig` with default values.""" + self.config_internal = RuntimeConfigInternal() + + def with_disk_manager_disabled(self) -> RuntimeConfig: + """Disable the disk manager, attempts to create temporary files will error. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_disabled() + """ + self.config_internal = self.config_internal.with_disk_manager_disabled() + return self + + def with_disk_manager_os(self) -> RuntimeConfig: + """Use the operating system's temporary directory for disk manager. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_os() + """ + self.config_internal = self.config_internal.with_disk_manager_os() + return self + + def with_disk_manager_specified(self, paths: list[str]) -> RuntimeConfig: + """Use the specified paths for the disk manager's temporary files. + + Parameters + ---------- + paths : list[str] + Paths to use for the disk manager's temporary files. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_disk_manager_specified(["/tmp"]) + """ + self.config_internal = self.config_internal.with_disk_manager_specified(paths) + return self + + def with_unbounded_memory_pool(self) -> RuntimeConfig: + """Use an unbounded memory pool. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_unbounded_memory_pool() + """ + self.config_internal = self.config_internal.with_unbounded_memory_pool() + return self + + def with_fair_spill_pool(self, size: int) -> RuntimeConfig: + """Use a fair spill pool with the specified size. + + This pool works best when you know beforehand the query has multiple spillable + operators that will likely all need to spill. Sometimes it will cause spills + even when there was sufficient memory (reserved for other operators) to avoid + doing so. + + ```text + ┌───────────────────────z──────────────────────z───────────────┐ + │ z z │ + │ z z │ + │ Spillable z Unspillable z Free │ + │ Memory z Memory z Memory │ + │ z z │ + │ z z │ + └───────────────────────z──────────────────────z───────────────┘ + ``` + + Parameters + ---------- + size : int + Size of the memory pool in bytes. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + ```python + >>> config = RuntimeConfig().with_fair_spill_pool(1024) + ``` + """ + self.config_internal = self.config_internal.with_fair_spill_pool(size) + return self + + def with_greedy_memory_pool(self, size: int) -> RuntimeConfig: + """Use a greedy memory pool with the specified size. + + This pool works well for queries that do not need to spill or have a single + spillable operator. See `RuntimeConfig.with_fair_spill_pool` if there are + multiple spillable operators that all will spill. + + Parameters + ---------- + size : int + Size of the memory pool in bytes. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_greedy_memory_pool(1024) + """ + self.config_internal = self.config_internal.with_greedy_memory_pool(size) + return self + + def with_temp_file_path(self, path: str) -> RuntimeConfig: + """Use the specified path to create any needed temporary files. + + Parameters + ---------- + path : str + Path to use for temporary files. + + Returns + ------- + RuntimeConfig + A new `RuntimeConfig` object with the updated setting. + + Examples + -------- + >>> config = RuntimeConfig().with_temp_file_path("/tmp") + """ + self.config_internal = self.config_internal.with_temp_file_path(path) + return self + + +class SQLOptions: + def __init__(self) -> None: + """Create a new `SQLOptions` with default values. + + The default values are: + - DDL commands are allowed + - DML commands are allowed + - Statements are allowed + """ + self.options_internal = SQLOptionsInternal() + + def with_allow_ddl(self, allow: bool = True) -> SQLOptions: + """Should DDL (Data Definition Language) commands be run? + + Examples of DDL commands include `CREATE TABLE` and `DROP TABLE`. + + Parameters + ---------- + allow : bool + Allow DDL commands to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + + Examples + -------- + >>> options = SQLOptions().with_allow_ddl(True) + """ + self.options_internal = self.options_internal.with_allow_ddl(allow) + return self + + def with_allow_dml(self, allow: bool = True) -> SQLOptions: + """Should DML (Data Manipulation Language) commands be run? + + Examples of DML commands include `INSERT INTO` and `DELETE`. + + Parameters + ---------- + allow : bool + Allow DML commands to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + + Examples + -------- + >>> options = SQLOptions().with_allow_dml(True) + """ + self.options_internal = self.options_internal.with_allow_dml(allow) + return self + + def with_allow_statements(self, allow: bool = True) -> SQLOptions: + """Should statements such as `SET VARIABLE` and `BEGIN TRANSACTION` be run? + + Parameters + ---------- + allow : bool + Allow statements to be run. + + Returns + ------- + SQLOptions + A new `SQLOptions` object with the updated setting. + + Examples + -------- + >>> options = SQLOptions().with_allow_statements(True) + """ + self.options_internal = self.options_internal.with_allow_statements(allow) + return self + + +class SessionContext: + def __init__( + self, config: SessionConfig | None = None, runtime: RuntimeConfig | None = None + ) -> None: + """Main interface for executing queries with DataFusion. + + Maintains the state of the connection between a user and an instance + of the connection between a user and an instance of the DataFusion + engine. + + Parameters + ---------- + config : SessionConfig | None + Session configuration options. + runtime : RuntimeConfig | None + Runtime configuration options. + + Examples + -------- + The following example demostrates how to use the context to execute + a query against a CSV data source using the `DataFrame` API: + + ```python + from datafusion import SessionContext + + ctx = SessionContext() + df = ctx.read_csv("data.csv") + ``` + """ + config = config.config_internal if config is not None else None + runtime = runtime.config_internal if config is not None else None + + self.ctx = SessionContextInternal(config, runtime) + + def register_object_store(self, schema: str, store: Any, host: str | None) -> None: + self.ctx.register_object_store(schema, store, host) + + def register_listing_table( + self, + name: str, + path: str, + table_partition_cols: list[tuple[str, str]] = [], + file_extension: str = ".parquet", + schema: pyarrow.Schema | None = None, + file_sort_order: list[list[Expr]] | None = None, + ) -> None: + if file_sort_order is not None: + file_sort_order = [[x.expr for x in xs] for xs in file_sort_order] + self.ctx.register_listing_table( + name, path, table_partition_cols, file_extension, schema, file_sort_order + ) + + def sql(self, query: str) -> DataFrame: + """Create a `DataFrame` from SQL query text. + + Note: This API implements DDL statements such as `CREATE TABLE` and + `CREATE VIEW` and DML statements such as `INSERT INTO` with in-memory + default implementation. See `SessionContext.sql_with_options`. + + Parameters + ---------- + query : str + SQL query text. + + Returns + ------- + DataFrame + DataFrame representation of the SQL query. + """ + return DataFrame(self.ctx.sql(query)) + + def sql_with_options(self, query: str, options: SQLOptions) -> DataFrame: + """Create a `DataFrame` from SQL query text, first validating that + the query is allowed by the provided options. + + Parameters + ---------- + query : str + SQL query text. + options : SQLOptions + SQL options. + + Returns + ------- + DataFrame + DataFrame representation of the SQL query. + """ + return DataFrame(self.ctx.sql_with_options(query, options.options_internal)) + + def create_dataframe( + self, + partitions: list[list[pyarrow.RecordBatch]], + name: str | None = None, + schema: pyarrow.Schema | None = None, + ) -> DataFrame: + return DataFrame(self.ctx.create_dataframe(partitions, name, schema)) + + def create_dataframe_from_logical_plan(self, plan: LogicalPlan) -> DataFrame: + """Create a `DataFrame` from an existing logical plan. + + Parameters + ---------- + plan : LogicalPlan + Logical plan. + + Returns + ------- + DataFrame + DataFrame representation of the logical plan. + """ + return DataFrame(self.ctx.create_dataframe_from_logical_plan(plan)) + + def from_pylist( + self, data: list[dict[str, Any]], name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from a list of dictionaries. + + Parameters + ---------- + data : list[dict[str, Any]] + List of dictionaries. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the list of dictionaries. + """ + return DataFrame(self.ctx.from_pylist(data, name)) + + def from_pydict( + self, data: dict[str, list[Any]], name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from a dictionary of lists. + + Parameters + ---------- + data : dict[str, list[Any]] + Dictionary of lists. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the dictionary of lists. + """ + return DataFrame(self.ctx.from_pydict(data, name)) + + def from_arrow_table( + self, data: pyarrow.Table, name: str | None = None + ) -> DataFrame: + """Create a `DataFrame` from an Arrow table. + + Parameters + ---------- + data : pyarrow.Table + Arrow table. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Arrow table. + """ + return DataFrame(self.ctx.from_arrow_table(data, name)) + + def from_pandas(self, data: pandas.DataFrame, name: str | None = None) -> DataFrame: + """Create a `DataFrame` from a Pandas DataFrame. + + Parameters + ---------- + data : pandas.DataFrame + Pandas DataFrame. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Pandas DataFrame. + """ + return DataFrame(self.ctx.from_pandas(data, name)) + + def from_polars(self, data: polars.DataFrame, name: str | None = None) -> DataFrame: + """Create a `DataFrame` from a Polars DataFrame. + + Parameters + ---------- + data : polars.DataFrame + Polars DataFrame. + name : str | None + Name of the DataFrame. + + Returns + ------- + DataFrame + DataFrame representation of the Polars DataFrame. + """ + return DataFrame(self.ctx.from_polars(data, name)) + + def register_table(self, name: str, table: pyarrow.Table) -> None: + self.ctx.register_table(name, table) + + def deregister_table(self, name: str) -> None: + self.ctx.deregister_table(name) + + def register_record_batches( + self, name: str, partitions: list[list[pyarrow.RecordBatch]] + ) -> None: + self.ctx.register_record_batches(name, partitions) + + def register_parquet( + self, + name: str, + path: str, + table_partition_cols: list[tuple[str, str]] = [], + parquet_pruning: bool = True, + file_extension: str = ".parquet", + skip_metadata: bool = True, + schema: pyarrow.Schema | None = None, + file_sort_order: list[list[Expr]] | None = None, + ) -> None: + """Register a Parquet file as a table. + + The registered table can be referenced from SQL statement executed against + this context. + + Parameters + ---------- + name : str + Name of the table to register. + path : str + Path to the Parquet file. + table_partition_cols : list[tuple[str, str]], optional + Partition columns, by default [] + parquet_pruning : bool, optional + Whether the parquet reader should use the predicate to prune row groups, by default True + file_extension : str, optional + File extension; only files with this extension are selected for data input, by default ".parquet" + skip_metadata : bool, optional + Whether the parquet reader should skip any metadata that may be in the file + schema. This can help avoid schema conflicts due to metadata. by default True + schema : pyarrow.Schema | None, optional + The data source schema, by default None + file_sort_order : list[list[Expr]] | None, optional + Sort order for the file, by default None + """ + self.ctx.register_parquet( + name, + path, + table_partition_cols, + parquet_pruning, + file_extension, + skip_metadata, + schema, + file_sort_order, + ) + + def register_csv( + self, + name: str, + path: str, + schema: pyarrow.Schema | None = None, + has_header: bool = True, + delimiter: str = ",", + schema_infer_max_records: int = 1000, + file_extension: str = ".csv", + file_compression_type: str | None = None, + ) -> None: + """Register a CSV file as a table. + + The registered table can be referenced from SQL statement executed against. + + Parameters + ---------- + name : str + Name of the table to register. + path : str + Path to the CSV file. + schema : pyarrow.Schema | None, optional + An optional schema representing the CSV file. If None, the CSV reader will try to infer it based on data in file, by default None + has_header : bool, optional + Whether the CSV file have a header. If schema inference is run on a file with no headers, default column names are created, by default True + delimiter : str, optional + An optional column delimiter, by default "," + schema_infer_max_records : int, optional + Maximum number of rows to read from CSV files for schema inference if needed, by default 1000 + file_extension : str, optional + File extension; only files with this extension are selected for data input, by default ".csv" + file_compression_type : str | None, optional + File compression type, by default None + """ + self.ctx.register_csv( + name, + path, + schema, + has_header, + delimiter, + schema_infer_max_records, + file_extension, + file_compression_type, + ) + + def register_json( + self, + name: str, + path: str, + schema: pyarrow.Schema | None = None, + schema_infer_max_records: int = 1000, + file_extension: str = ".json", + table_partition_cols: list[tuple[str, str]] = [], + file_compression_type: str | None = None, + ) -> None: + """Register a JSON file as a table. + + The registered table can be referenced from SQL statement executed against + this context. + + Parameters + ---------- + name : str + Name of the table to register. + path : str + Path to the JSON file. + schema : pyarrow.Schema | None, optional + The data source schema, by default None + schema_infer_max_records : int, optional + Maximum number of rows to read from JSON files for schema inference if needed, by default 1000 + file_extension : str, optional + File extension; only files with this extension are selected for data input, by default ".json" + table_partition_cols : list[tuple[str, str]], optional + Partition columns, by default [] + file_compression_type : str | None, optional + File compression type, by default None + """ + self.ctx.register_json( + name, + path, + schema, + schema_infer_max_records, + file_extension, + table_partition_cols, + file_compression_type, + ) + + def register_avro( + self, + name: str, + path: str, Review Comment: Same comment about `pathlib.Path` -- This is an automated message from the Apache Git Service. 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