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 | 1 | +# Licensed to the Apache Software Foundation (ASF) under one  | 
 | 2 | +# or more contributor license agreements.  See the NOTICE file  | 
 | 3 | +# distributed with this work for additional information  | 
 | 4 | +# regarding copyright ownership.  The ASF licenses this file  | 
 | 5 | +# to you under the Apache License, Version 2.0 (the  | 
 | 6 | +# "License"); you may not use this file except in compliance  | 
 | 7 | +# with the License.  You may obtain a copy of the License at  | 
 | 8 | +#  | 
 | 9 | +#   http://www.apache.org/licenses/LICENSE-2.0  | 
 | 10 | +#  | 
 | 11 | +# Unless required by applicable law or agreed to in writing,  | 
 | 12 | +# software distributed under the License is distributed on an  | 
 | 13 | +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY  | 
 | 14 | +# KIND, either express or implied.  See the License for the  | 
 | 15 | +# specific language governing permissions and limitations  | 
 | 16 | +# under the License.  | 
 | 17 | + | 
 | 18 | +"""This module supports physical and logical plans in DataFusion."""  | 
 | 19 | + | 
 | 20 | +from __future__ import annotations  | 
 | 21 | + | 
 | 22 | +import datafusion._internal as df_internal  | 
 | 23 | + | 
 | 24 | +from typing import List, Any, TYPE_CHECKING  | 
 | 25 | + | 
 | 26 | +if TYPE_CHECKING:  | 
 | 27 | +    from datafusion.context import SessionContext  | 
 | 28 | + | 
 | 29 | +__all__ = [  | 
 | 30 | +    "LogicalPlan",  | 
 | 31 | +    "ExecutionPlan",  | 
 | 32 | +]  | 
 | 33 | + | 
 | 34 | + | 
 | 35 | +class LogicalPlan:  | 
 | 36 | +    """Logical Plan.  | 
 | 37 | +
  | 
 | 38 | +    A `LogicalPlan` is a node in a tree of relational operators (such as  | 
 | 39 | +    Projection or Filter).  | 
 | 40 | +
  | 
 | 41 | +    Represents transforming an input relation (table) to an output relation  | 
 | 42 | +    (table) with a potentially different schema. Plans form a dataflow tree  | 
 | 43 | +    where data flows from leaves up to the root to produce the query result.  | 
 | 44 | +
  | 
 | 45 | +    `LogicalPlan`s can be created by the SQL query planner, the DataFrame API,  | 
 | 46 | +    or programmatically (for example custom query languages).  | 
 | 47 | +    """  | 
 | 48 | + | 
 | 49 | +    def __init__(self, plan: df_internal.LogicalPlan) -> None:  | 
 | 50 | +        """This constructor should not be called by the end user."""  | 
 | 51 | +        self._raw_plan = plan  | 
 | 52 | + | 
 | 53 | +    def to_variant(self) -> Any:  | 
 | 54 | +        """Convert the logical plan into its specific variant."""  | 
 | 55 | +        return self._raw_plan.to_variant()  | 
 | 56 | + | 
 | 57 | +    def inputs(self) -> List[LogicalPlan]:  | 
 | 58 | +        """Returns the list of inputs to the logical plan."""  | 
 | 59 | +        return [LogicalPlan(p) for p in self._raw_plan.inputs()]  | 
 | 60 | + | 
 | 61 | +    def __repr__(self) -> str:  | 
 | 62 | +        """Generate a printable representation of the plan."""  | 
 | 63 | +        return self._raw_plan.__repr__()  | 
 | 64 | + | 
 | 65 | +    def display(self) -> str:  | 
 | 66 | +        """Print the logical plan."""  | 
 | 67 | +        return self._raw_plan.display()  | 
 | 68 | + | 
 | 69 | +    def display_indent(self) -> str:  | 
 | 70 | +        """Print an indented form of the logical plan."""  | 
 | 71 | +        return self._raw_plan.display_indent()  | 
 | 72 | + | 
 | 73 | +    def display_indent_schema(self) -> str:  | 
 | 74 | +        """Print an indented form of the schema for the logical plan."""  | 
 | 75 | +        return self._raw_plan.display_indent_schema()  | 
 | 76 | + | 
 | 77 | +    def display_graphviz(self) -> str:  | 
 | 78 | +        """Print the graph visualization of the logical plan.  | 
 | 79 | +
  | 
 | 80 | +        Returns a `format`able structure that produces lines meant for graphical display  | 
 | 81 | +        using the `DOT` language. This format can be visualized using software from  | 
 | 82 | +        [`graphviz`](https://graphviz.org/)  | 
 | 83 | +        """  | 
 | 84 | +        return self._raw_plan.display_graphviz()  | 
 | 85 | + | 
 | 86 | +    @staticmethod  | 
 | 87 | +    def from_proto(ctx: SessionContext, data: bytes) -> LogicalPlan:  | 
 | 88 | +        """Create a LogicalPlan from protobuf bytes.  | 
 | 89 | +
  | 
 | 90 | +        Tables created in memory from record batches are currently not supported.  | 
 | 91 | +        """  | 
 | 92 | +        return LogicalPlan(df_internal.LogicalPlan.from_proto(ctx.ctx, data))  | 
 | 93 | + | 
 | 94 | +    def to_proto(self) -> bytes:  | 
 | 95 | +        """Convert a LogicalPlan to protobuf bytes.  | 
 | 96 | +
  | 
 | 97 | +        Tables created in memory from record batches are currently not supported.  | 
 | 98 | +        """  | 
 | 99 | +        return self._raw_plan.to_proto()  | 
 | 100 | + | 
 | 101 | + | 
 | 102 | +class ExecutionPlan:  | 
 | 103 | +    """Represent nodes in the DataFusion Physical Plan."""  | 
 | 104 | + | 
 | 105 | +    def __init__(self, plan: df_internal.ExecutionPlan) -> None:  | 
 | 106 | +        """This constructor should not be called by the end user."""  | 
 | 107 | +        self._raw_plan = plan  | 
 | 108 | + | 
 | 109 | +    def children(self) -> List[ExecutionPlan]:  | 
 | 110 | +        """Get a list of children `ExecutionPlan`s that act as inputs to this plan.  | 
 | 111 | +
  | 
 | 112 | +        The returned list will be empty for leaf nodes such as scans, will contain a  | 
 | 113 | +        single value for unary nodes, or two values for binary nodes (such as joins).  | 
 | 114 | +        """  | 
 | 115 | +        return [ExecutionPlan(e) for e in self._raw_plan.children()]  | 
 | 116 | + | 
 | 117 | +    def display(self) -> str:  | 
 | 118 | +        """Print the physical plan."""  | 
 | 119 | +        return self._raw_plan.display()  | 
 | 120 | + | 
 | 121 | +    def display_indent(self) -> str:  | 
 | 122 | +        """Print an indented form of the physical plan."""  | 
 | 123 | +        return self._raw_plan.display_indent()  | 
 | 124 | + | 
 | 125 | +    def __repr__(self) -> str:  | 
 | 126 | +        """Print a string representation of the physical plan."""  | 
 | 127 | +        return self._raw_plan.__repr__()  | 
 | 128 | + | 
 | 129 | +    @property  | 
 | 130 | +    def partition_count(self) -> int:  | 
 | 131 | +        """Returns the number of partitions in the physical plan."""  | 
 | 132 | +        return self._raw_plan.partition_count  | 
 | 133 | + | 
 | 134 | +    @staticmethod  | 
 | 135 | +    def from_proto(ctx: SessionContext, data: bytes) -> ExecutionPlan:  | 
 | 136 | +        """Create an ExecutionPlan from protobuf bytes.  | 
 | 137 | +
  | 
 | 138 | +        Tables created in memory from record batches are currently not supported.  | 
 | 139 | +        """  | 
 | 140 | +        return ExecutionPlan(df_internal.ExecutionPlan.from_proto(ctx.ctx, data))  | 
 | 141 | + | 
 | 142 | +    def to_proto(self) -> bytes:  | 
 | 143 | +        """Convert an ExecutionPlan into protobuf bytes.  | 
 | 144 | +
  | 
 | 145 | +        Tables created in memory from record batches are currently not supported.  | 
 | 146 | +        """  | 
 | 147 | +        return self._raw_plan.to_proto()  | 
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