830 lines
24 KiB
Python
830 lines
24 KiB
Python
![]() |
"""
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:func:`~pandas.eval` parsers.
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"""
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import ast
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from functools import partial, reduce
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from keyword import iskeyword
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import tokenize
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from typing import Callable, Optional, Set, Tuple, Type, TypeVar
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import numpy as np
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from pandas.compat import PY39
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import pandas.core.common as com
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from pandas.core.computation.ops import (
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ARITH_OPS_SYMS,
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BOOL_OPS_SYMS,
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CMP_OPS_SYMS,
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LOCAL_TAG,
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MATHOPS,
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REDUCTIONS,
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UNARY_OPS_SYMS,
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BinOp,
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Constant,
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Div,
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FuncNode,
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Op,
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Term,
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UnaryOp,
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UndefinedVariableError,
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is_term,
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)
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from pandas.core.computation.parsing import clean_backtick_quoted_toks, tokenize_string
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from pandas.core.computation.scope import Scope
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import pandas.io.formats.printing as printing
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def _rewrite_assign(tok: Tuple[int, str]) -> Tuple[int, str]:
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"""
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Rewrite the assignment operator for PyTables expressions that use ``=``
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as a substitute for ``==``.
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Parameters
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----------
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tok : tuple of int, str
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ints correspond to the all caps constants in the tokenize module
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Returns
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-------
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tuple of int, str
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Either the input or token or the replacement values
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"""
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toknum, tokval = tok
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return toknum, "==" if tokval == "=" else tokval
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def _replace_booleans(tok: Tuple[int, str]) -> Tuple[int, str]:
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"""
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Replace ``&`` with ``and`` and ``|`` with ``or`` so that bitwise
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precedence is changed to boolean precedence.
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Parameters
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----------
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tok : tuple of int, str
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ints correspond to the all caps constants in the tokenize module
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Returns
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-------
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tuple of int, str
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Either the input or token or the replacement values
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"""
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toknum, tokval = tok
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if toknum == tokenize.OP:
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if tokval == "&":
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return tokenize.NAME, "and"
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elif tokval == "|":
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return tokenize.NAME, "or"
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return toknum, tokval
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return toknum, tokval
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def _replace_locals(tok: Tuple[int, str]) -> Tuple[int, str]:
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"""
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Replace local variables with a syntactically valid name.
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Parameters
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----------
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tok : tuple of int, str
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ints correspond to the all caps constants in the tokenize module
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Returns
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-------
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tuple of int, str
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Either the input or token or the replacement values
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Notes
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-----
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This is somewhat of a hack in that we rewrite a string such as ``'@a'`` as
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``'__pd_eval_local_a'`` by telling the tokenizer that ``__pd_eval_local_``
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is a ``tokenize.OP`` and to replace the ``'@'`` symbol with it.
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"""
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toknum, tokval = tok
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if toknum == tokenize.OP and tokval == "@":
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return tokenize.OP, LOCAL_TAG
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return toknum, tokval
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def _compose2(f, g):
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"""
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Compose 2 callables.
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"""
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return lambda *args, **kwargs: f(g(*args, **kwargs))
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def _compose(*funcs):
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"""
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Compose 2 or more callables.
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"""
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assert len(funcs) > 1, "At least 2 callables must be passed to compose"
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return reduce(_compose2, funcs)
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def _preparse(
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source: str,
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f=_compose(
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_replace_locals, _replace_booleans, _rewrite_assign, clean_backtick_quoted_toks
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),
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) -> str:
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"""
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Compose a collection of tokenization functions.
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Parameters
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----------
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source : str
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A Python source code string
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f : callable
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This takes a tuple of (toknum, tokval) as its argument and returns a
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tuple with the same structure but possibly different elements. Defaults
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to the composition of ``_rewrite_assign``, ``_replace_booleans``, and
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``_replace_locals``.
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Returns
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-------
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str
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Valid Python source code
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Notes
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-----
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The `f` parameter can be any callable that takes *and* returns input of the
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form ``(toknum, tokval)``, where ``toknum`` is one of the constants from
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the ``tokenize`` module and ``tokval`` is a string.
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"""
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assert callable(f), "f must be callable"
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return tokenize.untokenize(f(x) for x in tokenize_string(source))
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def _is_type(t):
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"""
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Factory for a type checking function of type ``t`` or tuple of types.
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"""
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return lambda x: isinstance(x.value, t)
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_is_list = _is_type(list)
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_is_str = _is_type(str)
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# partition all AST nodes
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_all_nodes = frozenset(
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node
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for node in (getattr(ast, name) for name in dir(ast))
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if isinstance(node, type) and issubclass(node, ast.AST)
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)
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def _filter_nodes(superclass, all_nodes=_all_nodes):
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"""
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Filter out AST nodes that are subclasses of ``superclass``.
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"""
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node_names = (node.__name__ for node in all_nodes if issubclass(node, superclass))
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return frozenset(node_names)
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_all_node_names = frozenset(map(lambda x: x.__name__, _all_nodes))
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_mod_nodes = _filter_nodes(ast.mod)
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_stmt_nodes = _filter_nodes(ast.stmt)
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_expr_nodes = _filter_nodes(ast.expr)
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_expr_context_nodes = _filter_nodes(ast.expr_context)
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_boolop_nodes = _filter_nodes(ast.boolop)
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_operator_nodes = _filter_nodes(ast.operator)
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_unary_op_nodes = _filter_nodes(ast.unaryop)
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_cmp_op_nodes = _filter_nodes(ast.cmpop)
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_comprehension_nodes = _filter_nodes(ast.comprehension)
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_handler_nodes = _filter_nodes(ast.excepthandler)
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_arguments_nodes = _filter_nodes(ast.arguments)
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_keyword_nodes = _filter_nodes(ast.keyword)
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_alias_nodes = _filter_nodes(ast.alias)
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if not PY39:
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_slice_nodes = _filter_nodes(ast.slice)
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# nodes that we don't support directly but are needed for parsing
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_hacked_nodes = frozenset(["Assign", "Module", "Expr"])
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_unsupported_expr_nodes = frozenset(
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[
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"Yield",
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"GeneratorExp",
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"IfExp",
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"DictComp",
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"SetComp",
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"Repr",
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"Lambda",
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"Set",
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"AST",
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"Is",
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"IsNot",
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]
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)
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# these nodes are low priority or won't ever be supported (e.g., AST)
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_unsupported_nodes = (
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_stmt_nodes
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| _mod_nodes
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| _handler_nodes
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| _arguments_nodes
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| _keyword_nodes
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| _alias_nodes
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| _expr_context_nodes
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| _unsupported_expr_nodes
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) - _hacked_nodes
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# we're adding a different assignment in some cases to be equality comparison
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# and we don't want `stmt` and friends in their so get only the class whose
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# names are capitalized
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_base_supported_nodes = (_all_node_names - _unsupported_nodes) | _hacked_nodes
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intersection = _unsupported_nodes & _base_supported_nodes
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_msg = f"cannot both support and not support {intersection}"
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assert not intersection, _msg
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# TODO: Python 3.6.2: replace Callable[..., None] with Callable[..., NoReturn]
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def _node_not_implemented(node_name: str) -> Callable[..., None]:
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"""
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Return a function that raises a NotImplementedError with a passed node name.
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"""
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def f(self, *args, **kwargs):
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raise NotImplementedError(f"'{node_name}' nodes are not implemented")
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return f
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_T = TypeVar("_T", bound="BaseExprVisitor")
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def disallow(nodes: Set[str]) -> Callable[[Type[_T]], Type[_T]]:
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"""
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Decorator to disallow certain nodes from parsing. Raises a
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NotImplementedError instead.
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Returns
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-------
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callable
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"""
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def disallowed(cls: Type[_T]) -> Type[_T]:
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cls.unsupported_nodes = ()
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for node in nodes:
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new_method = _node_not_implemented(node)
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name = f"visit_{node}"
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cls.unsupported_nodes += (name,)
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setattr(cls, name, new_method)
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return cls
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return disallowed
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def _op_maker(op_class, op_symbol):
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"""
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Return a function to create an op class with its symbol already passed.
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Returns
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-------
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callable
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"""
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def f(self, node, *args, **kwargs):
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"""
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Return a partial function with an Op subclass with an operator already passed.
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Returns
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-------
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callable
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"""
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return partial(op_class, op_symbol, *args, **kwargs)
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return f
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_op_classes = {"binary": BinOp, "unary": UnaryOp}
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def add_ops(op_classes):
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"""
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Decorator to add default implementation of ops.
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"""
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def f(cls):
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for op_attr_name, op_class in op_classes.items():
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ops = getattr(cls, f"{op_attr_name}_ops")
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ops_map = getattr(cls, f"{op_attr_name}_op_nodes_map")
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for op in ops:
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op_node = ops_map[op]
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if op_node is not None:
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made_op = _op_maker(op_class, op)
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setattr(cls, f"visit_{op_node}", made_op)
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return cls
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return f
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@disallow(_unsupported_nodes)
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@add_ops(_op_classes)
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class BaseExprVisitor(ast.NodeVisitor):
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"""
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Custom ast walker. Parsers of other engines should subclass this class
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if necessary.
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Parameters
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----------
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env : Scope
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engine : str
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parser : str
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preparser : callable
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"""
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const_type: Type[Term] = Constant
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term_type = Term
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binary_ops = CMP_OPS_SYMS + BOOL_OPS_SYMS + ARITH_OPS_SYMS
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binary_op_nodes = (
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"Gt",
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"Lt",
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"GtE",
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"LtE",
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"Eq",
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"NotEq",
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"In",
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"NotIn",
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"BitAnd",
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"BitOr",
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"And",
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"Or",
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"Add",
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"Sub",
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"Mult",
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None,
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"Pow",
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"FloorDiv",
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"Mod",
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)
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binary_op_nodes_map = dict(zip(binary_ops, binary_op_nodes))
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unary_ops = UNARY_OPS_SYMS
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unary_op_nodes = "UAdd", "USub", "Invert", "Not"
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unary_op_nodes_map = {k: v for k, v in zip(unary_ops, unary_op_nodes)}
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rewrite_map = {
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ast.Eq: ast.In,
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ast.NotEq: ast.NotIn,
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ast.In: ast.In,
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ast.NotIn: ast.NotIn,
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}
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unsupported_nodes: Tuple[str, ...]
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def __init__(self, env, engine, parser, preparser=_preparse):
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self.env = env
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self.engine = engine
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self.parser = parser
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self.preparser = preparser
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self.assigner = None
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def visit(self, node, **kwargs):
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if isinstance(node, str):
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clean = self.preparser(node)
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try:
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node = ast.fix_missing_locations(ast.parse(clean))
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except SyntaxError as e:
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if any(iskeyword(x) for x in clean.split()):
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e.msg = "Python keyword not valid identifier in numexpr query"
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raise e
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method = "visit_" + type(node).__name__
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visitor = getattr(self, method)
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return visitor(node, **kwargs)
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def visit_Module(self, node, **kwargs):
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if len(node.body) != 1:
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raise SyntaxError("only a single expression is allowed")
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expr = node.body[0]
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return self.visit(expr, **kwargs)
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def visit_Expr(self, node, **kwargs):
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return self.visit(node.value, **kwargs)
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def _rewrite_membership_op(self, node, left, right):
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# the kind of the operator (is actually an instance)
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op_instance = node.op
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op_type = type(op_instance)
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# must be two terms and the comparison operator must be ==/!=/in/not in
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if is_term(left) and is_term(right) and op_type in self.rewrite_map:
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left_list, right_list = map(_is_list, (left, right))
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left_str, right_str = map(_is_str, (left, right))
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# if there are any strings or lists in the expression
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if left_list or right_list or left_str or right_str:
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op_instance = self.rewrite_map[op_type]()
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# pop the string variable out of locals and replace it with a list
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# of one string, kind of a hack
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if right_str:
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name = self.env.add_tmp([right.value])
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right = self.term_type(name, self.env)
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if left_str:
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name = self.env.add_tmp([left.value])
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left = self.term_type(name, self.env)
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op = self.visit(op_instance)
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return op, op_instance, left, right
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def _maybe_transform_eq_ne(self, node, left=None, right=None):
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if left is None:
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left = self.visit(node.left, side="left")
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if right is None:
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right = self.visit(node.right, side="right")
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op, op_class, left, right = self._rewrite_membership_op(node, left, right)
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return op, op_class, left, right
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def _maybe_downcast_constants(self, left, right):
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f32 = np.dtype(np.float32)
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if (
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left.is_scalar
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and hasattr(left, "value")
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and not right.is_scalar
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and right.return_type == f32
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):
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# right is a float32 array, left is a scalar
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name = self.env.add_tmp(np.float32(left.value))
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left = self.term_type(name, self.env)
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if (
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right.is_scalar
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and hasattr(right, "value")
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and not left.is_scalar
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and left.return_type == f32
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):
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||
|
# left is a float32 array, right is a scalar
|
||
|
name = self.env.add_tmp(np.float32(right.value))
|
||
|
right = self.term_type(name, self.env)
|
||
|
|
||
|
return left, right
|
||
|
|
||
|
def _maybe_eval(self, binop, eval_in_python):
|
||
|
# eval `in` and `not in` (for now) in "partial" python space
|
||
|
# things that can be evaluated in "eval" space will be turned into
|
||
|
# temporary variables. for example,
|
||
|
# [1,2] in a + 2 * b
|
||
|
# in that case a + 2 * b will be evaluated using numexpr, and the "in"
|
||
|
# call will be evaluated using isin (in python space)
|
||
|
return binop.evaluate(
|
||
|
self.env, self.engine, self.parser, self.term_type, eval_in_python
|
||
|
)
|
||
|
|
||
|
def _maybe_evaluate_binop(
|
||
|
self,
|
||
|
op,
|
||
|
op_class,
|
||
|
lhs,
|
||
|
rhs,
|
||
|
eval_in_python=("in", "not in"),
|
||
|
maybe_eval_in_python=("==", "!=", "<", ">", "<=", ">="),
|
||
|
):
|
||
|
res = op(lhs, rhs)
|
||
|
|
||
|
if res.has_invalid_return_type:
|
||
|
raise TypeError(
|
||
|
f"unsupported operand type(s) for {res.op}: "
|
||
|
f"'{lhs.type}' and '{rhs.type}'"
|
||
|
)
|
||
|
|
||
|
if self.engine != "pytables" and (
|
||
|
res.op in CMP_OPS_SYMS
|
||
|
and getattr(lhs, "is_datetime", False)
|
||
|
or getattr(rhs, "is_datetime", False)
|
||
|
):
|
||
|
# all date ops must be done in python bc numexpr doesn't work
|
||
|
# well with NaT
|
||
|
return self._maybe_eval(res, self.binary_ops)
|
||
|
|
||
|
if res.op in eval_in_python:
|
||
|
# "in"/"not in" ops are always evaluated in python
|
||
|
return self._maybe_eval(res, eval_in_python)
|
||
|
elif self.engine != "pytables":
|
||
|
if (
|
||
|
getattr(lhs, "return_type", None) == object
|
||
|
or getattr(rhs, "return_type", None) == object
|
||
|
):
|
||
|
# evaluate "==" and "!=" in python if either of our operands
|
||
|
# has an object return type
|
||
|
return self._maybe_eval(res, eval_in_python + maybe_eval_in_python)
|
||
|
return res
|
||
|
|
||
|
def visit_BinOp(self, node, **kwargs):
|
||
|
op, op_class, left, right = self._maybe_transform_eq_ne(node)
|
||
|
left, right = self._maybe_downcast_constants(left, right)
|
||
|
return self._maybe_evaluate_binop(op, op_class, left, right)
|
||
|
|
||
|
def visit_Div(self, node, **kwargs):
|
||
|
return lambda lhs, rhs: Div(lhs, rhs)
|
||
|
|
||
|
def visit_UnaryOp(self, node, **kwargs):
|
||
|
op = self.visit(node.op)
|
||
|
operand = self.visit(node.operand)
|
||
|
return op(operand)
|
||
|
|
||
|
def visit_Name(self, node, **kwargs):
|
||
|
return self.term_type(node.id, self.env, **kwargs)
|
||
|
|
||
|
def visit_NameConstant(self, node, **kwargs):
|
||
|
return self.const_type(node.value, self.env)
|
||
|
|
||
|
def visit_Num(self, node, **kwargs):
|
||
|
return self.const_type(node.n, self.env)
|
||
|
|
||
|
def visit_Constant(self, node, **kwargs):
|
||
|
return self.const_type(node.n, self.env)
|
||
|
|
||
|
def visit_Str(self, node, **kwargs):
|
||
|
name = self.env.add_tmp(node.s)
|
||
|
return self.term_type(name, self.env)
|
||
|
|
||
|
def visit_List(self, node, **kwargs):
|
||
|
name = self.env.add_tmp([self.visit(e)(self.env) for e in node.elts])
|
||
|
return self.term_type(name, self.env)
|
||
|
|
||
|
visit_Tuple = visit_List
|
||
|
|
||
|
def visit_Index(self, node, **kwargs):
|
||
|
""" df.index[4] """
|
||
|
return self.visit(node.value)
|
||
|
|
||
|
def visit_Subscript(self, node, **kwargs):
|
||
|
import pandas as pd
|
||
|
|
||
|
value = self.visit(node.value)
|
||
|
slobj = self.visit(node.slice)
|
||
|
result = pd.eval(
|
||
|
slobj, local_dict=self.env, engine=self.engine, parser=self.parser
|
||
|
)
|
||
|
try:
|
||
|
# a Term instance
|
||
|
v = value.value[result]
|
||
|
except AttributeError:
|
||
|
# an Op instance
|
||
|
lhs = pd.eval(
|
||
|
value, local_dict=self.env, engine=self.engine, parser=self.parser
|
||
|
)
|
||
|
v = lhs[result]
|
||
|
name = self.env.add_tmp(v)
|
||
|
return self.term_type(name, env=self.env)
|
||
|
|
||
|
def visit_Slice(self, node, **kwargs):
|
||
|
""" df.index[slice(4,6)] """
|
||
|
lower = node.lower
|
||
|
if lower is not None:
|
||
|
lower = self.visit(lower).value
|
||
|
upper = node.upper
|
||
|
if upper is not None:
|
||
|
upper = self.visit(upper).value
|
||
|
step = node.step
|
||
|
if step is not None:
|
||
|
step = self.visit(step).value
|
||
|
|
||
|
return slice(lower, upper, step)
|
||
|
|
||
|
def visit_Assign(self, node, **kwargs):
|
||
|
"""
|
||
|
support a single assignment node, like
|
||
|
|
||
|
c = a + b
|
||
|
|
||
|
set the assigner at the top level, must be a Name node which
|
||
|
might or might not exist in the resolvers
|
||
|
|
||
|
"""
|
||
|
if len(node.targets) != 1:
|
||
|
raise SyntaxError("can only assign a single expression")
|
||
|
if not isinstance(node.targets[0], ast.Name):
|
||
|
raise SyntaxError("left hand side of an assignment must be a single name")
|
||
|
if self.env.target is None:
|
||
|
raise ValueError("cannot assign without a target object")
|
||
|
|
||
|
try:
|
||
|
assigner = self.visit(node.targets[0], **kwargs)
|
||
|
except UndefinedVariableError:
|
||
|
assigner = node.targets[0].id
|
||
|
|
||
|
self.assigner = getattr(assigner, "name", assigner)
|
||
|
if self.assigner is None:
|
||
|
raise SyntaxError(
|
||
|
"left hand side of an assignment must be a single resolvable name"
|
||
|
)
|
||
|
|
||
|
return self.visit(node.value, **kwargs)
|
||
|
|
||
|
def visit_Attribute(self, node, **kwargs):
|
||
|
attr = node.attr
|
||
|
value = node.value
|
||
|
|
||
|
ctx = node.ctx
|
||
|
if isinstance(ctx, ast.Load):
|
||
|
# resolve the value
|
||
|
resolved = self.visit(value).value
|
||
|
try:
|
||
|
v = getattr(resolved, attr)
|
||
|
name = self.env.add_tmp(v)
|
||
|
return self.term_type(name, self.env)
|
||
|
except AttributeError:
|
||
|
# something like datetime.datetime where scope is overridden
|
||
|
if isinstance(value, ast.Name) and value.id == attr:
|
||
|
return resolved
|
||
|
raise
|
||
|
|
||
|
raise ValueError(f"Invalid Attribute context {type(ctx).__name__}")
|
||
|
|
||
|
def visit_Call(self, node, side=None, **kwargs):
|
||
|
|
||
|
if isinstance(node.func, ast.Attribute) and node.func.attr != "__call__":
|
||
|
res = self.visit_Attribute(node.func)
|
||
|
elif not isinstance(node.func, ast.Name):
|
||
|
raise TypeError("Only named functions are supported")
|
||
|
else:
|
||
|
try:
|
||
|
res = self.visit(node.func)
|
||
|
except UndefinedVariableError:
|
||
|
# Check if this is a supported function name
|
||
|
try:
|
||
|
res = FuncNode(node.func.id)
|
||
|
except ValueError:
|
||
|
# Raise original error
|
||
|
raise
|
||
|
|
||
|
if res is None:
|
||
|
# pandas\core\computation\expr.py:663: error: "expr" has no
|
||
|
# attribute "id" [attr-defined]
|
||
|
raise ValueError(
|
||
|
f"Invalid function call {node.func.id}" # type: ignore[attr-defined]
|
||
|
)
|
||
|
if hasattr(res, "value"):
|
||
|
res = res.value
|
||
|
|
||
|
if isinstance(res, FuncNode):
|
||
|
|
||
|
new_args = [self.visit(arg) for arg in node.args]
|
||
|
|
||
|
if node.keywords:
|
||
|
raise TypeError(
|
||
|
f'Function "{res.name}" does not support keyword arguments'
|
||
|
)
|
||
|
|
||
|
return res(*new_args)
|
||
|
|
||
|
else:
|
||
|
|
||
|
new_args = [self.visit(arg).value for arg in node.args]
|
||
|
|
||
|
for key in node.keywords:
|
||
|
if not isinstance(key, ast.keyword):
|
||
|
# pandas\core\computation\expr.py:684: error: "expr" has no
|
||
|
# attribute "id" [attr-defined]
|
||
|
raise ValueError(
|
||
|
"keyword error in function call " # type: ignore[attr-defined]
|
||
|
f"'{node.func.id}'"
|
||
|
)
|
||
|
|
||
|
if key.arg:
|
||
|
kwargs[key.arg] = self.visit(key.value).value
|
||
|
|
||
|
return self.const_type(res(*new_args, **kwargs), self.env)
|
||
|
|
||
|
def translate_In(self, op):
|
||
|
return op
|
||
|
|
||
|
def visit_Compare(self, node, **kwargs):
|
||
|
ops = node.ops
|
||
|
comps = node.comparators
|
||
|
|
||
|
# base case: we have something like a CMP b
|
||
|
if len(comps) == 1:
|
||
|
op = self.translate_In(ops[0])
|
||
|
binop = ast.BinOp(op=op, left=node.left, right=comps[0])
|
||
|
return self.visit(binop)
|
||
|
|
||
|
# recursive case: we have a chained comparison, a CMP b CMP c, etc.
|
||
|
left = node.left
|
||
|
values = []
|
||
|
for op, comp in zip(ops, comps):
|
||
|
new_node = self.visit(
|
||
|
ast.Compare(comparators=[comp], left=left, ops=[self.translate_In(op)])
|
||
|
)
|
||
|
left = comp
|
||
|
values.append(new_node)
|
||
|
return self.visit(ast.BoolOp(op=ast.And(), values=values))
|
||
|
|
||
|
def _try_visit_binop(self, bop):
|
||
|
if isinstance(bop, (Op, Term)):
|
||
|
return bop
|
||
|
return self.visit(bop)
|
||
|
|
||
|
def visit_BoolOp(self, node, **kwargs):
|
||
|
def visitor(x, y):
|
||
|
lhs = self._try_visit_binop(x)
|
||
|
rhs = self._try_visit_binop(y)
|
||
|
|
||
|
op, op_class, lhs, rhs = self._maybe_transform_eq_ne(node, lhs, rhs)
|
||
|
return self._maybe_evaluate_binop(op, node.op, lhs, rhs)
|
||
|
|
||
|
operands = node.values
|
||
|
return reduce(visitor, operands)
|
||
|
|
||
|
|
||
|
_python_not_supported = frozenset(["Dict", "BoolOp", "In", "NotIn"])
|
||
|
_numexpr_supported_calls = frozenset(REDUCTIONS + MATHOPS)
|
||
|
|
||
|
|
||
|
@disallow(
|
||
|
(_unsupported_nodes | _python_not_supported)
|
||
|
- (_boolop_nodes | frozenset(["BoolOp", "Attribute", "In", "NotIn", "Tuple"]))
|
||
|
)
|
||
|
class PandasExprVisitor(BaseExprVisitor):
|
||
|
def __init__(
|
||
|
self,
|
||
|
env,
|
||
|
engine,
|
||
|
parser,
|
||
|
preparser=partial(
|
||
|
_preparse,
|
||
|
f=_compose(_replace_locals, _replace_booleans, clean_backtick_quoted_toks),
|
||
|
),
|
||
|
):
|
||
|
super().__init__(env, engine, parser, preparser)
|
||
|
|
||
|
|
||
|
@disallow(_unsupported_nodes | _python_not_supported | frozenset(["Not"]))
|
||
|
class PythonExprVisitor(BaseExprVisitor):
|
||
|
def __init__(self, env, engine, parser, preparser=lambda x: x):
|
||
|
super().__init__(env, engine, parser, preparser=preparser)
|
||
|
|
||
|
|
||
|
class Expr:
|
||
|
"""
|
||
|
Object encapsulating an expression.
|
||
|
|
||
|
Parameters
|
||
|
----------
|
||
|
expr : str
|
||
|
engine : str, optional, default 'numexpr'
|
||
|
parser : str, optional, default 'pandas'
|
||
|
env : Scope, optional, default None
|
||
|
level : int, optional, default 2
|
||
|
"""
|
||
|
|
||
|
env: Scope
|
||
|
engine: str
|
||
|
parser: str
|
||
|
|
||
|
def __init__(
|
||
|
self,
|
||
|
expr,
|
||
|
engine: str = "numexpr",
|
||
|
parser: str = "pandas",
|
||
|
env: Optional[Scope] = None,
|
||
|
level: int = 0,
|
||
|
):
|
||
|
self.expr = expr
|
||
|
self.env = env or Scope(level=level + 1)
|
||
|
self.engine = engine
|
||
|
self.parser = parser
|
||
|
self._visitor = PARSERS[parser](self.env, self.engine, self.parser)
|
||
|
self.terms = self.parse()
|
||
|
|
||
|
@property
|
||
|
def assigner(self):
|
||
|
return getattr(self._visitor, "assigner", None)
|
||
|
|
||
|
def __call__(self):
|
||
|
return self.terms(self.env)
|
||
|
|
||
|
def __repr__(self) -> str:
|
||
|
return printing.pprint_thing(self.terms)
|
||
|
|
||
|
def __len__(self) -> int:
|
||
|
return len(self.expr)
|
||
|
|
||
|
def parse(self):
|
||
|
"""
|
||
|
Parse an expression.
|
||
|
"""
|
||
|
return self._visitor.visit(self.expr)
|
||
|
|
||
|
@property
|
||
|
def names(self):
|
||
|
"""
|
||
|
Get the names in an expression.
|
||
|
"""
|
||
|
if is_term(self.terms):
|
||
|
return frozenset([self.terms.name])
|
||
|
return frozenset(term.name for term in com.flatten(self.terms))
|
||
|
|
||
|
|
||
|
PARSERS = {"python": PythonExprVisitor, "pandas": PandasExprVisitor}
|