Mh6SrSSKJr SSKrSSKJr SSKrSSKJr SSK J r SSK J r SSK Jr SS KJrJr SS KJr SS KJr SS KJr SS KJr \(aSSKJr SSjrSSjrSrSrSSjr SSjr!SSSjjr"g)z Top level ``eval`` module. ) annotationsN) TYPE_CHECKING)find_stack_level)validate_bool_kwargis_extension_array_dtype)ENGINES)PARSERSExpr)tokenize_string) ensure_scope)NDFrame) pprint_thing)BinOpcSSKJn SSKJn Uc U(aSOSnU[;a/[ [R "55n[SUSU35eUS:XaU(d [S5eU$) z Make sure a valid engine is passed. Parameters ---------- engine : str String to validate. Raises ------ KeyError * If an invalid engine is passed. ImportError * If numexpr was requested but doesn't exist. Returns ------- str Engine name. r)NUMEXPR_INSTALLED) USE_NUMEXPRnumexprpythonzInvalid engine 'z' passed, valid engines are z~'numexpr' is not installed or an unsupported version. Cannot use engine='numexpr' for query/eval if 'numexpr' is not installed) pandas.core.computation.checkr#pandas.core.computation.expressionsrr listkeysKeyError ImportError)enginerr valid_enginess N/var/www/html/env/lib/python3.13/site-packages/pandas/core/computation/eval.py _check_enginersv*@? ~)x WW\\^, vh&B=/ R  #4 L  Mc`U[;a$[SUS[R"535eg)z Make sure a valid parser is passed. Parameters ---------- parser : str Raises ------ KeyError * If an invalid parser is passed zInvalid parser 'z' passed, valid parsers are N)r rr)parsers r _check_parserr#Ks6Wvh&B7<<>BR S  r cUb?UH8n[US5(aM[U5Rn[SUS35e gg)N __getitem__zResolver of type 'z+' does not implement the __getitem__ method)hasattrtype__name__ TypeError) resolversresolvernames r_check_resolversr-^sQ!H8]33H~..(/77"r c(U(d [S5eg)z Make sure an expression is not an empty string Parameters ---------- expr : object An object that can be converted to a string Raises ------ ValueError * If expr is an empty string zexpr cannot be an empty stringN) ValueError)exprs r_check_expressionr1is 9:: r c2[U5n[U5 U$)a Convert an object to an expression. This function converts an object to an expression (a unicode string) and checks to make sure it isn't empty after conversion. This is used to convert operators to their string representation for recursive calls to :func:`~pandas.eval`. Parameters ---------- expr : object The object to be converted to a string. Returns ------- str The string representation of an object. Raises ------ ValueError * If the expression is empty. )rr1)r0ss r_convert_expressionr4{s0 TAa Hr cUS:HnUS:gnU(aSnO U(aSnU(dU(a<[U5H,upgU[R:XdMUS:XdM#[W5e gg)Nrpandasz5The '@' prefix is only supported by the pandas parserzuThe '@' prefix is not allowed in top-level eval calls. please refer to your variables by name without the '@' prefix.@)r tokenizeOP SyntaxError)r0 stack_levelr"at_top_of_stacknot_pandas_parsermsgtoknumtokvals r_check_for_localsrAsh!Q&O(*E  M +-d3NF$3!#&&4,r c 4[US5n[U[5(aO[U5 UR 5V s/sH(oR 5S:wdMU R 5PM* n n OU/n [ U 5S:n U (aUc [S5e[U5n[U5 [U5 Sn Sn SnU GHn[U5n[XU5 [US-UUUUS9n[XXS 9nUS :Xa[UR R"5(dC[%UR S S5bO['S UR R(55(a$[*R,"S [.[15S9 Sn[2UnU"U5nUR55n UR6c$U (a [S5eU(a [S5eUR6nUR8cGM4UcGM:SnU(dJU (aCUR8n[U[:5(aUR=SS9nOUR=5nO UR8nU(a([U[:5(aXR@SS2U4'OXU'U(dUU 04nOUHnUU;dM U UU' O UUU 04- nSn Sn GM USLa U(aU$U $gs sn f![>an[S5UeSnAff=f![B[D4an[S5UeSnAff=f)a Evaluate a Python expression as a string using various backends. The following arithmetic operations are supported: ``+``, ``-``, ``*``, ``/``, ``**``, ``%``, ``//`` (python engine only) along with the following boolean operations: ``|`` (or), ``&`` (and), and ``~`` (not). Additionally, the ``'pandas'`` parser allows the use of :keyword:`and`, :keyword:`or`, and :keyword:`not` with the same semantics as the corresponding bitwise operators. :class:`~pandas.Series` and :class:`~pandas.DataFrame` objects are supported and behave as they would with plain ol' Python evaluation. Parameters ---------- expr : str The expression to evaluate. This string cannot contain any Python `statements `__, only Python `expressions `__. parser : {'pandas', 'python'}, default 'pandas' The parser to use to construct the syntax tree from the expression. The default of ``'pandas'`` parses code slightly different than standard Python. Alternatively, you can parse an expression using the ``'python'`` parser to retain strict Python semantics. See the :ref:`enhancing performance ` documentation for more details. engine : {'python', 'numexpr'}, default 'numexpr' The engine used to evaluate the expression. Supported engines are - None : tries to use ``numexpr``, falls back to ``python`` - ``'numexpr'`` : This default engine evaluates pandas objects using numexpr for large speed ups in complex expressions with large frames. - ``'python'`` : Performs operations as if you had ``eval``'d in top level python. This engine is generally not that useful. More backends may be available in the future. local_dict : dict or None, optional A dictionary of local variables, taken from locals() by default. global_dict : dict or None, optional A dictionary of global variables, taken from globals() by default. resolvers : list of dict-like or None, optional A list of objects implementing the ``__getitem__`` special method that you can use to inject an additional collection of namespaces to use for variable lookup. For example, this is used in the :meth:`~DataFrame.query` method to inject the ``DataFrame.index`` and ``DataFrame.columns`` variables that refer to their respective :class:`~pandas.DataFrame` instance attributes. level : int, optional The number of prior stack frames to traverse and add to the current scope. Most users will **not** need to change this parameter. target : object, optional, default None This is the target object for assignment. It is used when there is variable assignment in the expression. If so, then `target` must support item assignment with string keys, and if a copy is being returned, it must also support `.copy()`. inplace : bool, default False If `target` is provided, and the expression mutates `target`, whether to modify `target` inplace. Otherwise, return a copy of `target` with the mutation. Returns ------- ndarray, numeric scalar, DataFrame, Series, or None The completion value of evaluating the given code or None if ``inplace=True``. Raises ------ ValueError There are many instances where such an error can be raised: - `target=None`, but the expression is multiline. - The expression is multiline, but not all them have item assignment. An example of such an arrangement is this: a = b + 1 a + 2 Here, there are expressions on different lines, making it multiline, but the last line has no variable assigned to the output of `a + 2`. - `inplace=True`, but the expression is missing item assignment. - Item assignment is provided, but the `target` does not support string item assignment. - Item assignment is provided and `inplace=False`, but the `target` does not support the `.copy()` method See Also -------- DataFrame.query : Evaluates a boolean expression to query the columns of a frame. DataFrame.eval : Evaluate a string describing operations on DataFrame columns. Notes ----- The ``dtype`` of any objects involved in an arithmetic ``%`` operation are recursively cast to ``float64``. See the :ref:`enhancing performance ` documentation for more details. Examples -------- >>> df = pd.DataFrame({"animal": ["dog", "pig"], "age": [10, 20]}) >>> df animal age 0 dog 10 1 pig 20 We can add a new column using ``pd.eval``: >>> pd.eval("double_age = df.age * 2", target=df) animal age double_age 0 dog 10 20 1 pig 20 40 inplaceNzPmulti-line expressions are only valid in the context of data, use DataFrame.evalTF) global_dict local_dictr*target)rr"envr operand_typesc38# UHn[U5v M g7f)Nr).0elems r eval..Us;D)..;szEngine has switched to 'python' because numexpr does not support extension array dtypes. 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