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"""Top level ``eval`` module.
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"""
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- import warnings
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import tokenize
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from pandas .io .formats .printing import pprint_thing
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from pandas .core .computation import _NUMEXPR_INSTALLED
@@ -148,7 +147,7 @@ def _check_for_locals(expr, stack_level, parser):
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def eval (expr , parser = 'pandas' , engine = None , truediv = True ,
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local_dict = None , global_dict = None , resolvers = (), level = 0 ,
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- target = None , inplace = None ):
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+ target = None , inplace = False ):
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"""Evaluate a Python expression as a string using various backends.
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The following arithmetic operations are supported: ``+``, ``-``, ``*``,
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scope. Most users will **not** need to change this parameter.
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target : a target object for assignment, optional, default is None
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essentially this is a passed in resolver
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- inplace : bool, default True
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- If expression mutates, whether to modify object inplace or return
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- copy with mutation.
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+ inplace : bool, default False
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+ If `target` is provided, and the expression mutates `target`, whether
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+ to modify `target` inplace. Otherwise, return a copy of `target` with
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+ the mutation.
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- WARNING: inplace=None currently falls back to to True, but
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- in a future version, will default to False. Use inplace=True
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- explicitly rather than relying on the default.
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+ If `inplace=True`, but `target` cannot be modified inplace, a
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+ ValueError will be raised. Examples of targets that cannot be
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+ modified inplace are integers and strings. Examples of targets
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+ that can be modified inplace are lists and class instances.
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Returns
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-------
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ndarray, numeric scalar, DataFrame, Series
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+ Raises
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+ ------
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+ ValueError : `inplace=True`, but the provided `target` could not be
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+ modified inplace.
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Notes
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-----
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The ``dtype`` of any objects involved in an arithmetic ``%`` operation are
@@ -232,8 +237,23 @@ def eval(expr, parser='pandas', engine=None, truediv=True,
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pandas.DataFrame.query
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pandas.DataFrame.eval
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"""
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- inplace = validate_bool_kwarg (inplace , 'inplace' )
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- first_expr = True
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+
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+ def is_modifiable (obj ):
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+ target_type = type (obj ).__name__
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+ return hasattr (obj , "__dict__" ) or target_type == "dict"
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+
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+ inplace = validate_bool_kwarg (inplace , "inplace" )
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+
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+ # "Primitives" cannot be modified inplace because
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+ # they have no attributes that we can modify.
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+ #
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+ # The only exceptions are lists and dictionaries,
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+ # whose elements can be modified inplace.
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+ modifiable = is_modifiable (target )
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+
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+ if inplace and not modifiable :
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+ raise ValueError ("Cannot modify the provided target inplace" )
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+
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if isinstance (expr , string_types ):
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_check_expression (expr )
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exprs = [e .strip () for e in expr .splitlines () if e .strip () != '' ]
@@ -245,7 +265,10 @@ def eval(expr, parser='pandas', engine=None, truediv=True,
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raise ValueError ("multi-line expressions are only valid in the "
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"context of data, use DataFrame.eval" )
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+ ret = None
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first_expr = True
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+ target_modified = False
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+
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for expr in exprs :
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expr = _convert_expression (expr )
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engine = _check_engine (engine )
@@ -272,15 +295,13 @@ def eval(expr, parser='pandas', engine=None, truediv=True,
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# assign if needed
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if env .target is not None and parsed_expr .assigner is not None :
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- if inplace is None :
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- warnings .warn (
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- "eval expressions containing an assignment currently"
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- "default to operating inplace.\n This will change in "
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- "a future version of pandas, use inplace=True to "
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- "avoid this warning." ,
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- FutureWarning , stacklevel = 3 )
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- inplace = True
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+ if not is_modifiable (env .target ):
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+ raise ValueError ("Cannot assign expression output to target" )
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+
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+ target_modified = True
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+
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+ # Cannot assign to the target if it is not assignable.
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# if returning a copy, copy only on the first assignment
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if not inplace and first_expr :
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target = env .target .copy ()
@@ -304,7 +325,6 @@ def eval(expr, parser='pandas', engine=None, truediv=True,
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ret = None
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first_expr = False
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- if not inplace and inplace is not None :
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- return target
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-
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- return ret
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+ # We want to exclude `inplace=None` as being False.
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+ if inplace is False :
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+ return target if target_modified else ret
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