+ ܳjCdRt^RIHt^RIt^RIHtHt^RIt^RIH t ^RI H t ]'d^RI H t ^RIHt^RIHt^R IHt!R R 4t!R R 4tRRR3RRllt!RR4t]tRRltRt] !R4RRl4tRt] !R4RRl4tRt] !R4RR l4tR#)!z accessor.py contains base classes for implementing accessor properties that can be mixed into or pinned onto other pandas classes. ) annotationsN) TYPE_CHECKINGfinal) set_module)find_stack_level)Callable)TypeTIndex)NDFrameca]tRt^t$]!4tR]R&]!4tR]R&] RRl4t RRlt R V3R llt R t V;t#) DirNamesMixinset[str] _accessorszfrozenset[str] _hidden_attrscV^8dQhRR/#returnr)formats"U/home/luca/screen-checking/.venv/lib/python3.14/site-packages/pandas/core/accessor.py __annotate__DirNamesMixin.__annotate__$s444c <VPVP,#)z* Delete unwanted __dir__ for this object. )rr)selfs&r_dir_deletionsDirNamesMixin._dir_deletions#s !3!333rcV^8dQhRR/#rr)rs"rrr*sUUUrc jVPUu0uFp\W4'gKVkK up#uupi)z) Add additional __dir__ for this object. )rhasattr)raccessors& r_dir_additionsDirNamesMixin._dir_additions*s)*.TXGD/ 4 4 U  rr c`]tRt^=tRtRRltRRltRRlt]RR R 3R R ll4t R t R#)PandasDelegatez8 Abstract base class for delegating methods/properties. cV^8dQhRR/#rnamestrr)rs"rrPandasDelegate.__annotate__BsBB3Brc \RV 24h)zYou cannot access the property  TypeErrorrr;argskwargss&&*,r_delegate_property_get%PandasDelegate._delegate_property_getBs9$@AArc V^8dQhRRRR/#rr;r<rNoner)rs"rrr=Es>>3>4>rc \RV R24h)z The property z cannot be setr?)rr;valuerBrCs&&&*,r_delegate_property_set%PandasDelegate._delegate_property_setEs-v^<==rcV^8dQhRR/#r:r)rs"rrr=Hs::S:rc \RV 24h)zYou cannot call method r?rAs&&*,r_delegate_methodPandasDelegate._delegate_methodHs1$899rFc V#Nrxs&rPandasDelegate.Rs1rTc 0V^8dQhRRRRRRRRR RR R /#) r accessorsr&typr< overwriteboolaccessor_mappingCallable[[str], str]raise_on_missingrrHr)rs"rrr=LsPE&E&E& E&  E& / E&E& E&rc aaRVV3RllpRVV3RllpVFap V'g\SS!V 4R4fK"VR8Xd V!V 4p MV!V 4p V'g\W 4'dKU\W V 4Kc R#)a\ Add accessors to cls from the delegate class. Parameters ---------- cls Class to add the methods/properties to. delegate Class to get methods/properties and docstrings. accessors : list of str List of accessors to add. typ : {'property', 'method'} overwrite : bool, default False Overwrite the method/property in the target class if it exists. accessor_mapping: Callable, default lambda x: x Callable to map the delegate's function to the cls' function. raise_on_missing: bool, default True Raise if an accessor does not exist on delegate. False skips the missing accessor. cV^8dQhRR/#r:r)rs"rr.__annotate__js  S rc <aV3RlpV3RlpSVnSVn\VV\SS!S44PR7#)c&<VPS4#rR)rD)rr;s&r_getter[PandasDelegate._add_delegate_accessors.._create_delegator_property.._getterks22488rc(<VPSV4#rR)rK)r new_valuesr;s&&r_setter[PandasDelegate._add_delegate_accessors.._create_delegator_property.._setterns224DDr)fgetfsetdoc)r/propertygetattr__doc__)r;rdrhr\delegatesf r_create_delegator_propertyJPandasDelegate._add_delegate_accessors.._create_delegator_propertyjsI 9 E $G #G H&6t&<=EE rcV^8dQhRR/#r:r)rs"rrrazs  3 rcl<a\SS!S44p\P!V4V3Rl4pV#)c0<VP!S.VO5/VB#rR)rO)rrBrCr;s&*,rfSPandasDelegate._add_delegate_accessors.._create_delegator_method..f}s,,TCDCFCCr)rn functoolswraps)r;methodrvr\rpsf r_create_delegator_methodHPandasDelegate._add_delegate_accessors.._create_delegator_methodzs9X'7'=>F __V $ D% DHrNrm)rnr!setattr) clsrprXrYrZr\r^rqr{r;rvs &f&&&f& r_add_delegate_accessors&PandasDelegate._add_delegate_accessorsKss>     D$H&6t&:  1.add_delegate_accessorss/ ##   -- $  rr)rprXrYrZr\r^rsffffff rdelegate_namesrsP   "!rc,]tRt^tRtRRltRtRtR#)Accessoraa Custom property-like object. A descriptor for accessors. Parameters ---------- name : str Namespace that will be accessed under, e.g. ``df.foo``. accessor : cls Class with the extension methods. Notes ----- For accessor, The class's __init__ method assumes that one of ``Series``, ``DataFrame`` or ``Index`` as the single argument ``data``. c V^8dQhRRRR/#rGr)rs"rrAccessor.__annotate__s""S"t"rc WnW nR#rR)_name _accessor)rr;r"s&&&r__init__Accessor.__init__s  !rc DVf VP#VPV4#rR)r)robjr~s&&&r__get__Accessor.__get__s ;>> !~~c""r)rrN)r/r0r1r2rorrr5rrrrrs&"#rrc$V^8dQhRRRRRR/#)rr;r<r~ztype[NDFrame | Index]rCallable[[TypeT], TypeT]r)rs"rrrs$:: :)::rcaaRVV3RllpV#)a% Register a custom accessor on objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for pandas objects (DataFrame, Series, or Index). The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single object * raises an AttributeError if the object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. c V^8dQhRRRR/#)rr"rrr)rs"rr(_register_accessor..__annotate__s  E e rc <\SS4'd3\P!RV: RS: RS: R2\\ 4R7\ SS\ SV44SPPS4V#)zregistration of accessor z under name z for type z: is overriding a preexisting attribute with the same name.) stacklevel) r!warningswarn UserWarningrr}rradd)r"r~r;s&r decorator%_register_accessor..decoratorsq 3   MM+H<|(*SG,01+-   T8D(34 4 rr)r;r~rsff r_register_accessorrsZ   ra An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_dataframe_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all(pandas_obj[col].dtype == 'int64' for col in pandas_obj.columns): ... raise AttributeError("All columns must contain integer values only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() ... >>> df = pd.DataFrame([[1, 2], ['x', 'y']]) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: All columns must contain integer values only. >>> df = pd.DataFrame([[1, 2], [3, 4]]) >>> df.int_accessor.sum() 0 4 1 6 dtype: int64zpandas.api.extensionsc V^8dQhRRRR/#rr;r<rrr)rs"rrrFsE/E/cE/.FE/rc$^RIHp\W4#)a0 Register a custom accessor on DataFrame objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for DataFrame. The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single DataFrame object * raises an AttributeError if the DataFrame object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. Examples -------- An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_dataframe_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all( ... pandas_obj[col].dtype == "int64" for col in pandas_obj.columns ... ): ... raise AttributeError("All columns must contain integer values only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() >>> df = pd.DataFrame([[1, 2], ["x", "y"]]) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: All columns must contain integer values only. >>> df = pd.DataFrame([[1, 2], [3, 4]]) >>> df.int_accessor.sum() 0 4 1 6 dtype: int64 ) DataFrame)pandasrr)r;rs& rregister_dataframe_accessorrEsH! d ..ra An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_series_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not pandas_obj.dtype == 'int64': ... raise AttributeError("The series must contain integer data only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() ... >>> df = pd.Series([1, 2, 'x']) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: The series must contain integer data only. >>> df = pd.Series([1, 2, 3]) >>> df.int_accessor.sum() 6c V^8dQhRRRR/#rr)rs"rrrsA,A,3A,+CA,rc$^RIHp\W4#)a Register a custom accessor on Series objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for Series. The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single Series object * raises an AttributeError if the Series object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. Examples -------- An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_series_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not pandas_obj.dtype == "int64": ... raise AttributeError("The series must contain integer data only") ... self._obj = pandas_obj ... ... def sum(self): ... return self._obj.sum() >>> df = pd.Series([1, 2, "x"]) >>> df.int_accessor Traceback (most recent call last): ... AttributeError: The series must contain integer data only. >>> df = pd.Series([1, 2, 3]) >>> df.int_accessor.sum() 6 )Series)rrr)r;rs& rregister_series_accessorrs@ d ++ra[ An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_index_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all(isinstance(x, int) for x in pandas_obj): ... raise AttributeError("The index must only be an integer value") ... self._obj = pandas_obj ... ... def even(self): ... return [x for x in self._obj if x % 2 == 0] >>> df = pd.DataFrame.from_dict( ... {"row1": {"1": 1, "2": "a"}, "row2": {"1": 2, "2": "b"}}, orient="index" ... ) >>> df.index.int_accessor Traceback (most recent call last): ... AttributeError: The index must only be an integer value. >>> df = pd.DataFrame( ... {"col1": [1, 2, 3, 4], "col2": ["a", "b", "c", "d"]}, index=[1, 2, 5, 8] ... ) >>> df.index.int_accessor.even() [2, 8]c V^8dQhRRRR/#rr)rs"rrrsE+E+#E+*BE+rc$^RIHp\W4#)a} Register a custom accessor on Index objects. Parameters ---------- name : str Name under which the accessor should be registered. A warning is issued if this name conflicts with a preexisting attribute. Returns ------- callable A class decorator. See Also -------- register_dataframe_accessor : Register a custom accessor on DataFrame objects. register_series_accessor : Register a custom accessor on Series objects. register_index_accessor : Register a custom accessor on Index objects. Notes ----- This function allows you to register a custom-defined accessor class for Index. The requirements for the accessor class are as follows: * Must contain an init method that: * accepts a single Index object * raises an AttributeError if the Index object does not have correctly matching inputs for the accessor * Must contain a method for each access pattern. * The methods should be able to take any argument signature. * Accessible using the @property decorator if no additional arguments are needed. Examples -------- An accessor that only accepts integers could have a class defined like this: >>> @pd.api.extensions.register_index_accessor("int_accessor") ... class IntAccessor: ... def __init__(self, pandas_obj): ... if not all(isinstance(x, int) for x in pandas_obj): ... raise AttributeError("The index must only be an integer value") ... self._obj = pandas_obj ... ... def even(self): ... return [x for x in self._obj if x % 2 == 0] >>> df = pd.DataFrame.from_dict( ... {"row1": {"1": 1, "2": "a"}, "row2": {"1": 2, "2": "b"}}, orient="index" ... ) >>> df.index.int_accessor Traceback (most recent call last): ... AttributeError: The index must only be an integer value. >>> df = pd.DataFrame( ... {"col1": [1, 2, 3, 4], "col2": ["a", "b", "c", "d"]}, index=[1, 2, 5, 8] ... ) >>> df.index.int_accessor.even() [2, 8] r )rr r)r;r s& rregister_index_accessorrsH d **r) ro __future__rrxtypingrrrpandas.util._decoratorsrpandas.util._exceptionsrcollections.abcrpandas._typingrrr pandas.core.genericr r r8rrCachedAccessorr_register_df_examplesr_register_series_examplesr_register_index_examplesrrrrrs#5($+