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편집 파일: schema.cpython-38.pyc
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Update it if you want the schemas to reference the definitions somewhere else, e.g. for OpenAPI use ``#/components/schemas/``. The resulting generated schemas will still be at the top-level key ``definitions``, so you can extract them from there. But all the references will have the set prefix. :param ref_template: Use a ``string.format()`` template for ``$ref`` instead of a prefix. This can be useful for references that cannot be represented by ``ref_prefix`` such as a definition stored in another file. For a sibling json file in a ``/schemas`` directory use ``"/schemas/${model}.json#"``. :return: dict with the JSON Schema with a ``definitions`` top-level key including the schema definitions for the models and sub-models passed in ``models``. c S s g | ] }t |��qS re )rS )�.0�modelre re rf � <listcomp>� s zschema.<locals>.<listcomp>ri rj �rh �model_name_maprk rl � definitions)�get_flat_models_from_models�get_model_name_map�model_process_schema�update)rm rh ri rj rk rl Z clean_models� flat_modelsrr rs Z output_schemaro �m_schema� m_definitionsZm_nested_models� model_namere re rf �schemam s. � r| )ro rh rk rl r[ c C sl t | �} t| �}t|�}|| }t| ||||d�\}}} || krV|||< t|||d�}|rh|�d|i� |S )aa Generate a JSON Schema for one model. With all the sub-models defined in the ``definitions`` top-level JSON key. :param model: a Pydantic model (a class that inherits from BaseModel) :param by_alias: generate the schemas using the aliases defined, if any :param ref_prefix: the JSON Pointer prefix for schema references with ``$ref``, if None, will be set to the default of ``#/definitions/``. Update it if you want the schemas to reference the definitions somewhere else, e.g. for OpenAPI use ``#/components/schemas/``. The resulting generated schemas will still be at the top-level key ``definitions``, so you can extract them from there. But all the references will have the set prefix. :param ref_template: Use a ``string.format()`` template for ``$ref`` instead of a prefix. This can be useful for references that cannot be represented by ``ref_prefix`` such as a definition stored in another file. For a sibling json file in a ``/schemas`` directory use ``"/schemas/${model}.json#"``. :return: dict with the JSON Schema for the passed ``model`` rq Frs )rS �get_flat_models_from_modelru rv �get_schema_refrw ) ro rh rk rl rx rr r{ ry rz � nested_modelsre re rf � model_schema� s" � r� F)rY �schema_overridesr[ c C s� i }| j jst| jt�s6| j jp0| j�� �dd�|d< | j jrBd}| j jrZ| j j|d< d}| js�| j d k r�t | j �s�t | j �|d< d}||fS )N�_� ri Trj �default) � field_infori rT �type_r �alias�replacerj �requiredr� rM � outer_type_�encode_default)rY r� �schema_re re rf �get_field_info_schema� s r� )rh rk rl � known_models)rY rh rr rk rl r� r[ c C sr t | �\}}t| �}|r&|�|� d}t| ||||||p<t� d�\} } } d| krZ| | | fS |�| � || | fS dS )a� Process a Pydantic field and return a tuple with a JSON Schema for it as the first item. Also return a dictionary of definitions with models as keys and their schemas as values. If the passed field is a model and has sub-models, and those sub-models don't have overrides (as ``title``, ``default``, etc), they will be included in the definitions and referenced in the schema instead of included recursively. :param field: a Pydantic ``ModelField`` :param by_alias: use the defined alias (if any) in the returned schema :param model_name_map: used to generate the JSON Schema references to other models included in the definitions :param ref_prefix: the JSON Pointer prefix to use for references to other schemas, if None, the default of #/definitions/ will be used :param ref_template: Use a ``string.format()`` template for ``$ref`` instead of a prefix. This can be useful for references that cannot be represented by ``ref_prefix`` such as a definition stored in another file. For a sibling json file in a ``/schemas`` directory use ``"/schemas/${model}.json#"``. :param known_models: used to solve circular references :return: tuple of the schema for this field and additional definitions T�rh rr r� rk rl r� �$refN)r� � get_field_schema_validationsrw �field_type_schemar` ) rY rh rr rk rl r� �sr� Zvalidation_schema�f_schema� f_definitions�f_nested_modelsre re rf rZ � s$ � rZ � max_lengthZ maxLength� min_lengthZ minLength�regex�pattern.�_str_types_attrs�gtZexclusiveMinimum�ltZexclusiveMaximum�ge�minimum�le�maximum� multiple_ofZ multipleOf�_numeric_types_attrs)rY r[ c C s i }t | jt�r*| jjr&|�| jj� |S t | jttf�rjtD ]*\}}}t | j|d�}t ||�r>|||< q>t | jt �r�t | jt �s�tD ]*\}}}t | j|d�}t ||�r�|||< q�| jdk r�| jjr�| j|d< | jjr�|�| jj� t | jdd�}|�rt|| |� |S )z� Get the JSON Schema validation keywords for a ``field`` with an annotation of a Pydantic ``FieldInfo`` with validation arguments. N�const�__modify_schema__)rT r� r r� �extrarw �str�bytesr� �getattr� isinstance� numeric_types� issubclass�boolr� r� r� r� rg )rY r� � attr_name�t�keyword�attrrX re re rf r� ! s. r� )� unique_modelsr[ c C s� i }t � }| D ]f}t|j�}||kr6t|�}|||< q||krl|�|� |�|�}||t|�< ||t|�< q|||< qdd� |�� D �S )a� Process a set of models and generate unique names for them to be used as keys in the JSON Schema definitions. By default the names are the same as the class name. But if two models in different Python modules have the same name (e.g. "users.Model" and "items.Model"), the generated names will be based on the Python module path for those conflicting models to prevent name collisions. :param unique_models: a Python set of models :return: dict mapping models to names c S s i | ]\}}||�qS re re �rn �k�vre re rf � <dictcomp>Z s z&get_model_name_map.<locals>.<dictcomp>)r` �normalize_name�__name__�get_long_model_name�add�pop�items)r� Zname_model_mapZconflicting_namesro r{ Zconflicting_modelre re rf ru B s ru )ro r� r[ c C sJ |pt � }t � }|�| � ||O }ttt | j�� �}|t||d�O }|S )a? Take a single ``model`` and generate a set with itself and all the sub-models in the tree. I.e. if you pass model ``Foo`` (subclass of Pydantic ``BaseModel``) as ``model``, and it has a field of type ``Bar`` (also subclass of ``BaseModel``) and that model ``Bar`` has a field of type ``Baz`` (also subclass of ``BaseModel``), the return value will be ``set([Foo, Bar, Baz])``. :param model: a Pydantic ``BaseModel`` subclass :param known_models: used to solve circular references :return: a set with the initial model and all its sub-models �r� )r` r� r" r r2 � __fields__�values�get_flat_models_from_fields)ro r� rx �fieldsre re rf r} ] s r} )rY r� r[ c C s� ddl m} t� }| j}tt|dd�|�r0|j}| jrTt||�sT|t| j|d�O }n8t||�rx||krx|t ||d�O }nt|t �r�|� |� |S )a� Take a single Pydantic ``ModelField`` (from a model) that could have been declared as a subclass of BaseModel (so, it could be a submodel), and generate a set with its model and all the sub-models in the tree. I.e. if you pass a field that was declared to be of type ``Foo`` (subclass of BaseModel) as ``field``, and that model ``Foo`` has a field of type ``Bar`` (also subclass of ``BaseModel``) and that model ``Bar`` has a field of type ``Baz`` (also subclass of ``BaseModel``), the return value will be ``set([Foo, Bar, Baz])``. :param field: a Pydantic ``ModelField`` :param known_models: used to solve circular references :return: a set with the model used in the declaration for this field, if any, and all its sub-models r rV �__pydantic_model__Nr� ) �pydantic.v1.mainrW r` r� rT r� r� � sub_fieldsr� r} r r� )rY r� rW rx � field_typere re rf �get_flat_models_from_fieldq s r� )r� r� r[ c C s$ t � }| D ]}|t||d�O }q |S )a� Take a list of Pydantic ``ModelField``s (from a model) that could have been declared as subclasses of ``BaseModel`` (so, any of them could be a submodel), and generate a set with their models and all the sub-models in the tree. I.e. if you pass a the fields of a model ``Foo`` (subclass of ``BaseModel``) as ``fields``, and on of them has a field of type ``Bar`` (also subclass of ``BaseModel``) and that model ``Bar`` has a field of type ``Baz`` (also subclass of ``BaseModel``), the return value will be ``set([Foo, Bar, Baz])``. :param fields: a list of Pydantic ``ModelField``s :param known_models: used to solve circular references :return: a set with any model declared in the fields, and all their sub-models r� )r` r� )r� r� rx rY re re rf r� � s r� )rm r[ c C s t � }| D ]}|t|�O }q |S )a_ Take a list of ``models`` and generate a set with them and all their sub-models in their trees. I.e. if you pass a list of two models, ``Foo`` and ``Bar``, both subclasses of Pydantic ``BaseModel`` as models, and ``Bar`` has a field of type ``Baz`` (also subclass of ``BaseModel``), the return value will be ``set([Foo, Bar, Baz])``. )r` r} )rm rx ro re re rf rt � s rt )ro r[ c C s | j � d| j� ��dd�S )N�__�.)� __module__� __qualname__r� �ro re re rf r� � s r� )r� rk )rY rh rr rl r� rk r� r[ c C sv ddl m} i }t� } | jtttttt t hkr�t | |||||d�\} } } |� | � | � | � d| d�} | jtthkr|d| d< �n�| jt k�rdd i} tt| j�}t|jd d �}t | |||||d�\} } } |� | � | � | � |r�t�|�| i| d < | r�| | d < �n$| jtk�s(| jtk�r�t| j|��s�g }ttt | j�}|D ]>}t||||||d�\}}}|� |� | � |� |�|� �q@t |�}| jtk�r�|dk�r�|d nd|d�}d|gi} n d||d�} |dk�r&|| d< nJ| jt thk�s�t | j��t | ||||||d�\} } } |� | � | � | � | j| j k�rl| jtk�rH| j}n| j }t|dd �}|�rlt || | � | || fS )a Used by ``field_schema()``, you probably should be using that function. Take a single ``field`` and generate the schema for its type only, not including additional information as title, etc. Also return additional schema definitions, from sub-models. r rV �rh rr rk rl r� �array��typer� T� uniqueItemsr� �objectr� NZpatternProperties�additionalProperties� �allOf)r� �minItems�maxItemsr� r� r� )!r� rW r` �shaper+ r0 r, r- r( r* r' �field_singleton_schemarw r& r" r2 � key_fieldr� r� r< Z _get_patternr/ r) r� r r� r� �append�lenr. �AssertionErrorr� rg )rY rh rr rl r� rk r� rW rs r Z items_schemar� r� r� r� r� � sub_schemar� �sfZ sf_schemaZsf_definitionsZsf_nested_modelsZsub_fields_lenZall_of_schemasr� rX re re rf r� � s� � � � &� � � r� )rh rk rl r� rY )ro rh rr rk rl r� rY r[ c C s� ddl m}m} |pt� }t| t�rJttt | �} t| |d�} | i t� fS ttd | �} d| j j pf| j i} || �} | r~| | d< |� | � t | |||||d�\} } } | �| � | j j}t|�r�t||�j�dkr�|| � q�|| | � n | �|� | | | fS ) au Used by ``model_schema()``, you probably should be using that function. Take a single ``model`` and generate its schema. Also return additional schema definitions, from sub-models. The sub-models of the returned schema will be referenced, but their definitions will not be included in the schema. All the definitions are returned as the second value. r )�getdocr\ r^ rW ri rj r� r� )r_ r� r\ r` rT r r" r �enum_process_schema� __config__ri r� r� �model_type_schemarw � schema_extra�callabler� ra )ro rh rr rk rl r� rY r� r\ r� �docry rz r r� re re rf rv ' s8 � rv )rk )ro rh rr rl rk r� r[ c C s( i }g }i }t � } | j�� D ]�\} } z t| |||||d�\} } }W n8 tk rz } zt�|jt� W Y �q W 5 d}~X Y nX |� | � | � |� |r�| || j < | j r�|� | j � q | || < | j r |� | � q t |kr�|t }| jjp�| j|d< nd|d�}|�r||d< | jjdk�r d|d < ||| fS ) a) You probably should be using ``model_schema()``, this function is indirectly used by that function. Take a single ``model`` and generate the schema for its type only, not including additional information as title, etc. Also return additional schema definitions, from sub-models. r� Nri r� )r� � propertiesr� ZforbidFr� )r` r� r� rZ � SkipField�warnings�warn�message� UserWarningrw r� r� r� rR r� ri r� r� )ro rh rr rl rk r� r� r� rs r r� �fr� r� r� �skipZ out_schemare re rf r� Y sF � r� r^ )�enumrY r[ c C s` ddl }| j|�| jpd�dd� ttt | �D �d�}t| |� t| dd�}|r\t |||� |S )z� Take a single `enum` and generate its schema. This is similar to the `model_process_schema` function, but applies to ``Enum`` objects. r NzAn enumeration.c S s g | ] }|j �qS re )�value)rn �itemre re rf rp � s z'enum_process_schema.<locals>.<listcomp>)ri rj r� r� ) r_ r� �cleandoc�__doc__r" r r �add_field_type_to_schemar� rg )r� rY r_ r� rX re re rf r� � s � r� c s� t tt | j�}i }t� } t|�dkr@t|d |� |��|d�S i } | jdk } | �r | jdk sbt �i } | j� � D ]�\} }t | t �r�t | j�} tt|j��r�t|j�}� ��fdd�|D �| | < qp|j}t|d�r�|j}� | }t|��d�}|d | | < qp| j| d �| d < g }|D ]x}t||� |��|d�\}}}|�|� |�rXd |k�rX|d d }|�� d d hk�rt|�d � |�|� | �|� �q|| | �r�d nd< | || fS dS )aA This function is indirectly used by ``field_schema()``, you probably should be using that function. Take a list of Pydantic ``ModelField`` from the declaration of a type with parameters, and generate their schema. I.e., fields used as "type parameters", like ``str`` and ``int`` in ``Tuple[str, int]``. r� r r� Nc s$ i | ] }� | t � | ��d ��qS )F)r~ )rn Z sub_model�rr rk rl re rf r� � s � �z5field_singleton_sub_fields_schema.<locals>.<dictcomp>r� Fr� )Z propertyName�mappingZ discriminatorr� ZoneOfZanyOf)r" r r2 r� r` r� r� Zdiscriminator_keyZsub_fields_mappingr� r� r� r r� r� rQ rK r� rL �hasattrr� r~ Zdiscriminator_aliasrw rb r� r� )rY rh rr rl r� rk r� r� rs r r� Zfield_has_discriminatorZdiscriminator_models_refsZdiscriminator_valueZ sub_fieldZ sub_modelsZsub_field_typeZdiscriminator_model_nameZdiscriminator_model_refZsub_field_schemasr� r� �sub_definitions�sub_nested_modelsre r� rf �!field_singleton_sub_fields_schema� sn � � � � r� �string�path)r� �formatz date-timer r �numberz time-deltaZ ipv4networkZ ipv6networkZ ipv4interfaceZ ipv6interfaceZipv4Zipv6r� �binary�boolean�integer�uuidr� r� r� )r� r� r� �field_class_to_schemaz json-string)r� r� r[ c C sB t D ]8\}}t| |�s.| | kr*tkrn q|�|� q>qdS )a Update the given `schema` with the type-specific metadata for the given `field_type`. This function looks through `field_class_to_schema` for a class that matches the given `field_type`, and then modifies the given `schema` with the information from that type. N)r rT r rw )r� r� r� Zt_schemare re rf r� $ s " r� )�namerk rl r� r[ c C s4 |rd|| i}nd|j | d�i}|r0d|giS |S )Nr� r� r� )r� )r rk rl r� � schema_refre re rf r~ 2 s r~ c C s� ddl m} i }t� } | j} | jrP| jr0| jjs:t| |�sPt| ||||||d�S | t ksv| t ksv| j t ksvt | �tkr�i || fS t| �r�ddi|| fS t| �r�td| j� d���i } | jdk r�| jjr�| j| d < t| ��rDtd d � t| �D ��} td d � | D ��dk�r"tt| | �|||||d�S | d j } t| �| d< t| | � n�t| t ��r�|| } t | |�\} }| � t | |||�� t | | d�|| < n�t!| ��r�t"| j#|||||| d�^}}t|d �$� �}| � d|t|�t|�d�� n4t%| d��st| | � t&| dd�}|�rt'|| | � | �r$| || fS tt&| dd�|��r>| j#} t(| |��r�|| }| |k�r�t"| |||||| d�\}}}|� |� |||< | � |� n | �)|� t ||||�}||| fS t*| �}|dk �r�|�s�t+| j,k�r�| || fS t-d| � ���dS )z� This function is indirectly used by ``field_schema()``, you should probably be using that function. Take a single Pydantic ``ModelField``, and return its schema and any additional definitions from sub-models. r rV r� r� �nullz Callable zC was excluded from schema since JSON schema has no equivalent type.Nr� c s s" | ]}t |t�r|jn|V qd S �N)r� r r� )rn �xre re rf � <genexpr>h s z)field_singleton_schema.<locals>.<genexpr>c S s h | ] }|j �qS re )� __class__�rn r� re re rf � <setcomp>j s z)field_singleton_schema.<locals>.<setcomp>r� r� r� r^ )rh rr rk rl r� rY r� r� )r� r� r� r� r� r� z.Value not declarable with JSON Schema, field: ).r� rW r` r� r� r� r� rT r� r r� r r rK r� rP rM r� r r� rN �tuplerI r� rZ �#multitypes_literal_field_for_schema�listr� r r� rw r~ r� rO rv r� r� r� r� rg r� r� rJ r � __bases__� ValueError)rY rh rr rl r� rk r� rW rs r r� r� r� Z enum_namer� r� Z items_schemasrX r{ r� r� r rd re re rf r� : s� ���� & � � �� � r� )r� rY r[ c C sb t t�}| D ]}||j �|� q dd� |�� D �}t|jtt|� |j |j |j |j |j |jd�S )z� To support `Literal` with values of different types, we split it into multiple `Literal` with same type e.g. `Literal['qwe', 'asd', 1, 2]` becomes `Union[Literal['qwe', 'asd'], Literal[1, 2]]` c s s | ]}t t|� V qd S r )r% r )rn Zsame_type_valuesre re rf r � s z6multitypes_literal_field_for_schema.<locals>.<genexpr>)r r� �class_validators� model_configr� r� r� r� )r r r r� r� r2 r r! r r r r� r� r� r� )r� rY Zliteral_distinct_typesr� Zdistinct_literalsre re rf r � s �r )�dftr[ c C s� ddl m} t| |�s t| �r,tdt| ��} t| t�rHdd� | �� D �S t| t�rX| j S t| t t t f�rl| S t| t tf�r�| j}dd� | D �}t|�r�||� S ||�S | d kr�d S t| �S d S )Nr rV zdict[str, Any]c S s i | ]\}}t |�t |��qS re �r� r� re re rf r� � s z"encode_default.<locals>.<dictcomp>c s s | ]}t |�V qd S r r r re re rf r � s z!encode_default.<locals>.<genexpr>)r� rW r� r r" r3 �dictr� r r� �int�floatr� r r r rO )r rW r� Zseq_argsre re rf r� � s r� �_map_types_constraint)� annotationr� � field_name�validate_assignmentr[ c C sZ |� � }t� }|r t| |�\} }|r.|�d� || }|rVtd|� dd�|�� d���| S )a= Get an annotation with validation implemented for numbers and strings based on the field_info. :param annotation: an annotation from a field specification, as ``str``, ``ConstrainedStr`` :param field_info: an instance of FieldInfo, possibly with declarations for validations and JSON Schema :param field_name: name of the field for use in error messages :param validate_assignment: default False, flag for BaseModel Config value of validate_assignment :return: the same ``annotation`` if unmodified or a new annotation with validation in place Zallow_mutationz On field "z<" the following field constraints are set but not enforced: z, z\. For more details see https://docs.pydantic.dev/usage/schema/#unenforced-field-constraints)Zget_constraintsr` � get_annotation_with_constraintsr� r �join)r r� r r � constraints�used_constraintsZunused_constraintsre re rf � get_annotation_from_field_info� s �r )r r� r[ c s. t � �ttt d�� ��fdd� ��| ��fS )a� Get an annotation with used constraints implemented for numbers and strings based on the field_info. :param annotation: an annotation from a field specification, as ``str``, ``ConstrainedStr`` :param field_info: an instance of FieldInfo, possibly with declarations for validations and JSON Schema :return: the same ``annotation`` if unmodified or a new annotation along with the used constraints. )r� r[ c sn t � �s"t� t�s"t� tttf�r&� S t� �}|d k �r�t� �}t dd� |D ��rV� S |t krj�|d �S t |�r�t t �fdd�|D �� S t|t�r�jd k s��jd k s��jd k r��dddh� t�|d ��j�j�jd�S t|t��r.�jd k �s�jd k �r.��ddh� t�|d ��j�jd �S t|t��rz�jd k �sR�jd k �rz��ddh� t�|d ��j�jd �S tttttfD ]0}t||��r�|t �fd d�|D �� S �q�t|t��r�t|d �|d �f S d }d }t� t ��rt� t t f��r d }t t t d �� fdd� }n�t� t!��rlt� t"t#f��sld}t� t$��rft t t d �� fdd� }nt%}n�t� t&��r�d}t� t'��r�t t t d �� fdd� }nt(}npt� t)��rt� t*t+t,tttt-f��sd}t� t.��r�|d7 }t� t/��r�|d7 }t0� fdd�t)D ��}t1| }|�rj��t2|�� dd� �fdd�|D �D �}|�rjt3t4dt f |�}|f |�S � S )Nc s s | ]}t |t�V qd S r )r� r �rn �are re rf r s z>get_annotation_with_constraints.<locals>.go.<locals>.<genexpr>r c 3 s | ]}� |�V qd S r re r! ��gore rf r ! s � min_items� max_items� unique_items)r% r& r' )r% r& c 3 s | ]}� |�V qd S r re r! r# re rf r : s r� )r� r� )�kwr[ c s t � j� f| �S r �r� r� �r( �r� re rf �constraint_funcE s zDget_annotation_with_constraints.<locals>.go.<locals>.constraint_func)r� r� r� c s t � j� f| �S r r) r* r+ re rf r, L s c s t � j� f| �S r r) r* r+ re rf r, U s )r� r� r� r� r� )Z allow_inf_nan)Z max_digitsZdecimal_placesc 3 s | ]}t � |�r|V qd S r )r� )rn r� r+ re rf r l s c S s i | ]\}}|d k r||�qS r re )rn r� r� re re rf r� q s � z?get_annotation_with_constraints.<locals>.go.<locals>.<dictcomp>c 3 s | ]}|t � |�fV qd S r )r� )rn r� )r� re rf r s s .)5rN r� r rT r: r; r8 rK rJ �anyr$ rQ r! r r� r r% r& r' rw rF r rG r rD r r r r� r> r= r r r� r5 r4 r@ rH r� r? rA r� r9 r7 r6 r� r r �nextr r` r" r )r� �originrd r� �attrsr, Z numeric_typer] �r� r$ r r+ rf r$ s� ��� ��� �$$ " �� � z+get_annotation_with_constraints.<locals>.go)r` r r )r r� re r1 rf r s kr )r r[ c C s t �dd| �S )zU Normalizes the given name. This can be applied to either a model *or* enum. z[^a-zA-Z0-9.\-_]r� )�re�sub)r re re rf r� ~ s r� c @ s e Zd ZdZedd�dd�ZdS )r� z? Utility exception used to exclude fields from schema. N)r� r[ c C s || _ d S r )r� )�selfr� re re rf �__init__� s zSkipField.__init__)r� r� r� r� r� r5 re re re rf r� � s r� )F)N)F)�r2 r� � collectionsr � dataclassesr r r r r �decimalr r� r � ipaddressr r r r r r �pathlibr �typingr r r r r r r r r r r r r r r r r! r" r r# �typing_extensionsr$ r% Zpydantic.v1.fieldsr& r' r( r) r* r+ r, r- r. r/ r0 r1 r2 Zpydantic.v1.jsonr3 Zpydantic.v1.networksr4 r5 Zpydantic.v1.typesr6 r7 r8 r9 r: r; r< r= r> r? r@ rA rB rC rD rE rF rG rH Zpydantic.v1.typingrI rJ rK rL rM rN rO rP rQ Zpydantic.v1.utilsrR rS rT Zpydantic.v1.dataclassesrU r� rW �default_prefixZdefault_ref_templateZTypeModelOrEnumZ TypeModelSetr� rg r� r| r� r� rZ r r r� r� r� �__annotations__r� r� ru r} r� r� rt r� r� rv r� r� r� r� r r r r` � frozensetr Z json_schemer� r~ r� r r� r r r r� � Exceptionr� re re re rf �<module> s~ P < T, � � � 7� � &$� � 3 �.�. ! � � z� � 8� � 6( � � ^ �$ "� � ( � � "x