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API Reference

Wrappers#

BaseWrapper #

A base wrapper for Tekla Structures API objects.

This class provides a more Pythonic interface for interacting with Tekla Structures software.

When an attribute is accessed, the class uses the __getattr__ and __getattribute__ methods to convert the attribute to a more Pythonic format.

This class also uses the wrap function to automatically convert wrapped objects to their internal Tekla.Structures format when they are set as attributes.

When a C# IEnumerator instance is returned, this class converts it to a Python generator. Similarly, when an IDictionary subclass is returned, this class converts it to a Python dictionary.

References#

https://developer.tekla.com/tekla-structures/api/22/8180
Source code in pytekla\wrappers.py 
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class BaseWrapper:
    """
    A base wrapper for Tekla Structures API objects.

    This class provides a more Pythonic interface for interacting with Tekla Structures software.

    When an attribute is accessed, the class uses the `__getattr__` and `__getattribute__` methods to convert the attribute to a more Pythonic format.

    This class also uses the [`wrap`][pytekla.wrappers.wrap] function to automatically convert wrapped objects to their internal Tekla.Structures format when they are set as attributes.

    When a C# IEnumerator instance is returned, this class converts it to a Python generator. Similarly, when an IDictionary subclass is returned, this class converts it to a Python dictionary.

    References
    ----------
        https://developer.tekla.com/tekla-structures/api/22/8180
    """

    def __init__(self, tekla_object):
        """Initializes the class using a Tekla API object

        Parameters
        ----------
        tekla_object : Tekla.Structures object
            The object to wrap.
        """
        _set_tekla_object(self, tekla_object)

    def __getattribute__(self, name):
        result = object.__getattribute__(self, name)

        if name == "unwrap":
            return result

        if callable(result):
            return _attrs_wrapper(result)

        return _process_attr(result)

    def __getattr__(self, attr):
        to = _get_tekla_object(self)

        returned_attr = getattr(to, to_pascal_case(attr))

        if callable(returned_attr):
            return _attrs_wrapper(returned_attr)

        return _process_attr(returned_attr)

    def __setattr__(self, attr, value):
        if isinstance(value, BaseWrapper):
            value = value.unwrap()

        if attr in object.__getattribute__(self, "__dict__"):
            return object.__setattr__(self, attr, value)
        try:
            to = _get_tekla_object(self)
            to.__setattr__(to_pascal_case(attr), value)
        except AttributeError:
            raise AttributeError(
                f"'{_get_tekla_object(self)}' has not attribute '{attr}'"
            )

    def unwrap(self):
        """
        Get the original Tekla Structures object that is wrapped by this class or subclass instance.

        Returns
        -------
        Tekla.Structures object
            The original Tekla Structures object.

        Examples
        -------
        >>> obj = BaseWrapper(tekla_object)
        >>> original_obj = obj.unwrap()
        """
        return _get_tekla_object(self)

    def __repr__(self):
        """Return a string representation of the class name of the wrapped Tekla object.

        Returns
        -------
        str
            The string representation of the class name of the wrapped Tekla object.

        Examples
        -------
        >>> obj = BaseWrapper(tekla_object)
        >>> str(obj)
        '<PyTekla> OriginalName'
        """
        class_name = "<PyTekla> " + _get_tekla_object(self).__class__.__name__
        return class_name

__init__(tekla_object) #

Initializes the class using a Tekla API object

Parameters:

Name Type Description Default
tekla_object Tekla.Structures object

The object to wrap.

 required
Source code in pytekla\wrappers.py 
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def __init__(self, tekla_object):
    """Initializes the class using a Tekla API object

    Parameters
    ----------
    tekla_object : Tekla.Structures object
        The object to wrap.
    """
    _set_tekla_object(self, tekla_object)

unwrap() #

Get the original Tekla Structures object that is wrapped by this class or subclass instance.

Returns:

Type Description
Tekla.Structures object

The original Tekla Structures object.

Examples:

>>> obj = BaseWrapper(tekla_object)
>>> original_obj = obj.unwrap()
Source code in pytekla\wrappers.py 
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def unwrap(self):
    """
    Get the original Tekla Structures object that is wrapped by this class or subclass instance.

    Returns
    -------
    Tekla.Structures object
        The original Tekla Structures object.

    Examples
    -------
    >>> obj = BaseWrapper(tekla_object)
    >>> original_obj = obj.unwrap()
    """
    return _get_tekla_object(self)

__repr__() #

Return a string representation of the class name of the wrapped Tekla object.

Returns:

Type Description
str

The string representation of the class name of the wrapped Tekla object.

Examples:

>>> obj = BaseWrapper(tekla_object)
>>> str(obj)
'<PyTekla> OriginalName'
Source code in pytekla\wrappers.py 
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def __repr__(self):
    """Return a string representation of the class name of the wrapped Tekla object.

    Returns
    -------
    str
        The string representation of the class name of the wrapped Tekla object.

    Examples
    -------
    >>> obj = BaseWrapper(tekla_object)
    >>> str(obj)
    '<PyTekla> OriginalName'
    """
    class_name = "<PyTekla> " + _get_tekla_object(self).__class__.__name__
    return class_name

WithUserPropertyMixin #

Source code in pytekla\wrappers.py 
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class WithUserPropertyMixin:
    def get_user_property(self, property_name, property_type):
        """Gets the value of a user property for the given `property_name`.

        Parameters
        ----------
        property_name : str
            The name of the user property.
        property_type : type
            The type of the user property, must be `str`, `int`, or `float`.

        Returns
        -------
        str, int, float or None
            The value of the user property. None if it was not found.

        Raises
        ------
        TypeError
            If `property_type` is not `str`, `int`, or `float`.

        Examples
        -------
        >>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
        >>> value = model_object_wrapper.get_user_property('property_name', str)
        """
        check_property_type(property_type)
        to = _get_tekla_object(self)
        was_found, value = to.GetUserProperty(property_name, property_type())
        if was_found:
            return value

    def set_user_property(self, property_name, value):
        """
        Sets the user property with the specified name to the specified value.

        Parameters
        ----------
        property_name : str
            The name of the user property.
        value : str, int or float
            The value to set the user property to.

        Returns
        -------
        bool
            Indicates if the property was set.

        Raises
        ------
        TypeError
            If the value type is not one of [str, int, float].

        Examples
        -------
        >>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
        >>> model_object_wrapper.set_user_property('property_name', value)
        """
        check_property_type(type(value))
        to = _get_tekla_object(self)
        return to.SetUserProperty(property_name, value)

get_user_property(property_name, property_type) #

Gets the value of a user property for the given property_name.

Parameters:

Name Type Description Default
property_name str

The name of the user property.

 required
property_type type

The type of the user property, must be str, int, or float.

 required

Returns:

Type Description
str, int, float or None

The value of the user property. None if it was not found.

Raises:

Type Description
TypeError

If property_type is not str, int, or float.

Examples:

>>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
>>> value = model_object_wrapper.get_user_property('property_name', str)
Source code in pytekla\wrappers.py 
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def get_user_property(self, property_name, property_type):
    """Gets the value of a user property for the given `property_name`.

    Parameters
    ----------
    property_name : str
        The name of the user property.
    property_type : type
        The type of the user property, must be `str`, `int`, or `float`.

    Returns
    -------
    str, int, float or None
        The value of the user property. None if it was not found.

    Raises
    ------
    TypeError
        If `property_type` is not `str`, `int`, or `float`.

    Examples
    -------
    >>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
    >>> value = model_object_wrapper.get_user_property('property_name', str)
    """
    check_property_type(property_type)
    to = _get_tekla_object(self)
    was_found, value = to.GetUserProperty(property_name, property_type())
    if was_found:
        return value

set_user_property(property_name, value) #

Sets the user property with the specified name to the specified value.

Parameters:

Name Type Description Default
property_name str

The name of the user property.

 required
value str, int or float

The value to set the user property to.

 required

Returns:

Type Description
bool

Indicates if the property was set.

Raises:

Type Description
TypeError

If the value type is not one of [str, int, float].

Examples:

>>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
>>> model_object_wrapper.set_user_property('property_name', value)
Source code in pytekla\wrappers.py 
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def set_user_property(self, property_name, value):
    """
    Sets the user property with the specified name to the specified value.

    Parameters
    ----------
    property_name : str
        The name of the user property.
    value : str, int or float
        The value to set the user property to.

    Returns
    -------
    bool
        Indicates if the property was set.

    Raises
    ------
    TypeError
        If the value type is not one of [str, int, float].

    Examples
    -------
    >>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
    >>> model_object_wrapper.set_user_property('property_name', value)
    """
    check_property_type(type(value))
    to = _get_tekla_object(self)
    return to.SetUserProperty(property_name, value)

ModelObjectWrapper #

Bases: BaseWrapper, WithUserPropertyMixin

This class is a wrapper around Tekla.Structures.Model.ModelObject that provides helper methods for working with ModelObject's properties.

Examples:

Instantiate a ModelObjectWrapper instance from a Tekla Structures object:

>>> from Tekla.Structures.Model import Beam
>>> from pytekla import ModelObjectWrapper
>>> wrapped_beam = ModelObjectWrapper(Beam())

Access the wrapped object's attributes using Python's preferred naming convention:

>>> wrapped_beam.name
'BEAM'
>>> wrapped_beam.name = "MY BEAM"
>>> wrapped_beam.modify()

Retrieve the original Tekla Structures object from the ModelObjectWrapper instance:

>>> unwrapped_beam = wrapped_beam.unwrap()

References#

https://developer.tekla.com/tekla-structures/api/22/14416
Source code in pytekla\wrappers.py 
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class ModelObjectWrapper(BaseWrapper, WithUserPropertyMixin):
    """This class is a wrapper around Tekla.Structures.Model.ModelObject that provides helper methods
    for working with ModelObject's properties.

    Examples
    --------
    Instantiate a `ModelObjectWrapper` instance from a Tekla Structures object:

    >>> from Tekla.Structures.Model import Beam
    >>> from pytekla import ModelObjectWrapper
    >>> wrapped_beam = ModelObjectWrapper(Beam())

    Access the wrapped object's attributes using Python's preferred naming convention:

    >>> wrapped_beam.name
    'BEAM'
    >>> wrapped_beam.name = "MY BEAM"
    >>> wrapped_beam.modify()

    Retrieve the original Tekla Structures object from the `ModelObjectWrapper` instance:

    >>> unwrapped_beam = wrapped_beam.unwrap()

    References
    ----------
        https://developer.tekla.com/tekla-structures/api/22/14416
    """

    main_type = ModelObject

    def __init__(self, tekla_object):
        """Initializes the class using a Tekla API ModelObject object

        Parameters
        ----------
        tekla_object : Tekla.Structures object
            The object to wrap.
        """
        super().__init__(tekla_object)

    def get_report_property(self, property_name, property_type):
        """
        Gets the value of a report property for the given `property_name`.

        Parameters
        ----------
        property_name : str
            The name of the report property.
        property_type : type
            The type of the report property, must be `str`, `int`, or `float`.

        Returns
        -------
        str, int, float or None
            The value of the report property. None if it was not found.

        Raises
        ------
        TypeError
            If `property_type` is not `str`, `int`, or `float`.

        Examples
        -------
        >>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
        >>> value = model_object_wrapper.get_report_property('property_name', str)
        """
        check_property_type(property_type)
        to = _get_tekla_object(self)
        was_found, value = to.GetReportProperty(property_name, property_type())
        if was_found:
            return value

    def get_all_user_properties(self):
        """
        Get all user properties of the Tekla Model Object as a dictionary.

        Returns
        -------
        dict
            A dictionary containing the user properties and their values, with keys as property names and values as property values.

        Examples
        -------
        >>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
        >>> user_properties = model_object_wrapper.get_all_user_properties()
        """
        hash_table = Hashtable()
        to = _get_tekla_object(self)
        to.GetAllUserProperties(hash_table)
        return hash_table

    def get_multiple_report_properties(
        self, string_names=None, float_names=None, int_names=None
    ):
        """
        Get multiple report properties as a dictionary.

        Parameters
        ----------
        string_names : list of str, optional
            A list of string property names to retrieve.
        float_names : list of str, optional
            A list of float property names to retrieve.
        int_names : list of str, optional
            A list of integer property names to retrieve.

        Returns
        -------
        dict
            A dictionary containing the report properties and their values, with keys as property names and values as property values.

        Examples
        -------
        >>> model_object_wrapper = ModelObjectWrapper(some_model_object)
        >>> report_properties = model_object_wrapper.get_multiple_report_properties(
        ...     string_names=['Property1', 'Property2'],
        ...     float_names=['Property3', 'Property4'],
        ...     int_names=['Property5', 'Property6']
        ... )
        >>> report_properties
        {'Property1': 'value1', 'Property2': 'value2', 'Property3': 0.5, 'Property4': 2.0, 'Property5': 1, 'Property6': 3}
        """
        hash_table = Hashtable()
        to = _get_tekla_object(self)
        to.GetAllReportProperties(
            iterable_to_net_array_list(string_names or []),
            iterable_to_net_array_list(float_names or []),
            iterable_to_net_array_list(int_names or []),
            hash_table,
        )
        return hash_table

    def get_dynamic_string_property(self, property_name):
        """
        Get the value of a dynamic string property.

        Parameters
        ----------
        property_name : str
            The name of the property to retrieve.

        Returns
        -------
        str or None
            The value of the specified dynamic string property. None if the property was not found.

        Examples
        -------
        >>> model_object_wrapper = ModelObjectWrapper(some_model_object)
        >>> value = model_object_wrapper.get_dynamic_string_property('property_name')
        """
        to = _get_tekla_object(self)
        was_found, value = to.GetDynamicStringProperty(property_name, str())
        if was_found:
            return value

    def set_multiple_user_properties(self, **kwargs):
        """
        Sets multiple user properties with the specified names to the specified values.

        Parameters
        ----------
        kwargs : dict
            The names and values of the user properties to set.

        Returns
        -------
        bool
            Indicates if the properties were set.

        Examples
        --------
        >>> model_object_wrapper = ModelObjectWrapper(some_model_object)
        >>> model_object_wrapper.set_multiple_user_properties(prop1="value1", prop2=123, prop3=3.14)
        True
        """
        keys_str, values_str, keys_float, values_float, keys_int, values_int = [
            List[_type]() for _type in (str, str, str, float, str, int)
        ]

        for k, v in kwargs.items():
            match v:
                case str():
                    keys_str.Add(k)
                    values_str.Add(v)
                case int():
                    keys_int.Add(k)
                    values_int.Add(v)
                case float():
                    keys_float.Add(k)
                    values_float.Add(v)
        to = _get_tekla_object(self)
        return to.SetUserProperties(
            keys_str, values_str, keys_float, values_float, keys_int, values_int
        )

    def set_dynamic_string_property(self, property_name, value):
        """
        Sets the dynamic string property with the specified name to the specified value.

        Parameters
        ----------
        property_name : str
            The name of the dynamic string property.
        value : str
            The value to set the dynamic string property to.

        Returns
        -------
        bool
            Indicates if the property was set.

        Raises
        ------
        TypeError
            If the value type is not str.

        Examples
        -------
        >>> model_object_wrapper = ModelObjectWrapper(some_model_object)
        >>> model_object_wrapper.set_dynamic_string_property("my_property", "my_value")
        True
        """
        if type(value) != str:
            raise TypeError("'value' must be str")
        to = _get_tekla_object(self)
        return to.GetDynamicStringProperty(property_name, value)

__init__(tekla_object) #

Initializes the class using a Tekla API ModelObject object

Parameters:

Name Type Description Default
tekla_object Tekla.Structures object

The object to wrap.

 required
Source code in pytekla\wrappers.py 
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def __init__(self, tekla_object):
    """Initializes the class using a Tekla API ModelObject object

    Parameters
    ----------
    tekla_object : Tekla.Structures object
        The object to wrap.
    """
    super().__init__(tekla_object)

get_report_property(property_name, property_type) #

Gets the value of a report property for the given property_name.

Parameters:

Name Type Description Default
property_name str

The name of the report property.

 required
property_type type

The type of the report property, must be str, int, or float.

 required

Returns:

Type Description
str, int, float or None

The value of the report property. None if it was not found.

Raises:

Type Description
TypeError

If property_type is not str, int, or float.

Examples:

>>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
>>> value = model_object_wrapper.get_report_property('property_name', str)
Source code in pytekla\wrappers.py 
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def get_report_property(self, property_name, property_type):
    """
    Gets the value of a report property for the given `property_name`.

    Parameters
    ----------
    property_name : str
        The name of the report property.
    property_type : type
        The type of the report property, must be `str`, `int`, or `float`.

    Returns
    -------
    str, int, float or None
        The value of the report property. None if it was not found.

    Raises
    ------
    TypeError
        If `property_type` is not `str`, `int`, or `float`.

    Examples
    -------
    >>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
    >>> value = model_object_wrapper.get_report_property('property_name', str)
    """
    check_property_type(property_type)
    to = _get_tekla_object(self)
    was_found, value = to.GetReportProperty(property_name, property_type())
    if was_found:
        return value

get_all_user_properties() #

Get all user properties of the Tekla Model Object as a dictionary.

Returns:

Type Description
dict

A dictionary containing the user properties and their values, with keys as property names and values as property values.

Examples:

>>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
>>> user_properties = model_object_wrapper.get_all_user_properties()
Source code in pytekla\wrappers.py 
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def get_all_user_properties(self):
    """
    Get all user properties of the Tekla Model Object as a dictionary.

    Returns
    -------
    dict
        A dictionary containing the user properties and their values, with keys as property names and values as property values.

    Examples
    -------
    >>> model_object_wrapper = ModelObjectWrapper(some_tekla_object)
    >>> user_properties = model_object_wrapper.get_all_user_properties()
    """
    hash_table = Hashtable()
    to = _get_tekla_object(self)
    to.GetAllUserProperties(hash_table)
    return hash_table

get_multiple_report_properties(string_names=None, float_names=None, int_names=None) #

Get multiple report properties as a dictionary.

Parameters:

Name Type Description Default
string_names list of str, optional

A list of string property names to retrieve.

 None
float_names list of str, optional

A list of float property names to retrieve.

 None
int_names list of str, optional

A list of integer property names to retrieve.

 None

Returns:

Type Description
dict

A dictionary containing the report properties and their values, with keys as property names and values as property values.

Examples:

>>> model_object_wrapper = ModelObjectWrapper(some_model_object)
>>> report_properties = model_object_wrapper.get_multiple_report_properties(
...     string_names=['Property1', 'Property2'],
...     float_names=['Property3', 'Property4'],
...     int_names=['Property5', 'Property6']
... )
>>> report_properties
{'Property1': 'value1', 'Property2': 'value2', 'Property3': 0.5, 'Property4': 2.0, 'Property5': 1, 'Property6': 3}
Source code in pytekla\wrappers.py 
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def get_multiple_report_properties(
    self, string_names=None, float_names=None, int_names=None
):
    """
    Get multiple report properties as a dictionary.

    Parameters
    ----------
    string_names : list of str, optional
        A list of string property names to retrieve.
    float_names : list of str, optional
        A list of float property names to retrieve.
    int_names : list of str, optional
        A list of integer property names to retrieve.

    Returns
    -------
    dict
        A dictionary containing the report properties and their values, with keys as property names and values as property values.

    Examples
    -------
    >>> model_object_wrapper = ModelObjectWrapper(some_model_object)
    >>> report_properties = model_object_wrapper.get_multiple_report_properties(
    ...     string_names=['Property1', 'Property2'],
    ...     float_names=['Property3', 'Property4'],
    ...     int_names=['Property5', 'Property6']
    ... )
    >>> report_properties
    {'Property1': 'value1', 'Property2': 'value2', 'Property3': 0.5, 'Property4': 2.0, 'Property5': 1, 'Property6': 3}
    """
    hash_table = Hashtable()
    to = _get_tekla_object(self)
    to.GetAllReportProperties(
        iterable_to_net_array_list(string_names or []),
        iterable_to_net_array_list(float_names or []),
        iterable_to_net_array_list(int_names or []),
        hash_table,
    )
    return hash_table

get_dynamic_string_property(property_name) #

Get the value of a dynamic string property.

Parameters:

Name Type Description Default
property_name str

The name of the property to retrieve.

 required

Returns:

Type Description
str or None

The value of the specified dynamic string property. None if the property was not found.

Examples:

>>> model_object_wrapper = ModelObjectWrapper(some_model_object)
>>> value = model_object_wrapper.get_dynamic_string_property('property_name')
Source code in pytekla\wrappers.py 
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def get_dynamic_string_property(self, property_name):
    """
    Get the value of a dynamic string property.

    Parameters
    ----------
    property_name : str
        The name of the property to retrieve.

    Returns
    -------
    str or None
        The value of the specified dynamic string property. None if the property was not found.

    Examples
    -------
    >>> model_object_wrapper = ModelObjectWrapper(some_model_object)
    >>> value = model_object_wrapper.get_dynamic_string_property('property_name')
    """
    to = _get_tekla_object(self)
    was_found, value = to.GetDynamicStringProperty(property_name, str())
    if was_found:
        return value

set_multiple_user_properties(**kwargs) #

Sets multiple user properties with the specified names to the specified values.

Parameters:

Name Type Description Default
kwargs dict

The names and values of the user properties to set.

 {}

Returns:

Type Description
bool

Indicates if the properties were set.

Examples:

>>> model_object_wrapper = ModelObjectWrapper(some_model_object)
>>> model_object_wrapper.set_multiple_user_properties(prop1="value1", prop2=123, prop3=3.14)
True
Source code in pytekla\wrappers.py 
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def set_multiple_user_properties(self, **kwargs):
    """
    Sets multiple user properties with the specified names to the specified values.

    Parameters
    ----------
    kwargs : dict
        The names and values of the user properties to set.

    Returns
    -------
    bool
        Indicates if the properties were set.

    Examples
    --------
    >>> model_object_wrapper = ModelObjectWrapper(some_model_object)
    >>> model_object_wrapper.set_multiple_user_properties(prop1="value1", prop2=123, prop3=3.14)
    True
    """
    keys_str, values_str, keys_float, values_float, keys_int, values_int = [
        List[_type]() for _type in (str, str, str, float, str, int)
    ]

    for k, v in kwargs.items():
        match v:
            case str():
                keys_str.Add(k)
                values_str.Add(v)
            case int():
                keys_int.Add(k)
                values_int.Add(v)
            case float():
                keys_float.Add(k)
                values_float.Add(v)
    to = _get_tekla_object(self)
    return to.SetUserProperties(
        keys_str, values_str, keys_float, values_float, keys_int, values_int
    )

set_dynamic_string_property(property_name, value) #

Sets the dynamic string property with the specified name to the specified value.

Parameters:

Name Type Description Default
property_name str

The name of the dynamic string property.

 required
value str

The value to set the dynamic string property to.

 required

Returns:

Type Description
bool

Indicates if the property was set.

Raises:

Type Description
TypeError

If the value type is not str.

Examples:

>>> model_object_wrapper = ModelObjectWrapper(some_model_object)
>>> model_object_wrapper.set_dynamic_string_property("my_property", "my_value")
True
Source code in pytekla\wrappers.py 
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def set_dynamic_string_property(self, property_name, value):
    """
    Sets the dynamic string property with the specified name to the specified value.

    Parameters
    ----------
    property_name : str
        The name of the dynamic string property.
    value : str
        The value to set the dynamic string property to.

    Returns
    -------
    bool
        Indicates if the property was set.

    Raises
    ------
    TypeError
        If the value type is not str.

    Examples
    -------
    >>> model_object_wrapper = ModelObjectWrapper(some_model_object)
    >>> model_object_wrapper.set_dynamic_string_property("my_property", "my_value")
    True
    """
    if type(value) != str:
        raise TypeError("'value' must be str")
    to = _get_tekla_object(self)
    return to.GetDynamicStringProperty(property_name, value)

ModelWrapper #

Bases: BaseWrapper

Wrapper for the Tekla.Structures.Model.Model class.

This class provides a convenient interface for interacting with the Tekla Structures Model. It has several methods to get objects from the model.

References#

https://developer.tekla.com/tekla-structures/api/22/14382
Source code in pytekla\wrappers.py 
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class ModelWrapper(BaseWrapper):
    """Wrapper for the Tekla.Structures.Model.Model class.

    This class provides a convenient interface for interacting with the Tekla Structures Model.
    It has several methods to get objects from the model.

    References
    ----------
        https://developer.tekla.com/tekla-structures/api/22/14382
    """

    main_type = Model

    def __init__(self, tekla_object=None):
        """
        Create a new ModelWrapper instance.

        Examples
        --------
        >>> from pytekla import ModelWrapper
        >>> model = ModelWrapper()
        """
        if tekla_object is None:
            tekla_object = Model()
        super().__init__(tekla_object)
        object.__setattr__(self, "_picker", UI.Picker())
        to = _get_tekla_object(self)
        object.__setattr__(self, "_model_object_selector", to.GetModelObjectSelector())
        object.__setattr__(self, "_ui_model_object_selector", UI.ModelObjectSelector())

    def pick_objects(self, object_type="object", prompt=None):
        """Pick and element from the model.

        Parameters
        ----------
        object_type : str, optional
            The object type to select. Must be one of the following options:
            (object, part, weld, bolt group, reinforcement). By default "object".
        prompt : str, optional
            The string to display as user guidance. By default None.

        Raises
        ------
        ValueError
            If the object_type parameter is incorrect.

        Returns
        -------
        generator
            A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with the selected objects.

        Examples
        -------
        >>> model = ModelWrapper()
        >>> picked_objects = model.pick_objects(object_type="part", prompt="Select parts from the model")
        >>> for obj in selected_element:
        >>>     print(obj)
        """
        try:
            tekla_obj_type = PICKER_OBJECT_TYPES[object_type.lower()]
        except KeyError:
            raise ValueError(
                f"'object_type' must be one of the following options: {list(PICKER_OBJECT_TYPES.keys())}"
            )

        prompt_str = prompt or f"Select one or multiple {object_type}"
        picker = object.__getattribute__(self, "_picker")
        return picker.PickObjects(tekla_obj_type, prompt_str)

    def get_all_objects(self):
        """Get all objects in the model.

        Returns
        -------
        generator
            A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with all the model objects in the current model.

        Examples
        -------
        >>> model = ModelWrapper()
        >>> objects = model.get_all_objects()
        >>> for obj in objects:
        >>>     print(obj)
        """
        selector = object.__getattribute__(self, "_model_object_selector")
        return selector.GetAllObjects()

    def get_selected_objects(self):
        """Get the currently selected objects in the model.

        Returns
        -------
        generator
            A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with the currently selected objects in the model.

        Examples
        -------
        >>> model = ModelWrapper()
        >>> selected_objects = model.get_model_selected_objects()
        >>> for obj in selected_objects:
        >>>     print(obj)
        """
        ms = object.__getattribute__(self, "_ui_model_object_selector")
        return ms.GetSelectedObjects()

    def get_objects_with_types(self, types):
        """Get all objects in the model with specified types.

        Parameters
        ----------
        types : iterable of str
            The object types to retrieve.

        Returns
        -------
        generator
            A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with all the model objects with the specified types in the current model.

        Examples
        -------
        >>> model = ModelWrapper()
        >>> objects = model.get_objects_with_types(["Part", "Weld"])
        >>> for obj in objects:
        >>>     print(obj)
        """
        tekla_types = []
        for _type in types:
            tekla_type = _get_type_by_namespace("Model." + _type)
            tekla_types.append(clr.GetClrType(tekla_type))
        selector = object.__getattribute__(self, "_model_object_selector")
        return selector.GetAllObjectsWithType(tekla_types)

    def get_objects_by_filter(self, model_filter):
        """Get objects from model applying an existing filter.

        Parameters
        ----------
        model_filter : str or Tekla.Structures.Filtering.FilterExpression
            The filter to be applied to the model. It can be a string with the filter name, or a wrapped or unwrapped object of a FilterExpression subclass.

        Returns
        -------
        generator
            A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with the filtered objects in the model.

        Examples
        -------
        >>> model = ModelWrapper()
        >>> filtered_objects = model.get_objects_by_filter("my filter")
        >>> for obj in filtered_objects:
        >>>     print(obj)
        """
        selector = object.__getattribute__(self, "_model_object_selector")
        match (model_filter):
            case str():
                return selector.GetObjectsByFilterName(model_filter)
            case BaseWrapper():
                return selector.GetObjectsByFilter(model_filter.unwrap())
            case _:
                return selector.GetObjectsByFilter(model_filter)

    def get_objects_by_bounding_box(self, min_point_coords, max_point_coords):
        """
        Get objects from the model that are inside a bounding box defined by two points.

        Parameters
        ----------
        min_point_coords : (x: float, y: float, z: float)
            The minimum point coordinates of the bounding box.

        max_point_coords : (x: float, y: float, z: float)
            The maximum point coordinates of the bounding box.

        Returns
        -------
        generator
            A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with the filtered objects in the model.

        Examples
        -------
        >>> model = ModelWrapper()
        >>> min_point = (0.0, 0.0, 0.0)
        >>> max_point = (10.0, 10.0, 10.0)
        >>> filtered_objects = model.get_objects_by_bounding_box(min_point, max_point)
        >>> for obj in filtered_objects:
        >>>     print(obj)
        """
        selector = object.__getattribute__(self, "_model_object_selector")
        return selector.GetObjectsByBoundingBox(
            Point(*min_point_coords), Point(*max_point_coords)
        )

__init__(tekla_object=None) #

Create a new ModelWrapper instance.

Examples:

>>> from pytekla import ModelWrapper
>>> model = ModelWrapper()
Source code in pytekla\wrappers.py 
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def __init__(self, tekla_object=None):
    """
    Create a new ModelWrapper instance.

    Examples
    --------
    >>> from pytekla import ModelWrapper
    >>> model = ModelWrapper()
    """
    if tekla_object is None:
        tekla_object = Model()
    super().__init__(tekla_object)
    object.__setattr__(self, "_picker", UI.Picker())
    to = _get_tekla_object(self)
    object.__setattr__(self, "_model_object_selector", to.GetModelObjectSelector())
    object.__setattr__(self, "_ui_model_object_selector", UI.ModelObjectSelector())

pick_objects(object_type='object', prompt=None) #

Pick and element from the model.

Parameters:

Name Type Description Default
object_type str, optional

The object type to select. Must be one of the following options: (object, part, weld, bolt group, reinforcement). By default "object".

 'object'
prompt str, optional

The string to display as user guidance. By default None.

 None

Raises:

Type Description
ValueError

If the object_type parameter is incorrect.

Returns:

Type Description
generator

A generator of ModelObjectWrapper objects with the selected objects.

Examples:

>>> model = ModelWrapper()
>>> picked_objects = model.pick_objects(object_type="part", prompt="Select parts from the model")
>>> for obj in selected_element:
>>>     print(obj)
Source code in pytekla\wrappers.py 
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def pick_objects(self, object_type="object", prompt=None):
    """Pick and element from the model.

    Parameters
    ----------
    object_type : str, optional
        The object type to select. Must be one of the following options:
        (object, part, weld, bolt group, reinforcement). By default "object".
    prompt : str, optional
        The string to display as user guidance. By default None.

    Raises
    ------
    ValueError
        If the object_type parameter is incorrect.

    Returns
    -------
    generator
        A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with the selected objects.

    Examples
    -------
    >>> model = ModelWrapper()
    >>> picked_objects = model.pick_objects(object_type="part", prompt="Select parts from the model")
    >>> for obj in selected_element:
    >>>     print(obj)
    """
    try:
        tekla_obj_type = PICKER_OBJECT_TYPES[object_type.lower()]
    except KeyError:
        raise ValueError(
            f"'object_type' must be one of the following options: {list(PICKER_OBJECT_TYPES.keys())}"
        )

    prompt_str = prompt or f"Select one or multiple {object_type}"
    picker = object.__getattribute__(self, "_picker")
    return picker.PickObjects(tekla_obj_type, prompt_str)

get_all_objects() #

Get all objects in the model.

Returns:

Type Description
generator

A generator of ModelObjectWrapper objects with all the model objects in the current model.

Examples:

>>> model = ModelWrapper()
>>> objects = model.get_all_objects()
>>> for obj in objects:
>>>     print(obj)
Source code in pytekla\wrappers.py 
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def get_all_objects(self):
    """Get all objects in the model.

    Returns
    -------
    generator
        A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with all the model objects in the current model.

    Examples
    -------
    >>> model = ModelWrapper()
    >>> objects = model.get_all_objects()
    >>> for obj in objects:
    >>>     print(obj)
    """
    selector = object.__getattribute__(self, "_model_object_selector")
    return selector.GetAllObjects()

get_selected_objects() #

Get the currently selected objects in the model.

Returns:

Type Description
generator

A generator of ModelObjectWrapper objects with the currently selected objects in the model.

Examples:

>>> model = ModelWrapper()
>>> selected_objects = model.get_model_selected_objects()
>>> for obj in selected_objects:
>>>     print(obj)
Source code in pytekla\wrappers.py 
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def get_selected_objects(self):
    """Get the currently selected objects in the model.

    Returns
    -------
    generator
        A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with the currently selected objects in the model.

    Examples
    -------
    >>> model = ModelWrapper()
    >>> selected_objects = model.get_model_selected_objects()
    >>> for obj in selected_objects:
    >>>     print(obj)
    """
    ms = object.__getattribute__(self, "_ui_model_object_selector")
    return ms.GetSelectedObjects()

get_objects_with_types(types) #

Get all objects in the model with specified types.

Parameters:

Name Type Description Default
types iterable of str

The object types to retrieve.

 required

Returns:

Type Description
generator

A generator of ModelObjectWrapper objects with all the model objects with the specified types in the current model.

Examples:

>>> model = ModelWrapper()
>>> objects = model.get_objects_with_types(["Part", "Weld"])
>>> for obj in objects:
>>>     print(obj)
Source code in pytekla\wrappers.py 
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def get_objects_with_types(self, types):
    """Get all objects in the model with specified types.

    Parameters
    ----------
    types : iterable of str
        The object types to retrieve.

    Returns
    -------
    generator
        A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with all the model objects with the specified types in the current model.

    Examples
    -------
    >>> model = ModelWrapper()
    >>> objects = model.get_objects_with_types(["Part", "Weld"])
    >>> for obj in objects:
    >>>     print(obj)
    """
    tekla_types = []
    for _type in types:
        tekla_type = _get_type_by_namespace("Model." + _type)
        tekla_types.append(clr.GetClrType(tekla_type))
    selector = object.__getattribute__(self, "_model_object_selector")
    return selector.GetAllObjectsWithType(tekla_types)

get_objects_by_filter(model_filter) #

Get objects from model applying an existing filter.

Parameters:

Name Type Description Default
model_filter str or Tekla.Structures.Filtering.FilterExpression

The filter to be applied to the model. It can be a string with the filter name, or a wrapped or unwrapped object of a FilterExpression subclass.

 required

Returns:

Type Description
generator

A generator of ModelObjectWrapper objects with the filtered objects in the model.

Examples:

>>> model = ModelWrapper()
>>> filtered_objects = model.get_objects_by_filter("my filter")
>>> for obj in filtered_objects:
>>>     print(obj)
Source code in pytekla\wrappers.py 
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def get_objects_by_filter(self, model_filter):
    """Get objects from model applying an existing filter.

    Parameters
    ----------
    model_filter : str or Tekla.Structures.Filtering.FilterExpression
        The filter to be applied to the model. It can be a string with the filter name, or a wrapped or unwrapped object of a FilterExpression subclass.

    Returns
    -------
    generator
        A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with the filtered objects in the model.

    Examples
    -------
    >>> model = ModelWrapper()
    >>> filtered_objects = model.get_objects_by_filter("my filter")
    >>> for obj in filtered_objects:
    >>>     print(obj)
    """
    selector = object.__getattribute__(self, "_model_object_selector")
    match (model_filter):
        case str():
            return selector.GetObjectsByFilterName(model_filter)
        case BaseWrapper():
            return selector.GetObjectsByFilter(model_filter.unwrap())
        case _:
            return selector.GetObjectsByFilter(model_filter)

get_objects_by_bounding_box(min_point_coords, max_point_coords) #

Get objects from the model that are inside a bounding box defined by two points.

Parameters:

Name Type Description Default
min_point_coords (x

The minimum point coordinates of the bounding box.

 required

max_point_coords : (x: float, y: float, z: float) The maximum point coordinates of the bounding box.

Returns:

Type Description
generator

A generator of ModelObjectWrapper objects with the filtered objects in the model.

Examples:

>>> model = ModelWrapper()
>>> min_point = (0.0, 0.0, 0.0)
>>> max_point = (10.0, 10.0, 10.0)
>>> filtered_objects = model.get_objects_by_bounding_box(min_point, max_point)
>>> for obj in filtered_objects:
>>>     print(obj)
Source code in pytekla\wrappers.py 
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def get_objects_by_bounding_box(self, min_point_coords, max_point_coords):
    """
    Get objects from the model that are inside a bounding box defined by two points.

    Parameters
    ----------
    min_point_coords : (x: float, y: float, z: float)
        The minimum point coordinates of the bounding box.

    max_point_coords : (x: float, y: float, z: float)
        The maximum point coordinates of the bounding box.

    Returns
    -------
    generator
        A generator of [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper] objects with the filtered objects in the model.

    Examples
    -------
    >>> model = ModelWrapper()
    >>> min_point = (0.0, 0.0, 0.0)
    >>> max_point = (10.0, 10.0, 10.0)
    >>> filtered_objects = model.get_objects_by_bounding_box(min_point, max_point)
    >>> for obj in filtered_objects:
    >>>     print(obj)
    """
    selector = object.__getattribute__(self, "_model_object_selector")
    return selector.GetObjectsByBoundingBox(
        Point(*min_point_coords), Point(*max_point_coords)
    )

DrawingDbObjectWrapper #

Bases: BaseWrapper, WithUserPropertyMixin

A wrapper class for Tekla.Structures.Drawing.DataBaseObject subclasses.

Examples:

>>> from pytekla import DrawingDbOjectWrapper
>>> drawing_wrapper = DrawingDbOjectWrapper("Drawing.GADrawing")
>>> drawing_wrapper.set_user_property('property_name', 'property_value')

References#

https://developer.tekla.com/tekla-structures/api/22/10404
Source code in pytekla\wrappers.py 
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class DrawingDbObjectWrapper(BaseWrapper, WithUserPropertyMixin):
    """
    A wrapper class for Tekla.Structures.Drawing.DataBaseObject subclasses.

    Examples
    --------
    >>> from pytekla import DrawingDbOjectWrapper
    >>> drawing_wrapper = DrawingDbOjectWrapper("Drawing.GADrawing")
    >>> drawing_wrapper.set_user_property('property_name', 'property_value')

    References
    ----------
        https://developer.tekla.com/tekla-structures/api/22/10404
    """

    main_type = DatabaseObject

    def get_all_user_properties(self):
        """
        Return a dictionary containing all of the user-defined properties associated
        with this DatabaseObject object.

        Returns
        -------
        dict
            A dictionary containing the user-defined properties, where the keys are
            the names of the properties and the values are their corresponding values.

        Notes
        -----
        This method retrieves all of the user-defined properties associated with this
        DatabaseObject object, regardless of their data type. The properties are returned as a
        dictionary, where the keys are the property names and the values are their
        corresponding values.

        Examples
        --------
        >>> from pytekla import DrawingWrapper
        >>> drawing_wrapper = DrawingWrapper("GADrawing")
        >>> user_props = drawing_wrapper.get_all_user_properties()
        >>> user_props
        {'property1': 'value1', 'property2': 42, 'property3': 3.14}
        """
        to = _get_tekla_object(self)
        _, string_dict = to.GetStringUserProperties(Dictionary[String, String]())
        _, int_dict = to.GetIntegerUserProperties(Dictionary[String, Int32]())
        _, float_dict = to.GetDoubleUserProperties(Dictionary[String, Double]())

        # it's easier to process the result as a Python dict
        final_dict = {}

        for net_dict in (string_dict, int_dict, float_dict):
            final_dict |= net_idictionary_to_dict(net_dict)

        return final_dict

get_all_user_properties() #

Return a dictionary containing all of the user-defined properties associated with this DatabaseObject object.

Returns:

Type Description
dict

A dictionary containing the user-defined properties, where the keys are the names of the properties and the values are their corresponding values.
Notes#

This method retrieves all of the user-defined properties associated with this DatabaseObject object, regardless of their data type. The properties are returned as a dictionary, where the keys are the property names and the values are their corresponding values.

Examples:

>>> from pytekla import DrawingWrapper
>>> drawing_wrapper = DrawingWrapper("GADrawing")
>>> user_props = drawing_wrapper.get_all_user_properties()
>>> user_props
{'property1': 'value1', 'property2': 42, 'property3': 3.14}
Source code in pytekla\wrappers.py 
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def get_all_user_properties(self):
    """
    Return a dictionary containing all of the user-defined properties associated
    with this DatabaseObject object.

    Returns
    -------
    dict
        A dictionary containing the user-defined properties, where the keys are
        the names of the properties and the values are their corresponding values.

    Notes
    -----
    This method retrieves all of the user-defined properties associated with this
    DatabaseObject object, regardless of their data type. The properties are returned as a
    dictionary, where the keys are the property names and the values are their
    corresponding values.

    Examples
    --------
    >>> from pytekla import DrawingWrapper
    >>> drawing_wrapper = DrawingWrapper("GADrawing")
    >>> user_props = drawing_wrapper.get_all_user_properties()
    >>> user_props
    {'property1': 'value1', 'property2': 42, 'property3': 3.14}
    """
    to = _get_tekla_object(self)
    _, string_dict = to.GetStringUserProperties(Dictionary[String, String]())
    _, int_dict = to.GetIntegerUserProperties(Dictionary[String, Int32]())
    _, float_dict = to.GetDoubleUserProperties(Dictionary[String, Double]())

    # it's easier to process the result as a Python dict
    final_dict = {}

    for net_dict in (string_dict, int_dict, float_dict):
        final_dict |= net_idictionary_to_dict(net_dict)

    return final_dict

DrawingHandlerWrapper #

Bases: BaseWrapper

A wrapper class for Tekla.Structures.Drawing.DrawingHandler.

Examples:

>>> from pytekla import DrawingHandlerWrapper
>>> drawing_handler = DrawingHandlerWrapper()
>>> drawings = list(drawing_handler.get_drawings())
>>> active_drawing = drawing_handler.get_active_drawing()

References#

https://developer.tekla.com/tekla-structures/api/22/10647
Source code in pytekla\wrappers.py 
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class DrawingHandlerWrapper(BaseWrapper):
    """
    A wrapper class for Tekla.Structures.Drawing.DrawingHandler.

    Examples
    --------
    >>> from pytekla import DrawingHandlerWrapper
    >>> drawing_handler = DrawingHandlerWrapper()
    >>> drawings = list(drawing_handler.get_drawings())
    >>> active_drawing = drawing_handler.get_active_drawing()

    References
    ----------
        https://developer.tekla.com/tekla-structures/api/22/10647
    """

    main_type = DrawingHandler

    def __init__(self, tekla_object=None):
        """
        Create a new DrawingHandlerWrapper instance.

        Examples
        --------
        >>> from pytekla import DrawingHandlerWrapper
        >>> drawing_handler = DrawingHandlerWrapper()
        """
        if tekla_object is None:
            tekla_object = DrawingHandler()
        super().__init__(tekla_object)

    def get_drawings(self):
        """
        Generate all of the drawing objects in the Tekla model.

        Returns
        -------
        generator
            A generator of [`DrawingDbObjectWrapper`][pytekla.wrappers.DrawingDbObjectWrapper] objects.

        Examples
        --------
        >>> from pytekla import DrawingHandlerWrapper
        >>> drawing_handler = DrawingHandlerWrapper()
        >>> drawings = list(drawing_handler.get_drawings())
        """
        to = _get_tekla_object(self)
        return to.GetDrawings()

    def get_active_drawing(self):
        """
        Return the active drawing object, if one is currently selected.

        Returns
        -------
        DrawingDbObjectWrapper or None
            A DrawingWrapper object for the currently active drawing, or None if
            no drawing is currently active.

        Examples
        --------
        >>> from pytekla import DrawingHandlerWrapper
        >>> drawing_handler = DrawingHandlerWrapper()
        >>> active_drawing = drawing_handler.get_active_drawing()
        """
        to = _get_tekla_object(self)
        active_drawing = to.GetActiveDrawing()
        if active_drawing is not None:
            return active_drawing

__init__(tekla_object=None) #

Create a new DrawingHandlerWrapper instance.

Examples:

>>> from pytekla import DrawingHandlerWrapper
>>> drawing_handler = DrawingHandlerWrapper()
Source code in pytekla\wrappers.py 
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def __init__(self, tekla_object=None):
    """
    Create a new DrawingHandlerWrapper instance.

    Examples
    --------
    >>> from pytekla import DrawingHandlerWrapper
    >>> drawing_handler = DrawingHandlerWrapper()
    """
    if tekla_object is None:
        tekla_object = DrawingHandler()
    super().__init__(tekla_object)

get_drawings() #

Generate all of the drawing objects in the Tekla model.

Returns:

Type Description
generator

A generator of DrawingDbObjectWrapper objects.

Examples:

>>> from pytekla import DrawingHandlerWrapper
>>> drawing_handler = DrawingHandlerWrapper()
>>> drawings = list(drawing_handler.get_drawings())
Source code in pytekla\wrappers.py 
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def get_drawings(self):
    """
    Generate all of the drawing objects in the Tekla model.

    Returns
    -------
    generator
        A generator of [`DrawingDbObjectWrapper`][pytekla.wrappers.DrawingDbObjectWrapper] objects.

    Examples
    --------
    >>> from pytekla import DrawingHandlerWrapper
    >>> drawing_handler = DrawingHandlerWrapper()
    >>> drawings = list(drawing_handler.get_drawings())
    """
    to = _get_tekla_object(self)
    return to.GetDrawings()

get_active_drawing() #

Return the active drawing object, if one is currently selected.

Returns:

Type Description
DrawingDbObjectWrapper or None

A DrawingWrapper object for the currently active drawing, or None if no drawing is currently active.

Examples:

>>> from pytekla import DrawingHandlerWrapper
>>> drawing_handler = DrawingHandlerWrapper()
>>> active_drawing = drawing_handler.get_active_drawing()
Source code in pytekla\wrappers.py 
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def get_active_drawing(self):
    """
    Return the active drawing object, if one is currently selected.

    Returns
    -------
    DrawingDbObjectWrapper or None
        A DrawingWrapper object for the currently active drawing, or None if
        no drawing is currently active.

    Examples
    --------
    >>> from pytekla import DrawingHandlerWrapper
    >>> drawing_handler = DrawingHandlerWrapper()
    >>> active_drawing = drawing_handler.get_active_drawing()
    """
    to = _get_tekla_object(self)
    active_drawing = to.GetActiveDrawing()
    if active_drawing is not None:
        return active_drawing

wrap(some_object, *args, detect_types=True) #

Wrap the given object with a suitable wrapper class.

Parameters:

Name Type Description Default
some_object object

The object to wrap.

 required
args

Any values that you want to pass to the wrapped object to instanciate it.

 ()
detect_types bool, optional

Whether to automatically detect the type of the object and wrap it with an appropriate class. Defaults to True.

 True

Returns:

Type Description
object

The wrapped object.

Notes#

This function checks if the given object is a class and returns it unchanged if so. Otherwise, if detect_types is True, it attempts to determine the type using the namescape path of the object and wrap it with an appropriate class. If the object is not a string will try to wrap it with an appropriate class. If the object is not of a known type, it is returned unchanged.

The possible wrapper classes are:

  • BaseWrapper: The base wrapper class that other wrappers inherit from. Can wrap any object in the Tekla.Structures namespace.

  • ModelObjectWrapper: A wrapper for Tekla.Structures.Model.ModelObject subclasses instances.

  • ModelWrapper: A wrapper for Tekla.Structures.Model.Model instances.

  • DrawingDbObjectWrapper: A wrapper for Tekla.Structures.Drawing.DatabaseObject subclasses instances.

  • DrawingHandlerWrapper: A wrapper for Tekla.Structures.Drawing.DrawingHandler instances.

Examples:

>>> wrapped_obj = wrap("Model.Model")
>>> # ModelWrapper instance

>>> wrapped_obj = wrap("Model.Beam")
>>> # ModelObjectWrapper

>>> from Tekla.Structures.Model import Beam
>>> wrapped_obj = wrap(Beam())
>>> # ModelObjectWrapper
Source code in pytekla\wrappers.py 
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def wrap(some_object, *args, detect_types=True):
    """
    Wrap the given object with a suitable wrapper class.

    Parameters
    ----------
    some_object : object
        The object to wrap.
    args: object
        Any values that you want to pass to the wrapped object to instanciate it.
    detect_types : bool, optional
        Whether to automatically detect the type of the object and wrap it with an appropriate class.
        Defaults to True.

    Returns
    -------
    object
        The wrapped object.

    Notes
    -----
    This function checks if the given object is a class and returns it unchanged if so. Otherwise, if
    `detect_types` is True, it attempts to determine the type using the namescape path of the object and wrap it with an appropriate
    class. If the object is not a string will try to wrap it with an appropriate class. If the object is not of a known type, it is returned unchanged.

    The possible wrapper classes are:

    - [`BaseWrapper`][pytekla.wrappers.BaseWrapper]: The base wrapper class that other wrappers inherit from. Can wrap any object in the Tekla.Structures namespace.

    - [`ModelObjectWrapper`][pytekla.wrappers.ModelObjectWrapper]: A wrapper for Tekla.Structures.Model.ModelObject subclasses instances.

    - [`ModelWrapper`][pytekla.wrappers.ModelWrapper]: A wrapper for Tekla.Structures.Model.Model instances.

    - [`DrawingDbObjectWrapper`][pytekla.wrappers.DrawingDbObjectWrapper]: A wrapper for Tekla.Structures.Drawing.DatabaseObject subclasses instances.

    - [`DrawingHandlerWrapper`][pytekla.wrappers.DrawingHandlerWrapper]: A wrapper for Tekla.Structures.Drawing.DrawingHandler instances.

    Examples
    --------
    >>> wrapped_obj = wrap("Model.Model")
    >>> # ModelWrapper instance

    >>> wrapped_obj = wrap("Model.Beam")
    >>> # ModelObjectWrapper

    >>> from Tekla.Structures.Model import Beam
    >>> wrapped_obj = wrap(Beam())
    >>> # ModelObjectWrapper
    """
    unwrapped_args = [a.unwrap() if isinstance(a, BaseWrapper) else a for a in args]

    if inspect.isclass(some_object):
        return some_object

    if detect_types:
        if isinstance(some_object, str):
            if "Enum" in some_object:
                some_object_splitted = some_object.split(".")
                some_object = ".".join(some_object_splitted[:-1])
                some_object_type = _get_type_by_namespace(some_object)
                return BaseWrapper(getattr(some_object_type, some_object_splitted[-1]))

            some_object_type = _get_type_by_namespace(some_object)
            clr_type = clr.GetClrType(some_object_type)
            if clr_type.IsAbstract and clr_type.IsSealed:
                return BaseWrapper(some_object_type)
            some_object = some_object_type(*unwrapped_args)

    class_to_use = None

    for subclass in BaseWrapper.__subclasses__():
        if isinstance(some_object, subclass.main_type):
            class_to_use = subclass

    new_instance = None

    if class_to_use is not None:
        new_instance = class_to_use(some_object)
        return new_instance

    cls_name = str(some_object.__class__)

    if "Tekla.Structures" in cls_name:
        new_instance = BaseWrapper(some_object)
        return new_instance

    return some_object

Data manager#

create_model_objects_dataframe(objects, report_properties=None, user_properties=None, attributes=None, use_all_user_properties=False) #

Create a pandas DataFrame from objects based on provided properties and attributes.

Parameters:

Name Type Description Default
objects iterable of ModelObjectWrapper

A iterable of objects to be transformed into a DataFrame.

 required
report_properties dict, optional

A dictionary of report properties to be extracted from each object, with key being the report property name and value being the report property type. Default is None.

 None
user_properties dict, optional

A dictionary of user properties to be extracted from each object, with key being the user property name and value being the user property type. Default is None.

 None
attributes list, optional

A list of object attributes to be extracted from each object. Default is None.

 None
use_all_user_properties bool, optional

A flag indicating if all user properties should be extracted from each object. If set to True, the user_properties parameter will be ignored. Default is False.

 False

Returns:

Type Description
pd.DataFrame

A pandas DataFrame containing the extracted information.

Examples:

>>> objects = [obj1, obj2, obj3]
>>> report_properties = {'prop1': int, 'prop2': str}
>>> user_properties = {'prop3': float, 'prop4': str}
>>> attributes = ['attr1', 'attr2', 'attr2.attr3']
>>> create_dataframe(objects, report_properties, user_properties, attributes)
    prop1 prop2  prop3 prop4  attr1  attr2  attr3
    0     1    A   3.14    B1   1.0   0.5   0.7
    1     2    C   6.28    B2   2.0   1.0   1.1
    2     3    E   9.42    B3   3.0   1.5   1.5
Source code in pytekla\data_manager.py 
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def create_model_objects_dataframe(
    objects,
    report_properties=None,
    user_properties=None,
    attributes=None,
    use_all_user_properties=False,
):
    """
    Create a pandas DataFrame from objects based on provided properties and attributes.

    Parameters
    ----------
    objects : iterable of ModelObjectWrapper
        A iterable of objects to be transformed into a DataFrame.
    report_properties : dict, optional
        A dictionary of report properties to be extracted from each object, with key being the report property name and value being the report property type. Default is None.
    user_properties : dict, optional
        A dictionary of user properties to be extracted from each object, with key being the user property name and value being the user property type. Default is None.
    attributes : list, optional
        A list of object attributes to be extracted from each object. Default is None.
    use_all_user_properties : bool, optional
        A flag indicating if all user properties should be extracted from each object. If set to True, the `user_properties` parameter will be ignored. Default is False.

    Returns
    -------
    pd.DataFrame
        A pandas DataFrame containing the extracted information.

    Examples
    --------
    >>> objects = [obj1, obj2, obj3]
    >>> report_properties = {'prop1': int, 'prop2': str}
    >>> user_properties = {'prop3': float, 'prop4': str}
    >>> attributes = ['attr1', 'attr2', 'attr2.attr3']
    >>> create_dataframe(objects, report_properties, user_properties, attributes)
        prop1 prop2  prop3 prop4  attr1  attr2  attr3
        0     1    A   3.14    B1   1.0   0.5   0.7
        1     2    C   6.28    B2   2.0   1.0   1.1
        2     3    E   9.42    B3   3.0   1.5   1.5
    """
    data = []
    for obj in objects:
        obj_data = {}

        if report_properties:
            for report_prop_name, report_prop_type in report_properties.items():
                obj_data[report_prop_name] = obj.get_report_property(
                    report_prop_name, report_prop_type
                )

        if user_properties or use_all_user_properties:
            if use_all_user_properties:
                obj_data |= obj.get_all_user_properties()
            else:
                for user_prop_name, user_prop_type in user_properties.items():
                    obj_data[user_prop_name] = obj.get_user_property(
                        user_prop_name, user_prop_type
                    )

        if attributes:
            for attr in attributes:
                attrs = attr.split(".")
                current_obj = obj
                for at in attrs:
                    current_obj = getattr(current_obj, at, None)
                    if callable(current_obj):
                        current_obj = current_obj()
                obj_data[attr] = current_obj

        data.append(obj_data)

    return pd.DataFrame(data)