itertree package

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The main itertree class

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

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This part of code contains the main iTree object

class itertree.itree_main.iTree(tag=<class 'itertree.itree_helpers.NoTag'>, value=<class 'itertree.itree_helpers.NoValue'>, subtree=None, link=None, flags=0)

Bases: itertree.itree_private._iTreePrivate

__init__(tag=<class 'itertree.itree_helpers.NoTag'>, value=<class 'itertree.itree_helpers.NoValue'>, subtree=None, link=None, flags=0)

This is the main class related to itertree module. It represents the node in the nested tree structure.

In case the object contains a subtree this object is the parent of the children in the subtree and its inner children (children, sub-children, etc.). The ´iTree´-object itself can also be a child of a parent ´iTree´-object. If this is not the case the ´iTree´-object is the root of the tree.

Limitation: An ´iTree´-object can be integrated as a child in one ´iTree´ only (one parent only principle)!

Each ´iTree´-object contains a “tag”. The objects tag can be any hashable object.

Different as dictionaries it is allowed to put multiple items with the same tag inside the ´iTree´. Those items with the same tag are placed and ordered (enumerated) in the related tag-family. The specific items can be targeted via a zag_idx tuple (family-tag,family-index) which is the items unique key.

Linked ´iTree´-objects will behave a bit special. They have a read only structure (children) and they contain the children (tree) of the linked ´iTree´. The “local” attributes like tag, value, … can be set independent of the linked item (local properties).

To change the tree structure of such an object you can change the original link target. But an explicit reload ( ´load_links()´ ) is required to get the change active in the linked items.

Beside the linked item the user can add local items and mix them with the linked ones. But the general structure is always determined by the linked in children.

Beside the subtree the ´iTree´-object can also contain a value. The value can be any type of Python objects that is stored in the tree-node (comparable with the value of a dictionary). If it is required by the user to calculate the hash of the íTree´ via ´hash(item)´ some value objects might not be hashable and will raise an exception. But as long as the objects can be pickled a hash replacement will be found in the hash of ´iTree´. E.g. a dict placed as a value makes no troubles even if teh user likes to hash the tree.

As a helper the ´iTree´-object can be coupled with other objects (which might be helpful if you have a displayed tree in a GUI that is connected with the ´íTree´. Be aware that this helper function has only temporary character. It is not stored when dumping (standard dump) or considered in comparisons, etc. The coupled object is ignored by all internal functionalities. Also in linked items the coupled object is not taken over from the link and can be set independent.

The behavior of a íTree´ object can be influenced by specific properties or flags:

• Read-only tree: An ´iTree´ object where the subtree is protected and cannot be changed

• Read-only value: An ´iTree´ object where the value is protected and cannot be changed

The ´iTree´ object contains a large number of properties which should help the user to reach the required information as comfortable as possible. Especially the tree related information might be interesting:

• mytree.tag -> family-tag of the item

• mytree.idx -> absolute index of the object

• mytree.tag_idx -> key tuple (family-tag, family-index)

• mytree.idx_path -> tuple of absolute indexes from the root to the item

• mytree.tag_idx_path -> tuple of key-tuples from the root to the item

• mytree.parent -> parent item of the item

• mytree.root -> root item of the item (highest level parent)

• mytree.pre_item -> pre item (the children in the parent that is before this item)

• mytree.post_item -> post item (the children in the parent that is after this item)

• mytree.level -> How deep the item is in the tree related to the root

• mytree.max_depth -> How deep the sub-items (nested) of the ´iTree´ go in maximum (deep levels)

In case the ´iTree´ object is not part of another ´iTree´ (is root) those attributes will deliver in most cases ´None´.

• mytree.is_root -> True in case the item is a root ´iTree´)no parent)

• mytree.is_tree_read_only -> True in case the subtree is protected and read-only

• mytree.is_value_read_only -> True in case the item value is protected and read-only

• mytree.is_linked -> True in case the item is a linked item (read_only)

• mytree.is_link_root-> True in case the item is a root for a link to another ´iTree´

• mytree.link_root-> Delivers the related link-root in case the item is linked

• mytree.value-> Delivers the value object stored in the ´iTree´ item

There are different ways to access the children and sub-children in the tree of a ´iTree´ object.

The standard access for single items is via ´itree_obj[target]´ ( ´__getitem__(target)´) call. As targets the user has different options:

• index - absolute target index integer (fastest operation)

• key - key tuple (family_tag, family_index)

• tag or tag sets- family_tag object targeting a whole family

• target-list - absolute indexes or keys to be replaced (indexes and keys can be mixed)

• index slice - slice of absolute indexes

• key slice - tuple of (family_tag, family_index_slice)

• filter-method - method to filtering specific children

Beside the first level functions the iTree-object contains the helper class .deep which contains the in-depth functionalities targeting all the nested sub-children of the object.

As the name itertree should suggest a wide range of iteration methods are available in the class. They can be combined with different kind of filters.

Note

As optional filter_method-parameter the user can give:

• None- filter inactive

• Callable delivering True/False related to a characteristic of the ìTree-object (iterated items)

Beside this the internal filtering is normally a hierarchical filtering (If the parent does not match to the filter all children are excluded too, even that they match to the filter). Some methods contain a switch for non-hierarchical filtering too. But most often the non-hierarchical filtering can be realized via the build-in filter() method and in this case the switch is not available.

Here the power of the iterators is obvious because cascaded filter queries can be constructed and finally in only one full iteration over all the items is required to get the results back (sometimes the full iteration is not required).

It’s recommended to have a look into itertools package for better usage of the delivered iteration-generators.

The design of the ´iTree´´ object is made for best possible performance even that it is pure Python. Some part of the code might look less good readable or in the iteration-generators you find the if else outside the iteration functionality which is not realized via sub-functions we have here redundant codings. But its is made to avoid conditions or function calls inside the loops which would be bad for the performance.

Parameters

• tag (Hashable) – family tag of the iTree object (any hashable object)

• value (object) – value to be stored in the iTree object

• subtree (Optional[Iterable]) – Iterable or Iterator containing the subtree items or an argument list (internal functionality)

• link (Optional[iTLink]) – iTLink object targeting another iTree

• flags (int) –

  flags taken from iTFLAG class:

  • iTFLAG.READ_ONLY_TREE - mark the subtree of this iTree as read-only the subtree will be protected from changes in this case

  • iTFLAG.READ_ONLY_VALUE - mark the value of this iTree object as read-only

  • iTFLAG.LOAD_LINKS - load the links during instance automatically

  Multiple flags can be combined via |

__iter__

property parent

Property delivers current items parent-object.

Return type

Union[iTree, None]

Returns

iTree parent-object or None (in case no parent exists)

property is_root

Is this item a root-item (has no parent)?

Return type

bool

Returns

• True - is root

• False - is not root

property root

property delivers the root-item of the tree

In case the item has no parent it will deliver itself

Return type

iTree

Returns

iTree root item

property tag

This is the access to the object-tag. The tag gives the relation to the tag-family in iTree-objects.

The tag is comparable with a key in dictionaries but in iTrees the tag is not unique! For unique iTree identification the tag_idx property must be used.

Any hashable object can be used as a tag, but in case “exotic” objects are used and serialization is required the user may have to extend the functionality of the serializer.

Return type

Hashable

Returns

tag - hashable object giving the family relation

property idx

Index of this object in the iTree (related to the absolute order)

Method is very important for internal functionalities

Note

In general the item index is cached but in case of deleted items or reorder operations the cache might be outdated. In this case the index update based on a search might take longer.

Return type

Union[int, None]

Returns

unsigned integer representing the index (related to absolute order of iTree)

property idx_path

delivers a list of absolute indexes from the root to this item

For items with no parent (root_item) an empty tuple will be delivered

Note

We deliver here a tuple because it might be helpful if the object is hashable (usage as a dict key)

Return type

tuple

Returns

tuple of index integers (here we do not deliver an iterator!)

property tag_idx

The tag_idx is a unique identification of the item. It is represented by a tuple containing the family-tag and the family related index of the item.

If the item is not part of a parent-tree (root-item) in this case the result will be None.

Return type

Union[tuple, None]

Returns

tuple (family-tag, family-index) or None (if item has no parent)

property tag_idx_path

The path is a tuple of tag_idx tuples from root to this item. Each tag_idx is a tuple containing the pair family-tag and family-index.

For items with no parent (rooot_item) an empty tuple will be delivered

Note

We deliver here a tuple because it might be helpful if the object is hashable (usage as a dict key)

Return type

tuple

Returns

tuple of key tuples containing family-tag and family-index

force_cache_update(idx=True, fam_keys=True, all_keys=True)

Forces the update of the index and keys in cache

Normally this is not required the methode is mainly used for testing proposes

Parameters

• idx – True - update absolute-indexes

• fam_keys – True - update this items family-indexes

• all_keys – True - update all families faimily-indexes

property pre_item

Delivers the pre-item (predecessor) of this object in the parent-tree. If self is first item or there is no parent None will be delivered.

Return type

Union[iTree,None]

Returns

iTree predecessor or None (no match)

property post_item

Delivers the post-item (successor) of this object in the parent-tree. If self is first item or there is no parent None will be delivered.

Return type

Union[iTree,None]

Returns

iTree successor or None (no match)

property level

Delivers the distance (number of levels) to the root-item of the tree. Or in other words how deep in tree the item is positioned. In case item has no parent (is a root-item) this method will deliver 0.

Return type

int

Returns

integer - number of levels (outer direction)

property max_depth

Relative from this item the method measures the maximum depth of the tree and delivers the maximum number of levels that are found in this object.

If the user wants to now the maximum depth of the whole tree ensure that the property of the root-item is read. The user might use my_tree.root.max_depth to ensure this.

Return type

int

Returns

integer maximal number of levels that exists in the tree (inner direction)

property tag_number

property contains the number of tags (families) the itree contains :return: integer

property deep

Subclass containing the deep access to the nested structures of iTree :return:

property flags

Give the flags value of the object. The integer value stored in this property contains the bit flags related to the constants iTFLAG or _iTFLAG.

To see the details the user might use bin() or the helper property flags_repr which delivers a string containing all set flags.

;rtype: int :return: The flags set for this item

flags_repr(public_only=True)

String representation of flags for this item

Parameters

public_only (bool) –

• True - Consider only the public flags (given by the user) -> default

• False - Show all flags (also linked and placeholder flags)

;rtype: str :return: String repr of the flags set for this item

property is_tree_read_only

Is the tree protection flag set? In this case the tree structure cannot be changed

This property targets the tree structure not the value!

Return type

bool

Returns

• False - subtree can be changed (writeable)

• True - subtree is protected (read-only)

set_tree_read_only()

Set the tree protection flag. If the flag is set the subtree structure can not be changed anymore.

Warning

Setting the structural protection is always a deep operation. In all children and sub-children the protection flag will be activated too! But when unset the behavior it is not automatically made as a deep operation`. Here the differentiation in between the two methods unset_tree_read_only() and unset_tree_read_only_deep() exists.

unset_tree_read_only()

Unset the tree protection flag on the item. Only the children structure of this item is made writable by this operation.

Except

If the parent contains the tree protection flag a PermissionError will be raised

property is_value_read_only

Is iTree value read_only? Is the value protection flag iTFLAG.READ_ONLY_VALUE is set?

Return type

bool

Returns

True - read-only protection of value active False - value is writeable

set_value_read_only()

Set the write protection of the value (set flag: iTFLAG.READ_ONLY_VALUE)

unset_value_read_only()

Unset the write protection flag of the value (set flag: iTFLAG.READ_ONLY_VALUE). Value will be writeable afterwards

property value

Delivers the full value object stored in the iTree-object

Return type

object

Returns

value-object of the item

set_value(value)

Set/replace the value content of the iTree-object.

The method returns the previous stored value object that was replaced by the operation.

Note

If an iTValueModel is stored as value in the iTree by default the set_value() method will target the value which is stored inside the model. If the model itself should be exchanged the user must give the new model as value parameter of this method. To replace the model with another Python object the user must first delete the model via del_value() command and afterwards set the new value.

Parameters

value (object) – data-object that should be placed as value or in case we have a iTValueModel already as value it is placed inside the model.

Return type

object

Returns

old value object that was stored in iTree before

set_key_value(key, value)

Depending on the already stored object this operation is a sub-replacement of a part only.

The method returns the previous stored value object that was replaced by the operation.

The user can influence the behavior by giving the key parameter. And it depends on the already stored value object (e.g. a list or dict ). Only the value of the related item will be replaced or in case the item did not exist yet the might object will be extended by the given value ( dict only).

Depending on given key parameter and the already stored object we have the following possible behaviours:

• dict stored in value -> store the value in the dict with the key given in key_index

• dict stored in value and matching item-value is a iTValueModel -> replace value inside the model

• list stored in value -> key_index must be an index and replace the related item in the list with the value given

• list stored in value and matching (index) item-value is a iTValueModel -> replace value inside the model

• key == INF and list stored in value -> append given value in the list

Note

If an iTValueModel is stored as value in the iTree by default the mytree.set_value()-method will target the value which is stored inside the model. If the model itself should be exchanged the user must give a new model as value parameter of this method. To replace the model with another Python object the user must first delete the model via del mytree.value[key] command and afterwards set the new value or he sets the value directly via mytree.value[key]==new_value .

Parameters

• key (Optional[Hashable,int]) – key or index of the value object (depends on the object already stored in iTree ). if key==INF the value will be appended in case a list-like object is already stored in the iTree-object.

• value (object,) – value object that should be placed as value or in case a key is given the sub-value in the iTree or in case we have a iTValueModel is used inside the model.

Return type

object

Returns

old value object that was stored in iTree before

get_value()

Delivers the value-object of the item or a sub-value in case key_index parameter is used and a matching object is stored in the iTree .

Note

If iTValueModel is stored in iTree the method will not target the model it will target the value inside. If the model itself is required the value-property of iTree must be used.

Except

In case a key_index is given but the object is not a dict or a list like object an AttributeError will be raised ( __getitem__()`required). If no matching item is found an `IndexError or KeyError will be raised.

Return type

object

Returns

value object the iTree or iTValueModel (in case a model is stored in the iTree )

get_key_value(key)

Delivers the value-object of the item or a sub-value in case key_index parameter is used and a matching object is stored in the iTree .

In case the stored value is a dict-like object the key will be used as the key of the dict. In case the stored value is a list-like object the keyx will be used as the index of the list.

In case the target value is a iTValueModel the value inside will be targeted and not the model itself.

Note

If iTValueModel is stored in iTree the method will not target the model it will target the value inside. If the model itself is required the value-property of iTree must be used.

Except

In case a key_index is given but the object is not a dict or list like object an AttributeError will be raised ( __getitem__()-method required). If no matching item is found an IndexError or KeyError will be raised.

Parameters

key (Optional[Hashable,int]) – Optional key or index parameter

Return type

object

Returns

value object the iTree or iTValueModel (in case a model is stored in the iTree)

del_value()

Deletes the full value-object stored in ´iTree´ ( ´NoValue´ is stored in iTree).

This method will always delete the whole object stored in iTree even iTValueModel-objects are deleted. To delete the value content of a model mytree.value.clear() or ‘set_value(NoValue)’ might be used.

Returns

deleted value

del_key_value(key)

If no parameter is given deletes the full value-object stored in ´iTree´ (store ´NoValue´ ).

In case a key or index is given and the value contains a matching object we will only pop out the related sub-item.

This method will always delete the whole targeted object even iTValueModel-objects are deleted. To delete the value content of a model mytree.value.clear() or ‘set_value(NoValue)’ might be used.

Except

In case a key is given but the object is not dict or list like a TypeError or AttributeError will be raised ( __delitem__()-method is targeted); If the given key does not exist or an invalid parameter is given a KeyError or IndexError will be raised.

Parameters

key (Optional[Hashable,int]) – Optional key or index to exchange just sub-items in the value

Returns

deleted value

property coupled_object

The iTree-object can be coupled with another Python-object. The pointer to the object is stored and can be reached via this property. (E.g. this can be helpful when connecting the iTree with a visual item (hypertree-list item) in a GUI)

Returns

pointer to coupled-object or None if no object is stored

set_coupled_object(coupled_object)

Couple another Python-object with this iTree-object.

Compared with the value the coupled-object is not tracked by any internal functions. We do not consider it in any relation (e.g. __contains__() and do not dump it in files, etc. Even in linked items the coupled-object is not protected. And in copies it is ignored and not taken over.

Note

E.g. The coupled-object might be an object in a GUI that is related to this item.

Parameters

coupled_object – object pointer to the object that should be coupled with this iTree item

append(item=<class 'itertree.itree_helpers.NoValue'>)

Append the given iTree-object to the iTree (new last child) The append() method is the fastest way to add a single item to the end of the tree.

Except

In case iTree-object has already a parent a RecursionError will be raised Other exceptions might come up in case the iTree is protected (tree read-only mode).

Parameters

item (Union[iTree,object]) –

iTree-object to be appended

Warning

In case the given item-object is not a iTree-object the item is interpreted as a value and the iTree will be created implicit (with tag-family NoTag) in the way:

iTree(tag=NoTag, value=item) ~ ìTree(value=item) If no item is given an empty iTree is created tag=`NoTag`; value=`NoValue`.

>>> root=iTree('root')
>>> root.append('myvalue')
iTree(value='myvalue')
>>> root.append() # append an empty iTree-object
iTree()

Return type

iTree

Returns

Delivers the appended item itself (it might be useful for the user to get the updated information of the object).

appendleft(item=<class 'itertree.itree_helpers.NoValue'>)

Append the given iTree-object to the left of the parent-tree (new first child) The appendleft() method is the recommended method to add a new first item to iTree (quicker than insert(0,item) ). Compared to append() the method is slower and the cache index information gets invalid after the operation (will be automatically updated later on if required).

Except

In case iTree-object has already a parent a RecursionError will be raised. Other exceptions might come up in case the iTree is protected (tree read-only mode).

Parameters

item (Union[iTree,object]) –

iTree-object to be appended as first item.

Warning

As in append() in case the given item-object is not a iTree-object the item is interpreted as a value and the iTree will be created implicit.

Return type

iTree

Returns

Delivers the appended item itself (it might be useful for the user to get the updated information of the object).

insert(target, item=<class 'itertree.itree_helpers.NoValue'>)

Insert an item before a given target-position. The insertion works like in lists.

The insertion operation is slower as the append operations.

If target=None is given the operation inserts in the last position (== append()).

Except

In case iTree-object has already a parent a RecursionError will be raised Other exceptions might come up in case the iTree is protected (tree read-only mode).

Parameters

• target (Union[Integer,tuple,iTree,None]) –

  target position definition; target must target a single/unique item! Possible targets:

  • index - absolute target index integer, negative values supported too (count from the end).

  • key - key-tuple (family_tag, family_index) pair

  • item - iTree-item that is already a children (future successor)

  • None - if None is given we will append the item in the last position of the ´iTree´-object

• item (Union[iTree,object]) –

  iTree-object to be inserted in the tree.

  Warning

  As in append() in case the given item-object is not a iTree-object the item is interpreted as a value and the iTree will be created implicit.

Return type

iTree

Returns

Delivers the inserted item itself (it might be useful for the user to get the updated information of the object).

extend(items)

We extend the iTree with given items (multi append). The function is high performant and if you have to append a large number of items it is recommended to create an iterator of the items and feed them into this method. This is quicker compared to a loop doing multiple normal append() operations.

Note

In case the to be extended items have already a parent an implicit copy will be made. We do this because the internal copy can be created more effective. We accept also iTree-objects as extend_items parameter and the children which have a parent will be automatically copied to be integrated in this second tree. We have the same situation with a filtered iterator which might be used to extend this iTree too.

Parameters

items (Iterable) –

iterable-object that contains iTree-objects as items it can be:

• iterator or generator of iTree-objects (using next)

• iTree-object (children will be copied and extended in this tree)

• iterable of iTree-objects (list, tuple, …)

• argument list for iTree-instance ( ´__init__()´ ) (created by ´get_init_args()´ or ´get_init_args_deep()´ ) -> this is most often an internal functionality.

• iterator or generator of value-objects (using next) - implicit iTree-objects created

• iterable of value-objects (list, tuple, …)- implicit iTree-objects created

extendleft(items)

Multy item append on left hand-side (at the beginning) of the ´iTree´.

The operation is slower than ´extend()´ because it requires a reordering of all items in the iTree.

Note

The order of extended items is kept in the operation. It’s comparable with: ´[1,2,3]+[4,5,6]=[1,2,3,4,5,6]´ but the result is not a new instance, self is kept.

Note

In case the to be extended items have already a parent an implicit copy will be made. We do this because the internal copy can be created more effective. We accept also iTree-objects as extend_items parameter and the children which have a parent will be automatically copied to be integrated in this second tree. We have the same situation with a filtered iterator which might be used to extend this iTree too.

Parameters

items (Iterable) –

iterable-object that contains iTree-objects as items it can be:

• iterator or generator of iTree-objects (using next)

• iTree-object (children will be copied and extended in this tree

• iterable of iTree-objects (list, tuple, …)

• argument list for iTree-instance ( ´__init__()´ ) (created by ´get_init_args()´ or ´get_init_args_deep()´ )

• iterator or generator of value-objects (using next) - implicit iTree-objects created

• iterable of value-objects (list, tuple, …)- implicit iTree-objects created

__setitem__(target, value)

Replace an item with the given new item given in the value-parameter. The method handles also multiple replaces (rearrangements) like:

>>> mytree[1],mytree[0]=mytree[0],mytree[1]

Warning

Because of the parent only principle in rearrangements operations an implicit copy might be created.

Note

Linked items cannot be changed. If changes are required The user must change the link source tree items and afterwards actively rerun load_links() to reload the linked tree.

Except

In case the target is not found or the iTree is protected (read-only tree).

Parameters

• target –

  target object defining the replacement target; possible types are:

  • index - absolute target index integer (fastest operation)

  • key - key tuple (family_tag, family_index)

  • tag - Tag(family_tag) object targeting a whole family

  • target-list - absolute indexes or keys to be replaced (indexes and keys can be mixed)

  • index slice - slice of absolute indexes

  • key slice - tuple: (family_tag, family_index_slice)

  For multi targets the given value must have a matching structure (item list with same length).

  We have two special targets which are used for placing/replacing single items in the iTree:

  • Ellipsis … - new_items tag-family will be deleted and the new-item is placed in families first item position

  • items_tag - new_items tag-family will be delted and the new-item is placed in families last item position

  If those two special targets are used and the new-items family does not exist yet, the method will just append the new item, no exception will be raised.

• value – iTree object that should replace the target or in case of multi targets a tuple of items that should be used for replacements

Returns

value added items (only for internal usage)

move(target=None)

Move this item in given target position (item will be positioned before the given target). The given target must be a unique item! If None is given the item will be moved in the last position of the iTree. If an ìTree`-object is given as target it must be a children of the same parent (sibling).

Except

LookupError in case the target is not found or not unique!

Parameters

target (Union[Integer,tuple,iTree,None]) –

target-object defining the replacement target; possible types are:

• index - absolute target index integer, negative values supported too (count from the end).

• key - key-tuple (family_tag, family_index) pair

• item - iTree-item that is already a children (future successor)

• None - if None is given we will move the item to the last position in the ´iTree´-object

Returns

self (with updated indexes)

rename(new_tag)

give the item a new family tag

The renaming of the item implies a reordering of the items in the tree because the family order depends on the global/absolute order of items.

Parameters

new_tag (Hashable) – new tag (any kind of hashable object)

Return type

iTree

Returns

Delivers the renamed item itself (it might be useful for the user to get the updated information of the object).

reverse()

Reverse the order of all children in the iTree.

If you do not want to change the object itself (in place operation) you might use the iterator reversed() instead.

rotate(n=1)

Rotate children of the iTree-object n times (n positions) (rotate 1 times means move last item to first position)

If no parameter is given we rotate by one position only.

The rotation can be made in negative direction too (give negative numbers).

In case zero is given the operation is neutral and nothing will be changed.

Note

There is no in-depth counterpart of this method available.

Parameters

n (integer) – number of positions the items should be rotated

sort(key=None, reverse=False)

Sorting operation -> same behavior as sort of lists (parameter description is taken from list documentation).

Note

This is an “in place” operation which changes the content of the object the build-in sorted() might be use instead (if the original object should not be changed):

>>> a=iTree(subtree=[iTree(3),iTree(2),iTree(4),iTree(1)])
>>> a.render()
iTree()
> iTree(3)
> iTree(2)
> iTree(4)
> iTree(1)
>>> b=iTree(subtree=(a[i] for i in sorted(a.keys())))
iTree()
> iTree(1)
> iTree(2)
> iTree(3)
> iTree(4)

Internally in this operation a copied sorted list is created, and afterwards the whole structure is cleared and rebuild based on the sorted list.

The default-operation is to the sort based on the list of keys (tag-family, family_index) pair of the items. The base of the sorting can be modified by changing the target_type parameter.

Parameters

• key – specifies a function of one argument that is used to extract a comparison key from each list element (for example, key=str.lower). The key corresponding to each item in the list is calculated once and then used for the entire sorting process. The default value of None means that list items are sorted directly without calculating a separate key value.

• reverse – is a boolean value. If set to True, then the list elements are sorted as if each comparison were reversed.

__delitem__(target)

The function deletes the targeted item in the tree.

Except

In case the target is not found or the iTree is protected (read-only tree).

Parameters

target (Union[int,tuple,Hashable,Iterable,slice]) –

target object defining the replacement target; possible types are:

• index - absolute target index integer (fastest operation)

• key - key tuple (family_tag, family_index)

• tag - Tag(family_tag) object targeting a whole family

• target-list - absolute indexes or keys to be replaced (indexes and keys can be mixed)

• index-slice - slice of absolute indexes

• key-slice - tuple of (family_tag, family_index_slice)

• itree_filter - method (callable) for filtering the children of the object

Returns

deleted item

clear(keep_value=False, local_only=False)

deletes all children and the value!

All flags stay unchanged, except the load_links flag!

Parameters

• keep_value (bool) –

  • True - value is not deleted

  • False - value will be replaced with NoValue

• local_only (bool) –

  • True - clear only the local items

  • False - clear whole object (The object is reset to the no links loaded state and locals are deleted)

pop(target=- 1)

pop the item out of the tree, if no key is given the last item will be popped out

We do not have the method popleft because pop(0) does the same.

Parameters

target (Union[int,tuple,Hashable,Iterable,slice,iTree]) –

target of popped item(s):

• index - absolute target index integer (fastest operation)

• key - key tuple (family_tag, family_index)

• tag - Tag(family_tag) object targeting a whole family

• target-list - absolute indexes or keys to be replaced (indexes and keys can be mixed)

• index-slice - slice of absolute indexes

• key-slice - tuple of (family_tag, family_index_slice)

• itree_filter - method (callable) for filtering the children of the object

Returns

popped out item(s) (parent will be set to None). In case multiple items are removed an iterator over the removed items is given.

remove(item)

With remove the given target is a iTree child that should be removed.

The method is only in because we like to be compatible with lists interface but the pop method target allows already to use a child as a target too.

Except

If given item is not a child of the parent or the ìTree`-objects tree is protected

Parameters

item (Union[iTree,Iterable]) – Child or iterable of children to be removed from the tree

Returns

removed item(s) (parent will be set to None) - in case of multiple removes the method delivers a list no iterator because anyway a list is created

__getitem__(target)

Main common get method for children (first level items).

In case the given targets is a absolute index or a key (tag,family-index) pair the method will deliver a unique item back. This operation is prioritized over the other operations.

For all other targets the method will deliver a list with the targeted items as result.

In some cases an empty list might be delivered and no exception might be raised (e.g. filter query delivers no match).

In case user likes to have other return-types he might check the other available get methods ( get(), get.single(), get.iter()) or he might also use the itertree helper method getter_to_list() to convert any of the possible results into a list.

Except

In case of no match (even if a part is not matching (e.g. one index in an index-list) the method will raise a KeyError (no matching target given); IndexError (no matching index given) or ValueError (no valid type of target given).

Parameters

target (Union[int,tuple,list,slice]) –

target object targeting a child or multiple children in the ´iTree´. Possible types are:

• index - absolute target index integer (fastest operation)

• key - key tuple (family_tag, family_index)

• index-slice - slice of absolute indexes

• key-index-slice - tuple of (family_tag, family_index_slice)

• target-list - absolute indexes or keys to be replaced (indexes and keys can be mixed)

• key-index-list - tuple of (family_tag, family_index_list)

• tag - family_tag object targeting a whole family

• tag-set - a set of family-tags targeting the items of multiple families

• itree_filter - method (callable) for filtering the children of the object

• all-children - if build-in iter or …`(Ellipsis) is given a list of all children will be given (same like list(itree.__iter__()))

Return type

Union[iTree,list]

Returns

Target was index or key -> one iTree item will be given; for all other targets a list will be delivered.

copy_keep_value()

Create a copy of this item.

The difference in between normal copy() and this method is that the value objects are completely untouched in this operation (for immutable objects there is no difference in between the two copy operations).

Returns

copied iTree object

copy(*args, **kwargs)

create a copy of this item

The difference in between copy() and deepcopy() for iTree is just that we do in deepcopy() a deepcopy of all value items. In copy() we just copy the value object not the items inside, the pointers to the original objects are kept (for immutable objects there is no difference).

Returns

copied iTree object

deepcopy(*args, **kwargs)

create a deepcopy of this item

The difference in between copy() and deepcopy() for iTree is just that we do in deepcopy() a deepcopy of all value items. In copy() we just copy the value object not the items inside, the pointers to the original objects are kept (for immutable objects there is no difference).

Returns

deep copied new iTree object

filtered_len(filter_method)

Calculates the number of filtered children.

Parameters

filter_method (Callable) – filter method that checks for matching items and delivers True/False. The filter_method targets always the iTree-child-object and checks a characteristic of this object for matches (see filter_method)

Return type

int

Returns

Number of matching items found

is_tag_in(tag)

Checks if a iTree contains the given family-tag (first-level only) :param tag: family tag :return: True/False

is_in(item)

Checks if the given object is child of the iTree. Different to ´__contains__()´ we check here for the instance (specific) object (is) and not based on ´__eq__()´.

Parameters

item – iTree object to be searched for

Returns

• True - matching child is found

• False - no matching item found

__eq__(other)

compares if the tag, value and children content of another item matches with this item

Note

If you like to check if it is really the same object you should use ´is´ instead of ´==´ operator

Parameters

other – other iTree

Returns

boolean match result (True match/False no match)

equal(other, check_coupled=False, check_flags=False)

compares if the data content of another item matches with this item

Parameters

• other – other iTree

• check_coupled – check the couple object too? (Default False)

• check_flags – check the flags of the objects? (Default False)

Returns

boolean match result (True match/False no match)

count(item)

Counts how many equal (==) children are in the iTree-object.

Parameters

item (iTree) – The iTree-items will be compared with this item

Return type

int

Returns

Number of matching items found

index(item, start=None, stop=None)

The index method allows to search for the absolute index of a matching item in the iTree. The item must be a iTree object and the index will deliver the first match. The comparison is made via == operator.

If item is not found a IndexError will be raised

Note

To get the index of a specific item instance the .idx- property should be used.

Parameters

• item (iTree) – iTree object to be searched for

• start (Union[iTree,target_path]) – iTree item or start target_path where index search should be started (start item is included in search)

• stop (Union[iTree,target_path]) – iTree item or stop target_path where index search should be stopped (stop item is not included in search)

;rtype: int :return: absolute index of the found item

keys(filter_method=None)

Iterates over all children and deliver the children tag-idx tuple (family-tag,family_index)

Note

This is a dict like iterator that delivers the unique keys for all children.

Parameters

filter_method (Union[Callable,None]) –

filter method that checks the item and delivers True/False. The filter_method targets always the iTree-child-object and checks a characteristic of this object for matches

If None is given filtering is inactive.

Return type

Iterator

Returns

iterator over the tag-idx of the children

values(filter_method=None)

Iterates over all children and deliver the children values

Parameters

filter_method (Union[Callable,None]) –

filter method that checks for matching items and delivers True/False. The filter_method targets always the iTree-child-object and checks a characteristic of this object for matches (see filter_method)

If None is given filtering is inactive.

Return type

Iterator

Returns

iterator over the values stored in the children

items(filter_method=None, values_only=False)

Iterates over all children and deliver the children item-tuples (key,item) or (key,value). As key we use the unique tag-idx: (tag-family,family-index).

The function is comparable with dicts items() function.

Parameters

• filter_method (Union[Callable,None]) –

  filter method that checks for matching items and delivers True/False. The filter_method targets always the iTree-child-object and checks a characteristic of this object for matches (see filter_method)

  If None is given filtering is inactive.

• values_only (bool) –

  • False (default) - in the key,value tuple the iterator put the iTree object as value in

  • True - in the key,value tuple the iterator put “only” the value object of the iTree-object in

Return type

Generator

Returns

iterator over the target keys and item value of the children

iter_families(filter_method=None, order_last=False)

This is a special iterator that iterates over the families in iTree. It delivers per family the tag and a list of the containing items. The order is defined by the absolute index of the first item in each family

Method will be reached via iTree.Families.iter()

Parameters

• filter_method (Union[Callable,None]) –

  filter method that checks for matching items and delivers True/False. The filter_method targets always the iTree-child-object and checks a characteristic of this object for matches (see filter_method)

  If filter_method is None no filtering is performed

  Note

  An internal filtering is available because this may change the order of the delivered items. An external filter with same method might deliver a different result!

• order_last (bool) –

  • False (default) - The tag-order is based on the order of the first items in the family

  • True - The tag-order is based on the order of the last items in the family

Return type

Generator

Returns

iterator over all families delivers tuples of (family-tag, family-item-list)

iter_family_items(order_last=False)

This is a special iterator that iterates over the families in iTree. It iters over the items of each family the ordered by the first or the last items of the families.

Parameters

order_last (bool) –

• False (default) - The tag-order is based on the order of the first items in the family

• True - The tag-order is based on the order of the last items in the family

Return type

Generator

Returns

iterator over all families delivers tuples of (family-tag, family-item-list)

tags(order_last=False)

iters over all family-tags in level 1 (children). The order is based on first or last item in the family.

Parameters

order_last (bool) –

• False (default) - The tag-order is based on the order of the first items in the family

• True - The tag-order is based on the order of the last items in the family

Return type

Iterator

Returns

tag iterator

renders(filter_method=None, enumerate=None, renderer=<class 'itertree.itree_serializer.itree_renderer.iTreeRender'>)

render the iTree into a string

Parameters

• filter_method (Union[Callable,None]) –

  filter method that checks for matching items and delivers True/False. The filter_method targets always the iTree-child-object and checks a characteristic of this object for matches (see filter_method)

  If None is given filtering is inactive.

  The method uses the given filter always as an hierachical filter.

• enumerate (bool) –

  • True - Add an enumeration before the items

  • False (default) - Output without enumeration

• renderer (class) – Give another renderer class for different formatting

Return type

str

Returns

Tree representation as string

render(filter_method=None, enumerate=False, renderer=<class 'itertree.itree_serializer.itree_renderer.iTreeRender'>)

Print the rendered string of the iTree-object to the console (stdout).

Parameters

• filter_method (Union[Callable,None]) – filter method that checks for matching items and delivers True/False. The filter_method targets always the iTree-child-object and checks a characteristic of this object for matches. If None is given filtering is inactive.

• enumerate – add an enumeration before the rendered items

• renderer – Render to be used (The given render is stored and will be used until another renderer is given).

Returns

get_init_args(filter_method=None, _subtree_not_none=True)

Method creates list of arguments that can be used as a pointer to create an equal instance of an iTree object. This is a method is used in most cases for internal functionalities (especially copy()).

Parameters

• filter_method (Union[Callable,None]) –

  filter method that checks for matching items and delivers True/False. The filter_method targets always the iTree-child-object and checks a characteristic of this object for matches (see filter_method)

  If None is given filtering is inactive.

• _subtree_not_none – internal parameter controlling if the subtree is added or not

Returns

loads(data_str, check_hash=True, load_links=True, itree_serializer=<class 'itertree.itree_serializer.itree_json_serialize.iTStdJSONSerializer2'>)

create an iTree object by loading from a string

If not overloaded or reinitialized the iTree Standard Serializer will be used. In this case we expect a matching JSON representation.

Parameters

• data_str – source string that contains the iTree information

• check_hash – True the hash of the file will be checked and the loading will be stopped if it doesn’t match False - do not check the iTree hash

• load_links – True - linked iTree objects will be loaded

• itree_serializer – optional user defined serializer for iTree objects

Returns

iTree object loaded from file

load(file_path, check_hash=True, load_links=True, itree_serializer=<class 'itertree.itree_serializer.itree_json_serialize.iTStdJSONSerializer2'>)

create an iTree object by loading from a file

If not overloaded or reinitialized the iTree Standard Serializer will be used. In this case we expect a matching JSON representation.

Parameters

• file_path – file path to the file that contains the iTree information

• check_hash – True the hash of the file will be checked and the loading will be stopped if it doesn’t match False - do not check the iTree hash

• load_links – True - linked iTree objects will be loaded

• itree_serializer – optional user defined serializer for iTree objects

Returns

iTree object loaded from file

dumps(calc_hash=False, filter_method=None, itree_serializer=<class 'itertree.itree_serializer.itree_json_serialize.iTStdJSONSerializer2'>)

serializes the iTree object to JSON (default serializer)

Parameters

• calc_hash – Tell if the hash should be calculated and stored in the header of string

• itree_serializer – optional user defined serializer for iTree objects

Returns

serialized string (JSON in case of default serializer)

dump(target_path, pack=True, calc_hash=True, overwrite=False, filter_method=None, itree_serializer=<class 'itertree.itree_serializer.itree_json_serialize.iTStdJSONSerializer2'>)

serializes the iTree object to JSON (default serializer) and store it in a file

Parameters

• target_path – target path of the file where the iTree should be stored in

• pack – True - data will be packed via gzip before storage

• calc_hash – True - create the hash information of iTree and store it in the header

• overwrite – True - overwrite an existing file

• itree_serializer – optional user defined serializer for iTree obbjects

Returns

True if file is stored successful

property is_placeholder

Property shows that item is a placeholder class

Normally there should be no placeholder class in the iTree but in case a loaded link does no more contain the expected items it might happen that such a class artifact is still in the tree. In placeholders the value contains the family index in the linked class.

Return type

bool

Returns

True/False

property is_link_cover

If the item is local and covers a linked item the property is True

Return type

bool

Returns

True/False

property is_linked

In contrast to iTreeLinked class this is False

Return type

bool

Returns

True/False

property is_link_loaded

property link_root

delivers the highest level item that is linked in case item is not linked it delivers itself

Return type

iTree

Returns

highest level linked item found in the parents

property is_link_root

property that marks the iTree item as an item that contains a link

Returns

• True - is a link root item

• False is no iTree link item

load_links(force=False, delete_invalid_items=False, _items=None, _depth=0)

Runs ove all children and sub children in case a ITreeLink object is found the linked items are load in

In case ´iTree´ is link root: load all linked items

Parameters

• force –

  • False (default) - load only if not already loaded

  • True - load even if already loaded (update)

• delete_invalid_items –

  • False (default) - in case of invalid items we will raise an exception!

  • True - invalid items will be removed from parent no exception raised

• _items – internal list parameter used for recursive calls of the function

• _depth – Internal parameter related to current item depth

Returns

• True - success

• False - load failed

make_local(copy_subtree=True)

make the current linked object a local object This is only possible if the parent is a iTree object is the link root-> only the first level children in a linked iTree can be made local The operation raises an SyntaxError in case it is used on a deeper level of the linked tree

Returns

None

getitem_by_idx

get

itertree subclasses available in main

.get

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

The code is published under MIT license incl. human protect patch:

The MIT License (MIT) incl. human protect patch Copyright © 2022 <copyright holders>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Human protect patch: The program and its derivative work will neither be modified or executed to harm any human being nor through inaction permit any human being to be harmed.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information see: https://en.wikipedia.org/wiki/MIT_License

This part of code contains the specific get methods for the iTree object

The specific getters are quicker compared with the common ones we have in iTree (__getitem__(); get(); get_single())

.deep

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

The code is published under MIT license incl. human protect patch:

The MIT License (MIT) incl. human protect patch Copyright © 2022 <copyright holders>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Human protect patch: The program and its derivative work will neither be modified or executed to harm any human being nor through inaction permit any human being to be harmed.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information see: https://en.wikipedia.org/wiki/MIT_License

This part of code contains the main iTree object

itertree data classes

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

The code is published under MIT license incl. human protect patch:

The MIT License (MIT) incl. human protect patch Copyright © 2022 <copyright holders>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Human protect patch: The program and its derivative work will neither be modified or executed to harm any human being nor through inaction permit any human being to be harmed.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information see: https://en.wikipedia.org/wiki/MIT_License

This part of code contains the helper functions related to the iTree data attribute

class itertree.itree_data.iTValueModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: abc.ABC

This is the replacement for the old iTDataModel()-class.

This class can be used to define data models for the values that might be placed in the iTree.

The model should define min more detail which value objects are accepted or not and it defines also how not matching objects are handled:

• Deny the value and raise a ValueError exception

• Cast the value into a valid value object

But the definition of the data model allows limitations which goes far away from just data-type related topics. E.g. In the model the user can limit numerical values to a specific range (interval) or he might limit strings to specific characters.

All definitions related to checks and type casts must be defined by the user by overwriting the method check_and_cast_single_item(value_item) . The return of the method must e the checked and cast value. if the value does not match the method should raise a ValueError .

The method should always check and cast a single item, this is important. In case a list or an array like value should be stored in the model the base model will manage the required iteration over the sub-items and perform and utilize the single item check via the user defined method.

Note

In case a value like [1,2,3,45] is given each item in the list will be checked and/or casted.

This leads us to an important second definition functionality related to the model related to the size of dimensions (shape) of the value stored in the model. The definition of the shape is given as a parameter when the object is instanced. For the shape we expect a tuple with the dimension information. If a value object is given the maximum shape will be calculated and this will be compared with the expected one. The maximum is used because in nested lists the user can define sub-list with different length. Strings or bytes aare also seen as arrays in this case!

We have the following possibilities to define shapes:

• shape=Any -> accept any shape of the given value (no check performed)

• shape=tuple() -> empty tuple given no dimension expected model will accept single values only!

• shape=(Any,) -> tuple containing one element which is the Any helper class; We will accept single values or any 1 dimensional object here (e.g. values like: 1; ‘abc’; [1,2,3,4] )

• shape=(10,) -> tuple containing one element. We expect one dimensional values with a length lower or equal to the given integer number

• shape=(INF,) -> tuple containing one element that is INF (infinite). We expect one dimensional values of any length

• shape=(3,4) -> Two dimensions expected with fixed size (e.g. [[1],[2,3]] would match)

• shape=(INF,4) -> Two dimensions expected with first length unlimited and second length limited to 3

• shape=(4,ANY) -> Minimum one dimensions expected with first length limited to 4; here the user can also put infinite dimensions in (e.g [1]; [[1],[2]] ; [[[[888],[202,500]]]] would fit)

• shape=(4,ANY,INF) -> 1 dimension or 3 dimensions accepted, 2 dimension will not be accepted

Note

The model base object iTValueModel() contains two checking levels. First the user defined check via method definition for checks and casts of single items given. In second step the model also checks the dimension (shape) of the given value.

In case a str or bytes objects are given the behavior related to the checks will be a bit different as for the other objects. The method check_and_cast_single_item(value_item) will target the whole string as a single item! But the shape check will be done also on the string as an object with a length.

This means a string is a 1 dimensional object and the user might limit the size of the string via a shape. (E.g.: The object “Hello” has the shape: (5,); the object [‘one’, ‘two’,’three’] has the shape: (3,5) ) The user might use the method ‘get_max_shape()’ to measure the shape of objects that is considered in the model base class.

During the instance of the object a formatter can be defined too. This might help the user e.g. do define if an integer value should be converted to a hex or binary representation during string conversion. The build-in command str() of this model class will deliver the formatted value only. The repr() will deliver the class definition.

To use the model the user should put the instanced model object as value in the iTree. The real value objects can be placed during object instance via the parameter value or later on via the set() method of the model (value exchange too). In case the value is not matching to the model definition an ValueError exception will be raised. If the user like to test first if the value is matching he can use the in keyword to check this. In case of no match the exception content might be picked via the last_exception property of the model in this case (might give a hint why the value is not accepted).

Standard Parameters:

Parameters

• value – value object to be stored in the model (must match to the model). In case no value is stored in the model (empty model) the value will be NoValue.

• description – Description string

• shape –

  Define the dimensions the object should have:

  • None - shape is ignored object might have dimensions or not

  • tuple() - empty tuple or iterable - value object will have no size/dimension

  • (InfShape) - one dimensional value object with infinite size

  • 100. • one dimensional value object with max size of 100 items

  • (100,100) - two dimensional object with max size of 100 in each dimension

  • (InfShape,InfShape,InfShape) - three-dimensional object with infinite size in each dimension

  • …

  Note

  For multi-dimensional objects it’s recommended to use numpy arrays or objects which have the attribute shape representing the size for each dimension available instead of tuples or lists. If not the object performance might be worse (internal iterations required to measure the shape).

• formatter – Formatter for the single item of the value object (see string formatting in python) In case no formatter is given str() will be used for creation of the item string representation.

check_and_cast_single_item(value_item)

method that should be overwritten in the user models

Depending on the requirements the input value might be casted in a target type and he can be checked before or afterwards against check criteria for matches. In case of no match a ValueError should be raised

Except

Raise ValueError in case given value does not match

Parameters

value_item – The value given to the model

Returns

casted and checked value

set(value)

Set the value of the model in case the value does not match a ValueError exception will be raised

Parameters

value – value to be placed inside the model

Returns

old value stored in the model

get()

get the value that is placed inside the model

If no value is stored in the model the NoValue-object will be given back

Returns

value stored in the model

property value

property delivering the value stored in the model

Returns

value stored in the model

property description

optional description of the model

Returns

description related to the model

set_description(description)

set/exchange the description of the model

Parameters

description –

Returns

old description

property formatter

get the formatter stored in the model

Returns

formatter object

set_formatter(formatter)

set the formatter of the object

Parameters

formatter – The formatter can be a callable method that delivers a str object or a string that contains teh formatting info

Returns

old formatter

property contains

contains object stored in the model :return:

clear()

deletes teh value store din the model and place the NoValue-object in

property last_except

get the last exception

Returns

last exception raised by the model related the storage or check of a value

property is_iTValueModel

used for model identification

Returns

True

get_init_args(full=False, clear=False)

deliver all initial arguments used to instance this model object

Parameters

• full – True give always full list False (default) list is shortened in case of default parameter values

• clear – True - use NoValue object as value (ignore stored value) False - stored value is included in parameter tuple

Returns

Tuple of initial parameters

class itertree.itree_data.iTAnyValueModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTValueModel

Model that will take any python object without any restrictions

check_and_cast_single_item(value_item)

required overload will allow any object to be stored in the model

Parameters

value_item – potential value to be stored in the model

Returns

confirmed value to be stored in the model

class itertree.itree_data.iTRoundIntModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTValueModel

Model that would store integer values The model accepts any object that can be casted into a float and rounded to an integer to be stored as a int in the model

check_and_cast_single_item(value_item)

method that should be overwritten in the user models

Depending on the requirements the input value might be casted in a target type and he can be checked before or afterwards against check criteria for matches. In case of no match a ValueError should be raised

Except

Raise ValueError in case given value does not match

Parameters

value_item – The value given to the model

Returns

casted and checked value

class itertree.itree_data.iTIntModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTValueModel

This integer model allows only integers or strings containing a decimal integer to be stored in the model as int value

check_and_cast_single_item(value_item)

method that should be overwritten in the user models

Depending on the requirements the input value might be casted in a target type and he can be checked before or afterwards against check criteria for matches. In case of no match a ValueError should be raised

Except

Raise ValueError in case given value does not match

Parameters

value_item – The value given to the model

Returns

casted and checked value

class itertree.itree_data.iTInt8Model(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTValueModel

Integer model that limits the given values to int8 values

interval = mSetInterval(mSetItem(-128), mSetItem(127))

check_and_cast_single_item(value_item)

method that should be overwritten in the user models

Depending on the requirements the input value might be casted in a target type and he can be checked before or afterwards against check criteria for matches. In case of no match a ValueError should be raised

Except

Raise ValueError in case given value does not match

Parameters

value_item – The value given to the model

Returns

casted and checked value

get_init_args(full=False, clear=False)

deliver all initial arguments used to instance this model object

Parameters

• full – True give always full list False (default) list is shortened in case of default parameter values

• clear – True - use NoValue object as value (ignore stored value) False - stored value is included in parameter tuple

Returns

Tuple of initial parameters

class itertree.itree_data.iTUInt8Model(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTInt8Model

Integer model that limits the given values to uint8 values

interval = mSetInterval(mSetItem(0), mSetItem(255))

class itertree.itree_data.iTInt16Model(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTInt8Model

Integer model that limits the given values to int16 values

interval = mSetInterval(mSetItem(-32768), mSetItem(32767))

class itertree.itree_data.iTUInt16Model(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTInt8Model

Integer model that limits the given values to uint16 values

interval = mSetInterval(mSetItem(0), mSetItem(65535))

class itertree.itree_data.iTInt32Model(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTInt8Model

Integer model that limits the given values to int32 values

interval = mSetInterval(mSetItem(-2147483648), mSetItem(2147483647))

class itertree.itree_data.iTUInt32Model(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTInt8Model

Integer model that limits the given values to uint32 values

interval = mSetInterval(mSetItem(0), mSetItem(4294967295))

class itertree.itree_data.iTInt64Model(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTInt8Model

Integer model that limits the given values to int64 values

interval = mSetInterval(mSetItem(-9223372036854775808), mSetItem(9223372036854775807))

class itertree.itree_data.iTUInt64Model(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTInt8Model

Integer model that limits the given values to uint64 values

interval = mSetInterval(mSetItem(0), mSetItem(18446744073709551615))

class itertree.itree_data.iTFloatModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTValueModel

Float model that allows any float or string that can be casted to float to be stored in the model as float value

check_and_cast_single_item(value_item)

method that should be overwritten in the user models

Depending on the requirements the input value might be casted in a target type and he can be checked before or afterwards against check criteria for matches. In case of no match a ValueError should be raised

Except

Raise ValueError in case given value does not match

Parameters

value_item – The value given to the model

Returns

casted and checked value

class itertree.itree_data.iTStrModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTValueModel

A model to store a string

check_and_cast_single_item(value_item)

method that should be overwritten in the user models

Depending on the requirements the input value might be casted in a target type and he can be checked before or afterwards against check criteria for matches. In case of no match a ValueError should be raised

Except

Raise ValueError in case given value does not match

Parameters

value_item – The value given to the model

Returns

casted and checked value

class itertree.itree_data.iTStrFnPatternModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, pattern=None, formatter=None)

Bases: itertree.itree_data.iTStrModel

A model to store a string that matches to the fnmatch pattern

property pattern

get_init_args(full=False, clear=False)

deliver all initial arguments used to instance this model object

Parameters

• full – True give always full list False (default) list is shortened in case of default parameter values

• clear – True - use NoValue object as value (ignore stored value) False - stored value is included in parameter tuple

Returns

Tuple of initial parameters

class itertree.itree_data.iTStrRegexPatternModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, pattern=None, formatter=None)

Bases: itertree.itree_data.iTStrModel

A string model that matches to the regex pattern

property pattern

get_init_args(full=False, clear=False)

deliver all initial arguments used to instance this model object

Parameters

• full – True give always full list False (default) list is shortened in case of default parameter values

• clear – True - use NoValue object as value (ignore stored value) False - stored value is included in parameter tuple

Returns

Tuple of initial parameters

class itertree.itree_data.iTASCIIStrModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTValueModel

A string model that accepts only ASCII characters

check_and_cast_single_item(value_item)

method that should be overwritten in the user models

Depending on the requirements the input value might be casted in a target type and he can be checked before or afterwards against check criteria for matches. In case of no match a ValueError should be raised

Except

Raise ValueError in case given value does not match

Parameters

value_item – The value given to the model

Returns

casted and checked value

class itertree.itree_data.iTUTF8StrModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTValueModel

A string model that accepts only UTF-8 characters

check_and_cast_single_item(value_item)

method that should be overwritten in the user models

Depending on the requirements the input value might be casted in a target type and he can be checked before or afterwards against check criteria for matches. In case of no match a ValueError should be raised

Except

Raise ValueError in case given value does not match

Parameters

value_item – The value given to the model

Returns

casted and checked value

class itertree.itree_data.iTUTF16StrModel(value=<class 'itertree.itree_helpers.NoValue'>, description=None, shape=<class 'itertree.itree_helpers.Any'>, contains=None, formatter=<class 'str'>)

Bases: itertree.itree_data.iTStrModel

A string model that accepts only UTF16 characters

check_and_cast_single_item(value_item)

method that should be overwritten in the user models

Depending on the requirements the input value might be casted in a target type and he can be checked before or afterwards against check criteria for matches. In case of no match a ValueError should be raised

Except

Raise ValueError in case given value does not match

Parameters

value_item – The value given to the model

Returns

casted and checked value

class itertree.itree_data.iTEnumerateModel(value=<class 'itertree.itree_helpers.NoValue'>, enumerate_dict={})

Bases: itertree.itree_data.iTValueModel

check_and_cast_single_item(value_item)

method that should be overwritten in the user models

Depending on the requirements the input value might be casted in a target type and he can be checked before or afterwards against check criteria for matches. In case of no match a ValueError should be raised

Except

Raise ValueError in case given value does not match

Parameters

value_item – The value given to the model

Returns

casted and checked value

exception itertree.itree_data.iTDataValueError

Bases: ValueError

Exception to be raised in case a validator finds a non matching value related to the iDataModel

exception itertree.itree_data.iTDataTypeError

Bases: ValueError

Exception to be raised in case a validator finds a non matching value type related to the iDataModel

class itertree.itree_data.iTDataModel(value=<class 'itertree.itree_helpers.NoValue'>)

Bases: abc.ABC

The default iTree data model class This the interface definition for specific data model classes that might be created using this superclass

The data model checks the given value for a specific data item. So that we can ensure that the given value matches to the expectations. We can check for types, shapes (length), limits, or matching patterns.

Besides the check we can also define a default formatter for the value that is used when it is translated into a string.

(see examples/itree_data_examples.py)

property is_empty

tells if the iTreeDataModel is empty or contains a value :return:

property is_iTDataModel

get()

the stored value :return: object stored in value

set(value)

put a specific value into the data model

Except

raises an iTreeValidationError in case a not matching object is given

Parameters

value – value object to be placed in the data model

property value

the stored value :return: object stored in value

check(value)

put a specific value into the data model

Except

raises an iTreeValidationError in case a not matching object is given

Parameters

value – value object to be placed in the data model

clear()

clears (deletes) the current value content and sets the state to “empty”

Returns

returns the value object that was stored in the iTreeDataModel

abstract validator(value)

This method should check the given value.

It should raise an iDataValueError Exception with a failure explanation in case the value is not matching to the iDataModel.

..warning:: The validator in an explicit iDataModel class must always return the value itself and it must raise

the iDataValueError in case of a no matching value. It should also call the super().validator() method or at least consider that NoValue is a no matching value.

Except

iDataValueError in case value is not matching

Parameters

value – to be checked against the model

Returns

value (which might be casted)

abstract formatter(value=None)

The formatter function allows us to create a specific string representation

Especially in case of numerical values this is interesting. You can define here that an integer should be represented always as hex, bin, … or for floats you can give digits.

The formatter can be created by using the classical format options of string but for enumerations we can put here also a table, etc.

Returns

string representing the value

abstract get_init_args()

class itertree.itree_data.iTDataModelAny(value=<class 'itertree.itree_helpers.NoValue'>)

Bases: itertree.itree_data.iTDataModel

Example iDataModel class that accepts any kind of value

validator(value)

This method should check the given value.

It should raise an iDataValueError Exception with a failure explanation in case the value is not matching to the iDataModel.

..warning:: The validator in an explicit iDataModel class must always return the value itself and it must raise

the iDataValueError in case of a no matching value. It should also call the super().validator() method or at least consider that NoValue is a no matching value.

Except

iDataValueError in case value is not matching

Parameters

value – to be checked against the model

Returns

value (which might be casted)

formatter(value=None)

The formatter function allows us to create a specific string representation

Especially in case of numerical values this is interesting. You can define here that an integer should be represented always as hex, bin, … or for floats you can give digits.

The formatter can be created by using the classical format options of string but for enumerations we can put here also a table, etc.

Returns

string representing the value

get_init_args()

class itertree.itree_data.iTData(seq=None, **kwargs)

Bases: dict

Standard itertree Data management object might be overloaded or changed by the user

GET_LOOK_UP_METHOD = {0: <function iTData.<lambda>>, 1: <function iTData.<lambda>>, 2: <function iTData.<lambda>>}

update(E=None, **F)

function update of multiple items if one item is invalid the whole update will be skipped and an iDataValueError exception will thrown!

In case the replace_model flag is set the model will be exchanged.

Parameters taken from builtin dict:

Update D from dict/iterable E and F. If E is present and has a .keys() method, then does: If E is present and lacks a .keys() method, then does: In either case, this is followed by:

Except

raises iDataValueError exception if a value in the given object is not matching to the data-model. The iData object will not be updated in this case.

Parameters

• E –

  • with .keys() method: for k in E: D[k] = E[k]

  • without .keys() method: for k, v in E: D[k] = v

• **F –

  we run: for k in F: D[k] = F[k]

• replace_models –

  • True - Will replace the whole key related value (also iTDataModels are replaced)

  • False (default) - All values are replaced in case of iTDataModel object the internal value will

    be replaced

copy()

create a new object with same items

Returns

new object copied from self

clear() → None.  Remove all items from D.

pop(key=<class 'itertree.itree_helpers.NoKey'>, default=<class 'itertree.itree_helpers.NoKey'>, value_only=True)

delete a stored value

Except

will case KeyError if key is not found and default is not set

Parameters

• key – key where the item should be popped out

• value_only – True - only value will be deleted model will be kept in iTreeData False - whole model will be popped out

Default

define the value given back in case key is not found else KeyError will be raised

Returns

deleted item or default

get(key=<class 'itertree.itree_helpers.NoKey'>, default=None, return_type=0)

get a specific data item by key

Parameters

• key – key of the data item (if not given __NOKEY__ is used)

• default – default value that will be delivered in case of no match

• _return_type – We can deliver different returns * VALUE - value object * FULL - iTreeDataModel (only if used else same as VALUE) * STR - formatted string representation of the data value

Returns

requested value

fromkeys(*args, **kwargs)

create a new iData object based on given keys and optional value

• real signature unknown

delete_item(key, value_only=True)

delete a item by key

Except

KeyError is raised in case item key is unknown

Parameters

• key – key of the data item (if not given __NOKEY__ is used!

• value_only –

  • True - (default) in case of iDataModel items we delete only the internal value

    not the model itself

  • False - we delete the value independent from the type (also iDataModel objects)

Returns

deleted value

model_values()

iterator that takes in case of iDataModel values the value out of the model, in case of non iDataModel values the value is given directly as it is

Returns

iterator

model_items()

iterator that takes in case of iDataModel values the value out of the model, in case of non iDataModel values the value is given directly as it is

Returns

iterator

property is_empty

used for identification of this class :return: True

property is_no_key_only

used for identification of this class :return: True

property is_iTData

is_key_empty(key=<class 'itertree.itree_helpers.NoKey'>)

Function delivers a key empty state (it delivers True in case key is absent or value is __NOVALUE__ :param key: key to be check (delault is __NOKEY__ :return: True/False

deepcopy()

create a deep copy of this object

also all internal items will be copied!

Returns

new object deep copied from self

get_init_args()

class itertree.itree_data.iTDataReadOnly(seq=None, **kwargs)

Bases: itertree.itree_data.iTData

Standard itertree Data management object might be overloaded or changed by the user

pop(*arg, **kwargs)

delete a stored value

Except

will case KeyError if key is not found and default is not set

Parameters

• key – key where the item should be popped out

• value_only – True - only value will be deleted model will be kept in iTreeData False - whole model will be popped out

Default

define the value given back in case key is not found else KeyError will be raised

Returns

deleted item or default

update(*arg, **kwargs)

function update of multiple items if one item is invalid the whole update will be skipped and an iDataValueError exception will thrown!

In case the replace_model flag is set the model will be exchanged.

Parameters taken from builtin dict:

Update D from dict/iterable E and F. If E is present and has a .keys() method, then does: If E is present and lacks a .keys() method, then does: In either case, this is followed by:

Except

raises iDataValueError exception if a value in the given object is not matching to the data-model. The iData object will not be updated in this case.

Parameters

• E –

  • with .keys() method: for k in E: D[k] = E[k]

  • without .keys() method: for k, v in E: D[k] = v

• **F –

  we run: for k in F: D[k] = F[k]

• replace_models –

  • True - Will replace the whole key related value (also iTDataModels are replaced)

  • False (default) - All values are replaced in case of iTDataModel object the internal value will

    be replaced

clear() → None.  Remove all items from D.

delete_item(key, value_only=True)

delete a item by key

Except

KeyError is raised in case item key is unknown

Parameters

• key – key of the data item (if not given __NOKEY__ is used!

• value_only –

  • True - (default) in case of iDataModel items we delete only the internal value

    not the model itself

  • False - we delete the value independent from the type (also iDataModel objects)

Returns

deleted value

get_init_args()

itertree filter classes

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

The code is published under MIT license incl. human protect patch:

The MIT License (MIT) incl. human protect patch Copyright © 2022 <copyright holders>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Human protect patch: The program and its derivative work will neither be modified or executed to harm any human being nor through inaction permit any human being to be harmed.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information see: https://en.wikipedia.org/wiki/MIT_License

This part of code contains the iTree filter classes

we use here lambda to create a method which is feed with an item and delivers then True/False depending on the given condition so that it can be used in filter iterators

itertree.itree_filters.iter_items_over_filter_method(filter_method, item_iter)

helper function that delivers an iterator of True/False based on given filter_method and the item iterator given

Parameters

• filter_method – Item filter method

• item_iter – iterable where each item should be checked against the filter

Returns

iterator of True/False objects matches to filter or not

class itertree.itree_filters.has_item_flags(flag_mask, invert=False)

Bases: object

Check the iTree flags for match to the given flag mask

Parameters

• item – iTree-item to be checked against the criteria of the method (for filtering out or not)

• flag_mask – flag mask E.g. can be build like: iTFLAG.READ_ONLY_TREE|iTFLAG.READ_ONLY_VALUE

Return type

bool

Returns

• True -> match

• False -> no match

class itertree.itree_filters.is_item_tag(target_tag, invert=False)

Bases: object

Check the iTree tag is equal to the given target_tag

Parameters

• target_tag – tag string do not give Tag() objects here! Use Tag().tag if really required

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_tag_fnmatch(tag_match_pattern, invert=False)

Bases: object

Check the iTree tag is matching to given fnmatch match_pattern

Parameters

match_pattern – str or bytes related to fnmatch pattern definitions

class itertree.itree_filters.has_item_value(target_value, invert=False)

Bases: object

Check the iTree value is equal to given value

Parameters

• target_value – value object that should be equal with iTree.value

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_value_dict_value(target_value, invert=False)

Bases: object

Check if in case the iTree value is a dict a value in the dict is equal to given value

Parameters

• target_value – value object that should be equal with iTree.value

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_value_list_value(target_value, invert=False)

Bases: object

Check if in case the iTree value is a list a value in the list is equal to given value

Parameters

• target_value – value object that should be equal with iTree.value

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_value_fnmatch(target_value_pattern, invert=False)

Bases: object

Check if value matches to the given fnmatch pattern

Parameters

• target_value_pattern – str or bytes related to fnmatch pattern definitions

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_value_dict_value_fnmatch(target_value_pattern, invert=False)

Bases: object

Check if in case the iTree value is a dict a value in the dict matches to the given pattern

Parameters

• target_value_pattern – str or bytes related to fnmatch pattern definitions

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_value_list_item_fnmatch(target_value_pattern, invert=False)

Bases: object

Check if in case the iTree value is a list a value in the list matches to the given pattern

Parameters

• target_value_pattern – str or bytes related to fnmatch pattern definitions

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.is_item_value_in(target_value_interval, invert=False)

Bases: object

Check if iTree value is in the given iTInterval object, no numeric values will be ignored

Parameters

• target_key_interval – msetInterval object defining the range (any object that supports “in” can be used)

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_value_dict_value_in(target_value_interval, invert=False)

Bases: object

Check if in case the iTree value is a dict a value in the dict is in the given iTInterval object, no numeric values will be ignored

Parameters

• target_key_interval – msetInterval object defining the range (any object that supports “in” can be used)

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_value_list_item_in(target_value_interval, invert=False)

Bases: object

Check if in case the iTree value is a list a value in the list is in the given iTInterval object, non numeric values will be ignored

Parameters

• target_key_interval – msetInterval object defining the range (any object that supports “in” can be used)

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_value_dict_key(target_key, invert=False)

Bases: object

Check if in case the iTree value is a dict a key in the dict is equal with the given target_key no numeric values will be ignored

Parameters

target_key – dict key

class itertree.itree_filters.has_item_value_list_idx(target_idx, invert=False)

Bases: object

Check if in case the iTree value is a list the given target_key is lower than list length (inside) no numeric values will be ignored

Parameters

• target_idx – target-index

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_value_dict_key_fnmatch(target_key_pattern, invert=False)

Bases: object

Check if in case the iTree value is a dict a key in the dict matches to the given key pattern (fnmatch) no numeric values will be ignored

Parameters

• target_key_pattern – str or bytes related to fnmatch pattern definitions

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

class itertree.itree_filters.has_item_value_dict_key_in(target_key_interval, invert=False)

Bases: object

Check if in case the iTree value is a dict a key in the dict is in the given iTInterval object range no numeric values will be ignored

Parameters

• target_key_interval – msetInterval object defining the range (any object that supports “in” can be used)

• invert –

  • False (default) -> unchanged result

  • True -> invert the result True->False; False->True

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

The code is published under MIT license incl. human protect patch:

The MIT License (MIT) incl. human protect patch Copyright © 2022 <copyright holders>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Human protect patch: The program and its derivative work will neither be modified or executed to harm any human being nor through inaction permit any human being to be harmed.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. For more information see: https://en.wikipedia.org/wiki/MIT_License

This part of code contains helper classes used in DataTree object

class itertree.itree_mathsets.mSetItem(value, complement=False, formatter=<class 'str'>)

Bases: object

item object to used in the different mSet objects Depending on the object it is a “normal” item (mSetRoster) or it is the lower or upper limit of the mSetInterval object. In first case complemented items will be ignored.

The object contains a formatting option to define how the string representation of the item should look like. Especially integer formatting is used to to create representations of the other base like hex or octal.

Parameters

• value (object) – numerical value to be stored in object or definition str the user can give also a variable-name here

• complement (bool) – complement type item (only required for interval limits

• formatter – explicit formatter user can give as formatter 1. formatter method (callable) 2. escape string for format() method 3 escape string for classical “%” replacement

property is_mSetItem

Property used for identification of the object

Return type

bool

Returns

True

property is_complement

property tells if the object is complement

Return type

bool

Returns

True/False

property value

property contains the value of the item :return: value of the object

property formatter

property delivers the formatter of the object

Return type

Union[Callable,str]

Returns

formatter object (Callable or string)

property formatter_type

property delivers the formatter type integer constant of the object formatter

Return type

int

Returns

formatter type integer ( `_CALL`~0;,`_FORMAT`~1; ,`_OLD`~2 )

property is_var

property returns if the value is a variable name or a normal numerical value

Return type

bool

Returns

True - is variable; False - normal numerical value

get_init_args(full=False)

get the initial arguments for instance the object

Parameters

full (bool) – do not shorten even that we have default values

Return type

tuple

Returns

tuple of init arguments

math_repr(formatter=None)

delivers the formatted value :rtype formatter: Union[Callable,str,None][ :param formatter: optionally an explicit formatter can be given

Return type

str

Returns

Formatted value stored in the mSetItem-object

class itertree.itree_mathsets.mSetInterval(*definition, lower=None, upper=None, int_only=False, complement=False)

Bases: itertree.itree_mathsets._mSetBase

Mathematical interval set object. Here the user can define a mathematical interval with closed or open boarders.

For more details related to mathematical intervals you may have a look here: https://en.wikipedia.org/wiki/Interval_(mathematics)

property is_lower_closed

do we have a closed lower limit “(” :return: True is closed, False is open

property is_lower_open

do we have a open lower limit “(” :return: True is open, False is closed

property lower_value

Property delivers the lower limit value :return: value of the lower limit

property is_upper_closed

do we have a closed upper limit “(” :return: True is closed, False is open

property is_upper_open

do we have a open upper limit “(” :return: True is open, False is closed

property upper_value

Property delivers the upper limit value :return: value of the upper limit

property is_int_only

Is this an integer number only interval? :return:

property cardinality

The cardinality is somehow the size of the set it delivers how many items the set contains. The result is not in all cases correct furthermore it is just an estimation!

In many cases in float intervals the user will find infinite as the result of the operation. :return: number of items integer or float(‘inf’) for infinite results

property is_empty_set

Is the interval same as an empty set (no item inside) :return: True is empty; False is not empty

property is_empty_set_complement

Is the complement interval same as an empty set (no item inside). If this is the case the set is the universal set (any item inside). But this is a relative definition to the “universe”. E.g. strings will never be found inside a numerical set they are not in the “universe”.

Returns

True complement is empty; False complement is not empty

iter_in(value, vars_dict=None)

For each item in the given iterable value we check if the item is in this mSet object the result is a iterable over the single results :param value: to be checked iterable value (single item check) :param vars_dict: variable replacement dict :return: iterable True/False

filter(value, vars_dict=None)

For each item in the given iterable value we check if the item is in this mSet object or not in case it is in the item will be delivered back if not it is skipped

Parameters

• value – iterable value which items will be checked

• vars_dict – variable replacement dict

Returns

iterable of matching items

get_init_args(full=False)

delivers tuple of all initial arguments given to instance the mSet object :param full: True all arguments given also defaults :return: tuple of initial arguments

math_repr(formatters=None)

mathematical representation of the object (we try to match as good as possible to the mathematical standards here but we avoid exotic characters! :return: mathematical representation string

class itertree.itree_mathsets.mSetRoster(*definition, items=None, complement=False)

Bases: itertree.itree_mathsets._mSetBase

property cardinality

The cardinality is somehow the size of the set it delivers how many items the set contains. The result is not in all cases correct furthermore it is just an estimation!

In many cases in float intervals the user will find infinite as the result of the operation. :return: number of items integer or float(‘inf’) for infinite results

property is_empty_set

For some set definition no matching item can be found! Then the set is equal to the empty set and this property will deliver True

Return type

bool

Returns

True is empty set; False set contains items

property is_empty_set_complement

Is the complement interval same as an empty set (no item inside). If this is the case the set is the universal set (any item inside). But this is a relative definition to the “universe”. E.g. strings will never be found inside a numerical set they are not in the “universe”.

Returns

True complement is empty; False complement is not empty

items()

iter_in(value, vars_dict=None)

For each item in the given iterable value we check if the item is in this mSet object the result is a iterable over the single results :param value: to be checked iterable value (single item check) :param vars_dict: variable replacement dict :return: iterable True/False

filter(value, vars_dict=None)

For each item in the given iterable value we check if the item is in this mSet object or not in case it is in the item will be delivered back if not it is skipped

Parameters

• value – iterable value which items will be checked

• vars_dict – variable replacement dict

Returns

iterable of matching items

get_init_args(full=False)

delivers tuple of all initial arguments given to instance the mSet object :param full: True all arguments given also defaults :return: tuple of initial arguments

math_repr(formatters=None)

mathematical representation of the object (we try to match as good as possible to the mathematical standards here but we avoid exotic characters! :return: mathematical representation string

class itertree.itree_mathsets.mSetCombine(*definition, is_union=True, complement=False)

Bases: itertree.itree_mathsets._mSetBase

class where the user can combine different sets to unions

In this class the user can combine different types of sets (all objects with __contains__() and a length are allowed to be added.

If the object is used to check if a value is in it is sufficient if the value is in one of the subsets to create a positive response for a match

property is_union

property is_intersection

items()

property cardinality

The cardinality is somehow the size of the set it delivers how many items the set contains. The result is not in all cases correct furthermore it is just an estimation!

Especially in this case the cardinally is really an estimation only. It’s not teh case that we check here for overlapping intervals which might reduce the cardinality. We create just an estimation based the cardinalities of the subitems

In many cases in float intervals the user will find infinite as the result of the operation. :return: number of items integer or float(‘inf’) for infinite results

property is_empty_set

For some set definition no matching item can be found! Then the set is equal to the empty set and this property will deliver True

Return type

bool

Returns

True is empty set; False set contains items

property is_empty_set_complement

Is the complement interval same as an empty set (no item inside). If this is the case the set is the universal set (any item inside). But this is a relative definition to the “universe”. E.g. strings will never be found inside a numerical set they are not in the “universe”.

Returns

True complement is empty; False complement is not empty

math_repr()

mathematical representation of the object (we try to match as good as possible to the mathematical standards here but we avoid exotic characters! :return: mathematical representation string

iter_in(value, vars_dict=None)

For each item in the given iterable value we check if the item is in this mSet object the result is a iterable over the single results :param value: to be checked iterable value (single item check) :param vars_dict: variable replacement dict :return: iterable True/False

filter(value, vars_dict=None)

For each item in the given iterable value we check if the item is in this mSet object or not in case it is in the item will be delivered back if not it is skipped

Parameters

• value – iterable value which items will be checked

• vars_dict – variable replacement dict

Returns

iterable of matching items

get_init_args(full=False)

delivers tuple of all initial arguments given to instance the mSet object :param full: True all arguments given also defaults :return: tuple of initial arguments

itertree serializing

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

The code is published under MIT license incl. human protect patch:

The MIT License (MIT) incl. human protect patch Copyright © 2022 <copyright holders>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Human protect patch: The program and its derivative work will neither be modified or executed to harm any human being nor through inaction permit any human being to be harmed.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information see: https://en.wikipedia.org/wiki/MIT_License

This part of code contains the standard iTree serializers (JSON and rendering)

class itertree.itree_serializer.itree_json_serialize.iTStdJSONSerializer2(itree_class)

Bases: object

This is the standard serializer for DataTree which translates the structure into the JSON format. Users might implement their own serializers using the interface methods defined in this serializer

not_linked_filter()

ALL_TYPE = 0

BYTE_TYPE = 1

STR_TYPE = 2

DICT_TYPE = 3

ITER_TYPE = 4

NP_TYPE = 5

IT_TYPE = 6

IT_LINK_TYPE = 7

IT_CONST_TYPE = 8

NO_VALUE = 0

NO_TAG = 1

ANY = 2

NO_KEY = 3

TRANSLATE_OBJ2KEY = {<class 'itertree.itree_helpers.NoValue'>: 0, <class 'itertree.itree_helpers.Any'>: 2, <class 'itertree.itree_helpers.NoTag'>: 1, <class 'itertree.itree_helpers.NoKey'>: 3}

TRANSLATE_KEY2OBJ = {0: <class 'itertree.itree_helpers.NoValue'>, 1: <class 'itertree.itree_helpers.NoTag'>, 2: <class 'itertree.itree_helpers.Any'>, 3: <class 'itertree.itree_helpers.NoKey'>}

CONVERT_MAP = {<class 'collections.deque'>: <function iTStdJSONSerializer2.<lambda>>, <class 'str'>: <function iTStdJSONSerializer2.<lambda>>, <class 'float'>: <function iTStdJSONSerializer2.<lambda>>, <class 'type'>: <function iTStdJSONSerializer2.<lambda>>, <class 'dict'>: <function iTStdJSONSerializer2.<lambda>>, <class 'list'>: <function iTStdJSONSerializer2.<lambda>>, <class 'int'>: <function iTStdJSONSerializer2.<lambda>>, <class 'bytes'>: <function iTStdJSONSerializer2.<lambda>>, <class 'collections.OrderedDict'>: <function iTStdJSONSerializer2.<lambda>>, <class 'tuple'>: <function iTStdJSONSerializer2.<lambda>>, <class 'set'>: <function iTStdJSONSerializer2.<lambda>>}

CONVERT_FROM_JSON_MAP = {0: <function iTStdJSONSerializer2.<lambda>>, 1: <function iTStdJSONSerializer2.<lambda>>, 3: <function iTStdJSONSerializer2.<lambda>>, 4: <function iTStdJSONSerializer2.<lambda>>, 5: <function iTStdJSONSerializer2.<lambda>>, 6: <function iTStdJSONSerializer2.<lambda>>, 8: <function iTStdJSONSerializer2.<lambda>>}

convert_to_json_item(o)

convert_numpy(data, dtype, shape)

convert_it_type(o)

convert_from_json_obj(json_obj)

convert_single_itree_to_json_obj(depth, itree, fidx)

convert_single_itree_to_json_obj2(depth, itree, fidx)

dumps(o, add_header=False, calc_hash=False, filter_method=None)

In JSON the iTree object is represented in the following form Item-> dict with all properties (Special keys used) Tree structure is stored in list

Parameters

• o – iTree object to be serialized

• add_header – True - the header information will be added (containing Version info and hash) False - no header pure data

• calc_hash – True - A sha1 hash is calculated over the data section of iTree and added in the header False - no hash will be calculated

Return type

tuple

Returns

hash,string containing the serialized data -> if no hash calculation requested hash will be None

dump(o, file_path, pack=True, calc_hash=True, overwrite=False, filter_method=None)

Serialize iTree object into a file

Parameters

• o – iTree object to be serialized

• file_path – target file path where to store the data in

• pack – True - gzip the data, False - do not zip

• overwrite – True - an existing fie will be overwritten False (default) - in case the file exists an FileExistsError Exception will be raised

• calc_hash – True - A sha1 hash is calculated over the data section of iTree and added in the header False - no hash will be calculated

Returns

None

create_itree_from_raw(raw_o)

create_itree_from_raw2(raw_o)

loads(source_str, check_hash=True, load_links=True, _source=None)

create an iTree object by loading from a string.

Parameters

• source_str – source string that contains the iTree information

• check_hash – True the hash of the file will be checked and the loading will be stopped if it doesn’t match False - do not check the iTree hash

• load_links – True - linked iTree objects will be loaded

• _source – Path of a loaded source file (for internal use)

Returns

iTree object loaded from file

load(file_path, check_hash=True, load_links=True)

create an iTree object by loading from a file

Parameters

• file_path – file path to the file that contains the iTree information

• check_hash – True the hash of the file will be checked and the loading will be stopped if it doesn’t match False - do not check the iTree hash

• load_links – True - linked iTree objects will be loaded

Returns

iTree object loaded from file

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

The code is published under MIT license incl. human protect patch:

The MIT License (MIT) incl. human protect patch Copyright © 2022 <copyright holders>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Human protect patch: The program and its derivative work will neither be modified or executed to harm any human being nor through inaction permit any human being to be harmed.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information see: https://en.wikipedia.org/wiki/MIT_License

This part of code contains the standard iTree serializers (JSON and rendering)

class itertree.itree_serializer.itree_renderer.iTreeRender

Bases: object

Standard renderer fr the iTree object for creating a very simple pretty print output

renders(itree_object, filter_method=None, enumerate=False)

creates a pretty print string from iTree object and returns it in a string

The rendered outputs can be filtered but only in hierarchical way.

param itree_object

iTree object to be converted

param filter_method

item filter method or filter-constant to filter specific items out Note:: The root of the object is not filtered and always in the outputs first line

Parameters

enumerate –

add enumeration before the items

return

string containing the pretty print output

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

The code is published under MIT license incl. human protect patch:

The MIT License (MIT) incl. human protect patch Copyright © 2022 <copyright holders>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Human protect patch: The program and its derivative work will neither be modified or executed to harm any human being nor through inaction permit any human being to be harmed.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information see: https://en.wikipedia.org/wiki/MIT_License

This is a class wihch translates an iTree in a dot graph

This part of code contains the standard iTree serializers (JSON and rendering)

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

The code is published under MIT license incl. human protect patch:

The MIT License (MIT) incl. human protect patch Copyright © 2022 <copyright holders>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Human protect patch: The program and its derivative work will neither be modified or executed to harm any human being nor through inaction permit any human being to be harmed.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information see: https://en.wikipedia.org/wiki/MIT_License

This part of code contains the standard iTree serializers (JSON and rendering)

itertree.itree_serializer.itree_json_converter.Converter_1_1_1_to_2_0_0(src_path, check_hash=True)

class itertree.itree_serializer.itree_json_converter.Converter_1_1_1_to_2_0_0_Cls

Bases: object

This is the standard serializer for DataTree which translates the structure into the JSON format. Users might implement their own serializers using the interface methods defined in this serializer

ITREE_SERIALIZE_VERSION = '1.1.1'

TREE = 'iT'

DATA = 'DT'

LINK = 'LK'

TAG = 'TG'

IDX = 'IDX'

DATA_MODELL = 'DM'

DTYPE = 'TP'

DATA_CONTAINER = 'DC'

ITREE_ITEMS_DECODE = {'iT', 'iTI', 'iTPH', 'iTRO', 'iTl'}

convert(src_path, check_hash=True)

create_itree_from_raw(raw_o)

itertree helper classes

This code is taken from the itertree package: https://pypi.org/project/itertree/ GIT Home: https://github.com/BR1py/itertree The documentation can be found here: https://itertree.readthedocs.io/en/latest/index.html

The code is published under MIT license incl. human protect patch:

The MIT License (MIT) incl. human protect patch Copyright © 2022 <copyright holders>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Human protect patch: The program and its derivative work will neither be modified or executed to harm any human being nor through inaction permit any human being to be harmed.

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

For more information see: https://en.wikipedia.org/wiki/MIT_License

This part of code contains helper classes used in DataTree object

itertree.itree_helpers.accu_iterator(iterable, accu_method, initial_value=(None))

A method that enables itertools accumulation over a method .. note:: This method is just needed because in python <3.8 itertools accumulation has no initial parameter! :param iterable: iterable :param accu_method: accumulation method (will be fet by two parameters cumulated and new item) :return: accumulated iterator

itertree.itree_helpers.is_iterator_empty(iterator)

checks if the given iterator is empty

Parameters

iterator – iterator to be checked

Return type

tuple

Returns

• (True, iterator) - empty

• (False, iterator) - item inside

itertree.itree_helpers.rindex(lst, value)

find last occurance of a itme in the list :param lst: list :param value: search value :return:

class itertree.itree_helpers.iTLink(file_path=None, target_path=None, link_item=None)

Bases: object

Definition of a link to an element in another DataTree

get_init_args()

get_target_tree(self_itree, source_dir=None)

is_file_updated(source_dir=None)

property loaded

property is_loaded

property link_item

property file_path

property target_path

property link_tag

property link_data

property source_path

set_source_path(path)

set_loaded(tag=None, data=None)

property tags

set_tags_and_keys(tags, keys)

property file_crc

get_args()

class itertree.itree_helpers.iTFLAG

Bases: object

public flags for setting the iTree behavior during `__init__()

READ_ONLY_TREE = 1

READ_ONLY_VALUE = 2

LOAD_LINKS = 4

class itertree.itree_helpers.Any

Bases: object

Helper class used for marking that the ìTree()-object is “empty” no value is stored inside.

If required use the class as it is, do not instance an object.

class itertree.itree_helpers.NoValue

Bases: object

Helper class used for marking that the ìTree()-object is “empty” no value is stored inside.

If required use the class as it is, do not instance an object.

class itertree.itree_helpers.NoTag

Bases: object

Helper class used for the NoTag-family tag which is automatically used in case no explicit tag is given during creation of the ìTree()-object.

If required use the class as it is, do not instance an object.

class itertree.itree_helpers.NoKey

Bases: object

Helper class used for the NoKey entries in dicts stored as value object in the ìTree()-object.

If required use the class as it is, do not instance an object.

class itertree.itree_helpers.NoTarget

Bases: object

Helper class used for the NoKey entries in dicts stored as value object in the ìTree()-object.

If required use the class as it is, do not instance an object.

class itertree.itree_helpers.ArgTuple

Bases: tuple

class itertree.itree_helpers.Tag(tag=<class 'itertree.itree_helpers.NoTag'>)

Bases: object

Helper class used in get-methods for marking that the given value is a family-tag and not an index or key, etc.

tag

class itertree.itree_helpers.TagIdx(tag, idx)

Bases: tuple

property tag

Alias for field number 0

property idx

Alias for field number 1

itertree.itree_helpers.getter_to_list(get_result)

Helper function that always creates a list from a `iTree`get-method result.

1. In case we have a iterator the list with the iterator items is created.

2. In case we have a single item a list [single_item] is created

3. In case we have no item or empty iterator an empty list is created.

Parameters

get_result – result coming from a getter method

Return type

list

Returns

result list