pyiron_atomistics.sphinx.input_writer.Group

pyiron_atomistics.sphinx.input_writer.Group#

class pyiron_atomistics.sphinx.input_writer.Group(*args, **kwargs)[source]#

Bases: DataContainer

Dictionary-like object to store SPHInX inputs.

Attributes (sub-groups, parameters, & flags) can be set and accessed via dot notation, or as standard dictionary key/values.

to_{job_type} converts the Group to the format expected by the given DFT code in its input files.

__init__(init=None, table_name=None, lazy=False, wrap_blacklist=(), lock_method='warning')#

Create new container.

Parameters:

  • init (Sequence, Mapping) – initial data for the container, nested occurances of Sequence and Mapping are translated to nested containers

  • table_name (str) – default name of the data container in HDF5

  • lazy (bool) – if True, use HDFStub to load values lazily from HDF5

  • wrap_blacklist (tuple of types) – any values in init that are instances of the given types are not wrapped in DataContainerBase

Methods

__init__([init, table_name, lazy, ...])

Create new container.

append(val)

Add new value to the container without a key.

clear()

Remove all items from DataContainerBase.

copy()

Returns deep copy of it self.

create_group(name)

Add a new empty subcontainer under the given key.

extend(vals)

Append vals to the end of this DataContainerBase.

from_dict(obj_dict[, version])

Populate the object from the serialized object.

from_hdf(hdf[, group_name])

Read object to HDF.

from_hdf_args(hdf)

Read arguments for instance creation from HDF5 file.

get(key[, default, create])

If key exists, behave as generic, if not call create_group.

groups()

Iterate over keys to nested containers.

has_keys()

Check if the container has keys set or not.

insert(index, val[, key])

Add a new element to the container at the specified position, with an optional key.

instantiate(obj_dict[, version])

Create a blank instance of this class.

items()

keys()

list_all()

Returns dictionary of :method:`.list_groups()` and :method:`.list_nodes()`.

list_groups()

Return a list of names of all nested groups.

list_nodes()

Return a list of names of all nested nodes.

lock([method])

Set read_only.

mark(index, key)

Add a key to an existing item at index.

nodes()

Iterator over keys to terminal nodes.

pop(k[,d])

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem()

as a 2-tuple; but raise KeyError if D is empty.

read(file_name[, wrap])

Parse file as dictionary and add its keys to this container.

rewrite_hdf(hdf[, group_name])

Update the HDF representation.

search(key[, stop_on_first_hit])

Search for key in the Container hierarchy.

setdefault(k[,d])

to_builtin([stringify])

Convert the container back to builtin dict's and list's recursively.

to_dict()

Reduce the object to a dictionary.

to_hdf(hdf[, group_name])

Write object to HDF.

to_sphinx([content, indent])

unlocked()

Unlock the object temporarily.

update(init[, wrap, blacklist])

Add all elements or key-value pairs from init to this container.

values()

write(file_name)

Writes the DataContainerBase to a text file.

Attributes

read_only

False if the object can currently be written to
append(val)#

Add new value to the container without a key.

Parameters:

val – new element

clear()#

Remove all items from DataContainerBase.

copy()#

Returns deep copy of it self. A shallow copy can be obtained via the copy module.

Returns:

deep copy of itself

Return type:

DataContainer

>>> pl = DataContainer([[1,2,3]])
>>> pl.copy() == pl
True
>>> pl.copy() is pl
False
>>> all(a is not b for a, b in zip(pl.copy().values(), pl.values()))
True
create_group(name)#

Add a new empty subcontainer under the given key.

Parameters:

name (str) – key under which to store the new subcontainer in this container

Returns:

the newly created subcontainer

Return type:

DataContainerBase

Raises:

ValueError – name already exists in container and is not a sub container

>>> pl = DataContainerBase({})
>>> pl.create_group("group_name")
DataContainerBase([])
>>> list(pl.group_name)
[]
extend(vals)#

Append vals to the end of this DataContainerBase.

Parameters:

vals (Sequence) – any python sequence to draw new elements from

from_dict(obj_dict: dict, version: str = None)#

Populate the object from the serialized object.

Parameters:

  • obj_dict (dict) – data previously returned from to_dict()

  • version (str) – version tag written together with the data

from_hdf(hdf: ProjectHDFio, group_name: str = None)#

Read object to HDF.

If group_name is given descend into subgroup in hdf first.

Parameters:

  • hdf (ProjectHDFio) – HDF group to read from

  • group_name (str, optional) – name of subgroup

classmethod from_hdf_args(hdf: ProjectHDFio) → dict#

Read arguments for instance creation from HDF5 file.

Parameters:

hdf (ProjectHDFio) – HDF5 group object

Returns:

arguments that can be **kwarg-passed to cls().

Return type:

dict

get(key, default=None, create=False)#

If key exists, behave as generic, if not call create_group.

Parameters:

  • key (str) – key to search

  • default (optional) – return this instead if nothing found

  • create (bool, optional) – create empty container at key if nothing found

Raises:

  • IndexError – if key is not in the container and neither default not

  • create` are give –

Returns:

element at key or new empty subcontainer

Return type:

object

groups()#

Iterate over keys to nested containers.

Returns:

list of all keys to elements of DataContainerBase.

Return type:

list

has_keys()#

Check if the container has keys set or not.

Returns:

True if there is at least one key set

Return type:

bool

insert(index, val, key=None)#

Add a new element to the container at the specified position, with an optional key. If the key is already in the container it will be updated to point to the new element at the new index. If index is larger than container, append instead.

Parameters:

  • index (int) – place val after this element

  • val – new element to add

  • key (str, optional) – optional key to mark the new element

classmethod instantiate(obj_dict: dict, version: str = None) → Self#

Create a blank instance of this class.

This can be used when some values are already necessary for the objects __init__.

Parameters:

  • obj_dict (dict) – data previously returned from to_dict()

  • version (str) – version tag written together with the data

Returns:

a blank instance of the object that is sufficiently initialized to call _from_dict() on it

Return type:

object

items() → a set-like object providing a view on D's items#
keys() → a set-like object providing a view on D's keys#
list_all()#

Returns dictionary of :method:`.list_groups()` and :method:`.list_nodes()`.

Returns:

results of :method:`.list_groups() under the key "groups"; results of :method:`.list_nodes()` und the

key “nodes”

Return type:

dict

list_groups()#

Return a list of names of all nested groups.

Returns:

group names

Return type:

list of str

list_nodes()#

Return a list of names of all nested nodes.

Returns:

node names

Return type:

list of str

lock(method: Literal['error', 'warning'] | None = None)#

Set read_only.

Objects may be safely locked multiple times without further effect.

Parameters:

method (str, either "error" or "warning") – if “error” raise an Locked exception if modification is attempted; if “warning” raise a LockedWarning warning; default is “error” or the value passed to the constructor.

Raises:

ValueError – if method is not an allowed value

mark(index, key)#

Add a key to an existing item at index. If key already exists, it is overwritten.

Parameters:

  • index (int) – index of the existing element to mark

  • key (str) – key for the existing element

Raises:

IndexError – if index > len(self)

>>> pl = DataContainerBase([42])
>>> pl.mark(0, "head")
>>> pl.head == 42
True
nodes()#

Iterator over keys to terminal nodes.

Returns:

list of keys to normal values.

Return type:

list

pop(k[, d]) → v, remove specified key and return the corresponding value.#

If key is not found, d is returned if given, otherwise KeyError is raised.

popitem() → (k, v), remove and return some (key, value) pair#

as a 2-tuple; but raise KeyError if D is empty.

read(file_name, wrap=True)#

Parse file as dictionary and add its keys to this container.

For supported file types, see fileio.read().

Errors during reading of the files generate a warning, but leave the container unchanged.

Parameters:

  • file_name (str) – path to the input file

  • wrap (bool)

Raises:

ValueError – if file extension doesn’t match one of the supported ones

property read_only: bool#

False if the object can currently be written to

Setting this value will trigger _on_lock() and _on_unlock() if it changes.

Type:

bool

rewrite_hdf(hdf: ProjectHDFio, group_name: str = None)#

Update the HDF representation.

If an object is read from an older layout, this will remove the old data and rewrite it in the newest layout.

Parameters:

  • hdf (ProjectHDFio) – HDF group to read/write

  • group_name (str, optional) – name of subgroup

search(key, stop_on_first_hit=True)#

Search for key in the Container hierarchy.

This should be used if there is only one such item in the hierarchy.

If stop_on_first_hit is True the first item found is taken. Otherwise, a ValueError is raised if the key appears multiple times.

Parameters:

  • key (str) – the key to look for

  • stop_on_first_hit (bool) – whether to stop on the first hit

Raises:

  • TypeError – if key is not str

  • KeyError – if key is not found

  • ValueError – if stop_on_first_hit is False and key is found twice

Returns:

element at key

Return type:

object

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D#
to_builtin(stringify=False)#

Convert the container back to builtin dict’s and list’s recursively.

Parameters:

stringify (bool, optional) – convert all non-recursive elements to str

to_dict() → dict#

Reduce the object to a dictionary.

Returns:

serialized state of this object

Return type:

dict

to_hdf(hdf: ProjectHDFio, group_name: str = None)#

Write object to HDF.

If group_name is given create a subgroup in hdf first.

Parameters:

  • hdf (ProjectHDFio) – HDF group to write to

  • group_name (str, optional) – name of subgroup

unlocked() → _UnlockContext#

Unlock the object temporarily.

Context manager returns this object again and relocks it after the with statement finished.

Note

lock() vs. unlocked()

There is a small asymmetry between these two methods. lock() can only be done once (meaningfully), while unlocked() is a context manager and can be called multiple times.

update(init, wrap=False, blacklist=(), **kwargs)#

Add all elements or key-value pairs from init to this container. If wrap is not given, behaves as the generic method.

Parameters:

  • init (Sequence, Set, Mapping) – container to draw new elements from

  • wrap (bool) – if True wrap all encountered Sequences and Mappings in DataContainerBase recursively

  • blacklist (list of types) – when wrap is True, don’t wrap these types even if they’re instances of Sequence or Mapping

  • **kwargs – update from this mapping as well

values() → an object providing a view on D's values#
write(file_name)#

Writes the DataContainerBase to a text file.

For supported file types, see fileio.write().

Parameters:

file_name (str) – the name of the file to be writen to.