caosadvancedtools.models package

Submodules

caosadvancedtools.models.data_model module

class caosadvancedtools.models.data_model.DataModel(*args, enums: list[Record] | None = None)

Bases: dict

A managed data model.

When constructing a data model the LinkAhead representation can easily be created using the classes RecordType and Propery, storing them in a Container and inserting it in LinkAhead. However, this has one drawback: You cannot simply change someting and update the container. The container will insist on having valid ids for all contained Entities.

This class allows you to define your model as easily but also provides you with a method (sync_data_model) that will sync with the data model in an existing LinkAhead instance.

This is possible because entities, defined in this model, are identified with entities in LinkAhead using names. I.e. a RecordType “Experiment” in this model will update an existing RecordType with name “Experiment” in LinkAhead. Thus, be carefull not to change existing Entities that were created for a different purpose (e.g. someone else’s experiment).

DataModel inherits from dict. The keys are always the names of the entities. Thus you cannot have unnamed or ambiguously named entities in your model.

Additionally the DataModel takes an enums array parameter. This contains LinkAhead records which should serve as enum values. At present this only is relevant for synchronization with the LinkAhead server: These enum records will be synchronized just like the record types upon sync_data_model.

Example:

# Create a DataModel with a RecordType and a Property, not assuming any # relation between the two. dm = DataModel([db.RecordType(name=”myRecordType”),

db.Property(name=”myProperty”)])

# Sync the DataModel with the server, so that the server state is consistent # with this DataModel’s content. dm.sync_data_model() # Now the DataModel’s IDs are the same as on the server.

append(entity: Entity)
collect_entities() → list[Entity]

Collect all entities and return as a flat list.

This includes explicitly defined RecordTypes and Properties, as well as RecordTypes mentioned as Properties.

Returns:

out

Return type:

list[db.Entity]

static entities_without(entities, names)

Return a new list with all entities which do not have certain names.

Parameters:

  • entities (iterable) – A iterable with entities.

  • names (iterable of str) – Only entities which do not have one of these names will end up in the returned iterable.

Returns:

A list with entities.

Return type:

list

extend(entities: list[Entity])
get_deep(name: str, visited_props: dict | None = None, visited_parents: set | None = None)

Attempt to resolve references for the given name.

The returned entity has all the properties it inherits from its ancestry and all properties have the correct descriptions and datatypes. This methods only uses data which is available in this DataModel, which acts kind of like a cache pool.

Note that this may change this data model (subsequent “get” like calls may also return deeper content.)

static get_existing_entities(entities)

Return a list with those entities of the supplied iterable that exist in the LinkAhead instance.

Parameters:

entities (iterable) – The entities to be retrieved. This object will not be modified.

Raises:

TransactionError – If the retrieval fails.

sync_data_model(noquestion: bool = False, verbose: bool = True)

Synchronize this DataModel with a LinkAhead instance.

Updates existing entities from the LinkAhead instance and inserts non-existing entities into the instance. Note: This allows to easily overwrite changes that were made to an existing data model. Use this function with care and double check its effect.

Raises:

TransactionError – If one of the involved transactions fails.

sync_ids_by_name(valid_entities)

Add IDs from valid_entities to the entities in this DataModel.

“By name” means that the valid IDs (from the valid_entities) are assigned to the entities, their properties in this DataModel by their names, also parents are replaced by equally named entities in valid_entities. These changes happen in place to this DataModel!

Parameters:

valid_entities (list of Entity) – A list (e.g. a Container) of valid entities.

Return type:

None

caosadvancedtools.models.parser module

This module (and script) provides methods to read a DataModel from a YAML file.

If a file name is passed to parse_model_from_yaml it is parsed and a DataModel is created. The yaml file needs to be structured in a certain way which will be described in the following.

The file should only contain a dictionary. The keys are the names of RecordTypes or Properties. The values are again dictionaries describing the entities. This information can be defined via the keys listed in KEYWORDS. Notably, properties can be given in a dictionary under the xxxx_properties keys and will be added with the respective importance. These properties can be RecordTypes or Properties and can be defined right there. Every Property or RecordType only needs to be defined once anywhere. When it is not defined, simply the name can be supplied with no value. Parents can be provided under the ‘inherit_from_xxxx’ keywords. The value needs to be a list with the names. Here, NO NEW entities can be defined.

exception caosadvancedtools.models.parser.JsonSchemaDefinitionError(msg)

Bases: RuntimeError

class caosadvancedtools.models.parser.JsonSchemaParser(types_for_missing_array_items=None, ignore_unspecified_array_items=False)

Bases: Parser

Extends the yaml parser to read in datamodels defined in a json schema.

EXPERIMENTAL: While this class can already be used to create data models from basic json schemas, there are the following limitations and missing features:

  • Due to limitations of json-schema itself, we currently do not support inheritance in the imported data models

  • The same goes for suggested properties of RecordTypes

  • Already defined RecordTypes and (scalar) Properties can’t be re-used as list properties

  • Reference properties that are different from the referenced RT. (Although this is possible for list of references)

  • Values

  • Roles

  • The extern keyword from the yaml parser

parse_model_from_json_schema(filename: str, top_level_recordtype: bool = True)

Return a datamodel created from the definition in the json schema in filename.

Parameters:

  • filename (str) – The path to the json-schema file containing the datamodel definition

  • top_level_recordtype (bool, optional) – Whether there is a record type defined at the top level of the schema. Default is true.

Returns:

out – The created DataModel

Return type:

data_model.DataModel

class caosadvancedtools.models.parser.Parser(debug: bool = False)

Bases: object

parse_model_from_string(string, existing_model: dict | None = None) → DataModel

Create and return a data model from the given YAML string.

Parameters:

  • string (str) – The YAML string.

  • existing_model (dict, optional) – An existing model to which the created model shall be added.

Returns:

out – The created DataModel

Return type:

DataModel

parse_model_from_yaml(filename, existing_model: dict | None = None, add_enums: bool = False) → DataModel

Create and return a data model from the given file.

Parameters:

  • filename (str) – The path to the YAML file.

  • existing_model (dict, optional) – An existing model to which the created model shall be added.

  • add_enums (bool, default=False) –

    If True, add enums to the result. This enables enum-names elements which contain arrays of enum names, so that this keyword is recognized by the parser.

    For each of the values in this array, a simple Record is created, with the RecordType as parent and the value as the name. These records can conveniently be used as enum like references. The values (and thus enum names) do not have to be unique across RecordTypes: for example there may be Other enum values for different RecordTypes.

    For more information, see https://docs.indiscale.com/linkahead-docs/advanced-user-tools/yaml_interface.html

Returns:

out – The created DataModel

Return type:

data_model.DataModel

class caosadvancedtools.models.parser.SafeLineLoader(stream)

Bases: SafeLoader

Load a line and keep meta-information.

Note that this will add a __line__ element to all the dicts.

construct_mapping(node, deep=False)

Overwritung the parent method.

exception caosadvancedtools.models.parser.TwiceDefinedException(name)

Bases: Exception

exception caosadvancedtools.models.parser.YamlDefinitionError(line, template=None)

Bases: RuntimeError

caosadvancedtools.models.parser.main()
caosadvancedtools.models.parser.parse_model_from_json_schema(filename: str, top_level_recordtype: bool = True, types_for_missing_array_items: dict | None = None, ignore_unspecified_array_items: bool = False, existing_model: dict | None = None) → DataModel

Return a datamodel parsed from a json schema definition.

Parameters:

  • filename (str) – The path of the json schema file that is to be parsed

  • top_level_recordtype (bool, optional) – Whether there is a record type defined at the top level of the schema. Default is true.

  • types_for_missing_array_items (dict, optional) – dictionary containing fall-back types for json entries with type: array but without items specification. Default is an empty dict.

  • ignore_unspecified_array_items (bool, optional) – Whether to ignore type: array entries the type of which is not specified by their items property or given in types_for_missing_array_items. An error is raised if they are not ignored. Default is False.

  • existing_model (dict, optional) – An existing model to which the created model shall be added. Not fully implemented yet.

Returns:

out – The datamodel generated from the input schema which then can be used for synchronizing with LinkAhead.

Return type:

Datamodel

Note

This is an experimental feature, see JsonSchemaParser for information about the limitations of the current implementation.

caosadvancedtools.models.parser.parse_model_from_string(string, existing_model: dict | None = None, debug: bool = False) → DataModel

Parse a data model from a YAML string

This is a convenience function if the Parser object is not needed, it calls Parser.parse_model_from_string(...) internally.

Parameters:

  • existing_model (dict, optional) – An existing model to which the created model shall be added.

  • debug (bool, optional) – If True, turn on miscellaneous debugging. Default is False.

caosadvancedtools.models.parser.parse_model_from_yaml(filename, existing_model: dict | None = None, debug: bool = False, add_enums: bool = False) → DataModel

Parse a data model from a YAML file.

This is a convenience function if the Parser object is not needed, it calls Parser.parse_model_from_yaml(...) internally.

Parameters:

  • existing_model (dict, optional) – An existing model to which the created model shall be added.

  • debug (bool, optional) – If True, turn on miscellaneous debugging. Default is False.

  • add_enums (bool, default=False) – If True, add enums to the result. This enables enum-names elements, so that this keyword is recognized by the parser. See https://docs.indiscale.com/linkahead-docs/advanced-user-tools/yaml_interface for more information.

Module contents

Submodule for working with data models.