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easyfabric.data.model

Reference Objects​

@dataclass
class Reference(DataClassFromDictMixin)

Table relationship reference in an analytical model.

Points to another table that this table has a relationship with (e.g. a dimension referenced by a fact table).

LoadSettingRow Objects​

@dataclass
class LoadSettingRow(DataClassFromDictMixin)

One load setting of one table, flattened for iteration.

Measures Objects​

@dataclass
class Measures(DataClassFromDictMixin)

DAX measure definition for an analytical model.

Holds the measure name, DAX expression, format string, and display folder for use in tabular model deploymentThe process of "pushing a button" to make your configuration actual, working software in the cloud..

Column Objects​

@dataclass
class Column(DataClassFromDictMixin)

Model column with source mapping and data type.

Represents a column in a model table. A column is either source-backed (sourcecolumn) or a calculated column defined by a DAX expression.

Partition Objects​

@dataclass
class Partition(DataClassFromDictMixin)

Table partition definition for an analytical model.

Specifies the partition source query and processing load order for partitioned table refreshes.

Table Objects​

@dataclass
class Table(DataClassFromDictMixin)

Model table definition (fact or dimension).

Represents a table in an analytical model with its columns, measures, partitions, relationships, and load settings.

Model Objects​

@dataclass
class Model(DataClassFromDictMixin)

Analytical model definition with tables, columns, measures, and relationships.

Loaded from a YAMLA simple way to write configurations. It's basically a list that computers can read easily. model file, this is the top-level container for a tabular model's structure used during gold-layer deployment.

get_table​

def get_table(object_name: str) -> Optional[Table]

Find a table by its name or source table name.

Arguments:

  • object_name - The table name or source table name to search for (case-insensitive).

Returns:

The matching Table, or None if not found.

get_tables_lambda_filter​

def get_tables_lambda_filter(
        filter_func: Callable[[Table], bool]) -> list[Table]

Generic filter using a callable (e.g., for complex logic).

get_tables_by_field_filter​

def get_tables_by_field_filter(field: str,
                               value: str,
                               op: str = "==") -> list[Table]

Filters tables by a specific field and value using operator.

Arguments:

  • field str - Attribute name, e.g., 'tabletype'.
  • value str - Target value, e.g., 'dim'.
  • op str - Operator like '==', '!=', '>' (default '==').

Returns:

  • List[Table] - Filtered tables.

get_load_settings​

@staticmethod
def get_load_settings(tables: list[Table]) -> list[LoadSettingRow]

Flatten the load settings of the given tables into unique, ordered rows.

Carries loadactive rather than acting on it, so the caller decides what a setting the model switched off should mean. A setting without a notebook drives no load and is left out. Rows are unique over all five fields and ordered by table name, then load order.

Arguments:

  • tables list[Table] - Tables whose load settings to flatten.

Returns:

  • list[LoadSettingRow] - (name, tabletype, notebook, loadactive, loadorder).

from_yaml_file​

@classmethod
def from_yaml_file(cls, file_path: str)

Create a Model instance from a YAML file.