Core API Reference

This page documents the core classes and functions of the MTNA RDS Toolkit.

Server Connection

class dartfx.mtnards.MtnaRdsServer(*, host, base_path='rds', api_path='api', api_key=None, ssl_verify=True)

Bases: BaseModel

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

host: str

base_path: str | None

api_path: str | None

api_key: str | None

ssl_verify: bool

classmethod ensure_https_host(values)

property api_endpoint: str

property catalogs: dict[str, MtnaRdsCatalog]

Returns the server’s catalogs, loading them on first access.

refresh_catalogs()

Refreshes and returns the catalog list from the server.

property base_url: str

property api_url: str

property hostname: str

property info: MtnaRdsServerInfo

property explorer_url: str

property tabengine_url: str

api_request(path, method='GET', headers=None, params=None, body_json=None)

Makes an HTTP request to this server’s API.

create_catalog(id, name=None, description=None, is_private=True, lang='en')

Creates a new catalog on the server.

delete_catalog(id)

Deletes a catalog by ID.

delete_data_product(catalog_uri, data_product_uri)

Deletes a data product from a catalog.

get_catalog_by_uri(uri)

Returns a catalog by its URI, or None if not found.

get_catalog_by_id(id)

Returns a catalog by its ID, or None if not found.

get_ddi_codebook(catalog_id, product_id, include_variables=True, include_statistics=False)

Returns the DDI Codebook XML for a data product.

get_import_configuration(catalog_uri, product_uri, file_info)

Returns import configuration for a data product.

get_info()

Returns server information as a dictionary.

get_postman_collection(catalog_id=None, data_product_id=None)

Returns a Postman collection for the server, a catalog, or a data product.

get_process_details(process_id)

Returns details of a server-side process.

import_file(catalog_uri, product_uri, import_configuration)

Imports data into a data product.

is_up()

Returns True if the server is reachable, False otherwise.

upload_file(filepath)

Uploads a file to the server.

wait_for_process(pid, sleep=1, timeout=300, max_get_errors=10)

Waits for a server-side process to complete.

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• context (Any) – The context.

class dartfx.mtnards.base.MtnaRdsServerInfo(*, name, released, version)

Bases: BaseModel

name: str

released: str

version: str

model_config = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

Catalog

class dartfx.mtnards.MtnaRdsCatalog(*, uri, id, name=None, description=None, reference=None, revisionNumber=None, lastUpdate, isPrivate, dataProducts=None)

Bases: MtnaRdsResource

last_update: str

is_private: bool

data_products: list[MtnaRdsDataProduct] | None

attach_catalog_to_products()

get_data_product_by_uri(uri)

Returns a data product by its URI, or None if not found.

get_data_product_by_id(id)

Returns a data product by its ID, or None if not found.

property data_products_by_id: dict[str, MtnaRdsDataProduct]

Returns data products indexed by their id.

get_ddi_codebook(product_id, include_variables=True, include_statistics=False)

Returns the DDI Codebook XML for a data product in this catalog.

get_import_configuration(product_uri, file_info)

Returns import configuration for a data product.

create_sql_data_product(id, connection_string, table_name, username, password, name=None, description=None, is_private=True, lang='en')

Creates a SQL-backed data product in this catalog.

delete()

Deletes this catalog from the server.

delete_data_product(data_product_uri)

Deletes a data product from this catalog.

get_postman_collection(data_product_id=None)

Returns a Postman collection for this catalog or one of its data product.

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• context (Any) – The context.

Data Product

class dartfx.mtnards.MtnaRdsDataProduct(*, uri, id, name=None, description=None, reference=None, revisionNumber=None, abbreviation=None, cached=None, doi=None, changeLog=None, citation=None, dataProductType=None, isPrivate=None, keywords=None, lastUpdate=None, provenance=None, urls=None)

Bases: MtnaRdsResource

abbreviation: str | None

cached: bool | None

doi: bool | None

change_log: list[Any] | None

citation: str | None

data_product_type: str | None

is_private: bool | None

keywords: list[str] | None

last_update: str | None

provenance: str | None

urls: list[str] | None

property api_documentation_url: str

property catalog_id: str

property catalog_uri: str

property classifications: dict[str, MtnaRdsClassificationStub | MtnaRdsClassification]

property count_api_url: str

property csv_download_url: str

property explorer_url: str

property code_generators_api_url: str

property metadata_api_url: str

property parquet_download_url: str

property regression_api_url: str

property select_api_url: str

property tabulate_api_url: str

property tabengine_url: str

property variables: dict[str, MtnaRdsVariableStub | MtnaRdsVariable]

property variables_count: int

delete()

Deletes this data product from its catalog.

get_classification_by_uri(uri)

Returns a classification by its URI, or None if not found.

get_classification_by_id(id)

Returns a classification by its ID, or None if not found.

get_classification_variables(classification)

Returns all variables that use the given classification.

get_croissant(include_codes=True, max_codes=100)

Generates a Croissant ML metadata object for this data product.

get_ddi_codebook(include_variables=True, include_statistics=True)

Returns the DDI Codebook XML for this data product.

get_import_configuration(file_info)

Returns import configuration for uploading data into this product.

get_markdown(sections=None, max_codes=10)

Returns the markdown description of the data product.

get_postman_collection()

Returns a Postman collection for this data product.

get_variable_by_uri(uri)

Returns a variable by its URI, or None if not found.

get_variable_by_id(id)

Returns a variable by its ID, or None if not found.

load_metadata()

Loads full metadata (variables and classifications) from the server.

resolve_classifications()

Resolves all classification stubs into full classifications.

resolve_variables()

Resolves all variable stubs into full variables.

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• context (Any) – The context.

Variable

class dartfx.mtnards.variable.MtnaRdsVariableStub(*, uri, id, name=None, description=None, reference=None, revisionNumber=None)

Bases: MtnaRdsResource

classification_id: str | None

classification_uri: str | None

data_type: str | None

is_dimension: bool | None

is_measure: bool | None

is_required: bool | None

is_weight: bool | None

label: str | None

last_update: str | None

storage_type: str | None

property croissant_data_type: DataType

Returns the Croissant data type for this variable.

property catalog_id: str | None

property catalog_uri: str | None

property classification: MtnaRdsClassificationStub | MtnaRdsClassification | None

property data_product_id: str | None

property data_product_uri: str | None

property is_stub: bool

resolve()

Converts the stub into a detailed variable.

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• context (Any) – The context.

class dartfx.mtnards.MtnaRdsVariable(*, uri, id, name=None, description=None, reference=None, revisionNumber=None, classificationId=None, classificationUri=None, dataType=None, isDimension=None, isMeasure=None, isRequired=None, isWeight=None, label=None, lastUpdate=None, storageType=None)

Bases: MtnaRdsVariableStub

decimals: int | None

end_position: int | None

fixed_storage_width: int | None

format: str | None

index: int | None

start_position: int | None

resolve()

Already resolved — returns self.

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• context (Any) – The context.

Classification

class dartfx.mtnards.MtnaRdsClassificationStub(*, uri, id, name=None, description=None, reference=None, revisionNumber=None)

Bases: MtnaRdsResource

reference: bool | None

revision_number: int | None

code_count: int | None

property codes: list[MtnaRdsClassificationCode]

property is_stub: bool

resolve()

Converts the stub into a detailed classification.

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• context (Any) – The context.

class dartfx.mtnards.classification.MtnaRdsClassification(*, uri, id, name=None, description=None, reference=None, revisionNumber=None, code_count=None)

Bases: MtnaRdsClassificationStub

is_private: bool | None

keyword_count: int | None

last_update: str | None

level_count: int | None

resolve()

Already resolved — returns self.

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• context (Any) – The context.

class dartfx.mtnards.classification.MtnaRdsClassificationCode(*, uri, id=None, name=None, description=None, reference=None, revisionNumber=None, codeValue=None, isPrivate=None)

Bases: MtnaRdsResource

id: str | None

code_value: str | None

is_private: bool | None

reference: bool | None

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• context (Any) – The context.

Process

class dartfx.mtnards.process.MtnaRdsProcess(*, server=None, completed, id, failure=None, methodId, methodName, resourceName, resourceUri, status, completionDetails=None)

Bases: BaseModel

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

server: MtnaRdsServer | None

completed: int

id: str

failure: str | None

method_id: str

method_name: str

resource_name: str

resource_uri: str

status: str

completion_details: Any | None

property completed_successfully: bool

property failed: bool

property in_progress: bool

Base Classes

class dartfx.mtnards.base.MtnaRdsResource(*, uri, id, name=None, description=None, reference=None, revisionNumber=None)

Bases: BaseModel

model_config = {'populate_by_name': True, 'validate_by_alias': True, 'validate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

uri: str

id: str

name: str | None

description: str | None

reference: bool | None

revision_number: int | None

__eq__(other)

Two resources are equal if they share the same URI.

__hash__()

Make the object hashable by using the uri so it can be used in sets.

Type Definitions

The module uses type hints extensively. Common types include:

• str | None - Optional string values

• dict[str, T] - Dictionary with string keys

• list[T] - List of objects of type T

• bool | None - Optional boolean values

All public APIs include complete type hints for parameters and return values.