Reference

statbank package

statbank.api_exceptions module

exception StatbankApiError

Bases: Exception

Base class for Statbank Api Errors.

exception StatbankAuthError(*args, response_content=None, **kwargs)

Bases: HTTPError

Raised when authentication with Statbank fails.

Extends requests.HTTPError with an optional response_content attribute that can hold parsed JSON from the response.

Parameters:

  • *args (Any) – Positional arguments forwarded to requests.HTTPError.

  • response_content (dict[str, Any] | None) – Optional JSON-decoded payload to attach.

  • **kwargs (Any) – Keyword arguments forwarded to requests.HTTPError.

Return type:

None

exception StatbankParameterError

Bases: StatbankApiError

Exception for invalid request.

exception StatbankVariableSelectionError

Bases: StatbankApiError

Exception for invalid variable selection.

exception TooBigRequestError

Bases: StatbankApiError

Exception for request that is to big to handle for the Statbank Api.

The API is limited to 800,000 cells (incl. empty cells)

statbank.api_types module

class DelTabellType

Bases: TypedDict

A typed subpart of the returned Filbeskrivelse.

deltabell: str
eksempel_linje: str
internasjonal_rapportering: NotRequired[list[KolonneInternasjonalRapporteringType]]
null_prikk_missing: NotRequired[list[SuppressionDeltabellCodeListType]]
statistikkvariabler: list[KolonneStatistikkvariabelType]
variabler: list[KolonneVariabelType]
class FilBeskrivelseType

Bases: TypedDict

The content of the json returned by the uttrekssbeskrivelse endpoint, takes this shape.

Parts of it are later assigned to attributes on class-instances.

DeltabellTitler: list[dict[str, str]]
Huvudtabell: str
IRkodelister: NotRequired[list[KodelisteType]]
TabellId: str
Uttaksbeskrivelse_lagd: str
base: str
deltabller: list[DelTabellType]
kodelister: list[KodelisteType]
null_prikk_missing_kodeliste: NotRequired[list[SuppressionCodeListType]]
class KodeType

Bases: TypedDict

The code -> labels for the list in the Codelists.

kode: str
text: str
class KodelisteType

Bases: TypedDict

The codelists have their own name, which links from the column-metadata, and a list of code -> labels.

SumIALtTotalKode: NotRequired[str]
kodeliste: str
koder: list[KodeType]
class KodelisteTypeParsed

Bases: TypedDict

Reorganizing the kodelists to this is done under init of Uttrekk.

SumIALtTotalKode: NotRequired[str]
koder: dict[str, str]
class KolonneInternasjonalRapporteringType

Bases: TypedDict

The international-report-variables are rarely used, but has other metadata than the other columns..

Kodeliste_id: str
Kodeliste_text: str
beskrivning: str
egenskap: str
kolonnenummer: str
class KolonneStatistikkvariabelType

Bases: TypedDict

The statistic-variables are mostly the numerical variables in statbanken.

This class describes the types of the metadata about these columns in the Uttrekksbeskrivelse.

Antall_lagrede_desimaler: str
Antall_viste_desimaler: str
Enhet: str
Text: str
kolonnenummer: str
class KolonneVariabelType

Bases: TypedDict

The Variables are mostly the classification variables in statbanken.

This class describes the types of the metadata about these columns in the Uttrekksbeskrivelse.

Klassifikasjonsvariabel: str
Kodeliste_id: str
Kodeliste_text: str
Variabeltext: str
kolonnenummer: str
class QueryPartType

Bases: TypedDict

This represents each part of the query sent to statbanken.

code: str
selection: SelectionPartType
class QueryWholeType

Bases: TypedDict

The whole query-type is used to get the data from Statbank.

query: list[QueryPartType]
response: dict[str, str]
class SelectionPartType

Bases: TypedDict

The selection-type is used to get the data from Statbank.

filter: str
class SuppressionCodeListType

Bases: TypedDict

The suppression-codes are used to filter out rows in the Uttrekksbeskrivelse, lower-level.

Beskrivelse: str
Kode: str
Vises_som: str
class SuppressionDeltabellCodeListType

Bases: TypedDict

The suppression-codes are used to filter out rows in the Uttrekksbeskrivelse, top-level.

gjelder_for__kolonner_nummer: str
gjelder_for_text: str
kolonnenummer: str
class TransferPartType

Bases: TypedDict

There are multiple copies of this for every json.

Exception: None | str
GeneratedId: None | str
Message: str
Status: str
ValidationInfoItems: None | str
class TransferResultType

Bases: TypedDict

The types of the main result-json from a transfer.

ItemResults: list[TransferPartType]
TotalResult: TransferPartType

statbank.auth module

class StatbankAuth(use_db=None, *, config=None, auth=None)

Bases: object

Parent class for shared behavior between Statbankens “Transfer-API” and “Uttaksbeskrivelse-API”.

Parameters:

  • use_db (UseDb | Literal['TEST', 'PROD'] | None)

  • config (StatbankConfig | None)

  • auth (requests.auth.AuthBase | None)

check_database()

Checks if we are in prod environment. And which statbank-database we are sending to.

Return type:

str

Parameters:

self (Self)

check_env()

Check if you are on Dapla or in prodsone.

Simplified terribly by the addition of env vars for this, keeping this method for legacy reasons.

Return type:

str

Returns:

“DAPLA” if on dapla, “PROD” if you are in prodsone.

reset_auth()

Reset the auth by removing the entry from the .netrc-file first, then asking to enter the username and password again.

Return type:

None

class StatbankConfig(*, endpoint_base, encrypt_url, useragent, environment, region, netrc_path=None)

Bases: object

Holds config for Transfer-API” and “Uttaksbeskrivelse-API.

Parameters:
classmethod from_environ(use_db)

Load config from environment variables.

Return type:

Self

Parameters:

use_db (UseDb | None)

class TokenAuth(token, auth_scheme='Bearer')

Bases: AuthBase

Token based authorization.

Parameters:

  • token (str)

  • auth_scheme (str)

statbank.client module

class StatbankClient(date=datetime.date(2025, 12, 2), shortuser='', cc='', bcc='', overwrite=True, approve=Approve.JIT, check_username_password=True, use_db=None, *, config=None, auth=None)

Bases: StatbankAuth

This is the main interface towards the rest of the statbank-package.

An initialized client, an object of this class, will contain data/parameters that often is shared, among all transfers within a statistical production. Call methods under this client to: - transfer the data: .transfer() - only validate the data against a description: .validate() - get transfer/data description (filbeskrivelse): .get_description() - set the publish date with a datepicker: .date_picker() + .set_publish_date() - get published data from the external or internal API of statbanken: apidata_all() / apidata()

Parameters:

  • date (str | datetime.date | datetime.datetime)

  • shortuser (str)

  • cc (str)

  • bcc (str)

  • overwrite (bool)

  • approve (int | str | Approve)

  • check_username_password (bool)

  • use_db (UseDb | Literal['TEST', 'PROD'] | None)

  • config (StatbankConfig | None)

  • auth (requests.auth.AuthBase | None)

date

Date for publishing the transfer. Statbanken only allows publishing four months into the future?

Type:

dt.datetime

shortuser

The abbrivation of username at ssb. Three letters, like “cfc”. If not specified, we will try to get this from daplas environement variables.

Type:

str

cc

First person to be notified by email of transfer. Defaults to the same as “shortuser”

Type:

str

bcc

Second person to be notified by email of transfer. Defaults to the same as “cc”

Type:

str

overwrite

False = no overwrite True = overwrite

Type:

bool

approve

0 = MANUAL approval 1 = AUTOMATIC approval at transfer-time (immediately) 2 = JIT (Just In Time), approval right before publishing time

Type:

Approve | str | int

log

Each “action” (method used) on the client is appended to the log. Nice to use for appending to your own logging after you are done, or printing it in a try-except-block to see what the last actions were, before error being raised.

Type:

list[str]

use_db

If you are in PROD-dapla and want to send to statbank test-database, set this to “TEST”. When sending from TEST-environments you can only send to TEST-db, so this parameter is then ignored. Be aware that metadata tends to be outdated in the test-database.

Type:

UseDb | str | None

static apicodelist(id_or_url='', codelist_name='')

Get one specific or all the codelists of a published statbank-table as a dict or nested dicts.

Parameters:

  • id_or_url (str) – The id of the STATBANK-table to get the total query for, or supply the total url, if the table is “internal”.

  • codelist_name (str) – The name of the specific codelist to get.

Returns:

The codelist of the table as a dict or a nested dict.

Return type:

dict[str, str] | dict[str, dict[str, str]]

static apidata(id_or_url='', payload=None, include_id=False)

Get the contents of a published statbank-table as a pandas Dataframe, specifying a query to limit the return.

Parameters:

  • id_or_url (str) – The id of the STATBANK-table to get the total query for, or supply the total url, if the table is “internal”.

  • payload (dict[str, str]|None) – a dict of the query to include with the request, can be copied from the statbank-webpage.

  • include_id (bool) – If you want to include “codes” in the dataframe, set this to True

Returns:

A pandas dataframe with the table-content

Return type:

pd.DataFrame

static apidata_all(id_or_url='', include_id=False)

Get ALL the contents of a published statbank-table as a pandas Dataframe.

Parameters:

  • id_or_url (str) – The id of the STATBANK-table to get the total query for, or supply the total url, if the table is “internal”.

  • include_id (bool) – If you want to include “codes” in the dataframe, set this to True

Returns:

A pandas dataframe with the table-content

Return type:

pd.DataFrame

static apidata_rotate(df, ind='year', val='value')

Rotate the dataframe so that time is used as the index.

Parameters:

  • df (pd.dataframe) – dataframe (from <get_from_ssb> function

  • ind (str) – string of column name denoting time

  • val (str) – string of column name denoting values

Returns:

pivoted dataframe

Return type:

pd.DataFrame

static apimetadata(id_or_url='')

Get the metadata of a published statbank-table as a dict.

Parameters:

id_or_url (str) – The id of the STATBANK-table to get the total query for, or supply the total url, if the table is “internal”.

Returns:

The metadata of the table as the json returned from the API-get-request.

Return type:

dict[str, Any]

date_picker()

Display a datapicker-widget.

Assign it to a variable, that you after editing the date, pass into set_publish_date() date = client.datepicker() # Edit date client.set_publish_date(date)

Returns:

A datepicker widget from ipywidgets, with its date set to what the client currently holds.

Return type:

widgets.DatePicker

get_description(tableid='00000')

Get the “uttrekksbeskrivelse” for the tableid, which describes metadata.

about shape of data to be transferred, and metadata about the table itself in Statbankens system, like ID, name and content of codelists.

Parameters:

tableid (str) – The tableid of the “hovedtabell” in statbanken, a 5 digit string.

Returns:

An instance of the class StatbankUttrekksBeskrivelse, which is comparable to the old “filbeskrivelse”.

Return type:

StatbankUttrekksBeskrivelse

static read_description_json(json_path_or_str)

Re-initializes a StatbankUttrekksBeskrivelse from a stored json file/string.

Checks if provided string exists on disk, if it does, tries to load it as json. Otherwise expects you to provide a json-string that works for json.loads. Inserts first layer in json as attributes under a blank StatbankUttrekksBeskrivelse-object.

Parameters:

json_path_or_str (str) – Either a path on local storage, or a loaded json-string

Returns:

An instance of the class StatbankUttrekksBeskrivelse, which is comparable to the old “filbeskrivelse”.

Return type:

StatbankUttrekksBeskrivelse

static read_transfer_json(json_path_or_str)

Checks if provided string exists on disk, if it does, tries to load it as json.

Otherwise expects you to provide a json-string that works for json.loads. Inserts first layer in json as attributes under a blank StatbankTransfer-object.

Parameters:

json_path_or_str (str) – Either a path on local storage, or a loaded json-string

Returns:

An instance of the class StatbankTransfer, missing the data transferred and some other bits probably.

Return type:

StatbankTransfer

set_publish_date(date)

Set the publishing date on the client.

Takes the widget from date_picker assigned to a variable, which is probably the intended use. If sending a string, use the format 2000-12-31, you can also send in a datetime. Hours, minutes and seconds are replaced with statbankens publish time: 08:00:00

Parameters:

date (datetime) – date-picker widget, or a date-string formatted as 2000-12-31

Raises:

TypeError – If the date-parameter is of type other than datetime, string, or ipywidgets.DatePicker.

Return type:

None

transfer(dfs, tableid='00000')

Transfers your data to Statbanken.

Make sure you’ve set the publish-date correctly before sending.

Parameters:

  • dfs (dict[str, pd.DataFrame]) – The data to validate in a dictionary of deltabell-names as keys and pandas-dataframes as values.

  • tableid (str) – The tableid of the “hovedtabell” in statbanken, a 5 digit string.

Returns:

An instance of the class StatbankTransfer, which details the content of a successful transfer.

Return type:

StatbankTransfer

validate(dfs, tableid='00000', raise_errors=False, ignore_codes_not_in_data=False)

Gets an “uttrekksbeskrivelse” and validates the data against this.

All validation happens locally, so dont be afraid of any data being sent to statbanken using this method.

Parameters:

  • dfs (dict[str, pd.DataFrame) – The data to validate in a dictionary of deltabell-names as keys and pandas-dataframes as values.

  • tableid (str) – The tableid of the “hovedtabell” in statbanken, a 5 digit string. Defaults to “00000”.

  • raise_errors (bool) – True/False based on if you want the method to raise its own errors or not. Defaults to False.

  • ignore_codes_not_in_data (bool) – If set to True, will hide messages about codes in klass that are missing from the data.

Returns:

A dictionary of the errors the validation wants to raise.

Return type:

dict[str, str]

statbank.get_apidata module

apicodelist(id_or_url='', codelist_name='')

Get one specific or all the codelists of a published statbank-table as a dict or nested dicts.

Parameters:

  • id_or_url (str) – The id of the STATBANK-table to get the total query for, or supply the total url, if the table is “internal”.

  • codelist_name (str) – The name of the specific codelist to get.

Returns:

The codelist of the table as a dict or a nested dict.

Return type:

dict[str, str] | dict[str, dict[str, str]]

Raises:

ValueError – If the specified codelist_name is not in the returned metadata.

apidata(id_or_url='', payload=None, include_id=False)

Get the contents of a published statbank-table as a pandas Dataframe, specifying a query to limit the return.

Parameters:

  • id_or_url (str) – The id of the STATBANK-table to get the total query for, or supply the total url, if the table is “internal”.

  • payload (QueryWholeType | None) – a dict in the shape of a QueryWhole, to include with the request, can be copied from the statbank-webpage.

  • include_id (bool) – If you want to include “codes” in the dataframe, set this to True

Returns:

The table-content

Return type:

pd.DataFrame

Raises:

ValueError – If the first parameter is not recognized as a statbank ID or a direct url.

apidata_all(id_or_url='', include_id=False)

Get ALL the contents of a published statbank-table as a pandas Dataframe.

Parameters:

  • id_or_url (str) – The id of the STATBANK-table to get the total query for, or supply the total url, if the table is “internal”.

  • include_id (bool) – If you want to include “codes” in the dataframe, set this to True

Returns:

Table-content

Return type:

pd.DataFrame

apidata_query_all(id_or_url='')

Builds a query for ALL THE DATA in a table based on a request for metadata on the table.

Parameters:

id_or_url (str) – The id of the STATBANK-table to get the total query for, or supply the total url, if the table is “internal”.

Returns:

The prepared query based on all the codes in the table.

Return type:

QueryWholeType

apidata_rotate(df, ind='year', val='value')

Rotate the dataframe so that years are used as the index.

Parameters:

  • df (pd.DataFrame) – dataframe (from <get_from_ssb> function)

  • ind (str) – string of column name denoting time

  • val (str) – string of column name denoting values

Returns:

pivoted dataframe

Return type:

pd.DataFrame

apimetadata(id_or_url='')

Get the metadata of a published statbank-table as a dict.

Parameters:

id_or_url (str) – The id of the STATBANK-table to get the total query for, or supply the total url, if the table is “internal”.

Returns:

The metadata of the table as the json returned from the API-get-request.

Return type:

dict[str, Any]

Raises:

ValueError – If the first parameter is not recognized as a statbank ID or a direct url.

statbank.globals module

class Approve(*values)

Bases: IntEnum

Enum for approval codes.

AUTOMATIC = 1

Automatic approval at transfer-time (immediately).

JIT = 2

Just in time approval right before publishing time.

MANUAL = 0

Manual approval.

class DaplaEnvironment(*values)

Bases: Enum

Environment variable for what Dapla environment your running on.

DEV = 'DEV'
PROD = 'PROD'
TEST = 'TEST'
class DaplaRegion(*values)

Bases: Enum

Environment variable for what Dapla region your running on.

DAPLA_LAB = 'DAPLA_LAB'
ON_PREM = 'ON_PREM'
class UseDb(*values)

Bases: Enum

Hold options for database choices, targeted at Statbanken.

PROD = 'PROD'
TEST = 'TEST'

statbank.response_to_pandas module

exception StatbankDataBuildError

Bases: Exception

Custom exception for errors that occur during the building of Statbank data.

response_to_pandas(response, include_id=False)

Converts a response from the SSB Statbank API to a pandas DataFrame.

Parameters:

  • response (requests.models.Response) – The response object from the API.

  • include_id (bool) – Whether to include the ID columns in the output. Defaults to False.

Returns:

A pandas DataFrame containing the data from the response.

Return type:

pd.DataFrame

Raises:

StatbankDataBuildError – If the number of categories and values do not match.

stack_categories(varcodes)

Stacks the categories of the variables (in the correct order) from the response into a DataFrame.

Parameters:

varcodes (dict[str, list[Any]]) – A dictionary where the keys are variable names and the values are lists of codes.

Returns:

A pandas DataFrame containing the stacked categories.

Return type:

pd.DataFrame

statbank.statbank_logger module

class ColoredFormatter(*args, colors=None, **kwargs)

Bases: Formatter

Colored log formatter.

Parameters:

  • args (Any)

  • colors (dict[str, str] | None)

  • kwargs (Any)

format(record)

Format the specified record as text.

Return type:

str

Parameters:

record (LogRecord)

statbank.transfer module

class StatbankTransfer(data: dict[str, DataFrame], tableid: str = ..., shortuser: str = ..., date: str | date | datetime = ..., cc: str = ..., bcc: str = ..., overwrite: bool = ..., approve: int | str | Approve = ..., use_db: UseDb | Literal['TEST', 'PROD'] | None = ..., validation: bool = ..., delay: bool = ..., headers: None = None, *, config: StatbankConfig | None = ..., auth: AuthBase | None = ...)
class StatbankTransfer(data: dict[str, DataFrame], tableid: str = ..., shortuser: str = ..., date: str | date | datetime = ..., cc: str = ..., bcc: str = ..., overwrite: bool = ..., approve: int | str | Approve = ..., use_db: UseDb | Literal['TEST', 'PROD'] | None = ..., validation: bool = ..., delay: bool = ..., headers: dict[str, str] = ..., *, config: StatbankConfig | None = ..., auth: AuthBase | None = ...)

Bases: StatbankAuth

Class for talking with the “transfer-API”, which actually recieves the data from the user and sends it to Statbank.

Parameters:

  • data (dict[str, pd.DataFrame])

  • tableid (str)

  • shortuser (str)

  • date (str | datetime.date | datetime.datetime)

  • cc (str)

  • bcc (str)

  • overwrite (bool)

  • approve (int | str | Approve)

  • use_db (UseDb | Literal['TEST', 'PROD'] | None)

  • validation (bool)

  • delay (bool)

  • headers (dict[str, str] | None)

  • config (StatbankConfig | None)

  • auth (requests.auth.AuthBase | None)

data

name of “deltabell.dat” as keys. Number of DataFrames needs to match the number of “deltabeller” in the uttakksbeskrivelse. Dict-shape can be retrieved and validated before transfer with the Uttakksbeskrivelses-class.

Type:

dict[str, pd.DataFrame]

tableid

The numeric id of the table, matching the one found on the website. Should be a 5-length numeric-string. Alternatively it should be possible to send in the “hovedtabellnavn” instead of the tableid.

Type:

str

shortuser

The abbrivation of username at ssb. Three letters, like “cfc”

Type:

str

date

Date for publishing the transfer. Shape should be “yyyy-mm-dd”, like “2022-01-01”. Statbanken only allows publishing four months into the future?

Type:

str

cc

First person to be notified by email of transfer. Defaults to the same as “shortuser”

Type:

str

bcc

Second person to be notified by email of transfer. Defaults to the same as “cc”

Type:

str

overwrite

  • False = no overwrite

  • True = overwrite

Type:

bool

approve

  • 0 = MANUAL approval

  • 1 = AUTOMATIC approval at transfer-time (immediately)

  • 2 = JIT (Just In Time), approval right before publishing time

Type:

Approve | str | int

use_db

If you are in PROD-dapla and want to send to statbank test-database, set this to “TEST”. When sending from TEST-environments you can only send to TEST-db, so this parameter is then ignored. Be aware that metadata tends to be outdated in the test-database.

Type:

UseDb | str | None

validation

  • True, if you want the python-validation code to run user-side.

  • False, if its slow and unnecessary.

Type:

bool

boundary

String that defines the splitting of the body in the transfer-post-request. Kept here for uniform choice through the class.

Type:

str

urls

Urls for transfer, observing the result etc., built from environment variables.

Type:

dict[str, str]

params

This dict will be built into the post request. Keep it in this nice shape for later introspection.

Type:

dict[str, str]

body

The data parsed into the body-shape the Statbank-API expects in the transfer-post-request.

Type:

str

response

The resulting response from the transfer-request. Headers might be deleted without warning.

Type:

requests.Response

property delay: bool

Obfuscate the delay a bit from the user. We dont want transfers transferring again without recreating the object.

property headers: None

Deprecated attribute, Authinfo is not stored here anymore.

to_json(path=None)

Store a copy of the current state of the transfer-object as a json.

If path is provided, tries to write to it, otherwise will return a json-string for you to handle like you wish.

Parameters:

path (str) – if provided, will try to write a json to a local path.

Returns:

If path is provided, tries to write a json there and returns nothing. str: If path is not provided, returns the json-string for you to handle as you wish.

Return type:

None

transfer(headers=None)

Transfers your data to Statbanken.

Make sure you’ve set the publish-date correctly before sending. Will only work if the transfer has not already been sent, meaning it was “delayed”.

Parameters:

headers (dict[str, str] | None) – Mostly for internal use by the package. Needs to be a finished compiled headers for a request including Authorization.

Raises:

ValueError – If the transfer is already transferred.

Return type:

None

statbank.uttrekk module

class StatbankUttrekksBeskrivelse(tableid: str, raise_errors: bool = ..., headers: None = None, use_db: UseDb | Literal['TEST', 'PROD'] | None = ..., *, data: None = None, config: StatbankConfig | None = ..., auth: AuthBase | None = ...)
class StatbankUttrekksBeskrivelse(tableid: None = None, raise_errors: bool = ..., headers: None = None, use_db: UseDb | Literal['TEST', 'PROD'] | None = ..., *, data: UttrekksBeskrivelseData = ..., config: StatbankConfig | None = ..., auth: AuthBase | None = ...)
class StatbankUttrekksBeskrivelse(tableid: str, raise_errors: bool = ..., headers: dict[str, str] = ..., use_db: UseDb | Literal['TEST', 'PROD'] | None = ..., *, data: UttrekksBeskrivelseData | None = ..., config: StatbankConfig | None = ..., auth: AuthBase | None = ...)

Bases: StatbankAuth, StatbankUttrekkValidators

Class for talking with the “uttrekksbeskrivelses-API”, which describes metadata about shape of data to be transferred.

And metadata about the table itself in Statbankens system, like ID, name of codelists etc.

Parameters:

  • tableid (str | int | None)

  • raise_errors (bool)

  • headers (dict[str, str] | None)

  • use_db (UseDb | Literal['TEST', 'PROD'] | None)

  • data (UttrekksBeskrivelseData | None)

  • config (StatbankConfig | None)

  • auth (requests.auth.AuthBase | None)

url

Main url for transfer

Type:

str

filbeskrivelse

The “raw” json returned from the API-get-request, loaded into a dict.

Type:

dict

use_db

If you are in PROD-dapla and want to send to statbank test-database, set this to “TEST”. When sending from TEST-environments you can only send to TEST-db, so this parameter is then ignored. Be aware that metadata tends to be outdated in the test-database.

Type:

UseDb | str | None

property codelists: dict[str, KodelisteTypeParsed]

Metadata about column-contents, like formatting on time, or possible values (“codes”).

classmethod from_mapping(json_object)

Reads a mapping to recreate a instance of this class.

Return type:

Self

Parameters:

json_object (_UttrekksBeskrivelseDump)

get_totalcodes_dict()

Makes a dict from each codelist where a code for “totals” is included.

Keys being the name of the codelist, values being the code to put into categorical columns, that describes totals. This dict can be passed into the parameters “fillna_dict” and “grand_total” in the function “agg_all_combos” in the package ssb-fagfunksjoner.

Returns:

A dictionary with the codelist-names as keys, the total-codes as values.

Return type:

dict[str, str]

property headers: None

Deprecated attribute, Authinfo is not stored here anymore.

round_data(data, round_up=True)

Converts all decimal numbers to strings, with the correct number of decimals.

IMPORTANT: Rounds “real halves” (0.5) UP, instead of “to even numbers” like Python does by default. This is maybe the behaviour staticians are used to from Excel, SAS etc.

Parameters:

  • data (dict[str, pd.DataFrame]) – The data to validate in a dictionary of deltabell-names as keys and pandas-dataframes as values.

  • round_up (bool) – Default behaviour is rounding up like Excel or SAS. Setting this to False will instead use Python’s default “Round towards equal” / “Banker’s rounding”

Returns:

A dictionary in the same shape as sent in, but with dataframes altered to correct for rounding.

Return type:

dict[str, pd.DataFrame]

property subtables: dict[str, str]

Names and descriptions of the individual “table-parts” that needs to be sent in as different DataFrames.

property suppression: list[SuppressionCodeListType] | None

Details around extra columns which describe main column’s “prikking”, meaning their suppression-type.

property tableid: str

Originally the ID of the main table, which to get the Uttrekksbeskrivelse on.

property tablename: str

The name of the main table in Statbanken, not numbers, like the ID is.

property time_retrieved: str

Time of getting the Uttrekksbeskrivelse.

to_json(path=None)

Store a copy of the current state of the uttrekk-object as a json.

If path is provided, tries to write to it, otherwise will return a json-string for you to handle like you wish.

Parameters:

path (str) – if provided, will try to write a json to a local path

Returns:

If path is provided, tries to write a json to a file and returns nothing.

If path is not provided, returns the json-string for you to handle as you wish.

Return type:

None | str

to_mapping()

Create a mapping of this object that can be written as JSON.

Return type:

_UttrekksBeskrivelseDump

Parameters:

self (Self)

transferdata_template(dfs=None)

Get the shape the data should have to name the “deltabeller”.

If we didnt use a dictionary we would have to rely on the order of a list of “deltabeller”. Instead we chose to explicitly name the deltabller in this package, and make you check this after creation.

Parameters:

  • dfs (if provided, will try to use pandas dataframes sent in to populate the dict returned by the method.) – Send in one dataframe, several, a list of dataframes or similar. ORDER IS IMPORTANT make sure the result is what you expect.

  • Returns

  • -------

  • keys (A dictionary with correct)

  • passed. (but placeholders for where the dataframes should go if no Dataframes are)

  • in (A dict of dataframes as values if a list of Dataframes are sent)

  • parameters. (or dataframes as individual)

Return type:

dict[str, str] | dict[str, DataFrame]

validate(data, raise_errors=False, ignore_codes_not_in_data=False)

Uses the contents of itself to validate the data against.

All validation happens locally, so dont be afraid of any data being sent to statbanken using this method.

Parameters:

  • data (dict[str, pd.DataFrame]) – The data to validate in a dictionary of deltabell-names as keys and pandas-dataframes as values.

  • raise_errors (bool) – True/False based on if you want the method to raise its own errors or not.

  • ignore_codes_not_in_data (bool) – If set to True, will hide messages about codes in klass that are missing from the data.

Returns:

A dictionary of the errors the validation wants to raise.

Return type:

dict[str, ValueError]

Raises:

StatbankValidateError – if raise_errors is set to True and there are validation errors.

property variables: list[DelTabellType]

Metadata about the columns in the different table-parts.

class UttrekksBeskrivelseData(*, tableid, tablename, time_retrieved, subtables, variables, codelists, suppression)

Bases: object

Holds parsed data for StatbankUttrekksBeskrivelse.

Parameters:
time_retrieved

Time of getting the Uttrekksbeskrivelse

tableid

The ID of the main table.

tablename

The name of the main table in Statbanken.

subtables

Names and descriptions of the individual “table-parts” that needs to be sent in as different DataFrames.

variables

Metadata about the columns in the different table-parts.

codelists

Metadata about column-contents, like formatting on time, or possible values (“codes”).

suppression

Details around extra columns which describe main column’s “prikking”, meaning their suppression-type.

headers

Deprecated attribute. Authinfo not stored here anymore.

codelists: dict[str, KodelisteTypeParsed]
classmethod from_filbeskrivelse(filbeskrivelse)

Parses “filbeskrivelse” from Statbank API.

Return type:

Self

Parameters:

filbeskrivelse (FilBeskrivelseType)

classmethod from_mapping(json_object)

Reads a mapping to recreate a instance of this class.

Return type:

Self

Parameters:

json_object (_UttrekksBeskrivelseDump)

subtables: dict[str, str]
suppression: list[SuppressionCodeListType] | None
tableid: int
tablename: str
time_retrieved: datetime
variables: list[DelTabellType]

statbank.uttrekk_validations module

class StatbankUttrekkValidators

Bases: object

Split out from the main Uttrekk-class, this class contains all the validator-methods.

abstract property codelists: dict[str, KodelisteTypeParsed]

Metadata about column-contents, like formatting on time, or possible values (“codes”).

abstract property subtables: dict[str, str]

Names and descriptions of the individual “table-parts” that needs to be sent in as different DataFrames.

abstract property suppression: list[SuppressionCodeListType] | None

Details around extra columns which describe main column’s “prikking”, meaning their suppression-type.

abstract property variables: list[DelTabellType]

Metadata about the columns in the different table-parts.

exception StatbankValidateError

Bases: Exception

Use when raising errors stemming from the validators not running cleanly.

statbank.writable_netrc module

Modified version of tinynetrc.

class Netrc(filepath=None)

Bases: MutableMapping[str, NetrcRecord]

A mapping of a .netrc file, that can be used as a context manager, and save changes to disk.

Parameters:

filepath (Path | None)

filepath

Path where .netrc is stored.

machines

A dict storing netrc records.

property is_changed: bool

Check if changed from last save.

save()

Save changes to disk.

Return type:

None

Parameters:

self (Self)

class NetrcRecord(login, account, password)

Bases: object

Dataclass to store login info.

Parameters:

  • login (str)

  • account (str)

  • password (str)

account: str
login: str
password: str