helakit.nic

helakit.nic

NIC (National Identity Card) validation, decoding, and conversion.

NICBatchResult dataclass

NICBatchResult(results: list[ValidationResult], duplicates: dict[str, list[int]] = dict(), summary: NICSummary = (lambda: NICSummary(0, 0, 0, 0, 0, 0, 0))(), df: Any | None = None)

The outcome of validating a list / dataframe of NICs.

Attributes:

Name	Type	Description
results	list[ValidationResult]	One :class:ValidationResult per input row, in the same order as the input.
duplicates	dict[str, list[int]]	Mapping from canonical NIC (uppercased, V/X stripped) to the row indices it appeared at. Only entries with two or more indices are included.
summary	NICSummary	Roll-up counts.
df	Any | None	When the input was a pandas or polars DataFrame, this is a copy of that frame with helakit's per-row columns appended. None when the input was a list.

NICDecoded dataclass

NICDecoded(format: Literal['old', 'new'], dob: date, gender: Literal['male', 'female'], age: int, year: int, day_code: int, serial: int, check_digit: int, voting_eligible: bool | None)

Structured fields extracted from a valid NIC.

Attributes:

Name	Type	Description
format	Literal['old', 'new']	Either "old" (9 digits + V/X) or "new" (12 digits).
dob	date	Decoded date of birth.
gender	Literal['male', 'female']	Either "male" or "female", derived from the day-of-year encoding.
age	int	Age in completed years at the time of validation.
year	int	Full birth year.
day_code	int	Day-of-year encoding with the female 500 offset removed.
serial	int	Serial number assigned on the registration day.
check_digit	int	Final check digit (not currently verified — see :mod:helakit.nic._parse).
voting_eligible	bool | None	True if the old NIC ends in V, False if X, None for new-format NICs.

NICError

Bases: HelakitError

Base class for NIC-related errors raised by helakit.

NICFormatError

Bases: NICError

Raised when an input cannot be parsed as either NIC format.

Used by :func:helakit.nic.convert_nic because conversion has no sensible ValidationResult to return — failure must propagate as an exception.

NICSummary dataclass

NICSummary(total: int, valid: int, invalid: int, duplicate_groups: int, duplicate_rows: int, dob_mismatches: int, gender_mismatches: int)

Aggregate counts for a batch validation run.

Attributes:

Name	Type	Description
total	int	Number of input rows processed.
valid	int	Rows whose NIC passed structural validation.
invalid	int	Rows that failed structural validation.
duplicate_groups	int	Number of distinct NICs that appear in more than one row (after canonicalisation that strips V/X suffixes).
duplicate_rows	int	Total rows participating in any duplicate group.
dob_mismatches	int	Rows where the supplied DOB differed from the NIC-decoded DOB (only counted when both were available).
gender_mismatches	int	Same idea for gender.

convert_nic

convert_nic(value: str, *, century: int = ...) -> str

convert_nic(value: list[str] | tuple[str, ...], *, century: int = ..., errors: ErrorMode = ...) -> list[str | None]

convert_nic(value: Any, *, century: int = ..., nic_col: str | None = ..., errors: ErrorMode = ..., error_col: str | None = ...) -> Any

convert_nic(value: Any, *, century: int = DEFAULT_OLD_NIC_CENTURY, nic_col: str | None = None, errors: ErrorMode = 'raise', error_col: str | None = None) -> Any

Convert an old-format NIC to the new 12-digit format.

Parameters:

Name	Type	Description	Default
value	Any	Either a single NIC string, a list of strings, a pandas or polars Series, or a pandas/polars DataFrame. For Series input the function returns a Series of the same length, preserving index/name. For DataFrame input nic_col specifies which column to convert; the function returns a copy of the frame with a new nic_converted column added.	required
century	int	Century to assume for two-digit years on old NICs.	DEFAULT_OLD_NIC_CENTURY
nic_col	str | None	Required for tabular input.	None
errors	ErrorMode	How to handle individual values that cannot be converted. "raise" (default) propagates :class:NICFormatError on the first bad value — same as pandas strict mode. "coerce" replaces bad values with None so a single malformed row no longer fails the whole batch. "ignore" leaves the original input through untouched. Scalar input always raises regardless of this setting.	'raise'
error_col	str | None	Column name for per-row error messages (DataFrame input only). When supplied, the returned frame gets an extra column with the failure message or None for rows that converted cleanly. Implies errors="coerce" if errors is left at the default of "raise".	None

Returns:

Type	Description
Any	The same shape as the input — string for string, list for list,
Any	DataFrame for DataFrame.

Raises:

Type	Description
NICFormatError	If a value cannot be parsed (e.g. wrong length, non-numeric content) and errors="raise". New-format input passes through unchanged.
InvalidInputError	For unsupported input types or invalid errors values.

is_valid_nic

is_valid_nic(value: str, *, format: FormatHint = 'any') -> bool

Return True if value is a structurally valid NIC.

Scalar-only — for batch checks use :func:validate_nic and inspect each ValidationResult.

Raises:

Type	Description
InvalidInputError	If value is not a string.

validate_nic

validate_nic(data: str, *, format: FormatHint = ..., century: int = ...) -> ValidationResult

validate_nic(data: list[str] | list[dict[str, Any]] | tuple[str, ...], *, format: FormatHint = ..., nic_col: str | None = ..., dob_col: str | None = ..., gender_col: str | None = ..., century: int = ..., errors: BatchErrorMode = ...) -> NICBatchResult

validate_nic(data: Any, *, format: FormatHint = ..., nic_col: str | None = ..., dob_col: str | None = ..., gender_col: str | None = ..., century: int = ..., errors: BatchErrorMode = ...) -> NICBatchResult

validate_nic(data: Any, *, format: FormatHint = 'any', nic_col: str | None = None, dob_col: str | None = None, gender_col: str | None = None, century: int = DEFAULT_OLD_NIC_CENTURY, errors: BatchErrorMode = 'raise') -> ValidationResult | NICBatchResult

Validate one or many Sri Lankan NIC numbers.

Parameters:

Name	Type	Description	Default
data	Any	A single NIC string, a list[str], a list[dict], a pandas DataFrame, or a polars DataFrame.	required
format	FormatHint	Restrict to "old" or "new" only. "any" (default) accepts both.	'any'
nic_col	str | None	Column name holding NICs (required for tabular input).	None
dob_col	str | None	Column name holding dates of birth. When supplied each row is cross-checked and the per-row result records whether the decoded DOB matched.	None
gender_col	str | None	Column name holding gender (M/F/Male/ Female, case-insensitive).	None
century	int	Century to assume for two-digit years on old NICs. Defaults to 1900.	DEFAULT_OLD_NIC_CENTURY
errors	BatchErrorMode	Batch-only. "raise" (default) propagates :class:InvalidInputError if any cross-check dob or gender value is unparseable, matching strict pandas semantics. "coerce" records the failure as a per-row error in :attr:ValidationResult.errors (and the nic_errors column on DataFrame output) so a single malformed row no longer aborts the whole batch.	'raise'

Returns:

Name	Type	Description
A	ValidationResult | NICBatchResult	class:ValidationResult for scalar input, or a
	ValidationResult | NICBatchResult	class:NICBatchResult for any iterable input.

Raises:

Type	Description
InvalidInputError	For unsupported input types, an invalid errors value, or unparseable gender / DOB values when errors="raise".