pas.data_import

Attributes

`T`
`P`
`EXPECTED_HEADERS`

Classes

`Row`	Base class for protocol classes.
`ImportFile`	Provides a unified interface for both CSV and Excel files.
`HeaderValidationResult`

Functions

`preprocess_headers`(→ list[str])	Helper function to process headers using rename mapping.
`preprocess_csv_headers`(→ _typeshed.StrOrBytesPath)	Preprocesses a CSV file to rename specific headers to avoid issues
`validate_headers`(→ HeaderValidationResult)
`preprocess_excel_headers`(→ _typeshed.StrOrBytesPath)	Preprocess Excel headers using a context manager for temporary file
`match_expected_headers_or_fail`(→ None)
`with_open_excel_or_csv`(...)	Decorator to handle opening and parsing import files.
`import_commissions`(→ None)	Imports all data from commission file.

Module Contents

pas.data_import.T[source]

pas.data_import.P[source]

class pas.data_import.Row[source]

Bases: Protocol

Base class for protocol classes.

Protocol classes are defined as:

class Proto(Protocol):
    def meth(self) -> int:
        ...

Such classes are primarily used with static type checkers that recognize structural subtyping (static duck-typing).

For example:

class C:
    def meth(self) -> int:
        return 0

def func(x: Proto) -> int:
    return x.meth()

func(C())  # Passes static type check

See PEP 544 for details. Protocol classes decorated with @typing.runtime_checkable act as simple-minded runtime protocols that check only the presence of given attributes, ignoring their type signatures. Protocol classes can be generic, they are defined as:

class GenProto(Protocol[T]):
    def meth(self) -> T:
        ...

adress_anrede: str[source]

akademischer_titel: str[source]

anrede: str[source]

austritt_kommission: str[source]

bemerkungen: str[source]

beruf: str[source]

brief_anrede: str[source]

burgerort: str[source]

count: str[source]

e_mail_1: str[source]

e_mail_2: str[source]

eintritt_kommission: str[source]

fraktion: str[source]

geburtsdatum: str[source]

geschlecht: str[source]

id: str[source]

index: str[source]

nachname: str[source]

partei: str[source]

personalnummer: str[source]

privat_adresse: str[source]

privat_adresszusatz: str[source]

privat_ort: str[source]

privat_plz: str[source]

rolle_kommission: str[source]

rownumber: int[source]

spedition_kr_vorlagen: str[source]

telefon_geschaft: str[source]

telefon_mobile: str[source]

telefon_privat: str[source]

versand_adresse: str[source]

versand_adresszusatz: str[source]

versand_ort: str[source]

versand_plz: str[source]

versandart: str[source]

vertragsnummer: str[source]

vorname: str[source]

wahlkreis: str[source]

webseite: str[source]

zusatzinformationen: str[source]

pas.data_import.EXPECTED_HEADERS = ['adress_anrede', 'akademischer_titel', 'anrede', 'austritt_kommission', 'bemerkungen', 'beruf',...[source]

class pas.data_import.ImportFile(file: BinaryIO)[source]

Provides a unified interface for both CSV and Excel files.

ENCODINGS = ['utf-8', 'iso-8859-1'][source]

file[source]

rows: list[Any] = [][source]

_detect_type() → None[source]: Detect if file is CSV or Excel based on content.

_parse() → None[source]: Parse the file contents based on detected type.

_parse_csv() → None[source]

_parse_excel() → None[source]: Parse the file contents for excel files.

__enter__() → Self[source]

__exit__(exc_type: type[BaseException] | None, exc_val: BaseException | None, exc_tb: types.TracebackType | None) → None[source]

pas.data_import.preprocess_headers(headers: list[str], header_renames: dict[str, str]) → list[str][source]: Helper function to process headers using rename mapping.

pas.data_import.preprocess_csv_headers(csv_path_abs: _typeshed.StrOrBytesPath, expected: list[str] | None = None) → _typeshed.StrOrBytesPath[source]

Preprocesses a CSV file to rename specific headers to avoid issues with the CSV parser. Creates a temporary file with the modified headers. Renames:

“1. E-Mail” to “E_Mail_1” “2. E-Mail” to “E_Mail_2”

Returns:: Path to the temporary CSV file with preprocessed headers.

class pas.data_import.HeaderValidationResult[source]

is_valid: bool[source]

missing_headers: list[str][source]

unexpected_headers: list[str][source]

original_headers: list[str][source]

pas.data_import.validate_headers(current_headers: list[str], expected_headers: list[str]) → HeaderValidationResult[source]

pas.data_import.preprocess_excel_headers(excel_path: _typeshed.StrOrBytesPath, expected: list[str] | None = None) → _typeshed.StrOrBytesPath[source]

Preprocess Excel headers using a context manager for temporary file handling.

Args:: excel_path: Path to the input Excel file expected: Optional list of expected headers to validate against
Returns:: Path to the processed temporary file
Raises:: Exception: If header processing or validation fails

pas.data_import.match_expected_headers_or_fail(expected: Any, header_row: Any) → None[source]

pas.data_import.with_open_excel_or_csv(func: collections.abc.Callable[Ellipsis, T]) → collections.abc.Callable[Ellipsis, T][source]: Decorator to handle opening and parsing import files. Handles both CSV and Excel files, preprocessing headers as needed.

pas.data_import.import_commissions(import_file: ImportFile, session: sqlalchemy.orm.Session, commission_file_abs_path: str, **kwargs: Any) → None[source]: Imports all data from commission file.