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1225 | class Process:
"""Process utility class."""
# ------------------------------------------------------------------
# Class variables.
# ------------------------------------------------------------------
ERROR_01_901: ClassVar[str] = "01.901 Issue (p_i): Document rejected because of unknown file extension='{extension}'."
ERROR_01_903: ClassVar[str] = (
"01.903 Issue (p_i): Error with fitz.open() processing of file '{file_name}' " + "- RuntimeError - error: '{error_msg}'"
)
ERROR_21_901: ClassVar[str] = (
"21.901 Issue (p_2_i): Processing file '{full_name}' with pdf2image failed - PDFPageCountError - "
+ "error type: '{error_type}' - error: '{error_msg}'"
)
ERROR_31_902: ClassVar[str] = (
"31.902 Issue (n_2_p): The file '{full_name}' cannot be converted to an " + "'PDF' document - FileNotFoundError"
)
ERROR_31_903: ClassVar[str] = (
"31.903 Issue (n_2_p): The file '{full_name}' cannot be converted to an " + "'PDF' document - RuntimeError - error: '{error_msg}'"
)
ERROR_31_911: ClassVar[str] = "31.911 Issue (n_2_p): The pdf document {full_name} for PDFlib TET is an empty file"
ERROR_41_901: ClassVar[str] = (
"41.901 Issue (ocr): Converting the file '{full_name}' with Tesseract OCR failed - " + "RuntimeError - error: '{error_msg}'"
)
ERROR_41_911: ClassVar[str] = "41.911 Issue (ocr): Tesseract OCR has created an empty pdf file from the file {full_name}"
ERROR_51_901: ClassVar[str] = (
"51.901 Issue (tet): Opening document '{full_name}' - " + "error no: '{error_no}' - api: '{api_name}' - error: '{error_msg}'"
)
ERROR_61_901: ClassVar[str] = "61.901 Issue (s_p_j): Parsing the file '{full_name}' failed - FileNotFoundError"
ERROR_71_901: ClassVar[str] = "71.901 Issue (tkn): Tokenizing the file '{full_name}' failed - FileNotFoundError"
PANDOC_PDF_ENGINE_LULATEX: ClassVar[str] = "lulatex"
PANDOC_PDF_ENGINE_XELATEX: ClassVar[str] = "xelatex"
# ------------------------------------------------------------------
# Initialise the instance.
# ------------------------------------------------------------------
def __init__(self) -> None:
"""Initialise the instance."""
try:
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
except AttributeError:
dcr_core.core_glob.initialise_logger()
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
self._document_id: int = 0
self._full_name_in = ""
self._full_name_in_directory = ""
self._full_name_in_extension = ""
self._full_name_in_extension_int = ""
self._full_name_in_next_step = ""
self._full_name_in_pandoc = ""
self._full_name_in_parser_line = ""
self._full_name_in_parser_page = ""
self._full_name_in_parser_word = ""
self._full_name_in_pdf2image = ""
self._full_name_in_pdflib = ""
self._full_name_in_stem_name = ""
self._full_name_in_tesseract = ""
self._full_name_in_tokenizer_line = ""
self._full_name_in_tokenizer_page = ""
self._full_name_in_tokenizer_word = ""
self._full_name_orig = ""
self._is_delete_auxiliary_files = False
self._is_pandoc = False
self._is_pdf2image = False
self._is_tesseract = False
self._is_verbose = False
self._language_pandoc: str = ""
self._language_spacy: str = ""
self._language_tesseract: str = ""
self._no_lines_footer: int = 0
self._no_lines_header: int = 0
self._no_lines_toc: int = 0
self._no_pdf_pages: int = 0
self._exist = True
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# ------------------------------------------------------------------
# Check the document by the file extension and determine further
# processing.
# ------------------------------------------------------------------
def _document_check_extension(self):
"""Document processing control.
Check the document by the file extension and determine further
processing.
Raises:
RuntimeError: ERROR_01_903
"""
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
if self._full_name_in_extension_int == dcr_core.core_glob.FILE_TYPE_PDF:
try:
if bool("".join([page.get_text() for page in fitz.open(self._full_name_in)])):
self._full_name_in_pdflib = self._full_name_in
else:
self._is_pdf2image = True
self._is_tesseract = True
self._full_name_in_pdf2image = self._full_name_in
except RuntimeError as exc:
raise RuntimeError(
Process.ERROR_01_903.replace("{file_name}", self._full_name_in).replace("{error_msg}", str(exc)),
) from exc
elif self._full_name_in_extension_int in dcr_core.core_glob.FILE_TYPE_PANDOC:
self._is_pandoc = True
self._full_name_in_pandoc = self._full_name_in
elif self._full_name_in_extension_int in dcr_core.core_glob.FILE_TYPE_TESSERACT:
self._is_tesseract = True
self._full_name_in_tesseract = self._full_name_in
else:
raise RuntimeError(Process.ERROR_01_901.replace("{extension}", self._full_name_in_extension_int))
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# -----------------------------------------------------------------------------
# Delete the given auxiliary file.
# -----------------------------------------------------------------------------
def _document_delete_auxiliary_file(self, full_name: str) -> None:
"""Delete the given auxiliary file.
Args:
full_name (str): File name.
"""
if not self._is_delete_auxiliary_files:
return
# Don't remove the base document !!!
if full_name == self._full_name_in:
return
if os.path.isfile(full_name):
os.remove(full_name)
dcr_core.core_utils.progress_msg(self._is_verbose, f"Auxiliary file '{full_name}' deleted")
# ------------------------------------------------------------------
# Initialize the document recognition process.
# ------------------------------------------------------------------
def _document_init(self) -> None:
"""Initialize the document recognition process."""
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
self._document_id: int = 0
self._full_name_in: str = ""
self._full_name_in_directory: str = ""
self._full_name_in_extension: str = ""
self._full_name_in_extension_int: str = ""
self._full_name_in_next_step: str = ""
self._full_name_in_pandoc: str = ""
self._full_name_in_parser_line: str = ""
self._full_name_in_parser_page: str = ""
self._full_name_in_parser_word: str = ""
self._full_name_in_pdf2image: str = ""
self._full_name_in_pdflib: str = ""
self._full_name_in_stem_name: str = ""
self._full_name_in_tesseract: str = ""
self._full_name_in_tokenizer_line: str = ""
self._full_name_in_tokenizer_page: str = ""
self._full_name_in_tokenizer_word: str = ""
self._full_name_orig: str = ""
self._is_pandoc: bool = False
self._is_pdf2image: bool = False
self._is_tesseract: bool = False
self._language_pandoc: str = ""
self._language_spacy: str = ""
self._language_tesseract: str = ""
self._no_lines_footer: int = 0
self._no_lines_header: int = 0
self._no_lines_toc: int = 0
self._no_pdf_pages: int = 0
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# ------------------------------------------------------------------
# Convert the document to PDF format using Pandoc.
# ------------------------------------------------------------------
def _document_pandoc(self):
"""Convert the document to PDF format using Pandoc.
Raises:
RuntimeError: Any Pandoc issue.
"""
if self._is_pandoc:
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_utils.progress_msg(self._is_verbose, f"Start processing Pandoc {self._full_name_in_pandoc}")
self._full_name_in_pdflib = dcr_core.core_utils.get_full_name_from_components(
self._full_name_in_directory, self._full_name_in_stem_name, dcr_core.core_glob.FILE_TYPE_PDF
)
return_code, error_msg = Process.pandoc(
self._full_name_in_pandoc,
self._full_name_in_pdflib,
self._language_pandoc,
)
if return_code != "ok":
raise RuntimeError(error_msg)
self._document_delete_auxiliary_file(self._full_name_in_pandoc)
dcr_core.core_utils.progress_msg(self._is_verbose, f"End processing Pandoc {self._full_name_in_pdflib}")
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# ------------------------------------------------------------------
# Extract the text for all granularities from the PDF document.
# ------------------------------------------------------------------
def _document_parser(self):
"""Extract the text for all granularities from the PDF document."""
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
self._full_name_in_tokenizer_line = dcr_core.core_utils.get_full_name_from_components(
self._full_name_in_directory,
self._full_name_in_stem_name + "." + dcr_core.cls_nlp_core.NLPCore.LINE_XML_VARIATION + dcr_core.core_glob.FILE_TYPE_JSON,
)
self._full_name_in_tokenizer_page = dcr_core.core_utils.get_full_name_from_components(
self._full_name_in_directory,
self._full_name_in_stem_name + "." + dcr_core.cls_nlp_core.NLPCore.PAGE_XML_VARIATION + dcr_core.core_glob.FILE_TYPE_JSON,
)
self._full_name_in_tokenizer_word = dcr_core.core_utils.get_full_name_from_components(
self._full_name_in_directory,
self._full_name_in_stem_name + "." + dcr_core.cls_nlp_core.NLPCore.WORD_XML_VARIATION + dcr_core.core_glob.FILE_TYPE_JSON,
)
for (
full_name_in_parser,
full_name_in_tokenizer,
tetml_type,
is_parsing_line,
is_parsing_page,
is_parsing_word,
) in (
(
self._full_name_in_parser_line,
self._full_name_in_tokenizer_line,
dcr_core.cls_nlp_core.NLPCore.TETML_TYPE_LINE,
True,
False,
False,
),
(
self._full_name_in_parser_page,
self._full_name_in_tokenizer_page,
dcr_core.cls_nlp_core.NLPCore.TETML_TYPE_PAGE,
False,
True,
False,
),
(
self._full_name_in_parser_word,
self._full_name_in_tokenizer_word,
dcr_core.cls_nlp_core.NLPCore.TETML_TYPE_WORD,
False,
False,
True,
),
):
if (
is_parsing_page
and not dcr_core.core_glob.setup.is_tetml_page
or is_parsing_word
and not dcr_core.core_glob.setup.is_tetml_word
):
continue
self._document_parser_tetml_type(
full_name_in_parser,
full_name_in_tokenizer,
tetml_type,
is_parsing_line,
is_parsing_page,
is_parsing_word,
)
if is_parsing_line:
self._no_lines_footer = dcr_core.core_glob.line_type_header_footer.no_lines_footer
self._no_lines_header = dcr_core.core_glob.line_type_header_footer.no_lines_header
self._no_lines_toc = dcr_core.core_glob.line_type_toc.no_lines_toc
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# ------------------------------------------------------------------
# Extract the text for a specific granularity from the PDF document.
# ------------------------------------------------------------------
def _document_parser_tetml_type(
self,
full_name_in_parser,
full_name_in_tokenizer,
tetml_type,
is_parsing_line,
is_parsing_page,
is_parsing_word,
):
"""XML Parser processing.
Extract the text for a specific granularity from the PDF
document.
Raises:
RuntimeError: Any parser issue.
"""
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_utils.progress_msg(self._is_verbose, f"Start processing {tetml_type} {full_name_in_parser}")
dcr_core.core_glob.setup.is_parsing_line = is_parsing_line
dcr_core.core_glob.setup.is_parsing_page = is_parsing_page
dcr_core.core_glob.setup.is_parsing_word = is_parsing_word
return_code, error_msg = Process.parser(
full_name_in_parser,
full_name_in_tokenizer,
self._no_pdf_pages,
self._document_id,
self._full_name_orig,
)
if return_code != "ok":
raise RuntimeError(error_msg)
self._document_delete_auxiliary_file(full_name_in_parser)
dcr_core.core_utils.progress_msg(self._is_verbose, f"End processing {tetml_type} {full_name_in_tokenizer}")
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# ------------------------------------------------------------------
# Convert the PDF document to an image file using pdf2image.
# ------------------------------------------------------------------
def _document_pdf2image(self):
"""Convert the PDF document to an image file using pdf2image.
Raises:
RuntimeError: Any pdf2image issue.
"""
if self._is_pdf2image:
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_utils.progress_msg(self._is_verbose, f"Start processing pdf2image {self._full_name_in_pdf2image}")
self._full_name_in_tesseract = dcr_core.core_utils.get_full_name_from_components(
self._full_name_in_directory,
self._full_name_in_stem_name
+ "_[0-9]*."
+ (
dcr_core.core_glob.FILE_TYPE_PNG
if dcr_core.core_glob.setup.pdf2image_type == dcr_core.cls_setup.Setup.PDF2IMAGE_TYPE_PNG
else dcr_core.core_glob.FILE_TYPE_JPEG
),
)
return_code, error_msg, _ = Process.pdf2image(
self._full_name_in_pdf2image,
)
if return_code != "ok":
raise RuntimeError(error_msg)
self._document_delete_auxiliary_file(self._full_name_in_pdf2image)
dcr_core.core_utils.progress_msg(self._is_verbose, f"End processing pdf2image {self._full_name_in_tesseract}")
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# ------------------------------------------------------------------
# Extract the text and metadata from a PDF document to an XML file.
# ------------------------------------------------------------------
def _document_pdflib(self):
"""Extract the text and metadata from a PDF document to an XML file.
Raises:
RuntimeError: Any PDFlib TET issue.
"""
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_utils.progress_msg(self._is_verbose, f"Start processing PDFlib TET {self._full_name_in_pdflib}")
# noinspection PyUnresolvedReferences
self._no_pdf_pages = len(PyPDF2.PdfReader(self._full_name_in_pdflib).pages)
if self._no_pdf_pages == 0:
raise RuntimeError(f"The number of pages of the PDF document {self._full_name_in_pdflib} cannot be determined")
self._full_name_in_parser_line = dcr_core.core_utils.get_full_name_from_components(
self._full_name_in_directory,
self._full_name_in_stem_name + "." + dcr_core.cls_nlp_core.NLPCore.LINE_XML_VARIATION + dcr_core.core_glob.FILE_TYPE_XML,
)
return_code, error_msg = Process.pdflib(
full_name_in=self._full_name_in_pdflib,
full_name_out=self._full_name_in_parser_line,
document_opt_list=dcr_core.cls_nlp_core.NLPCore.LINE_TET_DOCUMENT_OPT_LIST,
page_opt_list=dcr_core.cls_nlp_core.NLPCore.LINE_TET_PAGE_OPT_LIST,
)
if return_code != "ok":
raise RuntimeError(error_msg)
dcr_core.core_utils.progress_msg(self._is_verbose, f"End processing PDFlib TET {self._full_name_in_parser_line}")
if dcr_core.core_glob.setup.is_tetml_page:
self._full_name_in_parser_page = dcr_core.core_utils.get_full_name_from_components(
self._full_name_in_directory,
self._full_name_in_stem_name + "." + dcr_core.cls_nlp_core.NLPCore.PAGE_XML_VARIATION + dcr_core.core_glob.FILE_TYPE_XML,
)
return_code, error_msg = Process.pdflib(
full_name_in=self._full_name_in_pdflib,
full_name_out=self._full_name_in_parser_page,
document_opt_list=dcr_core.cls_nlp_core.NLPCore.PAGE_TET_DOCUMENT_OPT_LIST,
page_opt_list=dcr_core.cls_nlp_core.NLPCore.PAGE_TET_PAGE_OPT_LIST,
)
if return_code != "ok":
raise RuntimeError(error_msg)
dcr_core.core_utils.progress_msg(self._is_verbose, f"End processing PDFlib TET {self._full_name_in_parser_page}")
if dcr_core.core_glob.setup.is_tetml_word:
self._full_name_in_parser_word = dcr_core.core_utils.get_full_name_from_components(
self._full_name_in_directory,
self._full_name_in_stem_name + "." + dcr_core.cls_nlp_core.NLPCore.WORD_XML_VARIATION + dcr_core.core_glob.FILE_TYPE_XML,
)
return_code, error_msg = Process.pdflib(
full_name_in=self._full_name_in_pdflib,
full_name_out=self._full_name_in_parser_word,
document_opt_list=dcr_core.cls_nlp_core.NLPCore.WORD_TET_DOCUMENT_OPT_LIST,
page_opt_list=dcr_core.cls_nlp_core.NLPCore.WORD_TET_PAGE_OPT_LIST,
)
if return_code != "ok":
raise RuntimeError(error_msg)
dcr_core.core_utils.progress_msg(self._is_verbose, f"End processing PDFlib TET {self._full_name_in_parser_word}")
self._document_delete_auxiliary_file(self._full_name_in_pdflib)
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# ------------------------------------------------------------------
# Convert one or more image files to a PDF file using Tesseract OCR.
# ------------------------------------------------------------------
def _document_tesseract(self):
"""Process the document with Tesseract OCR.
Convert one or more image files to a PDF file using Tesseract
OCR.
Raises:
RuntimeError: Any Tesseract OCR issue.
"""
if self._is_tesseract:
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_utils.progress_msg(self._is_verbose, f"Start processing Tesseract OCR {self._full_name_in_tesseract}")
if self._is_pdf2image:
self._full_name_in_stem_name += "_0"
self._full_name_in_pdflib = dcr_core.core_utils.get_full_name_from_components(
self._full_name_in_directory, self._full_name_in_stem_name, dcr_core.core_glob.FILE_TYPE_PDF
)
return_code, error_msg, children = Process.tesseract(
self._full_name_in_tesseract,
self._full_name_in_pdflib,
self._language_tesseract,
)
if return_code != "ok":
raise RuntimeError(error_msg)
# noinspection PyUnresolvedReferences
self._no_pdf_pages = len(PyPDF2.PdfReader(self._full_name_in_pdflib).pages)
if self._no_pdf_pages == 0:
raise RuntimeError(f"The number of pages of the PDF document {self._full_name_in_pdflib} cannot be determined")
for child in children:
self._document_delete_auxiliary_file(child)
dcr_core.core_utils.progress_msg(self._is_verbose, f"End processing Tesseract OCR {self._full_name_in_pdflib}")
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# ------------------------------------------------------------------
# Convert the PDF document to an image file using pdf2image.
# ------------------------------------------------------------------
def _document_tokenizer(self) -> None:
"""Tokenize the document with spaCy.
Raises:
RuntimeError: Any spaCy issue.
"""
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_utils.progress_msg(self._is_verbose, f"Start processing spaCy {self._full_name_in_tokenizer_line}")
try:
dcr_core.core_glob.tokenizer_spacy.exists()
except AttributeError:
dcr_core.core_glob.tokenizer_spacy = dcr_core.cls_tokenizer_spacy.TokenizerSpacy()
self._full_name_in_next_step = dcr_core.core_utils.get_full_name_from_components(
self._full_name_in_directory,
self._full_name_in_stem_name + ".line_token." + dcr_core.core_glob.FILE_TYPE_JSON,
)
return_code, error_msg = Process.tokenizer(
full_name_in=self._full_name_in_tokenizer_line,
full_name_out=self._full_name_in_next_step,
pipeline_name=self._language_spacy,
document_id=self._document_id,
full_name_orig=self._full_name_orig,
no_lines_footer=self._no_lines_footer,
no_lines_header=self._no_lines_header,
no_lines_toc=self._no_lines_toc,
)
if return_code != "ok":
raise RuntimeError(error_msg)
self._document_delete_auxiliary_file(self._full_name_in_tokenizer_line)
dcr_core.core_utils.progress_msg(self._is_verbose, f"End processing spaCy {self._full_name_in_next_step}")
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# ------------------------------------------------------------------
# Document content recognition for a specific file.
# ------------------------------------------------------------------
def document(
self,
full_name_in: str,
document_id: int = None,
full_name_orig: str = None,
is_delete_auxiliary_files: bool = None,
is_verbose: bool = None,
language_pandoc: str = None,
language_spacy: str = None,
language_tesseract: str = None,
output_directory: str = None,
) -> None:
"""Document content recognition for a specific file.
This method extracts the document content structure from a
given document and stores it in JSON format. For this purpose,
all non-pdf documents and all scanned pdf documents are first
converted into a searchable pdf format. Depending on the file
format, the tools Pandoc, pdf2image or Tesseract OCR are used
for this purpose. PDFlib TET then extracts the text and metadata
from the searchable pdf file and makes them available in XML format.
spaCY generates qualified tokens from the document text, and these
token data are then made available together with the metadata in a
JSON format.
Args:
full_name_in (str):
Full file name of the document file.
document_id (int, optional):
Document identification.
Defaults to -1 i.e. no document identification.
full_name_orig (str, optional):
Original full file name.
Defaults to the full file name of the document file.
is_delete_auxiliary_files (bool, optional):
Delete the auxiliary files after a successful processing step.
Defaults to parameter `delete_auxiliary_files` in `setup.cfg`.
is_verbose (bool, optional):
Display progress messages for processing.
Defaults to parameter `verbose` in `setup.cfg`.
language_pandoc (str, optional):
Pandoc language code.
Defaults to English.
language_spacy (str, optional):
spaCy language code.
Defaults to English transformer pipeline (roberta-base)..
language_tesseract (str, optional):
Tesseract OCR language code.
Defaults to English.
output_directory (str, optional):
Directory for the flat files to be created.
Defaults to the directory of the document file.
Raises:
RuntimeError: Any issue from Pandoc, pdf2image, PDFlib TET, spaCy, or Tesseract OCR.
"""
# Initialise the logging functionality.
dcr_core.core_glob.initialise_logger()
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_glob.logger.debug("param full_name_in=%s", full_name_in)
dcr_core.core_glob.logger.debug("param document_id =%i", document_id)
self._document_init()
self._document_id = document_id if document_id else -1
self._full_name_in = full_name_in
self._full_name_orig = full_name_orig if full_name_orig else full_name_in
self._language_pandoc = language_pandoc if language_pandoc else dcr_core.cls_nlp_core.NLPCore.LANGUAGE_PANDOC_DEFAULT
self._language_spacy = language_spacy if language_spacy else dcr_core.cls_nlp_core.NLPCore.LANGUAGE_SPACY_DEFAULT
self._language_tesseract = language_tesseract if language_tesseract else dcr_core.cls_nlp_core.NLPCore.LANGUAGE_TESSERACT_DEFAULT
dcr_core.core_glob.logger.debug("param full_name_orig =%s", self._full_name_orig)
dcr_core.core_glob.logger.debug("param language_pandoc =%s", self._language_pandoc)
dcr_core.core_glob.logger.debug("param language_spacy =%s", self._language_spacy)
dcr_core.core_glob.logger.debug("param language_tesseract=%s", self._language_tesseract)
# Load the configuration parameters.
dcr_core.core_glob.setup = dcr_core.cls_setup.Setup()
self._is_delete_auxiliary_files = (
is_delete_auxiliary_files if is_delete_auxiliary_files is not None else dcr_core.core_glob.setup.is_delete_auxiliary_files
)
self._is_verbose = is_verbose if is_verbose is not None else dcr_core.core_glob.setup.is_verbose
dcr_core.core_utils.progress_msg(self._is_verbose, f"Start processing document file {self._full_name_orig}")
dcr_core.core_utils.progress_msg(self._is_verbose, f"Language key Pandoc {self._language_pandoc}")
dcr_core.core_utils.progress_msg(self._is_verbose, f"Language key spaCy {self._language_spacy}")
dcr_core.core_utils.progress_msg(self._is_verbose, f"Language key Tesseract OCR {self._language_tesseract}")
(
full_name_in_directory,
self._full_name_in_stem_name,
self._full_name_in_extension,
) = dcr_core.core_utils.get_components_from_full_name(self._full_name_in)
self._full_name_in_directory = output_directory if output_directory is not None else full_name_in_directory
self._full_name_in_extension_int = (
self._full_name_in_extension.lower() if self._full_name_in_extension else self._full_name_in_extension
)
self._document_check_extension()
self._document_pandoc()
self._document_pdf2image()
self._document_tesseract()
self._document_pdflib()
self._document_parser()
self._document_tokenizer()
dcr_core.core_utils.progress_msg(self._is_verbose, f"End processing document file {self._full_name_orig}")
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
# ------------------------------------------------------------------
# Converting a Non-PDF file to a PDF file.
# ------------------------------------------------------------------
@classmethod
def pandoc(
cls,
full_name_in: str,
full_name_out: str,
language_pandoc: str,
) -> tuple[str, str]:
"""Convert a Non-PDF file to a PDF file.
The following file formats are converted into
PDF format here with the help of Pandoc:
- csv - comma-separated values
- docx - Office Open XML
- epub - e-book file format
- html - HyperText Markup Language
- odt - Open Document Format for Office Applications
- rst - reStructuredText (RST
- rtf - Rich Text Format
Args:
full_name_in (str):
The directory name and file name of the input file.
full_name_out (str):
The directory name and file name of the output file.
language_pandoc (str):
The Pandoc name of the document language.
Returns:
tuple[str, str]:
("ok", "") if the processing has been completed successfully,
otherwise a corresponding error code and error message.
"""
try:
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
except AttributeError:
dcr_core.core_glob.initialise_logger()
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_glob.logger.debug("param full_name_in =%s", full_name_in)
dcr_core.core_glob.logger.debug("param full_name_out =%s", full_name_out)
dcr_core.core_glob.logger.debug("param language_pandoc=%s", language_pandoc)
# Convert the document
extra_args = [
f"--pdf-engine={Process.PANDOC_PDF_ENGINE_XELATEX}",
"-V",
f"lang:{language_pandoc}",
]
try:
pypandoc.convert_file(
full_name_in,
dcr_core.core_glob.FILE_TYPE_PDF,
extra_args=extra_args,
outputfile=full_name_out,
)
if len(PyPDF2.PdfReader(full_name_out).pages) == 0:
error_msg = Process.ERROR_31_911.replace("{full_name}", full_name_out)
dcr_core.core_glob.logger.debug("return =%s", (error_msg[:6], error_msg))
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return error_msg[:6], error_msg
except FileNotFoundError:
error_msg = Process.ERROR_31_902.replace("{full_name}", full_name_in)
dcr_core.core_glob.logger.debug("return =%s", (error_msg[:6], error_msg))
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return error_msg[:6], error_msg
except RuntimeError as err:
error_msg = Process.ERROR_31_903.replace("{full_name}", full_name_in).replace("{error_msg}", str(err))
dcr_core.core_glob.logger.debug("return =%s", (error_msg[:6], error_msg))
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return error_msg[:6], error_msg
dcr_core.core_glob.logger.debug("return =%s", dcr_core.core_glob.RETURN_OK)
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return dcr_core.core_glob.RETURN_OK
# ------------------------------------------------------------------
# Extracting the text from the PDF document.
# ------------------------------------------------------------------
@classmethod
def parser(
cls,
full_name_in: str,
full_name_out: str,
no_pdf_pages: int,
document_id: int = -1,
full_name_orig: str = dcr_core.core_glob.INFORMATION_NOT_YET_AVAILABLE,
) -> tuple[str, str]:
"""Extract the text from the PDF document.
From the line-oriented XML output file of PDFlib TET,
the text and relevant metadata are extracted with the
help of an XML parser and stored in a JSON file.
Args:
full_name_in (str):
The directory name and file name of the input file.
full_name_out (str):
The directory name and file name of the output file.
no_pdf_pages (int):
Total number of PDF pages.
document_id (int, optional):
The identification number of the document.
Defaults to -1.
full_name_orig (str, optional):
The file name of the originating document.
Defaults to dcr_core.core_glob.INFORMATION_NOT_YET_AVAILABLE.
Returns:
tuple[str, str]:
("ok", "") if the processing has been completed successfully,
otherwise a corresponding error code and error message.
"""
try:
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
except AttributeError:
dcr_core.core_glob.initialise_logger()
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_glob.logger.debug("param document_id =%i", document_id)
dcr_core.core_glob.logger.debug("param full_name_orig=%s", full_name_orig)
dcr_core.core_glob.logger.debug("param full_name_in =%s", full_name_in)
dcr_core.core_glob.logger.debug("param full_name_out =%s", full_name_out)
dcr_core.core_glob.logger.debug("param no_pdf_pages =%i", no_pdf_pages)
try:
# Create the Element tree object
tree = defusedxml.ElementTree.parse(full_name_in)
# Get the root Element
root = tree.getroot()
dcr_core.core_glob.text_parser = dcr_core.cls_text_parser.TextParser()
for child in root:
child_tag = child.tag[dcr_core.cls_nlp_core.NLPCore.PARSE_ELEM_FROM :]
match child_tag:
case dcr_core.cls_nlp_core.NLPCore.PARSE_ELEM_DOCUMENT:
dcr_core.core_glob.text_parser.parse_tag_document(
directory_name=os.path.dirname(full_name_in),
document_id=document_id,
environment_variant=dcr_core.core_glob.setup.environment_variant,
file_name_curr=os.path.basename(full_name_in),
file_name_next=full_name_out,
file_name_orig=full_name_orig,
no_pdf_pages=no_pdf_pages,
parent=child,
parent_tag=child_tag,
)
case dcr_core.cls_nlp_core.NLPCore.PARSE_ELEM_CREATION:
pass
except FileNotFoundError:
error_msg = Process.ERROR_61_901.replace("{full_name}", full_name_in)
dcr_core.core_glob.logger.debug("return =%s", (error_msg[:6], error_msg))
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return error_msg[:6], error_msg
dcr_core.core_glob.logger.debug("return =%s", dcr_core.core_glob.RETURN_OK)
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return dcr_core.core_glob.RETURN_OK
# ------------------------------------------------------------------
# Converting a scanned PDF file to a set of image files.
# ------------------------------------------------------------------
@classmethod
def pdf2image(
cls,
full_name_in: str,
) -> tuple[str, str, list[tuple[str, str]]]:
"""Convert a scanned PDF file to a set of image files.
To extract the text from a scanned PDF document, it must
first be converted into one or more image files, depending
on the number of pages. Then these image files are converted
into a normal PDF document with the help of an OCR programme.
The input file for this method must be a scanned PDF document,
which is then converted into image files with the help of PDF2Image.
Args:
full_name_in (str):
The directory name and file name of the input file.
Returns:
tuple[str, str, list[tuple[str,str]]]:
("ok", "", [...]) if the processing has been completed successfully,
otherwise a corresponding error code and error message.
"""
try:
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
except AttributeError:
dcr_core.core_glob.initialise_logger()
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_glob.logger.debug("param full_name_in=%s", full_name_in)
try:
images = pdf2image.convert_from_path(full_name_in)
children: list[tuple[str, str]] = []
no_children = 0
directory_name = os.path.dirname(full_name_in)
stem_name = os.path.splitext(os.path.basename(full_name_in))[0]
try:
os.remove(
dcr_core.core_utils.get_full_name_from_components(
directory_name,
stem_name
+ "_*."
+ (
dcr_core.core_glob.FILE_TYPE_PNG
if dcr_core.core_glob.setup.pdf2image_type == dcr_core.cls_setup.Setup.PDF2IMAGE_TYPE_PNG
else dcr_core.core_glob.FILE_TYPE_JPEG
),
)
)
except OSError:
pass
# Store the image pages
for img in images:
no_children += 1
file_name_next = (
stem_name
+ "_"
+ str(no_children)
+ "."
+ (
dcr_core.core_glob.FILE_TYPE_PNG
if dcr_core.core_glob.setup.pdf2image_type == dcr_core.cls_setup.Setup.PDF2IMAGE_TYPE_PNG
else dcr_core.core_glob.FILE_TYPE_JPEG
)
)
full_name_next = dcr_core.core_utils.get_full_name_from_components(
directory_name,
file_name_next,
)
img.save(
full_name_next,
dcr_core.core_glob.setup.pdf2image_type,
)
children.append((file_name_next, full_name_next))
except PDFPageCountError as err:
error_msg = (
Process.ERROR_21_901.replace("{full_name}", full_name_in)
.replace("{error_type}", str(type(err)))
.replace("{error_msg}", str(err))
)
dcr_core.core_glob.logger.debug("return =%s", (error_msg[:6], error_msg, []))
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return error_msg[:6], error_msg, []
dcr_core.core_glob.logger.debug(
"return =%s", (dcr_core.core_glob.RETURN_OK[0], dcr_core.core_glob.RETURN_OK[1], children)
)
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return dcr_core.core_glob.RETURN_OK[0], dcr_core.core_glob.RETURN_OK[1], children
# ------------------------------------------------------------------
# Processing a PDF file with PDFlib TET.
# ------------------------------------------------------------------
@classmethod
def pdflib(
cls,
full_name_in: str,
full_name_out: str,
document_opt_list: str,
page_opt_list: str,
) -> tuple[str, str]:
"""Process a PDF file with PDFlib TET.
The data from a PDF file is made available in XML files
with the help of PDFlib TET. The granularity of the XML
files can be word, line or paragraph depending on the
document and page options selected.
Args:
full_name_in (str):
Directory name and file name of the input file.
full_name_out (str):
Directory name and file name of the output file.
document_opt_list (str):
Document level options:
word: engines={noannotation noimage text notextcolor novector}
line: engines={noannotation noimage text notextcolor novector}
page: engines={noannotation noimage text notextcolor novector} lineseparator=U+0020
page_opt_list (str):
Page level options:
word: granularity=word tetml={elements={line}}
line: granularity=line
page: granularity=page
Returns:
tuple[str, str]:
("ok", "") if the processing has been completed successfully,
otherwise a corresponding error code and error message.
"""
try:
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
except AttributeError:
dcr_core.core_glob.initialise_logger()
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_glob.logger.debug("param full_name_in =%s", full_name_in)
dcr_core.core_glob.logger.debug("param full_name_out =%s", full_name_out)
dcr_core.core_glob.logger.debug("param document_opt_list=%s", document_opt_list)
dcr_core.core_glob.logger.debug("param page_opt_list =%s", page_opt_list)
tet = dcr_core.PDFlib.TET.TET()
doc_opt_list = f"tetml={{filename={{{full_name_out}}}}} {document_opt_list}"
if (file_curr := tet.open_document(full_name_in, doc_opt_list)) == -1:
error_msg = (
Process.ERROR_51_901.replace("{full_name}", full_name_in)
.replace("{error_no}", str(tet.get_errnum()))
.replace("{api_name}", tet.get_apiname() + "()")
.replace("{error_msg}", tet.get_errmsg())
)
dcr_core.core_glob.logger.debug("return =%s", (error_msg[:6], error_msg))
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return error_msg[:6], error_msg
# get number of pages in the document */
no_pages = tet.pcos_get_number(file_curr, "length:pages")
# loop over pages in the document */
for page_no in range(1, int(no_pages) + 1):
tet.process_page(file_curr, page_no, page_opt_list)
# This could be combined with the last page-related call
tet.process_page(file_curr, 0, "tetml={trailer}")
tet.close_document(file_curr)
tet.delete()
dcr_core.core_glob.logger.debug("return =%s", dcr_core.core_glob.LOGGER_END)
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return dcr_core.core_glob.RETURN_OK
# ------------------------------------------------------------------
# Converting image files to PDF files via OCR.
# ------------------------------------------------------------------
@classmethod
def tesseract(
cls,
full_name_in: str,
full_name_out: str,
language_tesseract: str,
) -> tuple[str, str, list[str]]:
"""Convert image files to PDF files via OCR.
The documents of the following document types are converted
to the PDF format using Tesseract OCR:
- bmp - bitmap image file
- gif - Graphics Interchange Format
- jp2 - JPEG 2000
- jpeg - Joint Photographic Experts Group
- png - Portable Network Graphics
- pnm - portable any-map format
- tif - Tag Image File Format
- tiff - Tag Image File Format
- webp - Image file format with lossless and lossy compression
After processing with Tesseract OCR, the files split previously
into multiple image files are combined into a single PDF document.
Args:
full_name_in (str):
The directory name and file name of the input file.
full_name_out (str):
The directory name and file name of the output file.
language_tesseract (str):
The Tesseract name of the document language.
Returns:
tuple[str, str, list[str]]:
("ok", "", [...]) if the processing has been completed successfully,
otherwise a corresponding error code and error message.
"""
try:
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
except AttributeError:
dcr_core.core_glob.initialise_logger()
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_glob.logger.debug("param full_name_in =%s", full_name_in)
dcr_core.core_glob.logger.debug("param full_name_out =%s", full_name_out)
dcr_core.core_glob.logger.debug("param language_tesseract=%s", language_tesseract)
children: list[str] = []
pdf_writer = PyPDF2.PdfWriter()
for full_name in sorted(glob.glob(full_name_in)):
try:
pdf = pytesseract.image_to_pdf_or_hocr(
extension="pdf",
image=full_name,
lang=language_tesseract,
timeout=dcr_core.core_glob.setup.tesseract_timeout,
)
with open(full_name_out, "w+b") as file_handle:
# PDF type is bytes by default
file_handle.write(pdf)
if len(PyPDF2.PdfReader(full_name_out).pages) == 0:
error_msg = Process.ERROR_41_911.replace("{full_name_out}", full_name_out)
dcr_core.core_glob.logger.debug("return =%s", (error_msg[:6], error_msg, []))
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return error_msg[:6], error_msg, []
pdf_reader = PyPDF2.PdfReader(full_name_out)
for page in pdf_reader.pages:
# Add each page to the writer object
pdf_writer.add_page(page)
children.append(full_name)
except RuntimeError as err:
error_msg = Process.ERROR_41_901.replace("{full_name}", full_name_in).replace("{error_msg}", str(err))
dcr_core.core_glob.logger.debug("return =%s", (error_msg[:6], error_msg, []))
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return error_msg[:6], error_msg, []
# Write out the merged PDF
with open(full_name_out, "wb") as file_handle:
pdf_writer.write(file_handle)
dcr_core.core_glob.logger.debug(
"return =%s", (dcr_core.core_glob.RETURN_OK[0], dcr_core.core_glob.RETURN_OK[1], children)
)
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return dcr_core.core_glob.RETURN_OK[0], dcr_core.core_glob.RETURN_OK[1], children
# ------------------------------------------------------------------
# Tokenizing the text from the PDF document.
# ------------------------------------------------------------------
@classmethod
def tokenizer(
cls,
full_name_in: str,
full_name_out: str,
pipeline_name: str,
document_id: int = -1,
full_name_orig: str = "",
no_lines_footer: int = -1,
no_lines_header: int = -1,
no_lines_toc: int = -1,
) -> tuple[str, str]:
"""Tokenizing the text from the PDF document.
The line-oriented text is broken down into qualified
tokens with the means of SpaCy.
Args:
full_name_in (str):
The directory name and file name of the input file.
full_name_out (str):
The directory name and file name of the output file.
pipeline_name (str):
The loaded SpaCy pipeline.
document_id (int, optional):
The identification number of the document.
Defaults to -1.
full_name_orig (str, optional):
The file name of the originating document. Defaults to "".
no_lines_footer (int, optional):
Total number of footer lines.
Defaults to -1.
no_lines_header (int, optional):
Total number of header lines.
Defaults to -1.
no_lines_toc (int, optional):
Total number of TOC lines.
Defaults to -1.
Returns:
tuple[str, str]:
("ok", "") if the processing has been completed successfully,
otherwise a corresponding error code and error message.
"""
try:
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
except AttributeError:
dcr_core.core_glob.initialise_logger()
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_START)
dcr_core.core_glob.logger.debug("param document_id =%i", document_id)
dcr_core.core_glob.logger.debug("param full_name_in =%s", full_name_in)
dcr_core.core_glob.logger.debug("param full_name_orig =%s", full_name_orig)
dcr_core.core_glob.logger.debug("param full_name_out =%s", full_name_out)
dcr_core.core_glob.logger.debug("param no_lines_footer=%i", no_lines_footer)
dcr_core.core_glob.logger.debug("param no_lines_header=%i", no_lines_header)
dcr_core.core_glob.logger.debug("param no_lines_toc =%i", no_lines_toc)
dcr_core.core_glob.logger.debug("param pipeline_name =%s", pipeline_name)
try:
dcr_core.core_glob.text_parser = dcr_core.cls_text_parser.TextParser.from_files(
file_encoding=dcr_core.core_glob.FILE_ENCODING_DEFAULT, full_name_line=full_name_in
)
dcr_core.core_glob.tokenizer_spacy.process_document(
document_id=document_id,
file_name_next=full_name_out,
file_name_orig=full_name_orig,
no_lines_footer=no_lines_footer,
no_lines_header=no_lines_header,
no_lines_toc=no_lines_toc,
pipeline_name=pipeline_name,
)
except FileNotFoundError:
error_msg = Process.ERROR_71_901.replace("{full_name}", full_name_in)
dcr_core.core_glob.logger.debug("return =%s", (error_msg[:6], error_msg))
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return error_msg[:6], error_msg
dcr_core.core_glob.logger.debug("return =%s", dcr_core.core_glob.RETURN_OK)
dcr_core.core_glob.logger.debug(dcr_core.core_glob.LOGGER_END)
return dcr_core.core_glob.RETURN_OK
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