def main():
args = docopt(__doc__, version='meTypeset 0.1')
bare_gv = GV(args)
if args['--debug']:
bare_gv.debug.enable_debug(args['--nogit'])
nlm_instance = TeiToNlm(bare_gv)
if args['process']:
# run non-transform portions of teitonlm
TeiToNlm(bare_gv).run(True, False)
# run reference linker
rl = ReferenceLinker(bare_gv)
rl.run(args['--interactive'])
rl.cleanup()
bibliography_classifier = BibliographyClassifier(bare_gv)
# run table classifier
cc = CaptionClassifier(bare_gv)
if int(args['--aggression']) > int(
bare_gv.settings.get_setting(
'tablecaptions', None, domain='aggression')):
cc.run_tables()
if int(args['--aggression']) > int(
bare_gv.settings.get_setting(
'graphiccaptions', None, domain='aggression')):
cc.run_graphics()
if args['--interactive']:
bibliography_classifier.run_prompt(True)
# process any bibliography entries that are possible
BibliographyDatabase(bare_gv).run()
# remove stranded titles
manipulate = NlmManipulate(bare_gv)
manipulate.final_clean()
if args['--identifiers']:
IdGenerator(bare_gv).run()
if args['--chain']:
# construct and run an XSLT chainer
XslChain(bare_gv).run()
if args['--clean']:
ComplianceEnforcer(bare_gv).run()
def main():
args = docopt(__doc__, version='meTypeset 0.1')
bare_gv = GV(args)
if args['--debug']:
bare_gv.debug.enable_debug(args['--nogit'])
nlm_instance = TeiToNlm(bare_gv)
if args['process']:
# run non-transform portions of teitonlm
TeiToNlm(bare_gv).run(True, False)
# run reference linker
rl = ReferenceLinker(bare_gv)
rl.run(args['--interactive'])
rl.cleanup()
bibliography_classifier = BibliographyClassifier(bare_gv)
# run table classifier
cc = CaptionClassifier(bare_gv)
if int(args['--aggression']) > int(bare_gv.settings.get_setting('tablecaptions',
None, domain='aggression')):
cc.run_tables()
if int(args['--aggression']) > int(bare_gv.settings.get_setting('graphiccaptions',
None, domain='aggression')):
cc.run_graphics()
if args['--interactive']:
bibliography_classifier.run_prompt(True)
# process any bibliography entries that are possible
BibliographyDatabase(bare_gv).run()
# remove stranded titles
manipulate = NlmManipulate(bare_gv)
manipulate.final_clean()
if args['--identifiers']:
IdGenerator(bare_gv).run()
if args['--chain']:
# construct and run an XSLT chainer
XslChain(bare_gv).run()
if args['--clean']:
ComplianceEnforcer(bare_gv).run()
def run_modules(self):
ag = int(self.gv.settings.args['--aggression'])
self.debug.print_debug(self,
u'Running at aggression level {0} {1}'.format(ag,
"[grrr!]" if ag == 10 else ""))
if ag > 10:
self.debug.print_debug(self, "WARNING: safety bail-out features are disabled at aggression level 11")
if self.args['bibscan']:
BibliographyDatabase(self.gv).scan()
else:
# check for stylesheets
self.gv.check_file_exists(self.gv.docx_style_sheet_dir)
# metadata file
gv.metadata_file = self.set_metadata_file()
self.gv.mk_dir(self.gv.output_folder_path)
if self.args['doc']:
# run doc to docx conversion
# then run docx to tei
UnoconvToDocx(self.gv).run('doc')
DocxToTei(self.gv).run(True, self.args['--proprietary'])
elif self.args['odt']:
# run odt to docx conversion
# then run docx to tei
UnoconvToDocx(self.gv).run('odt')
DocxToTei(self.gv).run(True, self.args['--proprietary'])
elif self.args['other']:
# run other unoconv-supported format to docx conversion
# then run docx to tei
UnoconvToDocx(self.gv).run('unoconv')
DocxToTei(self.gv).run(True, self.args['--proprietary'])
elif self.args['docx']:
# run docx to tei conversion
# includes hooks for proprietary transforms if enabled
DocxToTei(self.gv).run(True, self.args['--proprietary'])
elif self.args['docxextracted']:
self.debug.print_debug(self, u'Skipping docx extraction')
DocxToTei(self.gv).run(False, self.args['--proprietary'])
elif self.args['tei']:
self.debug.print_debug(self, u'Skipping docx extraction; processing TEI file')
DocxToTei(self.gv).run(False, self.args['--proprietary'], tei=True)
if self.args['--puretei']:
self.debug.print_debug(self, u'Exiting as TEI transform complete')
return
metadata = Metadata(self.gv)
metadata.pre_clean()
# run size classifier
# aggression 5
SizeClassifier(self.gv).run()
# run bibliographic addins handler
# aggression 4
found_bibliography = BibliographyAddins(self.gv).run()
# run list classifier
# aggression 4
ListClassifier(self.gv).run()
bibliography_classifier = BibliographyClassifier(self.gv)
if not found_bibliography:
# run bibliographic classifier
# aggression 4
bibliography_classifier.run()
# tei
# aggression 3
TeiManipulate(self.gv).run()
# run tei to nlm conversion
TeiToNlm(self.gv).run(not found_bibliography)
if self.gv.settings.args['--purenlm']:
self.debug.print_debug(self, u'Exiting as NLM transform complete')
return
manipulate = NlmManipulate(self.gv)
if not self.gv.used_list_method:
manipulate.fuse_references()
# run reference linker
if not (self.args['--nolink']):
rl = ReferenceLinker(self.gv)
rl.run(self.args['--interactive'])
rl.cleanup()
# run table classifier
cc = CaptionClassifier(self.gv)
if int(self.args['--aggression']) > int(self.gv.settings.get_setting('tablecaptions',
self, domain='aggression')):
cc.run_tables()
if int(self.args['--aggression']) > int(self.gv.settings.get_setting('graphiccaptions',
self, domain='aggression')):
cc.run_graphics()
# run metadata merge
metadata.run()
if self.args['--interactive']:
bibliography_classifier.run_prompt(True)
# process any bibliography entries that are possible
BibliographyDatabase(self.gv).run()
# remove stranded titles and cleanup
manipulate.final_clean()
if self.args['--identifiers']:
IdGenerator(self.gv).run()
if self.args['--chain']:
# construct and run an XSLT chainer
XslChain(self.gv).run()
if self.args['--clean']:
ComplianceEnforcer(self.gv).run()
def run_modules(self):
ag = int(self.gv.settings.args['--aggression'])
self.debug.print_debug(
self, u'Running at aggression level {0} {1}'.format(
ag, "[grrr!]" if ag == 10 else ""))
if ag > 10:
self.debug.print_debug(
self,
"WARNING: safety bail-out features are disabled at aggression level 11"
)
if self.args['bibscan']:
BibliographyDatabase(self.gv).scan()
else:
# check for stylesheets
self.gv.check_file_exists(self.gv.docx_style_sheet_dir)
# metadata file
gv.metadata_file = self.set_metadata_file()
self.gv.mk_dir(self.gv.output_folder_path)
if self.args['doc']:
# run doc to docx conversion
# then run docx to tei
UnoconvToDocx(self.gv).run('doc')
DocxToTei(self.gv).run(True, self.args['--proprietary'])
elif self.args['odt']:
# run odt to docx conversion
# then run docx to tei
UnoconvToDocx(self.gv).run('odt')
DocxToTei(self.gv).run(True, self.args['--proprietary'])
elif self.args['other']:
# run other unoconv-supported format to docx conversion
# then run docx to tei
UnoconvToDocx(self.gv).run('unoconv')
DocxToTei(self.gv).run(True, self.args['--proprietary'])
elif self.args['docx']:
# run docx to tei conversion
# includes hooks for proprietary transforms if enabled
DocxToTei(self.gv).run(True, self.args['--proprietary'])
elif self.args['docxextracted']:
self.debug.print_debug(self, u'Skipping docx extraction')
DocxToTei(self.gv).run(False, self.args['--proprietary'])
elif self.args['tei']:
self.debug.print_debug(
self, u'Skipping docx extraction; processing TEI file')
DocxToTei(self.gv).run(False,
self.args['--proprietary'],
tei=True)
if self.args['--puretei']:
self.debug.print_debug(self,
u'Exiting as TEI transform complete')
return
metadata = Metadata(self.gv)
metadata.pre_clean()
# run size classifier
# aggression 5
SizeClassifier(self.gv).run()
# run bibliographic addins handler
# aggression 4
found_bibliography = BibliographyAddins(self.gv).run()
# run list classifier
# aggression 4
ListClassifier(self.gv).run()
bibliography_classifier = BibliographyClassifier(self.gv)
if not found_bibliography:
# run bibliographic classifier
# aggression 4
bibliography_classifier.run()
# tei
# aggression 3
TeiManipulate(self.gv).run()
# run tei to nlm conversion
TeiToNlm(self.gv).run(not found_bibliography)
if self.gv.settings.args['--purenlm']:
self.debug.print_debug(self,
u'Exiting as NLM transform complete')
return
manipulate = NlmManipulate(self.gv)
if not self.gv.used_list_method:
manipulate.fuse_references()
# run reference linker
if not (self.args['--nolink']):
rl = ReferenceLinker(self.gv)
rl.run(self.args['--interactive'])
rl.cleanup()
# run table classifier
cc = CaptionClassifier(self.gv)
if int(self.args['--aggression']) > int(
self.gv.settings.get_setting(
'tablecaptions', self, domain='aggression')):
cc.run_tables()
if int(self.args['--aggression']) > int(
self.gv.settings.get_setting(
'graphiccaptions', self, domain='aggression')):
cc.run_graphics()
# run metadata merge
metadata.run()
if self.args['--interactive']:
bibliography_classifier.run_prompt(True)
# process any bibliography entries that are possible
BibliographyDatabase(self.gv).run()
# remove stranded titles and cleanup
manipulate.final_clean()
if self.args['--identifiers']:
IdGenerator(self.gv).run()
if self.args['--chain']:
# construct and run an XSLT chainer
XslChain(self.gv).run()
if self.args['--clean']:
ComplianceEnforcer(self.gv).run()