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Commit516c417

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Copilotjosix
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Implement terminology extraction tools and generate translation dictionaries
Co-authored-by: josix <18432820+josix@users.noreply.github.com>
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‎.scripts/README.md‎

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Useful scripts for the translation.
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##Translation Dictionary Generation
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Extract and build a translation dictionary for terminologies across different .po files to maintain consistency.
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###extract_terminology.py
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Main script that processes all .po files and extracts terminology:
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```sh
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python3 .scripts/extract_terminology.py
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```
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Generates`terminology_dictionary.csv` with all extracted terms and their translations.
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###create_focused_dictionary.py
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Creates a curated dictionary focusing on the most important Python terminology:
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```sh
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python3 .scripts/create_focused_dictionary.py
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```
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Generates`focused_terminology_dictionary.csv` with categorized high-priority terms.
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See the terminology documentation for detailed usage and integration with translation workflow.
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##From Google Translation
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Translate all untranslated entries of the given .po file with Google Translate.
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```sh
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.scripts/google_translate.sh library/csv.po
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```
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#!/usr/bin/env python3
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"""
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Create a focused terminology dictionary for the most important Python terms.
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This script extracts the most critical Python terminology for translation consistency.
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"""
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importcsv
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fromcollectionsimportdefaultdict,Counter
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defcreate_focused_dictionary():
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"""Create a focused dictionary with the most important terms."""
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# Read the full terminology dictionary
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important_terms= []
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withopen("terminology_dictionary.csv",'r',encoding='utf-8')ascsvfile:
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reader=csv.DictReader(csvfile)
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forrowinreader:
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source_term=row['source_term'].strip()
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frequency=int(row['frequency'])
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files_count=int(row['files_count'])
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# Focus on high-priority terms
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is_important=False
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# High priority: Python built-in types and keywords
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ifsource_term.lower()in {
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'class','function','method','module','package','object','type',
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'int','str','list','dict','tuple','set','float','bool','complex',
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'none','true','false','return','import','def','async','await',
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'lambda','yield','raise','try','except','finally','with','as'
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}:
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is_important=True
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# High priority: Common Python concepts
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elifany(conceptinsource_term.lower()forconceptin [
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'exception','error','iterator','generator','decorator','property',
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'classmethod','staticmethod','metaclass','inheritance','polymorphism'
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]):
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is_important=True
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# High priority: Terms that appear in many files (widespread usage)
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eliffiles_count>=20andfrequency>=10:
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is_important=True
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# Medium priority: Code elements in backticks
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elif'`'insource_termorsource_term.startswith('__')andsource_term.endswith('__'):
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is_important=True
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# Medium priority: Terms with technical patterns
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elifany(patterninsource_termforpatternin ['()','Error','Exception','Class']):
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is_important=True
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ifis_important:
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important_terms.append(row)
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# Sort by frequency (most common first)
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important_terms.sort(key=lambdax:int(x['frequency']),reverse=True)
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# Write focused dictionary
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withopen("focused_terminology_dictionary.csv",'w',newline='',encoding='utf-8')ascsvfile:
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fieldnames= ['source_term','translated_term','frequency','files_count',
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'priority','category','example_files']
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writer=csv.DictWriter(csvfile,fieldnames=fieldnames)
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writer.writeheader()
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forterm_datainimportant_terms:
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source_term=term_data['source_term'].strip()
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# Categorize the term
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category='Other'
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priority='Medium'
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ifsource_term.lower()in {
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'class','function','method','module','package','object','type'
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}:
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category='Core Concepts'
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priority='High'
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elifsource_term.lower()in {
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'int','str','list','dict','tuple','set','float','bool','complex'
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}:
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category='Built-in Types'
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priority='High'
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elifsource_term.lower()in {
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'none','true','false','return','import','def','async','await'
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}:
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category='Keywords/Constants'
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priority='High'
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elif'error'insource_term.lower()or'exception'insource_term.lower():
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category='Exceptions'
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priority='High'
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elif'`'insource_term:
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category='Code Elements'
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priority='Medium'
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elifint(term_data['files_count'])>=50:
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category='Common Terms'
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priority='High'
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writer.writerow({
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'source_term':source_term,
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'translated_term':term_data['translated_term'],
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'frequency':term_data['frequency'],
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'files_count':term_data['files_count'],
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'priority':priority,
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'category':category,
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'example_files':term_data['example_files']
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})
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print(f"Created focused terminology dictionary with{len(important_terms)} important terms")
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# Print category statistics
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categories=defaultdict(int)
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priorities=defaultdict(int)
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forterminimportant_terms:
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source_term=term['source_term'].strip()
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ifsource_term.lower()in {'class','function','method','module','package','object','type'}:
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categories['Core Concepts']+=1
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elifsource_term.lower()in {'int','str','list','dict','tuple','set','float','bool','complex'}:
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categories['Built-in Types']+=1
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elifsource_term.lower()in {'none','true','false','return','import','def','async','await'}:
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categories['Keywords/Constants']+=1
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elif'error'insource_term.lower()or'exception'insource_term.lower():
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categories['Exceptions']+=1
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elif'`'insource_term:
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categories['Code Elements']+=1
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else:
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categories['Common Terms']+=1
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print("\nCategory breakdown:")
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forcategory,countincategories.items():
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print(f"{category}:{count} terms")
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if__name__=="__main__":
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create_focused_dictionary()

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