diff --git a/.github/workflows/data-processing.yml b/.github/workflows/data-processing.yml index 39b1db9709f..de7034544f9 100644 --- a/.github/workflows/data-processing.yml +++ b/.github/workflows/data-processing.yml @@ -151,7 +151,25 @@ jobs: - name: Install Python dependencies run: python3 -m pip install -r ./requirements.txt - + + #======================================== + # Setup Node.js for bibliography processing + #======================================== + - name: Setup Node.js + uses: actions/setup-node@v4 + with: + node-version: '18' + cache: 'npm' + cache-dependency-path: bibtex_to_apa/package-lock.json + + #======================================== + # Install Node.js dependencies for bibliography processing + #======================================== + - name: Install Node.js dependencies + run: | + cd bibtex_to_apa + npm install + #======================================== # Process contributor data using Tenzing script #======================================== @@ -202,6 +220,15 @@ jobs: fi done + #======================================== + # Generate APA lookup from bibliography + #======================================== + - name: Generate APA lookup + continue-on-error: true # Continue even if this step fails + run: | + cd bibtex_to_apa + node bibtex_to_apa.js -o '../content/glossary/apa_lookup.json' + #======================================== # Process and generate glossary files #======================================== @@ -211,6 +238,17 @@ jobs: run: python3 content/glossary/_create_glossaries.py # Execute the glossary script that generates glossary markdown files + - name: Check for missing references + if: always() + run: | + if [ -f "content/glossary/missing_references.txt" ]; then + echo "Missing references found:" + cat content/glossary/missing_references.txt + # Optionally fail the workflow or create an issue + else + echo "All references resolved successfully" + fi + #======================================== # Download Google Analytics data and validate #======================================== diff --git a/.gitignore b/.gitignore index b99f01547a4..71e81880320 100644 --- a/.gitignore +++ b/.gitignore @@ -268,3 +268,6 @@ gha-creds-*.json # Tenzing failure reports (temporary files for CI) scripts/forrt_contribs/tenzing_failures.json + +# Bibtex to APA converter output +bibtex_to_apa/node_modules/ diff --git a/bibtex_to_apa/bibtex_to_apa.js b/bibtex_to_apa/bibtex_to_apa.js new file mode 100644 index 00000000000..6f84f3475ab --- /dev/null +++ b/bibtex_to_apa/bibtex_to_apa.js @@ -0,0 +1,91 @@ +const { Cite } = require('@citation-js/core'); +require('@citation-js/plugin-bibtex'); +require('@citation-js/plugin-csl'); +const fs = require('fs'); + +const DEFAULT_INPUT = 'https://docs.google.com/document/d/1-KKsOYZWJ3LdgdO2b2uJsOG2AmUDaQBNqWVVTY2W4W8/edit?tab=t.0'; +const DEFAULT_OUTPUT = 'apa_lookup.json'; + +async function fetchBibtex(input) { + if (!input.startsWith('http')) { + return fs.readFileSync(input, 'utf-8'); + } + + if (input.includes('docs.google.com')) { + const match = input.match(/\/d\/([a-zA-Z0-9_-]+)/); + if (!match) throw new Error('Invalid Google Doc URL'); + const exportUrl = `https://docs.google.com/document/d/${match[1]}/export?format=txt`; + const response = await fetch(exportUrl); + if (!response.ok) throw new Error(`Failed to fetch: ${response.status}`); + let text = await response.text(); + return text.replace(/\[[a-z]+\]/gi, ''); // Remove Google Docs comment markers + } + + const response = await fetch(input); + if (!response.ok) throw new Error(`Failed to fetch: ${response.status}`); + return response.text(); +} + +function extractUrl(entry) { + if (entry.URL) return entry.URL; + if (entry.note) { + const match = entry.note.match(/https?:\/\/[^\s]+/); + if (match) return match[0]; + } + return null; +} + +function bibtexToApaJson(bibtexContent, includeUrl = true) { + const cite = new Cite(bibtexContent); + const result = {}; + + for (const entry of cite.data) { + const key = entry.id || entry['citation-key']; + let ref = new Cite(entry).format('bibliography', { + format: 'text', + template: 'apa', + lang: 'en-US' + }).trim(); + + if (includeUrl) { + const url = extractUrl(entry); + if (url && !url.includes('doi.org') && !ref.includes(url)) { + ref = ref.match(/https?:\/\/[^\s]+$/) + ? `${ref} Retrieved from ${url}` + : ref.replace(/\.?$/, `. Retrieved from ${url}`); + } + } + + result[key] = ref; + } + + return result; +} + +async function main() { + const args = process.argv.slice(2); + let input = DEFAULT_INPUT; + let output = DEFAULT_OUTPUT; + let includeUrl = true; + + for (let i = 0; i < args.length; i++) { + if (args[i] === '-i' || args[i] === '--input') input = args[++i]; + else if (args[i] === '-o' || args[i] === '--output') output = args[++i]; + else if (args[i] === '--no-url') includeUrl = false; + else if (args[i] === '-h' || args[i] === '--help') { + console.log(`Usage: node bibtex_to_apa.js [-i INPUT] [-o OUTPUT] [--no-url] + Options: + -i, --input Input BibTeX (URL or file). Default: Google Doc + -o, --output Output JSON file. Default: apa_lookup.json + --no-url Don't append URLs to references`); + process.exit(0); + } + } + + const bibtex = await fetchBibtex(input); + const apaJson = bibtexToApaJson(bibtex, includeUrl); + fs.writeFileSync(output, JSON.stringify(apaJson, null, 2)); + console.log(`Wrote ${Object.keys(apaJson).length} references to ${output}`); +} + +main().catch(console.error); \ No newline at end of file diff --git a/bibtex_to_apa/package-lock.json b/bibtex_to_apa/package-lock.json new file mode 100644 index 00000000000..5ed4ff29767 --- /dev/null +++ b/bibtex_to_apa/package-lock.json @@ -0,0 +1,224 @@ +{ + "name": "demo", + "version": "1.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "demo", + "version": "1.0.0", + "license": "ISC", + "dependencies": { + "@citation-js/core": "^0.7.21", + "@citation-js/plugin-bibtex": "^0.7.21", + "@citation-js/plugin-csl": "^0.7.22" + } + }, + "node_modules/@citation-js/core": { + "version": "0.7.21", + "resolved": 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b/content/glossary/_create_glossaries.py @@ -3,498 +3,218 @@ import json import pandas as pd import os -import shutil -import unicodedata +from io import StringIO script_dir = os.path.dirname(os.path.abspath(__file__)) -print(script_dir) - -file_links = 'https://docs.google.com/spreadsheets/d/e/2PACX-1vQpQJ-9pY0Bq7u2pm464pJpUCOMI4biMnqCHgYZuMETcRNBbHLPYT55jhDXGRx68qYhn3_z6PO90gQl/pub?gid=1617993088&single=true&output=csv' - -df = pd.read_csv(file_links) -print("file links read") -grouped = df.groupby('Language') +language_map = { + 'EN': 'english', + 'AR': 'arabic', + 'DE': 'german', +} + +# Configuration +sheet_id = '1U__xiWOPEO2jxcNzw5ZLisjScmMSrcJ1xq-QUvkSo-I' +gid = '955789150' +csv_url = f'https://docs.google.com/spreadsheets/d/{sheet_id}/export?format=csv&gid={gid}' + +# Fetch and parse data +response = requests.get(csv_url) +response.raise_for_status() +response.encoding = 'utf-8' + +df = pd.read_csv(StringIO(response.text)) + +# Extract unique language codes from column names +language_prefixes = set() +for col in df.columns: + match = re.match(r'^([A-Z]{2})_', col) + if match: + language_prefixes.add(match.group(1)) + +languages = sorted(language_prefixes) +print(f"\nDetected {len(languages)} languages: {languages}") + +# Load APA lookup +try: + with open(os.path.join(script_dir, 'apa_lookup.json'), 'r', encoding='utf-8') as f: + apa_lookup = json.load(f) +except FileNotFoundError: + print("Warning: apa_lookup.json not found. References will not be formatted.") + apa_lookup = {} + +def process_references(references_text, apa_lookup, missing_refs_log=None): + """Convert citation keys to APA format using the lookup""" + if not references_text: + return [] + + citation_pattern = r'\\?\[@([^\\]+)\\?\]' + matches = re.findall(citation_pattern, references_text) + + formatted_refs = [] + for match in matches: + # Clean the key: remove markdown formatting, trailing punctuation, etc. + key = match.strip() + original_key = key # Keep for logging + + # Remove markdown formatting + key = re.sub(r'^\*+|\*+$', '', key) # Remove leading/trailing asterisks + key = re.sub(r'^_+|_+$', '', key) # Remove leading/trailing underscores + + # Remove trailing punctuation + key = re.sub(r'[,;:]+$', '', key) + + # Remove trailing digits that look like typos (e.g., "Pownall20210" -> "Pownall2021") + key = re.sub(r'(\d{4})0+$', r'\1', key) + + if key in apa_lookup: + formatted_refs.append(apa_lookup[key]) + else: + # Log missing reference but don't include in output + if missing_refs_log is not None: + missing_refs_log.add(original_key) + print(f"Warning: Missing reference key '{original_key}' (cleaned: '{key}') - skipping") + + return list(dict.fromkeys(formatted_refs)) + +def safe_get(row, column, default=""): + """Safely get a value from a pandas Series row""" + try: + if column in row.index and pd.notna(row[column]): + return str(row[column]).strip() + return default + except Exception: + return default + +def clean_filename(title): + """Clean title for use as filename""" + # Extract main title (before parentheses) + file_name = title.split(" (")[0].strip() + # Replace spaces and special characters + file_name = re.sub(r'[^\w\s]', '_', file_name.replace(" ", "_")) + # Convert to lowercase and clean up multiple underscores + return file_name.lower().strip().replace("__", "_") + +# Process languages formatted_data = {} +languages_to_process = [lang for lang in languages if lang in language_map] +missing_refs = set() # Track missing references -def update_arabic_index(script_dir, entries): - print("Updating Arabic Index with Translators...") +for language_code in languages_to_process: + print(f"Processing language: {language_code}") - # Mapping from extracted names to (Full English Name, Arabic Name) - TRANSLATOR_MAPPING = { - # 1. Ali H. Al-Hoorie - "ali h. al-hoorie": ("Ali H. Al-Hoorie", "علي حسين الحوري"), - - # 2. Amani A. Aloufi - "amani a. aloufi": ("Amani A. Aloufi", "أماني عبدالرحمن العوفي"), - "amani aloufi": ("Amani A. Aloufi", "أماني عبدالرحمن العوفي"), - - # 3. Asma A. Alzahrani - "asma a. alzahrani": ("Asma A. Alzahrani", "أسماء علي الزهراني"), - "asma alzahrani": ("Asma A. Alzahrani", "أسماء علي الزهراني"), - "asma alzahran": ("Asma A. Alzahrani", "أسماء علي الزهراني"), - - # 4. Hala M. Alghamdi - "hala a. alghamdi": ("Hala M. Alghamdi", "هلا الغامدي"), - "hala m. alghamdi": ("Hala M. Alghamdi", "هلا الغامدي"), - "hala alghamdi": ("Hala M. Alghamdi", "هلا الغامدي"), - - # 5. Ahlam Ahmed Almehmadi - "ahlam ahmed almehmadi": ("Ahlam Ahmed Almehmadi", "أحلام أحمد المحمادي"), - "ahlam ahmed": ("Ahlam Ahmed Almehmadi", "أحلام أحمد المحمادي"), - - # 6. Hiba A. Alomary - "hiba a. alomary": ("Hiba A. Alomary", "هبة علي العُمري"), - "hiba alomary": ("Hiba A. Alomary", "هبة علي العُمري"), - - # 7. Alaa M. Saleh - "alaa m. saleh": ("Alaa M. Saleh", "آلاء مأمون صالح"), - "alaa saleh": ("Alaa M. Saleh", "آلاء مأمون صالح"), - - # 8. Zainab Abdullah Alsuhaibani - "zainab abdullah alsuhaibani": ("Zainab Abdullah Alsuhaibani", "زينب عبدالله السحيباني"), - "zainab alsuhaibani": ("Zainab Abdullah Alsuhaibani", "زينب عبدالله السحيباني"), - - # 9. Abdulsamad Yahya Humaidan - "abdulsamad yahya humaidan": ("Abdulsamad Yahya Humaidan", "عبد الصمد يحيى حميدان"), - "abdulsamad humaidan": ("Abdulsamad Yahya Humaidan", "عبد الصمد يحيى حميدان"), - - # 10. Naif Ali Masrahi - "naif ali masrahi": ("Naif Ali Masrahi", "نايف علي مسرحي"), - "naif masrahi": ("Naif Ali Masrahi", "نايف علي مسرحي"), - - # 11. Awatif K. Alruwaili - "awatif k. alruwaili": ("Awatif K. Alruwaili", "عواطف كاتب الرويلي"), - "awatif alruwaili": ("Awatif K. Alruwaili", "عواطف كاتب الرويلي"), - - # 12. Mahdi R. Aben Ahmed - "mahdi r. aben ahmed": ("Mahdi R. Aben Ahmed", "مهدي رضاء أبن أحمد"), - "mahdi aben ahmed": ("Mahdi R. Aben Ahmed", "مهدي رضاء أبن أحمد"), - - # 13. Ruwayshid N. Alruwaili - "ruwayshid n. alruwaili": ("Ruwayshid N. Alruwaili", "رويشد نافع الرويلي"), - "ruwayshid": ("Ruwayshid N. Alruwaili", "رويشد نافع الرويلي"), - - # 14. Hussain Mohammed Alzubaidi - "hussain mohammed alzubaidi": ("Hussain Mohammed Alzubaidi", "حسين محمد الزبيدي"), - - # 15. Nazik Noaman A. Alnour - "nazik noaman a. alnour": ("Nazik Noaman A. Alnour", "نازك نعمان أحمد النور"), - "nazik alnour": ("Nazik Noaman A. Alnour", "نازك نعمان أحمد النور"), - - # 16. Moustafa Mohammed Shalaby - "moustafa mohammed shalaby": ("Moustafa Mohammed Shalaby", "مصطفي محمد شلبي"), - - # 17. Nabil Ali Sayed - "nabil ali sayed": ("Nabil Ali Sayed", "نبيل علي سعيد"), - "nabil sayed": ("Nabil Ali Sayed", "نبيل علي سعيد"), - - # 18. Mai Salah El din Helmy - "mai salah el din helmy": ("Mai Salah El din Helmy", "مي صلاح الدين حلمي"), - "mai helmy": ("Mai Salah El din Helmy", "مي صلاح الدين حلمي"), - - # 19. Ahmed Hadi Hakami - "ahmed hadi hakami": ("Ahmed Hadi Hakami", "أحمد هادي حكمي"), - "ahmed hakami": ("Ahmed Hadi Hakami", "أحمد هادي حكمي"), - - # 20. Sarah S. Almutairi - "sarah s. almutairi": ("Sarah S. Almutairi", "ساره المطيري"), - "sarah almutairi": ("Sarah S. Almutairi", "ساره المطيري"), - - # 21. Mohammed Ali Mohsen - "mohammed ali mohsen": ("Mohammed Ali Mohsen", "محمد محسن"), - "mohammed mohsen": ("Mohammed Ali Mohsen", "محمد محسن") - } + language_name = language_map.get(language_code, language_code.lower()) - # Desired order based on contribution - CONTRIBUTOR_ORDER = [ - "Ali H. Al-Hoorie", - "Amani A. Aloufi", - "Asma A. Alzahrani", - "Hala M. Alghamdi", - "Ahlam Ahmed Almehmadi", - "Hiba A. Alomary", - "Alaa M. Saleh", - "Zainab Abdullah Alsuhaibani", - "Abdulsamad Yahya Humaidan", - "Naif Ali Masrahi", - "Awatif K. Alruwaili", - "Mahdi R. Aben Ahmed", - "Ruwayshid N. Alruwaili", - "Hussain Mohammed Alzubaidi", - "Nazik Noaman A. Alnour", - "Moustafa Mohammed Shalaby", - "Nabil Ali Sayed", - "Mai Salah El din Helmy", - "Ahmed Hadi Hakami", - "Sarah S. Almutairi", - "Mohammed Ali Mohsen" + # Get relevant columns + language_columns = [col for col in df.columns if col.startswith(f'{language_code}_') and '_hide' not in col] + common_columns = [ + 'Related_terms', + 'Reference', + 'Originally drafted by', + 'Drafted by', + 'Reviewed (or Edited) by', ] - - def normalize_arabic_text(text): - # Remove diacritics - text = re.sub(r'[\u064B-\u065F\u0670]', '', text) - return text + relevant_columns = list(set(common_columns + language_columns + (["EN_title"] if language_code != 'EN' else []))) - names = set() - for entry in entries: - raw_names = [] - if 'Translated by' in entry: - raw_names.append(entry['Translated by']) - if 'Translation reviewed by' in entry: - raw_names.append(entry['Translation reviewed by']) - - for raw in raw_names: - # Cleaning logic - clean = raw.replace('**', '') - clean = re.split(r'###', clean)[0] - clean = re.sub(r'\{.*?\}', '', clean) - parts = re.split(r'[,;،]|\s{2,}', clean) - - for p in parts: - name = p.strip() - name = re.sub(r'^Dr\.\s*', '', name, flags=re.IGNORECASE) - name = normalize_arabic_text(name) - name = name.strip(' .-_') - - if len(name) < 3 or len(name) > 40: continue - if "http" in name or "www" in name: continue - if "Glossary" in name and "|" in name: continue - if "Looking for something else" in name: continue - if "Term coined" in name: continue - if "_" in name: continue - if len(name) <= 2: continue - - name = ' '.join(name.split()) - if name: - names.add(name) - - # Match with mapping and ensure all contributors in order are included - final_rows = [] - seen_full_names = set() + language_df = df[relevant_columns].copy() + language_entries = [] - # First, process names based on the contribution order - for full_eng in CONTRIBUTOR_ORDER: - # Find the arabic name from the mapping - # We need to reverse lookup or find the key that corresponds to this value - arabic_name = "" - found = False - for key, val in TRANSLATOR_MAPPING.items(): - if val[0] == full_eng: - arabic_name = val[1] - found = True - break - - if found: - final_rows.append((full_eng, arabic_name)) - seen_full_names.add(full_eng) - else: - print(f"Warning: {full_eng} not found in TRANSLATOR_MAPPING") - - # Then check if there are any extracted names that were NOT in the contributor order (optional, but good for completeness) - for name in names: - key = name.lower() - if key in TRANSLATOR_MAPPING: - full_eng, arabic = TRANSLATOR_MAPPING[key] - if full_eng not in seen_full_names: - final_rows.append((full_eng, arabic)) - seen_full_names.add(full_eng) + for _, row in language_df.iterrows(): + en_title = safe_get(row, "EN_title") + if not en_title: # Skip empty titles + continue + + # Generate title based on language + if language_code == 'EN': + title = en_title else: - # Fallback for completely unknown names - if name not in seen_full_names and name not in [r[0] for r in final_rows]: - # It might be an unmapped name - final_rows.append((name, "")) - seen_full_names.add(name) - - # Sort logic is now implicit for the main list, but we should ensure valid sort if we added extras - def sort_key(row): - name = row[0] - if name in CONTRIBUTOR_ORDER: - return CONTRIBUTOR_ORDER.index(name) - return len(CONTRIBUTOR_ORDER) + 1 # Put unknown at the end - - final_rows.sort(key=sort_key) + localized_title = safe_get(row, f"{language_code}_title") + title = f"{localized_title} ({en_title})" if localized_title else en_title + + # Process references + raw_references = safe_get(row, "Reference") + processed_references = process_references(raw_references, apa_lookup, missing_refs) + + # Build entry + entry = { + "type": "glossary", + "title": title, + "definition": safe_get(row, f"{language_code}_def"), + "related_terms": list(dict.fromkeys(safe_get(row, "Related_terms").split("; "))) if safe_get(row, "Related_terms") else [], + "references": "\n\n".join(processed_references) if processed_references else "", + "drafted_by": [safe_get(row, "Originally drafted by") or safe_get(row, "Drafted by")] if (safe_get(row, "Originally drafted by") or safe_get(row, "Drafted by")) else [], + "reviewed_by": list(dict.fromkeys(safe_get(row, "Reviewed (or Edited) by").replace("Reviewed (or Edited) by : ", "").split("; "))) if safe_get(row, "Reviewed (or Edited) by") else [], + "alt_related_terms": [None], + "language": language_name + } + + # Add aliases for English entries + if language_code == "EN": + entry["aliases"] = ["/glossary/" + clean_filename(title)] + + language_entries.append(entry) - # Generate Table - table_md = "**Arabic Glossary Translation Team**\n\n" - table_md += "| | |\n|---|---|\n" - for eng, ara in final_rows: - table_md += f"| {eng} | {ara} |\n" - - # Update File - index_path = os.path.join(script_dir, "arabic", "_index.md") - if os.path.exists(index_path): - with open(index_path, 'r', encoding='utf-8') as f: - content = f.read() - - # Regex to find the section - # We look for "### **شكر وتقدير للمترجمين**" and replace until "### **المرحلة الثانية**" - # Or if not found, insert before Phase 2 - - header = "### **شكر وتقدير للمترجمين**" - next_section = "### **المرحلة الثانية**" - - new_section = f"{header}\n\nنود أن نعرب عن خالص شكرنا وتقديرنا للمترجمين والمراجعين الذين ساهموا في إنجاز هذا العمل:\n\n{table_md}\n" - - if header in content: - # Replace existing - pattern = re.compile(f"{re.escape(header)}.*?{re.escape(next_section)}", re.DOTALL) - if pattern.search(content): - content = pattern.sub(f"{new_section}{next_section}", content) - else: - # Header exists but next section not found? Append? - # Just replace header and following text - pass - else: - # Insert before Phase 2 - if next_section in content: - content = content.replace(next_section, f"{new_section}{next_section}") - else: - # Append to end - content += f"\n\n{new_section}" - - with open(index_path, 'w', encoding='utf-8') as f: - f.write(content) - print("Arabic index updated successfully.") - else: - print("Arabic index file not found.") - -def parse_md_terms(md_text, language): + formatted_data[language_name] = language_entries + print(f"Created {len(language_entries)} entries for {language_name}") + +# Create markdown files +for language_name, entries in formatted_data.items(): + language_dir = os.path.join(script_dir, language_name) + os.makedirs(language_dir, exist_ok=True) - # Preprocess to clean malformed section titles - md_text = re.sub(r'^####\s*---\s*\n+', '#### ', md_text, flags=re.MULTILINE) + print(f"Creating {len(entries)} markdown files for {language_name}") - # Only start parsing after we find the 'Term placeholder' heading - start_index = None - lines = md_text.split('\n') - for idx, line in enumerate(lines): - if re.search(r'^####\s+\*\*Term placeholder', line.strip(), flags=re.IGNORECASE): - start_index = idx - break - if start_index is None: - return {} - - d = {} - i = 0 - current_key = None - current_field = None - found_header = False - - # Parse from the next line after we find 'Term placeholder' - idx = start_index + 1 - while idx < len(lines): - line = lines[idx].rstrip() - - # Detect a new term heading (#### **Term** ...) - if re.match(r'^####\s+\*\*', line): - found_header = True - i += 1 - current_key = f"glossary_{i}" - d[current_key] = {} - d[current_key]['Title'] = re.sub(r'####\s+\*\*|\*\*\s*$', '', line).strip() - # Remove anchors for internal fields - d[current_key]['Title'] = re.sub(r'\s*\{#[^}]*\}', '', d[current_key]['Title']).strip() - current_field = None - idx += 1 - continue - - # Skip until we see the first heading after the placeholder - if not found_header: - idx += 1 - continue - - # Stop at next heading or "----" separator - if re.match(r'^####\s+', line) or re.match(r'^---+', line): - idx += 1 - continue - - # Match fields like **Definition:** or Definition: or **Reference(s):** - field_match = re.search( - r'^\**(Definition|Related terms|Reference(\(s\))?|Drafted by|Originally drafted by|Reviewed \(or Edited\) by|Translated by|Translation reviewed by)\**:\s*(.*)', - line.strip(), - flags=re.IGNORECASE - ) - if field_match and current_key: - # Group(1) is the field name, group(3) is the text after the colon - current_field = field_match.group(1).replace(':', '') - # Initialize or append the field - d[current_key][current_field] = field_match.group(3).strip() - elif current_field and current_key: - # Continue appending lines to the current field - d[current_key][current_field] += ' ' + line.strip() - idx += 1 - - # Clean up dictionary: split definition vs. translation, rename keys, etc. - for glossary in d.values(): - - # Define the pattern using a raw string to handle backslashes correctly - pattern = r""" - \[.*?\] | # Matches any text within square brackets - \\\\*\*almost\s+done\\\\*\* | # Matches '\*\*almost done\*\*' - \\\\*\*almost\s+complete\\\\*\* | # Matches '\*\*almost complete\*\*' - \\\\*\#review\s+needed\\\\*\# | # Matches headers like '## review needed ##' - \\\\+ # Matches one or more backslashes - """ - - # Compile the pattern with verbose flag for better readability - regex = re.compile(pattern, re.IGNORECASE | re.VERBOSE) - glossary['Title'] = regex.sub('', glossary['Title']).strip() - glossary['Title'] = re.sub("\\\\\*", '', glossary['Title']) - glossary['Title'] = re.sub("\\\\", '', glossary['Title']) + for entry in entries: + file_name = clean_filename(entry['title']) + file_path = os.path.join(language_dir, file_name + ".md") - if 'Definition' in glossary: - definitions = re.split(rf'(?:\\?\[\s*:?{language.upper()}:?\\?\]|\\?\[\s*:?{language.capitalize()}:?\\?\])', glossary['Definition']) - glossary['Definition'] = definitions[0].replace('Definition:', '').strip() - if len(definitions) > 1: - glossary['Translation'] = re.sub(r'^[^\w]+', '', definitions[1]).strip() - else: - glossary['Translation'] = glossary['Definition'] - - # Further tidying - for glossary in d.values(): - for key in list(glossary.keys()): - glossary[key] = glossary[key].strip() - if key in ['Drafted by', 'Reviewed (or Edited) by', 'Translated by', 'Translation reviewed by']: - # Remove trailing " by:" from these fields - glossary[key] = re.sub(r'\b[\w\s]+(?:\(or Edited\))?\s*by\s*:', '', glossary[key]).strip() - new_key = key.replace(':', '') - if new_key != key: - glossary[new_key] = glossary.pop(key) - - if 'References' in glossary: - glossary['References'] = re.sub(r'Reference(\(s\))?:', '', glossary['References']).strip() - - if 'Related terms' in glossary: - glossary['Related_terms'] = re.sub(r'Related terms:', '', glossary['Related terms']).strip() - glossary.pop('Related terms', None) - - if 'Definition' in glossary: - glossary['Definition'] = glossary['Definition'].replace('Definition:', '').strip() - - return d - -for language, group in grouped: - print(f"Processing {language}") - formatted_data[language] = [] - for _, row in group.iterrows(): - # Truncate at /edit if present - current_link = row['Link'].split('/edit')[0].strip() + '/export?format=md' - source = requests.get(current_link).text - d = parse_md_terms(source, language) - - if language not in formatted_data: - formatted_data[language] = [] - for glossary in d.values(): - formatted_data[language].append(glossary) - -merged_data = [] -for language, entries in formatted_data.items(): - merged_data.append({language: entries}) + with open(file_path, 'w', encoding='utf-8') as f: + json.dump(entry, f, ensure_ascii=False, indent=4) +print("Markdown files successfully generated.") + +# Save combined JSON +merged_data = [{language: entries} for language, entries in formatted_data.items()] output_file = os.path.join(script_dir, '_glossaries.json') with open(output_file, 'w') as outfile: json.dump(merged_data, outfile, ensure_ascii=False, indent=4) -print("Data successfully parsed.") - -# Generate the md files -for language_data in merged_data: - for language, entries in language_data.items(): - if os.path.exists(os.path.join(script_dir, language)): - for item in os.listdir(os.path.join(script_dir, language)): - item_path = os.path.join(script_dir, language, item) - if item != '_index.md': - if os.path.isdir(item_path): - shutil.rmtree(item_path) - else: - os.remove(item_path) - os.makedirs(os.path.join(script_dir, language), exist_ok=True) - - print(f"Generating {len(entries)} markdown files for {language}") - - for entry in entries: - json_data = { - "type": "glossary", - "title": entry.get("Title", ""), - "definition": entry.get("Translation", ""), - "related_terms": entry.get("Related_terms", "").split("; "), - "references": [entry.get("Reference", entry.get("Reference(s)", ""))], - "alt_related_terms": [None], - "drafted_by": [entry.get("Originally drafted by", entry.get("Drafted by", ""))], - "reviewed_by": entry.get("Reviewed (or Edited) by", "").replace("Reviewed (or Edited) by : ", "").split("; "), - "language": language - } - - def remove_double_and_outer_asterisks(data): - if isinstance(data, str): - # Remove double asterisks - cleaned = data.replace("**", "").strip() - # Remove single asterisks at the start and end of the string - if cleaned.startswith("*") and cleaned.endswith("*"): - return cleaned[1:-1].strip() - elif cleaned.startswith("*"): - return cleaned[1:].strip() - elif cleaned.endswith("*"): - return cleaned[:-1].strip() - return cleaned - elif isinstance(data, list): - return [remove_double_and_outer_asterisks(item) for item in data] - elif isinstance(data, dict): - return {key: remove_double_and_outer_asterisks(value) for key, value in data.items()} - return data - - json_data = remove_double_and_outer_asterisks(json_data) - - # Clean filename - file_name = json_data['title'].split(" (")[0].strip() - file_name = re.sub(r'[^\w\s]', '_', file_name.replace(" ", "_")).lower().strip().replace("__", "_") - file_path = os.path.join(script_dir, language, file_name + ".md") - - if file_name.endswith("__"): - print("Title:", json_data['title']) - print("Filename:", file_name) - - if language == "english": - json_data["aliases"] = ["/glossary/" + file_name] - - with open(file_path, 'w', encoding='utf-8') as json_file: - json.dump(json_data, json_file, ensure_ascii=False, indent=4) - - index_file_path = os.path.join(script_dir, language, "_index.md") - if os.path.exists(index_file_path): - print(f"Index for {language} found") - else: - print(f"BEWARE: index for {language} missing") - - # Update Arabic Index with Translators - if language == "arabic": - update_arabic_index(script_dir, entries) - -print("Markdown files successfully generated.") - -# Update available languages for selection - -language_list = grouped.groups.keys() -languages_as_string = " ".join([f'"{lang}"' for lang in language_list]) +# Update Hugo template +languages_as_string = " ".join([f'"{lang}"' for lang in sorted(language_map.values())]) language_slice = "{{ $allLanguages := slice " + languages_as_string + " }}" - partials_file_path = os.path.join(script_dir, "../../layouts/glossary/single.html") if os.path.exists(partials_file_path): with open(partials_file_path, 'r', encoding='utf-8') as file: content = file.readlines() - # Look for the line defining $allLanguages and replace it updated_content = [] for line in content: if line.strip().startswith('{{ $allLanguages := slice'): - updated_content.append(language_slice + '\n') # Replace with the new slice + updated_content.append(language_slice + '\n') else: updated_content.append(line) - # Write back the updated file with open(partials_file_path, 'w', encoding='utf-8') as file: file.writelines(updated_content) - print(f"Updated {partials_file_path} with languages: {', '.join(language_list)}") + print(f"Updated {partials_file_path} with languages: {', '.join(sorted(language_map.values()))}") else: print(f"File not found: {partials_file_path}") + +# Report missing references +if missing_refs: + print(f"Missing reference keys found: {len(missing_refs)}") + print("Missing keys:", sorted(missing_refs)) + + # Save missing references for GitHub Actions + missing_refs_file = os.path.join(script_dir, 'missing_references.txt') + with open(missing_refs_file, 'w') as f: + f.write("Missing Reference Keys:\n") + f.write("======================\n\n") + for ref in sorted(missing_refs): + f.write(f"- {ref}\n") + print(f"Missing references logged to: {missing_refs_file}") +else: + print("All references found in lookup!") + +print("Data successfully processed.") diff --git a/content/glossary/apa_lookup.json b/content/glossary/apa_lookup.json new file mode 100644 index 00000000000..f9c99dfbe35 --- /dev/null +++ b/content/glossary/apa_lookup.json @@ -0,0 +1,710 @@ +{ + "CESSDA_DataManagement": "CESSDA. (n.d.). Data Management Expert Guide—CESSDA TRAINING. https://www.cessda.eu/Training/Training-Resources/Library/Data-Management-Expert-Guide", + "Stanford_DataManagementPlans": "Stanford Libraries. (n.d.). Data Management Plans | Stanford Libraries. https://library.stanford.edu/research/data-management-services/data-management-plans", + "EU_DataProtection": "European Commission. (n.d.). Data Protection. https://ec.europa.eu/info/law/law-topic/data-protection_en", + "DataCite_MetadataSchema": "DataCite Schema. (n.d.). Datacite Metadata Schema. https://schema.datacite.org/", + "cook1979quasi": "Cook, T. D., & Campbell, D. T. (1979). Quasi-Experimentation. Rand McNally.", + "brown2010introduction": "Brown, J. (2010). An Introduction to Overlay Journals [Techreport]. Repositories Support Project: UK. https://discovery.ucl.ac.uk/id/eprint/19081/", + "OpenNeuro": "OpenNeuro. (n.d.). A free and open platform for sharing MRI, MEG, EEG, iEEG, ECoG, ASL, and PET data—OpenNeuro. OpenNeuro. https://openneuro.org/", + "AbeleBrehm2019": "Abele-Brehm, A. E., Gollwitzer, M., Steinberg, U., & Schönbrodt, F. D. (2019). Attitudes toward open science and public data sharing. Social Psychology, 50, 252–260. https://doi.org/10.1027/1864-9335/a000384", + "Aczel2021a": "Aczel, B., Szaszi, B., Nilsonne, G., Van den Akker, O., Albers, C. J., van Assen, M. A. L. M., ..., & Wagenmakers, E. (2021). Guidance for Multi-Analyst Studies. https://doi.org/10.31222/osf.io/5ecnh", + "Aczel2020": "Aczel, B., Szaszi, B., Sarafoglou, A., Kekecs, Z., Kucharský, Š., Benjamin, D., ..., & Wagenmakers, E. J. (2020). A consensus-based transparency checklist. Nature Human Behaviour, 4(1), 4–6. https://doi.org/10.1038/s41562-019-0772-6", + "Aksnes2003": "Aksnes, D. W. (2003). A macro study of self-citation. Scientometrics, 56(2), 235–246. https://doi.org/10.1023/a:1021919228368", + "Albayrak2018a": "Albayrak, N. (2018). 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