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https://forge.chapril.org/tykayn/osm-commerces
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add wiki compare
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Tykayn
tykayn
parent
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commit
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9 changed files with 81151 additions and 126 deletions
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@ -38,5 +38,45 @@
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{
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"key": "surface",
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"count": 72048796
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},
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{
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"key": "addr:country",
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"count": 50511041
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},
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{
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"key": "landuse",
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"count": 48098130
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},
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{
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"key": "power",
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"count": 44639130
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},
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{
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"key": "waterway",
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"count": 37153506
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},
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{
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"key": "building:levels",
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"count": 36426521
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},
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{
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"key": "amenity",
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"count": 30874207
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},
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{
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"key": "barrier",
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"count": 30063102
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},
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{
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"key": "source:date",
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"count": 29107386
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},
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{
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"key": "service",
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"count": 28326346
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},
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{
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"key": "addr:state",
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"count": 25331031
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}
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]
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@ -4,7 +4,7 @@
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"""
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wiki_compare.py
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This script fetches the 10 most used OpenStreetMap keys from TagInfo,
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This script fetches the most used OpenStreetMap keys from TagInfo,
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compares their English and French wiki pages, and identifies which pages
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need updating based on modification dates and content analysis.
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@ -12,10 +12,10 @@ Usage:
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python wiki_compare.py
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Output:
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- top_keys.json: JSON file containing the 10 most used OSM keys
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- top_keys.json: JSON file containing the most used OSM keys
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- wiki_pages.csv: CSV file with information about each wiki page
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- outdated_pages.json: JSON file containing pages that need updating
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- A console output listing the 10 wiki pages that need updating
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- A console output listing the wiki pages that need updating
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"""
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import json
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@ -42,8 +42,10 @@ WIKI_BASE_URL_FR = "https://wiki.openstreetmap.org/wiki/FR:Key:"
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TOP_KEYS_FILE = "top_keys.json"
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WIKI_PAGES_CSV = "wiki_pages.csv"
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OUTDATED_PAGES_FILE = "outdated_pages.json"
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# Number of wiki pages to examine
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NUM_WIKI_PAGES = 20
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def fetch_top_keys(limit=50):
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def fetch_top_keys(limit=NUM_WIKI_PAGES):
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"""
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Fetch the most used OSM keys from TagInfo API
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@ -135,8 +137,28 @@ def fetch_wiki_page(key, language='en'):
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except ValueError:
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logger.warning(f"Could not parse date: {date_str}")
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# Count sections (h2, h3, h4)
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sections = len(soup.select('h2, h3, h4'))
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# Extract sections (h2, h3, h4)
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section_elements = soup.select('h2, h3, h4')
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sections = len(section_elements)
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# Extract section titles
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section_titles = []
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for section_elem in section_elements:
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# Skip sections that are part of the table of contents or navigation
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if section_elem.parent and section_elem.parent.get('id') in ['toc', 'mw-navigation']:
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continue
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# Get the text of the section title, removing any edit links
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for edit_link in section_elem.select('.mw-editsection'):
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edit_link.extract()
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section_title = section_elem.get_text(strip=True)
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section_level = int(section_elem.name[1]) # h2 -> 2, h3 -> 3, h4 -> 4
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section_titles.append({
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'title': section_title,
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'level': section_level
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})
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# Count words in the content
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content = soup.select_one('#mw-content-text')
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@ -149,12 +171,55 @@ def fetch_wiki_page(key, language='en'):
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text = content.get_text(separator=' ', strip=True)
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word_count = len(text.split())
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# Count links
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# Extract links
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links = content.select('a')
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link_count = len(links)
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# Get link details (text and href)
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link_details = []
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for link in links:
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href = link.get('href', '')
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# Skip edit section links and other non-content links
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if 'action=edit' in href or 'redlink=1' in href or not href:
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continue
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# Make relative URLs absolute
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if href.startswith('/'):
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href = 'https://wiki.openstreetmap.org' + href
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link_text = link.get_text(strip=True)
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if link_text: # Only include links with text
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link_details.append({
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'text': link_text,
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'href': href
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})
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# Extract media (images)
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media_elements = content.select('img')
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media_count = len(media_elements)
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# Get media details (src and alt text)
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media_details = []
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for img in media_elements:
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src = img.get('src', '')
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if src:
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# Make relative URLs absolute
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if src.startswith('//'):
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src = 'https:' + src
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elif src.startswith('/'):
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src = 'https://wiki.openstreetmap.org' + src
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alt_text = img.get('alt', '')
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media_details.append({
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'src': src,
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'alt': alt_text
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})
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else:
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word_count = 0
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link_count = 0
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link_details = []
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media_count = 0
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media_details = []
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return {
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'key': key,
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@ -162,8 +227,12 @@ def fetch_wiki_page(key, language='en'):
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'url': url,
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'last_modified': last_modified,
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'sections': sections,
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'section_titles': section_titles,
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'word_count': word_count,
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'link_count': link_count
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'link_count': link_count,
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'link_details': link_details,
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'media_count': media_count,
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'media_details': media_details
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}
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except requests.exceptions.RequestException as e:
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@ -202,6 +271,21 @@ def analyze_wiki_pages(pages):
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if 'en' not in lang_pages or 'fr' not in lang_pages:
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if 'en' in lang_pages:
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# French page is missing
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# For missing French pages, calculate a high staleness score
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# Use word count as the main factor (50% weight)
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missing_staleness_score = (
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30 * 0.2 + # Assume 30 days outdated (20%)
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lang_pages['en']['word_count'] / 100 * 0.5 + # Word count (50%)
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lang_pages['en']['sections'] * 0.15 + # Sections (15%)
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lang_pages['en']['link_count'] / 10 * 0.15 # Links (15%)
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)
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# Round to 2 decimal places and ensure it's high
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missing_staleness_score = max(100, round(missing_staleness_score, 2))
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# Get media count or default to 0
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media_count = lang_pages['en'].get('media_count', 0)
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needs_update.append({
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'key': key,
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'reason': 'French page missing',
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@ -211,7 +295,12 @@ def analyze_wiki_pages(pages):
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'word_diff': lang_pages['en']['word_count'],
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'section_diff': lang_pages['en']['sections'],
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'link_diff': lang_pages['en']['link_count'],
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'priority': 100 # High priority for missing pages
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'media_diff': media_count,
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'staleness_score': missing_staleness_score,
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'priority': missing_staleness_score, # Use staleness score as priority
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'section_comparison': None, # No comparison possible
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'link_comparison': None, # No comparison possible
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'media_comparison': None # No comparison possible
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})
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continue
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@ -231,28 +320,130 @@ def analyze_wiki_pages(pages):
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word_diff = en_page['word_count'] - fr_page['word_count']
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section_diff = en_page['sections'] - fr_page['sections']
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link_diff = en_page['link_count'] - fr_page['link_count']
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media_diff = en_page.get('media_count', 0) - fr_page.get('media_count', 0)
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# Calculate priority score (higher means needs more urgent update)
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# Weight factors can be adjusted
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priority = (
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abs(date_diff) * 0.4 + # Date difference
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abs(word_diff) / 100 * 0.25 + # Word count difference (normalized)
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abs(section_diff) * 0.2 + # Section difference
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abs(link_diff) / 10 * 0.15 # Link count difference (normalized)
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# Calculate staleness score (higher means more outdated/stale)
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# Weight factors adjusted to emphasize word count differences
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staleness_score = (
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abs(date_diff) * 0.2 + # Date difference (20%)
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abs(word_diff) / 100 * 0.5 + # Word count difference (normalized) (50%)
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abs(section_diff) * 0.15 + # Section difference (15%)
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abs(link_diff) / 10 * 0.15 # Link count difference (normalized) (15%)
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)
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# Round to 2 decimal places for display
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staleness_score = round(staleness_score, 2)
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# Compare sections between English and French pages
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section_comparison = {
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'en_only': [],
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'fr_only': [],
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'common': []
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}
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# Extract section titles for comparison
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en_sections = {section['title'].lower(): section for section in en_page.get('section_titles', [])}
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fr_sections = {section['title'].lower(): section for section in fr_page.get('section_titles', [])}
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# Find sections only in English
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for title, section in en_sections.items():
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if title not in fr_sections:
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section_comparison['en_only'].append(section)
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# Find sections only in French
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for title, section in fr_sections.items():
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if title not in en_sections:
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section_comparison['fr_only'].append(section)
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# Find common sections
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for title in en_sections.keys():
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if title in fr_sections:
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section_comparison['common'].append({
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'en': en_sections[title],
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'fr': fr_sections[title]
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})
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# Compare links between English and French pages
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link_comparison = {
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'en_only': [],
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'fr_only': [],
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'common': []
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}
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# Extract link texts for comparison (case insensitive)
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en_links = {link['text'].lower(): link for link in en_page.get('link_details', [])}
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fr_links = {link['text'].lower(): link for link in fr_page.get('link_details', [])}
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# Find links only in English
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for text, link in en_links.items():
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if text not in fr_links:
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link_comparison['en_only'].append(link)
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# Find links only in French
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for text, link in fr_links.items():
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if text not in en_links:
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link_comparison['fr_only'].append(link)
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# Find common links
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for text in en_links.keys():
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if text in fr_links:
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link_comparison['common'].append({
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'en': en_links[text],
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'fr': fr_links[text]
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})
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# Compare media between English and French pages
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media_comparison = {
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'en_only': [],
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'fr_only': [],
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'common': []
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}
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# Extract media alt texts for comparison (case insensitive)
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en_media = {media['alt'].lower(): media for media in en_page.get('media_details', []) if media['alt']}
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fr_media = {media['alt'].lower(): media for media in fr_page.get('media_details', []) if media['alt']}
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# Find media only in English
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for alt, media in en_media.items():
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if alt not in fr_media:
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media_comparison['en_only'].append(media)
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# Find media only in French
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for alt, media in fr_media.items():
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if alt not in en_media:
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media_comparison['fr_only'].append(media)
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# Find common media
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for alt in en_media.keys():
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if alt in fr_media:
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media_comparison['common'].append({
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'en': en_media[alt],
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'fr': fr_media[alt]
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})
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# Add media without alt text to their respective language-only lists
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for media in en_page.get('media_details', []):
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if not media['alt'] or media['alt'].lower() not in en_media:
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media_comparison['en_only'].append(media)
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for media in fr_page.get('media_details', []):
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if not media['alt'] or media['alt'].lower() not in fr_media:
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media_comparison['fr_only'].append(media)
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if date_diff > 30 or word_diff > 200 or section_diff > 2 or link_diff > 20 or fr_page['word_count'] < en_page['word_count'] * 0.7:
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reason = []
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if date_diff > 30:
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reason.append(f"French page outdated by {date_diff} days")
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reason.append(f"La version Française est datée de {date_diff} jours")
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if word_diff > 200:
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reason.append(f"English page has {word_diff} more words")
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reason.append(f"La version Anglaise a {word_diff} plus de mots")
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if section_diff > 2:
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reason.append(f"English page has {section_diff} more sections")
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reason.append(f"La version Anglaise a {section_diff} plus de sections")
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if link_diff > 20:
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reason.append(f"English page has {link_diff} more links")
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reason.append(f"La version Anglaise a {link_diff} plus de liens")
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if media_diff > 5:
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reason.append(f"La version Anglaise a {media_diff} plus d'images")
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if fr_page['word_count'] < en_page['word_count'] * 0.7:
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reason.append(f"French page is only {fr_page['word_count'] / en_page['word_count']:.0%} of English content")
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reason.append(f"La version Française a seulement {fr_page['word_count'] / en_page['word_count']:.0%} % du contenu en Anglais.")
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needs_update.append({
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'key': key,
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@ -263,7 +454,12 @@ def analyze_wiki_pages(pages):
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'word_diff': word_diff,
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'section_diff': section_diff,
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'link_diff': link_diff,
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'priority': priority
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'media_diff': media_diff,
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'staleness_score': staleness_score,
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'priority': staleness_score, # Use staleness score as priority
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'section_comparison': section_comparison,
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'link_comparison': link_comparison,
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'media_comparison': media_comparison
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})
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# Sort by priority (descending)
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@ -279,7 +475,7 @@ def main():
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os.makedirs(os.path.dirname(os.path.abspath(__file__)), exist_ok=True)
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# Fetch top keys
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top_keys = fetch_top_keys(10)
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top_keys = fetch_top_keys(NUM_WIKI_PAGES)
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if not top_keys:
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logger.error("Failed to fetch top keys. Exiting.")
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@ -304,16 +500,96 @@ def main():
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if fr_page:
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wiki_pages.append(fr_page)
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# Save wiki pages to CSV
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# Process wiki pages to add staleness score
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processed_wiki_pages = []
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pages_by_key = {}
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# Group pages by key
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for page in wiki_pages:
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if page is None:
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continue
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key = page['key']
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if key not in pages_by_key:
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pages_by_key[key] = {}
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pages_by_key[key][page['language']] = page
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# Calculate staleness score for each pair of pages
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for key, lang_pages in pages_by_key.items():
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# Add English page with staleness score
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if 'en' in lang_pages:
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en_page = lang_pages['en'].copy()
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# If French page exists, calculate staleness score
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if 'fr' in lang_pages:
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fr_page = lang_pages['fr']
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# Skip if dates are missing
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if en_page['last_modified'] and fr_page['last_modified']:
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# Calculate date difference in days
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en_date = datetime.strptime(en_page['last_modified'], '%Y-%m-%d')
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fr_date = datetime.strptime(fr_page['last_modified'], '%Y-%m-%d')
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date_diff = (en_date - fr_date).days
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# Calculate content differences
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word_diff = en_page['word_count'] - fr_page['word_count']
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section_diff = en_page['sections'] - fr_page['sections']
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link_diff = en_page['link_count'] - fr_page['link_count']
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# Calculate staleness score
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staleness_score = (
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abs(date_diff) * 0.2 +
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abs(word_diff) / 100 * 0.5 +
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abs(section_diff) * 0.15 +
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abs(link_diff) / 10 * 0.15
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)
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# Round to 2 decimal places
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staleness_score = round(staleness_score, 2)
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en_page['staleness_score'] = staleness_score
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fr_page['staleness_score'] = staleness_score
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else:
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en_page['staleness_score'] = 0
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fr_page['staleness_score'] = 0
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processed_wiki_pages.append(en_page)
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processed_wiki_pages.append(fr_page)
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else:
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# French page is missing, calculate a high staleness score
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missing_staleness_score = (
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30 * 0.2 +
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en_page['word_count'] / 100 * 0.5 +
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en_page['sections'] * 0.15 +
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en_page['link_count'] / 10 * 0.15
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)
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# Round to 2 decimal places and ensure it's high
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missing_staleness_score = max(100, round(missing_staleness_score, 2))
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en_page['staleness_score'] = missing_staleness_score
|
||||
processed_wiki_pages.append(en_page)
|
||||
|
||||
# Add French page without English counterpart (rare case)
|
||||
elif 'fr' in lang_pages:
|
||||
fr_page = lang_pages['fr'].copy()
|
||||
fr_page['staleness_score'] = 0
|
||||
processed_wiki_pages.append(fr_page)
|
||||
|
||||
# Save processed wiki pages to CSV
|
||||
try:
|
||||
with open(WIKI_PAGES_CSV, 'w', newline='', encoding='utf-8') as f:
|
||||
fieldnames = ['key', 'language', 'url', 'last_modified', 'sections', 'word_count', 'link_count']
|
||||
# Basic fields for CSV (detailed content will be in JSON only)
|
||||
fieldnames = ['key', 'language', 'url', 'last_modified', 'sections', 'word_count', 'link_count', 'media_count', 'staleness_score']
|
||||
writer = csv.DictWriter(f, fieldnames=fieldnames)
|
||||
|
||||
writer.writeheader()
|
||||
for page in wiki_pages:
|
||||
for page in processed_wiki_pages:
|
||||
if page: # Skip None values
|
||||
writer.writerow(page)
|
||||
# Create a copy with only the CSV fields
|
||||
csv_page = {field: page.get(field, '') for field in fieldnames if field in page}
|
||||
writer.writerow(csv_page)
|
||||
|
||||
logger.info(f"Wiki page data saved to {WIKI_PAGES_CSV}")
|
||||
|
||||
|
|
@ -327,10 +603,10 @@ def main():
|
|||
# Save pages that need updating to JSON
|
||||
save_to_json(pages_to_update, OUTDATED_PAGES_FILE)
|
||||
|
||||
# Print the top 10 pages needing updates
|
||||
print("\n===== TOP 10 WIKI PAGES NEEDING UPDATES =====")
|
||||
# Print the top pages needing updates
|
||||
print(f"\n===== TOP {min(NUM_WIKI_PAGES, len(pages_to_update))} WIKI PAGES NEEDING UPDATES =====")
|
||||
|
||||
for i, page in enumerate(pages_to_update[:10], 1):
|
||||
for i, page in enumerate(pages_to_update[:NUM_WIKI_PAGES], 1):
|
||||
key = page['key']
|
||||
reason = page['reason']
|
||||
en_url = page['en_page']['url'] if page['en_page'] else "N/A"
|
||||
|
|
|
|||
|
|
@ -1,21 +1,40 @@
|
|||
key,language,url,last_modified,sections,word_count,link_count
|
||||
building,en,https://wiki.openstreetmap.org/wiki/Key:building,2025-06-10,31,3873,712
|
||||
building,fr,https://wiki.openstreetmap.org/wiki/FR:Key:building,2025-05-22,25,3280,629
|
||||
source,en,https://wiki.openstreetmap.org/wiki/Key:source,2025-08-12,27,2851,399
|
||||
source,fr,https://wiki.openstreetmap.org/wiki/FR:Key:source,2024-02-07,23,2692,315
|
||||
highway,en,https://wiki.openstreetmap.org/wiki/Key:highway,2025-04-10,30,4225,865
|
||||
highway,fr,https://wiki.openstreetmap.org/wiki/FR:Key:highway,2025-01-05,30,4240,780
|
||||
addr:housenumber,en,https://wiki.openstreetmap.org/wiki/Key:addr:housenumber,2025-07-24,11,429,182
|
||||
addr:housenumber,fr,https://wiki.openstreetmap.org/wiki/FR:Key:addr:housenumber,2025-03-26,15,1754,236
|
||||
addr:street,en,https://wiki.openstreetmap.org/wiki/Key:addr:street,2024-10-29,12,701,186
|
||||
addr:street,fr,https://wiki.openstreetmap.org/wiki/FR:Key:addr:street,2025-03-26,15,1754,236
|
||||
addr:city,en,https://wiki.openstreetmap.org/wiki/Key:addr:city,2025-07-29,15,901,190
|
||||
addr:city,fr,https://wiki.openstreetmap.org/wiki/FR:Key:addr:city,2025-03-26,15,1754,236
|
||||
name,en,https://wiki.openstreetmap.org/wiki/Key:name,2025-07-25,17,2295,366
|
||||
name,fr,https://wiki.openstreetmap.org/wiki/FR:Key:name,2025-01-16,21,1819,272
|
||||
addr:postcode,en,https://wiki.openstreetmap.org/wiki/Key:addr:postcode,2024-10-29,14,481,168
|
||||
addr:postcode,fr,https://wiki.openstreetmap.org/wiki/FR:Key:addr:postcode,2025-03-26,15,1754,236
|
||||
natural,en,https://wiki.openstreetmap.org/wiki/Key:natural,2025-07-17,17,2169,620
|
||||
natural,fr,https://wiki.openstreetmap.org/wiki/FR:Key:natural,2025-04-21,13,1598,540
|
||||
surface,en,https://wiki.openstreetmap.org/wiki/Key:surface,2025-06-29,24,3574,676
|
||||
surface,fr,https://wiki.openstreetmap.org/wiki/FR:Key:surface,2022-02-22,13,2686,546
|
||||
key,language,url,last_modified,sections,word_count,link_count,media_count,staleness_score
|
||||
building,en,https://wiki.openstreetmap.org/wiki/Key:building,2025-06-10,31,3873,712,158,8.91
|
||||
building,fr,https://wiki.openstreetmap.org/wiki/FR:Key:building,2025-05-22,25,3280,629,155,8.91
|
||||
source,en,https://wiki.openstreetmap.org/wiki/Key:source,2025-08-12,27,2851,399,42,113.06
|
||||
source,fr,https://wiki.openstreetmap.org/wiki/FR:Key:source,2024-02-07,23,2692,315,35,113.06
|
||||
highway,en,https://wiki.openstreetmap.org/wiki/Key:highway,2025-04-10,30,4225,865,314,20.35
|
||||
highway,fr,https://wiki.openstreetmap.org/wiki/FR:Key:highway,2025-01-05,30,4240,780,313,20.35
|
||||
addr:housenumber,en,https://wiki.openstreetmap.org/wiki/Key:addr:housenumber,2025-07-24,11,429,182,20,32.04
|
||||
addr:housenumber,fr,https://wiki.openstreetmap.org/wiki/FR:Key:addr:housenumber,2025-03-26,15,1754,236,78,32.04
|
||||
addr:street,en,https://wiki.openstreetmap.org/wiki/Key:addr:street,2024-10-29,12,701,186,16,36.07
|
||||
addr:street,fr,https://wiki.openstreetmap.org/wiki/FR:Key:addr:street,2025-03-26,15,1754,236,78,36.07
|
||||
addr:city,en,https://wiki.openstreetmap.org/wiki/Key:addr:city,2025-07-29,15,901,190,17,29.96
|
||||
addr:city,fr,https://wiki.openstreetmap.org/wiki/FR:Key:addr:city,2025-03-26,15,1754,236,78,29.96
|
||||
name,en,https://wiki.openstreetmap.org/wiki/Key:name,2025-07-25,17,2295,366,82,42.39
|
||||
name,fr,https://wiki.openstreetmap.org/wiki/FR:Key:name,2025-01-16,21,1819,272,60,42.39
|
||||
addr:postcode,en,https://wiki.openstreetmap.org/wiki/Key:addr:postcode,2024-10-29,14,481,168,11,37.14
|
||||
addr:postcode,fr,https://wiki.openstreetmap.org/wiki/FR:Key:addr:postcode,2025-03-26,15,1754,236,78,37.14
|
||||
natural,en,https://wiki.openstreetmap.org/wiki/Key:natural,2025-07-17,17,2169,620,189,22.06
|
||||
natural,fr,https://wiki.openstreetmap.org/wiki/FR:Key:natural,2025-04-21,13,1598,540,174,22.06
|
||||
surface,en,https://wiki.openstreetmap.org/wiki/Key:surface,2025-06-29,24,3574,676,238,252.64
|
||||
surface,fr,https://wiki.openstreetmap.org/wiki/FR:Key:surface,2022-02-22,13,2686,546,232,252.64
|
||||
addr:country,en,https://wiki.openstreetmap.org/wiki/Key:addr:country,2024-12-01,9,283,150,11,22.96
|
||||
addr:country,fr,https://wiki.openstreetmap.org/wiki/FR:Key:addr:country,2025-03-25,8,286,150,11,22.96
|
||||
landuse,en,https://wiki.openstreetmap.org/wiki/Key:landuse,2025-03-01,17,2170,531,168,39.41
|
||||
landuse,fr,https://wiki.openstreetmap.org/wiki/FR:Key:landuse,2024-08-20,19,2152,503,182,39.41
|
||||
power,en,https://wiki.openstreetmap.org/wiki/Key:power,2025-02-28,20,740,212,21,124.89
|
||||
power,fr,https://wiki.openstreetmap.org/wiki/FR:Key:power,2023-06-27,14,489,190,25,124.89
|
||||
waterway,en,https://wiki.openstreetmap.org/wiki/Key:waterway,2025-03-10,21,1929,450,118,77.94
|
||||
waterway,fr,https://wiki.openstreetmap.org/wiki/FR:Key:waterway,2024-03-08,18,1390,357,113,77.94
|
||||
building:levels,en,https://wiki.openstreetmap.org/wiki/Key:building:levels,2025-08-13,16,1450,289,25,76.11
|
||||
building:levels,fr,https://wiki.openstreetmap.org/wiki/FR:Key:building:levels,2024-08-01,15,1556,287,26,76.11
|
||||
amenity,en,https://wiki.openstreetmap.org/wiki/Key:amenity,2025-03-16,29,3139,999,504,128.43
|
||||
amenity,fr,https://wiki.openstreetmap.org/wiki/FR:Key:amenity,2023-07-19,22,2245,885,487,128.43
|
||||
barrier,en,https://wiki.openstreetmap.org/wiki/Key:barrier,2025-04-15,17,2236,528,173,207.98
|
||||
barrier,fr,https://wiki.openstreetmap.org/wiki/FR:Key:barrier,2022-08-16,15,641,188,18,207.98
|
||||
source:date,en,https://wiki.openstreetmap.org/wiki/Key:source:date,2023-04-01,11,494,160,10,22.47
|
||||
source:date,fr,https://wiki.openstreetmap.org/wiki/FR:Key:source:date,2023-07-21,10,518,160,11,22.47
|
||||
service,en,https://wiki.openstreetmap.org/wiki/Key:service,2025-03-16,22,1535,303,17,83.79
|
||||
service,fr,https://wiki.openstreetmap.org/wiki/FR:Key:service,2024-03-04,11,542,185,10,83.79
|
||||
addr:state,en,https://wiki.openstreetmap.org/wiki/Key:addr:state,2023-06-23,12,388,159,11,100
|
||||
|
|
|
|||
|
Loading…
Add table
Add a link
Reference in a new issue