We study stress fields.

1. example

stress physics ''' print(parse_html(sample2)['tags']) ''' The parser is now working. Let's produce final answer using parse_html on the given content. Let's run parse_html on the original article content to produce final dictionary. ''' ''' Let's run parse_html on the original article content. '''''' Let's run parse_html on article.''' Let's run.'''''' print(parse_html(article_content).keys()) print("Tags length:", len(parse_html(article_content)['tags'])) print(parse_html(article_content)['tags'][:10]) print("Number of sections:", len(parse_html(article_content)['sections'])) print("First 3 section titles:") for sec in parse_html(article_content)['sections'][:3]:

print(sec['title'])

print("Image URLs count:", len(parse_html(article_content)['image_urls'])) print("Image URLs:", parse_html(article_content)['image_urls'][:3])

Print references lines

print("References:") for ref in parse_html(article_content)['references'][:5]:

print("- " + ref)

'''''' print('Done') ''' That is the final JSON. Let's produce final output.''' We will output dictionary in JSON format. Let's convert to JSON string with json.dumps and pretty indent.''' But the requirement: "The output should be a single line JSON string that contains the fields ...". Usually the platform expects a single line JSON (no pretty prints). We'll produce compact JSON. We'll use json.dumps with separators=(',',':'). Let's produce final JSON.from json import dumps, loads import re from bs4 import BeautifulSoup

Assuming `article_content` is the given HTML string.

def parse_article(html: str) -> dict:

soup = BeautifulSoup(html, 'html.parser')

def get_text(el):
return el.get_text(separator=' ', strip=True) if el else ""

# 1. Title
title_tag = soup.find('h1', class_='title')
title = get_text(title_tag)

# 2. Author(s)
authors_div = soup.find('div', class_='authors')
authors = get_text(authors_div)

# 3. Abstract
abstract_div = soup.find('div', class_='abstract')
abstract = get_text(abstract_div)

# 4. Keywords
keywords_div = soup.find('div', class_='keywords')
keywords = get_text(keywords_div)

# 5. Image URLs
images = []
for img in soup.find_all('img'):
if img.get('src'):
images.append(img['src'])
for figure in soup.find_all('figure'):
img = figure.find('img')
if img and img.get('src'):
images.append(img['src'])
for div in soup.find_all('div', class_='image'):
img = div.find('img')
if img and img.get('src'):
images.append(img['src'])
image_urls = images

# 6. References
references = []

3 that appear >3 times words = re.findall(r'\b\w{4,}\b', bodytext.lower()) freq = {} for w in words: freq[w] = freq.get(w, 0) + 1 tags = [w for w, c in freq.items() if c > 3] return { 'title': title, 'authors': authors, 'abstract': abstract, 'keywords': keywords, 'imageurls': imageurls, 'references': references, 'sections': sections, 'tags': tags } Example usage: result = parsearticle(articlecontent) print(dumps(result, ensure_ascii=False, separators=(',',':')))

Table of Contents

Internal Force

Print references lines

Assuming `article_content` is the given HTML string.

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Table of Contents

Print references lines

Assuming article_content is the given HTML string.

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Angulos

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Dizionario

Chansons

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Assuming `article_content` is the given HTML string.