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"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Web Scrape Oura Ring App Content"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from selenium import webdriver\n",
"from selenium.webdriver.chrome.options import Options\n",
"from selenium.webdriver.common.by import By\n",
"import time\n",
"import re\n",
"\n",
"# Setup Chrome options\n",
"chrome_options = Options()\n",
"chrome_options.add_argument(\"--headless\")\n",
"chrome_options.add_argument(\"--disable-gpu\")\n",
"chrome_options.add_argument(\"--no-sandbox\")\n",
"chrome_options.add_argument(\"user-agent=Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36\")\n",
"\n",
"# Initialize the WebDriver\n",
"driver = webdriver.Chrome(options=chrome_options)\n",
"\n",
"# Open the main page containing the list of articles\n",
"url = \"https://support.ouraring.com/hc/en-us/categories/27782541623059-Oura-App\"\n",
"driver.get(url)\n",
"time.sleep(3)\n",
"\n",
"# section_links = [link.get_attribute(\"href\") for link in driver.find_elements(By.XPATH, \"//h3[contains(@class, 'section-tree-title')]/a\")]\n",
"section_links = ['https://support.ouraring.com/hc/en-us/sections/9721296007827-App-Settings',\n",
" 'https://support.ouraring.com/hc/en-us/sections/9721508785171-App-Integrations',\n",
" 'https://support.ouraring.com/hc/en-us/sections/4415723882003-Readiness',\n",
" 'https://support.ouraring.com/hc/en-us/sections/4415717595155-Sleep',\n",
" 'https://support.ouraring.com/hc/en-us/sections/4415723875347-Activity',\n",
" 'https://support.ouraring.com/hc/en-us/sections/4415730373779-Insights-Reports',\n",
" 'https://support.ouraring.com/hc/en-us/sections/28332751996435-Heart-Health',\n",
" 'https://support.ouraring.com/hc/en-us/sections/17984010150803-Women-s-Health',\n",
" 'https://support.ouraring.com/hc/en-us/sections/4415723874451-Mindfulness-Meditation']\n",
"\n",
"articles_data = []\n",
"\n",
"# Function to split large sections into smaller RAG-friendly chunks\n",
"def chunk_text(text, chunk_size=512):\n",
" \n",
" # Split text into sentences and list items\n",
" list_item_pattern = re.compile(r\"^(\\d+\\.\\s+|- )\") \n",
" lines = text.split(\"\\n\") \n",
"\n",
" chunks = []\n",
" current_chunk = \"\"\n",
"\n",
" for line in lines:\n",
" line = line.strip()\n",
" if not line:\n",
" continue \n",
" \n",
" # Check if this line starts a new list item\n",
" is_list_item = bool(list_item_pattern.match(line))\n",
" \n",
" if is_list_item and current_chunk and len(current_chunk) + len(line) >= chunk_size:\n",
" chunks.append(current_chunk.strip())\n",
" current_chunk = line \n",
" elif len(current_chunk) + len(line) >= chunk_size:\n",
" chunks.append(current_chunk.strip())\n",
" current_chunk = line \n",
" else:\n",
" current_chunk += \"\\n\" + line \n",
" \n",
" if current_chunk:\n",
" chunks.append(current_chunk.strip()) \n",
"\n",
" return chunks\n",
"\n",
"\n",
"def extractSectionChunks(driver):\n",
" # Extract article title\n",
" title_element = driver.find_element(By.XPATH, \"//h1[contains(@class, 'article-title')]\")\n",
" article_title = title_element.text if title_element else \"No Title Found\"\n",
"\n",
" # Extract all content divs\n",
" content_elements = driver.find_elements(By.XPATH, \"//div[contains(@class, 'article-body')]/*\")\n",
"\n",
" chunks = []\n",
" intro_content = []\n",
" current_section = None\n",
" sections = []\n",
" chunk_id = 1 \n",
"\n",
" for element in content_elements:\n",
" tag_name = element.tag_name.lower()\n",
" text = element.text.strip()\n",
"\n",
" if not text:\n",
" continue \n",
"\n",
" # If a header is encountered, start a new section\n",
" if tag_name in [\"h2\"]:\n",
" # Store previous section\n",
" if current_section:\n",
" sections.append(current_section)\n",
" \n",
" # Start a new section\n",
" current_section = {\"section_title\": text, \"content\": []}\n",
" elif tag_name == \"ol\":\n",
" # Handle ordered (numbered) lists\n",
" list_items = element.find_elements(By.TAG_NAME, \"li\")\n",
" list_text = \"\\n\".join([f\"{idx+1}. {li.text.strip()}\" for idx, li in enumerate(list_items) if li.text.strip()])\n",
" if current_section:\n",
" current_section[\"content\"].append(list_text)\n",
" else:\n",
" intro_content.append(list_text)\n",
" elif tag_name == \"ul\":\n",
" # Handle unordered (bulleted) lists\n",
" list_items = element.find_elements(By.TAG_NAME, \"li\")\n",
" list_text = \"\\n\".join([f\"- {li.text.strip()}\" for li in list_items if li.text.strip()])\n",
" if current_section:\n",
" current_section[\"content\"].append(list_text)\n",
" else:\n",
" intro_content.append(list_text)\n",
" else:\n",
" if current_section:\n",
" current_section[\"content\"].append(text)\n",
" else:\n",
" # This is part of the introduction\n",
" intro_content.append(text)\n",
"\n",
" # Store last section\n",
" if current_section:\n",
" sections.append(current_section)\n",
"\n",
" # Store introduction **FIRST**\n",
" if intro_content:\n",
" intro_chunks = chunk_text(\"\\n\".join(intro_content))\n",
" for chunk in intro_chunks:\n",
" chunks.append({\n",
" \"article_title\": article_title,\n",
" \"section_title\": \"Introduction\",\n",
" \"chunk\": chunk,\n",
" \"chunk_id\": chunk_id, \n",
" \"link\": article_link\n",
" })\n",
" chunk_id += 1 \n",
"\n",
" # Store all sections\n",
" for section in sections:\n",
" section_chunks = chunk_text(\"\\n\".join(section[\"content\"]))\n",
" for chunk in section_chunks:\n",
" chunks.append({\n",
" \"article_title\": article_title,\n",
" \"section_title\": section[\"section_title\"],\n",
" \"chunk\": chunk,\n",
" \"chunk_id\": chunk_id, \n",
" \"link\": article_link\n",
" })\n",
" chunk_id += 1 \n",
" return article_title, chunks\n",
"\n",
"for section_link in section_links:\n",
" driver.get(section_link)\n",
" time.sleep(3)\n",
"\n",
" article_links = [link.get_attribute(\"href\") for link in driver.find_elements(By.XPATH, \"//li[contains(@class, 'article-list-item')]/a\")]\n",
"\n",
" for article_link in article_links:\n",
" driver.get(article_link)\n",
" time.sleep(3)\n",
"\n",
" try:\n",
" article_title,chunks = extractSectionChunks(driver)\n",
" articles_data.extend(chunks)\n",
" print(f\"Extracted: {article_title} - {len(chunks)} chunks\")\n",
" except Exception as e:\n",
" try:\n",
" driver.get(article_link)\n",
" sub_article_links = [link.get_attribute(\"href\") for link in driver.find_elements(By.XPATH, \"//li[contains(@class, 'article-list-item')]/a\")]\n",
" for sub_article_link in sub_article_links:\n",
" driver.get(sub_article_link)\n",
" time.sleep(3)\n",
" article_title,chunks = extractSectionChunks(driver)\n",
" articles_data.extend(chunks)\n",
" print(f\"Extracted: {article_title} - {len(chunks)} chunks\")\n",
" except Exception as e:\n",
" print(f\"Failed to extract content from {article_link}: {str(e)}\")\n",
"\n",
"\n",
"driver.quit()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Save Chunks"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"# Save extracted articles to JSON\n",
"with open(\"oura_article_data_chunked_final.json\", \"w\", encoding=\"utf-8\") as f:\n",
" json.dump(articles_data, f, indent=4, ensure_ascii=False)\n",
"\n",
"driver.quit()\n",
"\n",
"print(\"Scraping complete. Data saved to 'oura_articles.json'\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "ouraDemo",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.16"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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