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Quora Question, Profile & Stats Scraper

Under maintenance

Pricing

Pay per usage

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Quora Question, Profile & Stats Scraper

Quora Question, Profile & Stats Scraper

Under maintenance

Scrapes Quora questions, answers, user profiles, and personal stats. Supports keyword search, question edit logs, profile data, and content statistics.

Pricing

Pay per usage

Rating

0.0

(0)

Developer

Dav Bhagalpur

Dav Bhagalpur

Maintained by Community

Actor stats

0

Bookmarked

1

Total users

1

Monthly active users

7 days ago

Last modified

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Quora Scraper (Apify Actor)

A robust, stealthy Apify Actor for scraping Quora questions, answers, user profiles, and statistics. It uses undetected-chromedriver and seamlessly supports Apify Residential Proxies for maximum bypass success.

🚀 Features

  • Question Search & Extraction: Input keywords and scrape questions along with all their answers using Quora's advanced search.
  • Direct Question Logs: Extract detailed history (answers, authors, timestamps) from specific Question URLs.
  • Profile Scraping: Extract public profile information, bio, followers, and credentials.
  • User Stats: Extract total views, upvotes, shares, and content count.
  • Authentication: Easy cookie injection via Actor Input (m-b and m-s).
  • Stealth: Built-in support for proxy authentication, Manifest V3 stealth extensions, and headless undetected-chromedriver on Linux.

🛠️ How to Use (Apify Cloud)

  1. Add this Actor to your Apify account.

  2. In the Input tab, configure your run:

    • Task: Select query, scrape_question, scrape_profile, or scrape_stats.
    • Cookies: Provide valid m-b and m-s cookies from an active Quora session to access data securely.
    • Keywords / URLs: Provide search terms or direct Quora URLs depending on the task.
    • Proxy: We highly recommend enabling Residential Proxies for best results to avoid Quora's IP bans.
  3. Click Start. The Actor will output the extracted data into the Apify Default Dataset in JSON format.

Input Schema Definition

Here is an example of the JSON input you can provide:

{
"task": "query",
"keywords": ["machine learning"],
"type": "question",
"time": "week",
"max": 10,
"headless": true,
"cookies": {
"m-b": "YOUR_M_B_COOKIE_HERE",
"m-s": "YOUR_M_S_COOKIE_HERE"
}
}

💻 Local Development

1. Prerequisites

  • Python 3.11+
  • Apify CLI installed (npm install -g apify-cli)
  • Google Chrome installed on your system

2. Run Locally

Create a .actor/ directory (if it doesn't exist) and ensure INPUT.json is set up in storage/key_value_stores/default/INPUT.json.

Then, run the actor locally via the Apify CLI:

$apify run

3. Deploy to Apify

Once you've made your changes, push the updated code to the Apify Cloud:

$apify push

⚙️ Architecture

This project was migrated from a FastAPI/Uvicorn server to an Apify Actor.

  • src/main.py: The main entry point that receives Apify Input and routes to the correct scraper task.
  • hybrid_parser.py & profile_scraper.py: The core scraping engines powered by Selenium and undetected-chromedriver.
  • Dockerfile: Custom Python 3.11 image containing Google Chrome and Xvfb for Linux headless rendering.