Trading Site Web Scraper
Budget: $30 – $250 USD
I need a clean, well-documented Python script that reliably collects live stock prices and historical data from a specific trading site. The scraper should run headless, respect reasonable rate limits, and export results to CSV (or JSON if it makes more sense) so I can feed the files straight into my analysis pipeline.
Key points
• Task focus: pure web scraping—no additional analytics or dashboards at this stage.
• Target site: a single online trading platform; the job includes figuring out the best way to navigate any login, pagination, or API-like endpoints it exposes.
• Data scope: current stock prices and full historical series for each instrument I specify. Trade volumes are not required.
• Tech stack: Python 3.x with common libraries such as Requests / aiohttp, BeautifulSoup or lxml, and—if efficiency demands it—Selenium or Playwright for dynamic content. Please keep dependencies minimal.
• Output: one self-contained script plus clear instructions so I can schedule it via cron or Task Scheduler.
Acceptance criteria
1. I run `python scraper.py --symbol AAPL` and receive two files: `AAPL_latest.csv` and `AAPL_history.csv`.
2. The script handles retries and polite rate limiting without crashing.
3. All functions and classes carry concise docstrings; any site-specific constants live in a single config section for easy future tweaks.
Key points
• Task focus: pure web scraping—no additional analytics or dashboards at this stage.
• Target site: a single online trading platform; the job includes figuring out the best way to navigate any login, pagination, or API-like endpoints it exposes.
• Data scope: current stock prices and full historical series for each instrument I specify. Trade volumes are not required.
• Tech stack: Python 3.x with common libraries such as Requests / aiohttp, BeautifulSoup or lxml, and—if efficiency demands it—Selenium or Playwright for dynamic content. Please keep dependencies minimal.
• Output: one self-contained script plus clear instructions so I can schedule it via cron or Task Scheduler.
Acceptance criteria
1. I run `python scraper.py --symbol AAPL` and receive two files: `AAPL_latest.csv` and `AAPL_history.csv`.
2. The script handles retries and polite rate limiting without crashing.
3. All functions and classes carry concise docstrings; any site-specific constants live in a single config section for easy future tweaks.