ScrapingTables

Gaffa Table Scraper

Code examples for the blog post "How to Scrape a Table with Python (The Easy Way)" using the Gaffa Browser Request API.

Files

File	Description
capture_dom.py	Fetches raw HTML DOM via Gaffa and parses the table locally with BeautifulSoup
parse_table_demo.py	Uses Gaffa's parse_table action on the Gaffa demo site — returns JSON directly with no processing
parse_table_wikipedia.py	Uses Gaffa's parse_table action on Wikipedia's GDP by Country table — real-world example

Requirements

• Python 3.8+
• A Gaffa API key — sign up at gaffa.dev and create your key in the API Keys section of the dashboard

Setup

1. Clone the repo

git clone https://github.com/GaffaAI/GaffaPythonExamples.git
cd scraping-tables

2. Install dependencies

pip install requests beautifulsoup4 python-dotenv

3. Add your API key

Create a .env file in the root of the project:

GAFFA_API_KEY=your_key_here

Usage

Capture DOM + BeautifulSoup (Approach 1)

python capture_dom.py

Fetches the Gaffa demo table as raw HTML and parses it with BeautifulSoup. Outputs the data to the console and saves it to table_data.json.

---

parse_table on the demo site (Approach 2 — basic)

python parse_table_demo.py

Uses Gaffa's parse_table action to fetch and parse the demo table in one step. No BeautifulSoup needed. Prints the JSON output to the console.

---

parse_table on Wikipedia (Approach 2 — real-world)

python parse_table_wikipedia.py

Uses Gaffa's parse_table action on Wikipedia's List of Countries by GDP (Nominal). Saves the output to gdp_data.json and prints a preview of the first 3 records.

Sample Output

parse_table_wikipedia.py returns data like this:

[
  {
    "country_territory": "World",
    "imf__2026__1": "123,584,494",
    "world_bank__2024__6": "111,326,370",
    "united_nations__2024__7": "100,834,796"
  },
  {
    "country_territory": "United States",
    "imf__2026__1": "31,821,293",
    "world_bank__2024__6": "28,750,956",
    "united_nations__2024__7": "29,298,000"
  }
]

Column headers are automatically normalised by Gaffa — lowercased and special characters replaced with underscores.

Notes

• For sites that require proxy access or restrict by geography, add proxy_location="us" (or any supported region) to route the request through the appropriate IP.
• All JSON output files (table_data.json, gdp_data.json) are saved to the output/ folder.