Fast, lightweight HTTP-based Google Maps scraper for places & reviews.

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A request-based scraper that extracts Google Maps place data and reviews without browser automation.

Key features:

• Concurrency -> Parallel workers with independent sessions
• Resume support -> Job tracking + per-place review resumption from saved cursors
• Session persistence -> 0-RTT TLS resumption via session.json
• Rate limit handling -> Exponential backoff + connection refresh on 429
• WAL-mode SQLite -> Concurrent reads/writes without lock contention
• Email extraction -> Fetches the business website and extracts contact emails

Install

pip install -r requirements.txt

Requires Python 3.10+.

Quick Start

# Search + scrape places and reviews
python main.py search "restaurants in Paris" --max-places=20 --max-reviews=50

# Scrape a single place by ID
python main.py place "0x89e377427d7f0199:0x5937c65cee2427f0" --max-reviews=200

# Search only (fast discovery, no details/reviews)
python main.py list "hotels in Dubai" --max-places=30

# Resume an interrupted job
python main.py resume <job_id> --max-reviews=100

# Database stats
python main.py stats

# Extract emails from business websites
python main.py search "hotels in London" --max-places=50 --extract-emails

Commands

Command	Description	Returns
search	Search + full scrape	All fields + reviews
place	Scrape a single known place	All fields + reviews (resumes from DB cursor)
list	Search only -> no details/reviews	Name, address, rating, coords, categories
resume	Resume a job	Continues from last saved cursor per place
stats	Database statistics	Place count, review count, pending jobs

Options

Flag	Description	Default
--db	SQLite database path	output/gmaps.db
--max-places	Max places to scrape (None = unlimited)	unlimited
--max-reviews	Max reviews per place (None = all, 0 = skip)	unlimited
--workers	Concurrent workers	4
--delay	Min seconds between requests	2.5
--proxy	Proxy URL (socks5://... or http://...)	None
--session-file	Session persistence path	output/session.json
--lang	Language code	en
--gl	Country/region code	us
--extract-emails	Fetch website & extract email if missing	false

Typical Workflows

Discover first, scrape selected places later

python main.py list "coffee shops in Amsterdam" --max-places=20
python main.py place "0x47c609c7..." --max-reviews=200

Scrape details now, reviews later

python main.py search "restaurants in Nairobi" --max-places=20 --max-reviews=0
python main.py resume <job_id> --max-reviews=300

Large-scale scraping

python main.py search "hotels in London" --max-places=100 --max-reviews=50 --workers=8

Extract contact emails from websites

When Google Maps doesn't list an email, the scraper can visit the business website and extract it:

python main.py search "restaurants in Nairobi" --max-places=30 --extract-emails

Works with search, place, and resume.

How Resume Works

• search / place --> Saves a pagination cursor per place in the database
• resume <job_id> --> Re-opens places that need more reviews and continues from their saved cursors
• place repeat runs --> Skips if you already have enough reviews; fetches more if you increased --max-reviews

Disclaimer

This tool is provided for educational and research purposes. By using it, you agree to comply with applicable laws regarding data collection.