cd sandbox/gta-pet-businesses

GTA pet businesses

Read-only sample output from LeadBuilder.

~/leadbuilder/gta-pet-businesses/summary

This is a real sample output from LeadBuilder, a Python pipeline I built to research business contact details. For this run, I searched OpenStreetMap for pet businesses in the Greater Toronto Area, crawled their websites, and collected public contact information. The pipeline code is private. This page only shows the results, and visitors cannot start a crawl.

Niche: Pet businesses. Region: Greater Toronto Area. Run on September 30, 2026.

What the run produced

458 businesses discovered
215 qualified and shown here
With a phone number
214
With a website
184
Websites crawled
161
Skipped because robots.txt said no
7
With an email address
57
Part of a chain
102

Email check: each email's domain was checked to confirm it accepts mail. Individual mailboxes were not confirmed.

~/leadbuilder/gta-pet-businesses/records.csv

Browse the records

215 records match.

Business Address Email Phone Crawl result
Hound & Purr 1181 The Queensway — +1 416-253-9494 Crawled successfully
K9 Couture 594 Yonge Street s•••@k•••.ca +1 416-915-9959 Crawled successfully
Kennel Cafe 285 Roncesvalles Avenue, Toronto — +1 416-531-3177 Crawled successfully
Kennel Cafe — — +1 416-531-3177 Crawled successfully
Knick Kach Paddy Whack 481 Queen Street East w•••@k•••.ca +1 416-519-2929 Crawled successfully
Knick Knack Paddy Whack Dog Food — w•••@k•••.ca +1 416-519-2929 Crawled successfully
Le Chien Elegant Fellbrigg Avenue — +1 416-932-0181 No website listed
M & J Happy Pet Products 360 Revus Avenue, Mississauga, ON, L5G 4S4 m•••@r•••.com +1 905-990-8882 Crawled successfully
McCarron Farm & Pet Service — s•••@m•••.com +1 905-838-2646 Crawled successfully
Mississauga Aquarium 1125 Dundas Street East, Mississauga m•••@g•••.com +1 905-766-3228 Crawled successfully
My Petropolis 3365 Lake Shore Boulevard West, Etobicoke — +1 416-792-3600 Site returned HTTP 404
myPet Shop on Yonge 4720 Yonge Street, North York, ON, M2N 5M4 — +1 416-528-1788 No website listed
NAFB Aquarium Centre 2260 Kingston Road, M1N 1T9 — +1 416-267-7252 Site returned HTTP 403
Nice Diggz 5094 Dundas Street West n•••@g•••.com +1 647-867-3644 Crawled successfully
Nice Diggz 571 St. Clair Avenue West, Toronto, Ontario info@n•••.com +1 647-867-3644 Crawled successfully
Nose To Toes Grooming 126 King Road — +1 905-773-2333 No website listed
Old Mill Dog Spa — — +1 416-767-4787 Crawled successfully
Ouidog 9580 Yonge Street, Richmond Hill, Ontario, L4C 1V6 o•••@g•••.com +1 437-453-4955 Crawled successfully
Pampered Paws — info@p•••.com +1 416-962-7877 Crawled successfully
Paw Envy 778 Annette Street p•••@g•••.com +1 647-451-7244 Crawled successfully
Pawland 754 Mount Pleasant Road, M4S 2N6 — +1 416-205-9393 Crawled successfully
Pawmart 1402 Yonge Street, Toronto, ON, M4T 1Y5 — +1 844-448-0844 Skipped: robots.txt asked us not to crawl
Pawny Tail Pet Grooming & More 60 Brian Harrison Way, Toronto, ON, M1P 5J5 — +1 647-296-8818 No website listed
Pawpals 276 Manitoba Street, Etobicoke info@p•••.ca +1 416-255-1574 Crawled successfully
Paws Avenue Grooming Salon — — +1 905-990-5505 No website listed
~/leadbuilder/how-it-works.md

How it works

  1. Set up the project

    Choose the niche, the city or region, and a record limit in a settings file. The same pipeline can then be run for any type of business in any area.

  2. Discover businesses

    Search OpenStreetMap for businesses that match the niche and region, and save each one with its name, address, phone, website and map location.

  3. Crawl websites politely

    Visit each business website, check robots.txt first, and skip any site that asks not to be crawled. In this run, 7 sites were skipped for that reason.

  4. Extract contacts

    Read the crawled pages to find email addresses, phone numbers and social media profiles, and record the page where each one was found.

  5. Clean and remove duplicates

    Tidy up the data and merge records that are really the same business. Chain stores are marked so they can be told apart from independent shops.

  6. Check emails

    Check that each email's domain is set up to receive mail. Individual mailboxes are not confirmed, so the results are shown honestly as domain checks.

  7. Export

    Keep only the qualified records and save them as a CSV, with a source link for every piece of data.

  8. Showcase and test

    Write a README that explains how to set up and run the pipeline, add automated tests that check each step works, and prepare sample data. This page is built from that sample data.