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
Dirty Pawz 804 Queen Street East info@d•••.com +1 647-906-8892 Crawled successfully
Dog Daycare & Grooming Boutique 2722 Yonge Street, Toronto — +1 416-483-3511 Crawled successfully
Dog Haven Studio 1712A Queen Street East, Toronto, Ontario, M4L 1G7 info@d•••.ca +1 416-519-2777 Crawled successfully
Doggie Playland 365 Olivewood Road, Etobicoke, M8Z 2Z8 — +1 416-233-9111 No website listed
Doggieland 2322 Bloor Street West b•••@d•••.ca +1 416-766-4364 Crawled successfully
Doggy Styles Pet Services 3134 Lake Shore Boulevard West, Etobicoke — +1 416-253-1488 Connection problem (ConnectionError)
Dogs & Goddesses — — +1 905-670-2229 Site returned HTTP 403
Dogstar Boutique & Spa — — +1 647-797-2248 No website listed
DT Aquarium 1596 Queen Street East — +1 647-738-5133 Site returned HTTP 403
Duke's Pet Foods 24 Broadleaf Avenue d•••@g•••.com +1 905-425-3364 Crawled successfully
EmBark Academy 1054 Queen Street East e•••@g•••.com +1 437-914-9177 Crawled successfully
Fit Dogs 227 Broadview Avenue info@f•••.ca +1 416-929-9287 Crawled successfully
Fluffy Paws Dog & Cat Grooming — — +1 905-239-2300 No website listed
Forest Hill Pets 446 Spadina Road, Toronto, Ontario, M5P 2W4 f•••@g•••.com +1 416-485-4243 Crawled successfully
Fragbox Corals 588 Marlee Avenue — +1 416-265-8481 Crawled successfully
Fur Bar 844 King Street West, Toronto n•••@f•••.ca +1 416-366-7729 Crawled successfully
Furs on Us Grooming Salon — — +1 905-846-0505 No website listed
Global Pet Foods 125 Lower Jarvis Street, Toronto — +1 416-368-4222 Crawled successfully
Global Pet Foods 1278 The Queensway, Toronto, Ontario, M8Z 1S3 — +1 647-341-5202 Skipped: robots.txt asked us not to crawl
Global Pet Foods 17730 Leslie Street, Newmarket — +1 905-853-9550 Skipped: robots.txt asked us not to crawl
Global Pet Foods 1700 King Road, King City, L7B 0N1 — +1 905-833-7387 Skipped: robots.txt asked us not to crawl
Global Pet Foods 9200 Bathurst Street, Thornhill, Ontario, L4J 8W1 — +1 905-597-3353 Skipped: robots.txt asked us not to crawl
Gogo Pets 660 Yonge Street hello@g•••.ca +1 416-926-8288 Crawled successfully
HappyPets Pantry 563 Sherbourne Street, M4X1W7 contact@h•••.com +1 416-923-8888 Crawled successfully
Helmutt's Pet Supply 865 Queen Street West, Toronto, M6J 1G4 — +1 416-504-1265 Skipped: not a web page
~/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.