TalorData SERP API helps you retrieve structured Google Local SERP data through a Python workflow for local SEO monitoring, business listing research, competitor analysis, location intelligence, AI applications, and lead generation. The workflow extracts key result fields, including business names, addresses, ratings, and ranking positions, so you can use the data in local SEO dashboards, agency reports, prospecting workflows, AI agents, and automation pipelines.
To run this tool, you need Python 3.11 or newer and a TalorData SERP token.
Get your API key：Sign up at TalorData and get your API key from the dashboard.
python -m pip install poetry==1.8.2
poetry installThis tool collects Google Local results through TalorData SERP API.
Use google_local when you want the local pack-style result list.
For a Local request:
engine=google_local
The request requires a query with q, such as q=coffee or q=foie gras.
The local Google Local page preview looks like this:
The TalorData request parameters are summarized here:
Set your TalorData token first. Choose the command for your terminal.
On Windows Command Prompt:
set TALORDATA_SERP_API_TOKEN=<your_talordata_serp_token>
echo %TALORDATA_SERP_API_TOKEN%On Windows PowerShell:
$env:TALORDATA_SERP_API_TOKEN="<your_talordata_serp_token>"
$env:TALORDATA_SERP_API_TOKENOn macOS or Linux:
export TALORDATA_SERP_API_TOKEN=<your_talordata_serp_token>
echo "$TALORDATA_SERP_API_TOKEN"To collect Google Local results as CSV, run:
poetry run talordata-google-local-serp \
--query "coffee" \
--output places.csv \
--format csvTo collect JSON instead:
poetry run talordata-google-local-serp \
--query "coffee" \
--output places.jsonTo inspect the raw TalorData SERP response while exporting:
poetry run talordata-google-local-serp \
--query "coffee" \
--output places.csv \
--format csv \
--debug-response raw-response.jsonAfter running the command, the terminal output should look similar to this:
When the tool finishes, you should see a places.csv or places.json file in the directory where you ran it.
If you choose CSV, open places.csv in Excel, Google Sheets, or any text editor. It should have these columns:
title,place_id,link,address,phone,website,rating,reviews,type,gps_coordinates,position
"Boucherie West Village","ChIJq58thpNZwokRcsvqjnNzYcc","https://example.com","99 7th Ave S, New York, NY 10014","(212) 837-1616","https://example.com",4.8,9426,"French restaurant","40.733047,-74.0028772",1A generated CSV preview looks like this:
Each row is one place result. Use CSV for place lists and JSON when you need full nested Google Local metadata.
This project does not fetch Google Local HTML directly. TalorData SERP API handles upstream fetching, request routing, parsing, and structured JSON output.
If Google returns an upstream no-result response, the CLI surfaces that error instead of silently writing an empty output file.
TalorData Google Local SERP API returns structured place data such as place names, IDs, addresses, phone numbers, websites, ratings, review counts, place types, coordinates, thumbnails, and rank positions.
The same API request is shown here as a quick visual reference:
import os
from pprint import pprint
import requests
payload = {
"engine": "google_local",
"q": "coffee",
"location": "United States",
"json": "2",
"output_format": "json",
"google_domain": "google.com",
"gl": "us",
"hl": "en",
}
response = requests.post(
"https://serpapi.talordata.net/serp/v1/request",
headers={
"Authorization": f"Bearer {os.environ['TALORDATA_SERP_API_TOKEN']}",
"Content-Type": "application/x-www-form-urlencoded",
},
data=payload,
timeout=30,
)
response.raise_for_status()
pprint(response.json())Supported Google Local parameters:
qenginegoogle_domainglhllocationuulellstartnumtypeplace_iddata_iddeviceno_cache
The output cleaner supports local_results[] and TalorData envelope responses where JSON is nested inside data, result, response, or json.
Run the CLI help:
poetry run talordata-google-local-serp --helpExplore TalorData SERP API integrations and use cases: