[Python] Google Places API always returns only 20 results, no nextPageToken for any query

I’m using Google Places API (v1 places:searchText) to search businesses.

For every query (e.g. “Namkeen Companies in Delhi”, “Hotels in India”), I only get 20 results.

The response never includes nextPageToken.

I’ve added 2-second delay, correct pagination code, but token is always None.

Official docs say you can get up to 60 results using pagination. Why is nextPageToken missing for every location and query?

Am I missing something? Or is this API behavior expected? How can I get more results per query?

Any advice appreciated.

import requests
import pandas as pd
from datetime import datetime
import time

# Direct API key (replace with your actual key)
API_KEY = "API KEY"

url = "https://places.googleapis.com/v1/places:searchText"
headers = {
"Content-Type": "application/json",
"X-Goog-Api-Key": API_KEY,
"X-Goog-FieldMask": "places.displayName,places.formattedAddress,places.id,places.types,places.rating,places.userRatingCount"
}

# Try multiple queries to get more results like Google Maps
search_queries = [
"Hotels in India"
]

all_results = []

for query in search_queries:
print(f"\nSearching for: {query}")
page_token = None
page = 1

while True:
print(f" Requesting page {page}")
data = {
"textQuery": query
}
if page_token:
data["pageToken"] = page_token

response = requests.post(url, headers=headers, json=data)
print(f" Response status: {response.status_code}")

if response.status_code != 200:
print(f" Error: {response.text}")
break

resp_json = response.json()
results = resp_json.get("places", [])
print(f" Found {len(results)} results on page {page}")

# Add results to our collection, avoiding duplicates
for place in results:
place_id = place.get("id", "")
if not any(existing.get("id", "") == place_id for existing in all_results):
all_results.append(place)

page_token = resp_json.get("nextPageToken")
if not page_token:
break
page += 1
time.sleep(2) # Google recommends a short delay before using nextPageToken

print(f"\nTotal unique results found: {len(all_results)}")

# Prepare data for Excel
excel_data = []
for i, place in enumerate(all_results, 1):
name = place.get("displayName", {}).get("text", "Unknown")
address = place.get("formattedAddress", "No address")
place_id = place.get("id", "")
types = ", ".join(place.get("types", []))
rating = place.get("rating", "N/A")
user_rating_count = place.get("userRatingCount", "N/A")

excel_data.append({
"S.No": i,
"Company Name": name,
"Address": address,
"Place ID": place_id,
"Types": types,
"Rating": rating,
"Review Count": user_rating_count
})

# Create DataFrame and save to Excel
df = pd.DataFrame(excel_data)

# Generate filename with timestamp
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
filename = f"namkeen_companies_delhi_{timestamp}.xlsx"

# Save to Excel with formatting
with pd.ExcelWriter(filename, engine='openpyxl') as writer:
df.to_excel(writer, sheet_name='Namkeen Companies', index=False)

# Get the workbook and worksheet
workbook = writer.book
worksheet = writer.sheets['Namkeen Companies']

# Auto-adjust column widths
for column in worksheet.columns:
max_length = 0
column_letter = column[0].column_letter
for cell in column:
try:
if len(str(cell.value)) > max_length:
max_length = len(str(cell.value))
except:
pass
adjusted_width = min(max_length + 2, 50) # Max width of 50
worksheet.column_dimensions[column_letter].width = adjusted_width

print(f"\nResults saved to: {filename}")
print(f"Total companies found: {len(all_results)}")

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