Amazon product-search demand API
Amazon search interest and bestseller feeds via the Trends API. Ecommerce research without scrapers.
Key: trendsapi.ai/#get-key. HTTP contract: trendsapi-ai/trendsapi.
JS: trendsapi-amazon.
Authentication
pip install trendsapi-amazon
export TRENDSAPI_KEY=your_key
Python 3.9+. The wrapper re-exports TrendsAPI, AsyncTrendsAPI, and TrendsAPIError from the official client.
from trendsapi_amazon import TrendsAPI
client = TrendsAPI() # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")
Keyword helpers default to source: "amazon". Pass source= to hit any other platform with the same client. Official full client (every source, no preset): trendsapi.
Methods
| Method | REST mode |
Returns |
|---|---|---|
get_time_series(keyword, source=, data_mode=) |
get_time_series |
list[TrendsDataPoint] |
get_growth(keyword, percent_growth=, source=, data_mode=) |
get_growth |
GetGrowthResponse |
get_live(limit=, offset=, category=) |
get_top_trends |
GetTopTrendsResponse |
get_top_trends(type=, ...) |
get_top_trends |
GetTopTrendsResponse |
source is lowercase (amazon). type is exact (Amazon Best Sellers Top Rated). Mixing them is a 400.
from trendsapi_amazon import TrendsAPI
client = TrendsAPI() # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")
series = client.get_time_series("standing desk")
print(series[-1].date, series[-1].value)
growth = client.get_growth("standing desk", percent_growth=["3M", "12M"])
print(growth.results[0].growth, growth.results[0].direction)
hot = client.get_live(limit=10)
print(hot.data) # [[1, "..."], ...]
get_time_series
points = client.get_time_series("standing desk")
Each point:
| Field | Always | Meaning |
|---|---|---|
date |
yes | YYYY-MM-DD |
value |
yes | 0-100 index for this series |
keyword |
yes | Echo |
volume |
no | Absolute volume when available |
source or datatype |
no | Pipeline label |
Python returns list[TrendsDataPoint]. Use .date and .value, not ["date"].
JS returns the same fields as object properties.
get_growth
g = client.get_growth("standing desk", percent_growth=["12M", "3M", "YTD"])
print(g.results[0].growth, g.results[0].direction)
percent_growth default: ["12M"]. Presets: 7D 14D 30D 1M 2M 3M 6M 9M 12M/1Y 18M 24M/2Y 36M/3Y 48M 60M/5Y MTD QTD YTD. Custom: {"name": "Launch", "recent": "2024-06-01", "baseline": "2024-01-01"}.
| Field | Meaning |
|---|---|
search_term |
Keyword |
data_source |
Source |
results |
One object per window (period, growth, direction, dates, values) |
metadata |
Counts / success flag |
Several windows still count as one request. Python: growth.results[0].growth. JS: growth.results[0].growth.
get_live
hot = client.get_live(limit=10)
| Field | Meaning |
|---|---|
as_of_ts |
Snapshot time |
type |
Feed name |
limit, offset, count |
Pagination |
data |
[rank, label] rows |
Python: hot.data. JS: hot.data. Optional offset= and category= (Amazon Best Sellers by Category, Top Websites only).
Async
import asyncio
from trendsapi_amazon import AsyncTrendsAPI
async def main():
c = AsyncTrendsAPI()
return await asyncio.gather(
c.get_time_series("standing desk"),
c.get_time_series("standing desk", source="google search"),
)
asyncio.run(main())
Each 200 is one billed request.
Pandas
from dataclasses import asdict
import pandas as pd
from trendsapi_amazon import TrendsAPI
df = pd.DataFrame(asdict(p) for p in TrendsAPI().get_time_series("standing desk"))
df["date"] = pd.to_datetime(df["date"])
print(df.set_index("date")["value"].resample("ME").mean().tail())
Call (curl)
| Field | Value |
|---|---|
| Endpoint | POST https://api.trendsapi.ai/api |
| Auth | Authorization: Bearer $TRENDSAPI_KEY |
| History | source: amazon with get_time_series or get_growth |
| Keyword | Product phrase, e.g. standing desk |
Live type |
Amazon Best Sellers Top Rated, Amazon Best Sellers by Category |
curl -sS -X POST https://api.trendsapi.ai/api \
-H "Authorization: Bearer $TRENDSAPI_KEY" \
-H "Content-Type: application/json" \
-d '{"mode":"get_time_series","source":"amazon","keyword":"standing desk"}'
Source notes
valueis a 0-100 search-interest index, not units sold.- Feeds answer what is selling now. Keyword series answer what is searched.
- Google Shopping is a different
source(google shopping).
Errors
| HTTP | Client |
|---|---|
| 200 | Parsed payload. Python dataclasses / JS typed objects |
| 400 | Raises. Fix source or type spelling |
| 401 | Raises. Check TRENDSAPI_KEY |
| 404 | Raises. No series for that keyword. Do not retry |
| 429 | Raises. Quota |
| 5xx | Client retries, then raises |
The HTTP body field is a JSON string. SDKs decode it. Raw curl must parse body a second time.
Site: https://trendsapi.ai/trends/amazon-trends. GitHub: trendsapi-ai/amazon-trends-api.
License
MIT. See LICENSE.
Metadata
Release files for trendsapi-amazon 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| trendsapi_amazon-1.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.4 kB
Release files / trendsapi_amazon-1.0.1.tar.gz
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