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 and every source: trendsapi-ai/trendsapi.

Authentication

pip install trendsapi-amazon
export TRENDSAPI_KEY=your_key

Python 3.9+. Same key as the HTTP API.

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())

JavaScript / TypeScript

npm install trendsapi-amazon

Node 18+, Deno, Bun, Workers. Same API key. Field tables above apply.

Methods

Method	REST mode	Returns
getTimeSeries(keyword, { source, data_mode })	get_time_series	weekly points
getGrowth(keyword, { percent_growth, source, data_mode })	get_growth	growth object
getLive({ limit, offset, category })	get_top_trends	live feed
getTopTrends({ type, ... })	get_top_trends	live feed

import { TrendsAPI } from "trendsapi-amazon";

const client = new TrendsAPI({ apiKey: process.env.TRENDSAPI_KEY! });
const series = await client.getTimeSeries("standing desk");
console.log(series.at(-1)?.date, series.at(-1)?.value);

const growth = await client.getGrowth("standing desk", {
  percent_growth: ["3M", "12M"],
});
console.log(growth.results[0].growth, growth.results[0].direction);

const live = await client.getLive({ limit: 10 });
console.log(live.data);                 // [[1, "..."], ...]

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

• value is 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.

License

MIT. See LICENSE.