Wikipedia Trends API README

pip install trendsapi-wikipedia
export TRENDSAPI_KEY=your_key

from trendsapi_wikipedia import TrendsAPI

client = TrendsAPI()                    # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")

from trendsapi_wikipedia import TrendsAPI

client = TrendsAPI()                    # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")

series = client.get_time_series("large language model")
print(series[-1].date, series[-1].value)

growth = client.get_growth("large language model", percent_growth=["3M", "12M"])
print(growth.results[0].growth, growth.results[0].direction)

hot = client.get_live(limit=10)
print(hot.data)                         # [[1, "..."], ...]

points = client.get_time_series("large language model")

g = client.get_growth("large language model", percent_growth=["12M", "3M", "YTD"])
print(g.results[0].growth, g.results[0].direction)

hot = client.get_live(limit=10)

import asyncio
from trendsapi_wikipedia import AsyncTrendsAPI

async def main():
    c = AsyncTrendsAPI()
    return await asyncio.gather(
        c.get_time_series("large language model"),
        c.get_time_series("large language model", source="google search"),
    )

asyncio.run(main())

from dataclasses import asdict
import pandas as pd
from trendsapi_wikipedia import TrendsAPI

df = pd.DataFrame(asdict(p) for p in TrendsAPI().get_time_series("large language model"))
df["date"] = pd.to_datetime(df["date"])
print(df.set_index("date")["value"].resample("ME").mean().tail())

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":"wikipedia","keyword":"large language model"}'