seekit 0.0.1

Python API for various search engines

seekit

seekit wraps multiple search providers behind a common SerpItem model and can search live using curl_cffi request templates derived from captured HAR files.

Supported providers:

• Baidu
• Bilibili
• Bing
• Brave
• Douyin
• DuckDuckGo
• Google
• Reddit
• So.com
• Sogou
• Threads
• TikTok
• Toutiao
• Weibo
• Yandex
• YouTube
• Zhihu

Install

uv add seekit

For the CLI:

uv tool install seekit

Usage

Search live:

import seekit

results = seekit.search("latest OpenAI reasoning model", provider="google")
for item in results[:3]:
    print(item.provider, item.title, item.url)

CLI:

seekit tiktok OpenAI
seekit google latest OpenAI reasoning model --limit 5

Each parsed item uses the shared pydantic model:

class SerpItem(BaseModel):
    provider: str
    title: str | None
    excerpt: str | None
    url: str | None
    author: str | None
    cover_url: str | None

Fixture parsing is still available for tests and parser debugging:

from pathlib import Path

results = seekit.parse_har("google", Path("data/pages/google.har"))

Development

uv run pytest

Tests read the HAR fixtures under data/pages, verify the normalized item shape, and validate that live request templates substitute the search keyword correctly.

Release

make publish-testpypi
make publish-pypi

These targets build with uv build and publish with uvx uv-publish.