cv-cat

cv-cat / BilibiliApis

Public

B站Bilibili算法逆向

14
9
69% credibility
Found Apr 10, 2026 at 14 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

This project runs a web service to search Bilibili for videos by keyword, returning sorted lists of results including titles, authors, and stats, using provided login information.

How It Works

1
🔍 Discover the video finder

You find a simple tool that helps you quickly gather lists of popular videos from Bilibili by searching topics.

2
💻 Set up the tool

Download the files and start the helper app on your computer with a few easy steps.

3
👤 Log into Bilibili

Open Bilibili in your browser, sign in to your account, and copy your personal access code from the page tools.

4
🔗 Connect your account

Paste the access code into the tool, and it links up safely so you can search like a real user.

5
📝 Run a search

Type in a topic like 'funny cats', pick sorting by views or comments, and choose how many videos to get.

📈 Get your video list

You receive a clean list of matching videos with titles, creators, play counts, and more to explore trends or ideas.

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Star Growth

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AI-Generated Review

What is BilibiliApis?

BilibiliApis is a Python FastAPI service that lets you search Bilibili videos in bulk by keyword, automatically paginating to fetch exactly the number you need, sorted by play count or danmaku. It solves the hassle of Bilibili's WBI authentication by handling signatures via an embedded JS runtime, so you just POST your login cookies to get clean JSON results with video IDs, titles, authors, and stats. Fire it up locally or via Docker, hit the /docs for interactive testing, and integrate video data into your apps without reverse-engineering the API yourself.

Why is it gaining traction?

It stands out by automating the tricky WBI crypto and cookie auth that blocks most scrapers, delivering reliable searches via a simple POST endpoint like /search_some_by_num. Developers dig the one-click Docker deploy and auto-pagination for large pulls, skipping manual loops. The focus on AI-friendly data like trends and heatmaps hooks folks building content tools over raw libraries.

Who should use this?

AI agent builders feeding Bilibili trends into LLMs for analysis. Content marketers automating video discovery by keyword for strategy insights. Data pipeline devs needing quick, authenticated pulls of top videos sorted by engagement metrics.

Verdict

Grab it for quick Bilibili video searches if you're okay with its 0.7% credibility score and 14 stars signaling early-stage maturity—docs are solid with curl examples, but expect tweaks for production. Solid prototype for prototyping, not battle-tested scale.

(178 words)

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