# Bilibili Video Scraper (`solid-scraper/bilibili-video-scraper`) Actor 🎬 Bilibili Video Scraper extracts metadata & links from Bilibili videos fast and reliably. Perfect for creators, marketers & researchers to analyze content, track trends, and build datasets—without manual work. 🚀 - **URL**: https://apify.com/solid-scraper/bilibili-video-scraper.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community) - **Categories:** Videos, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ### Bilibili Video Scraper 🔍 **Bilibili Video Scraper** is a tool that extracts detailed metadata from Bilibili videos, turning a list of video links into structured results you can analyze, enrich, or export. Whether you’re looking for **Bilibili video scraper tool** outputs, **Bilibili video downloader**-style assets, or **Bilibili metadata scraper** data (likes, coins, favorites, author info, and topic tags), this actor helps you gather it at scale—saving you hours of manual work. --- ### Why choose Bilibili Video Scraper? | Feature | Benefit | |---|---| | ✅ **All-in-one video metadata extraction** | Collect key video stats, author details, and topic tags from each Bilibili video link in one run | | ✅ **Reliability with built-in fallbacks** | Includes resilience and graceful handling when a video page can’t be processed | | ✅ **Structured JSON output** | Gets clean fields like `title`, `author`, `like_count`, `favorite_count`, and `topic_tag` ready for downstream workflows | | ✅ **Scales to batches of URLs** | Process multiple Bilibili video links sequentially and push all results to a dataset automatically | | ✅ **Dataset-ready for analysis & export** | Produces output that’s straightforward to preview and export as JSON/CSV from Apify | | ✅ **Proxy support for stable scraping** | Works with proxy configuration to improve success when sites are sensitive to traffic | --- ### Key features - 🔎 **Bilibili video metadata extraction**: Pulls video title, description, author info, and engagement stats into a structured item - 📊 **Engagement stats in Bilibili-style counts**: Formats likes, coins, favorites, and shares into readable strings (e.g., “9.8万”) - 🧠 **Topic tag detection**: Derives a `topic_tag` from available tags associated with the video page - 🏷️ **Comprehensive tagging output**: Includes `tags` plus a primary `topic_tag` for easier categorization - 📝 **Note count support (when available)**: Extracts the “篇笔记” value when present on the page - 💾 **Dataset saving out of the box**: Pushes results to the Apify dataset automatically after processing your input URLs - 🔄 **Resilient processing**: Skips invalid inputs and handles missing metadata fields gracefully without crashing the entire batch - 🌐 **URL support for standard Bilibili video links**: Accepts direct Bilibili video URLs like `https://www.bilibili.com/video/BV.../` --- ### Input Provide input via an `input.json` file. Example structure: ```json { "urls": [ "https://www.bilibili.com/video/BV1dj411E7vt/" ] } ```` #### Input Fields | Field | Required | Description | |---|---|---| | `urls` | No | A list of Bilibili video URLs to scrape. Add one or more `https://www.bilibili.com/video/BV.../` links. | *** ### Output The actor saves your scraped video metadata as a dataset containing an array of JSON objects. ```json [ { "id": "BV1dj411E7vt", "cover": "@96w.webp", "title": "Video title", "url": "https://www.bilibili.com/video/BV1dj411E7vt/", "view_count": "", "dm_count": "", "pubdate": "", "copyright": "", "like_count": "9.8万", "coin_count": "123万", "favorite_count": "4.5万", "share_count": "6789", "note_count": "1篇笔记", "description": "Video description", "reply_count": "", "topic_tag": "tag-name", "author": "Author name", "author_url": "https://space.bilibili.com/123456789/", "avatar": "author-face-image-id", "tags": [] } ] ``` #### Output Fields | Field | Type | Description | |---|---|---| | `id` | string | The Bilibili video identifier (`bvid`) extracted from the page state | | `cover` | string | Cover image path built from the author avatar reference (when available) | | `title` | string | Video title | | `url` | string | The input video URL you provided | | `view_count` | string | View count field (returned as an empty string in the current output mapping) | | `dm_count` | string | Danmaku count field (returned as an empty string in the current output mapping) | | `pubdate` | string | Publication date field (returned as an empty string in the current output mapping) | | `copyright` | string | Copyright field (returned as an empty string in the current output mapping) | | `like_count` | string | Like count formatted in Bilibili style (e.g., “9.8万”) | | `coin_count` | string | Coin count formatted in Bilibili style | | `favorite_count` | string | Favorite count formatted in Bilibili style | | `share_count` | string | Share count formatted in Bilibili style | | `note_count` | string | Extracted “篇笔记” count when present; otherwise empty | | `description` | string | Video description text (`desc`) | | `reply_count` | string | Reply count field (returned as an empty string in the current output mapping) | | `topic_tag` | string | A primary topic tag selected from the available tag list (first tag name) | | `author` | string | Author display name | | `author_url` | string | Author profile URL (`https://space.bilibili.com/{mid}/`) when author `mid` is available | | `avatar` | string | Author face reference value from the page state | | `tags` | array | Full list of tag names (may be empty) | > Note: Errors and per-URL failure states are not emitted as separate “error objects” in the output mapping—only successfully built items are pushed to the dataset. *** ### How to use Bilibili Video Scraper (via Apify Console) 1. **Open Apify Console** Log in at https://console.apify.com and go to the **Actors** section. 2. **Find the actor** Search for **Bilibili Video Scraper** and open its actor page. 3. **Go to the INPUT panel** Paste your input JSON, using the `urls` array. 4. **Add your Bilibili video links** Include one or more URLs like `https://www.bilibili.com/video/BV.../`. 5. **(Optional) Proxy settings** If you use proxy configuration in your workflow, enable it in the actor UI where applicable. This actor also uses built-in proxy support for more stable scraping. 6. **Run the actor** Click **Run**. Watch the logs for “Processing” updates and progress. Items with missing or unparseable metadata are skipped. 7. **Open your dataset results** After completion, open the **OUTPUT** section to access the dataset where results were pushed. 8. **Export your data** Export the dataset as JSON or CSV for your analysis pipeline or reporting workflows. No coding required — get accurate Bilibili metadata outputs in minutes. *** ### Advanced features & SEO optimization - 🚀 **Engineered for Bilibili video metadata scraper workflows**: Designed to transform a list of Bilibili video URLs into structured fields for analysis (likes, coins, favorites, author info, and topic tags). - 🧰 **Great for Bilibili batch video download planning**: Even if you’re building a “download Bilibili videos” pipeline, this provides the metadata foundation you can join with other download steps. - 🛡️ **Resilience when pages change or blocks occur**: Includes resilience and safe handling when metadata can’t be found, improving reliability across batches. - 🔄 **Politeness delays between URLs**: Helps reduce friction when processing multiple Bilibili links in one run. - 📌 **Structured outputs for automation**: Clean JSON fields make it easy to feed “Bilibili video scraping API” style pipelines without manual parsing. *** ### Best use cases - 📈 **Marketing teams enriching content libraries**: Build a searchable database of Bilibili video metadata for campaign planning and performance analysis. - 🔎 **Analysts categorizing video topics at scale**: Use `topic_tag` and `tags` to group content and compare engagement across niches. - 🎯 **Lead generation researchers**: Collect author-facing details (like `author_url`) as part of broader creator discovery workflows. - 🧪 **Product and content research**: Track engagement indicators such as likes, coins, favorites, and shares for hypothesis testing. - 🗂️ **Data pipeline builders**: Feed structured JSON into downstream systems (ETL, dashboards, or “Bilibili video URL extractor” style automation). - 🧾 **Creators and community managers**: Quickly compile metadata for multiple videos to support internal reporting and content strategy decisions. - 💻 **Developers building extensions or utilities**: Use the dataset output as the metadata step for a larger “Bilibili danmaku downloader” / subtitles / audio workflow (when combined with other steps). *** ### Technical specifications - **Supported Input Formats** - ✅ `urls`: an array of Bilibili video URLs (e.g. `https://www.bilibili.com/video/BV.../`) - ❌ No support for non-Bilibili video types (input should be Bilibili links) - **Proxy Support** - ✅ Supported (built-in proxy support for stable scraping) - ❌ Not required, but recommended for larger batches or environments prone to blocking - **Retry Mechanism** - ✅ Includes resilience and safe handling when metadata can’t be extracted - ❌ No user-configurable retry parameters are exposed in the provided input schema - **Dataset Structure** - ✅ One dataset item per successfully parsed Bilibili URL - ✅ Output is an array of JSON objects pushed to the dataset - **Rate Limits & Performance** - ✅ Processes the provided URLs in sequence with delays between requests - ✅ Designed for practical batching (no specific batch limit is defined in the provided files) - **Limitations** - ❌ Some fields are returned as empty strings in the current output mapping (`view_count`, `dm_count`, `pubdate`, `copyright`, `reply_count`) - ❌ If the actor can’t parse metadata from the page state, that URL may be skipped (no item pushed for that entry) *** ### FAQ #### What does the Bilibili Video Scraper extract from each video? ✅ It extracts structured metadata such as `title`, `description`, author information (`author`, `author_url`, `avatar`), engagement stats (`like_count`, `coin_count`, `favorite_count`, `share_count`), a `topic_tag`, and the list of `tags` when available. #### Do I need to provide any special settings besides URLs? No. The provided input schema only includes `urls`. Proxy support is handled as part of the actor’s execution, but you don’t need to add extra fields to use the basic functionality. #### What does `topic_tag` mean? `topic_tag` is derived from the available tag list found on the video page state. In the current mapping, it selects the first tag name as the primary topic. #### Are view counts and reply counts included? They are present as fields (`view_count` and `reply_count`) in the output schema, but in the current output mapping these specific fields are returned as empty strings. #### Can I scrape multiple Bilibili videos in one run? Yes. Provide multiple Bilibili video URLs in the `urls` array. The actor will process them and push successful results to the dataset. #### Where can I download the results? After the run completes, open the **OUTPUT** dataset in Apify Console and export the data as JSON or CSV. #### Is this actor suitable for “Bilibili video downloader” projects? Yes—especially if you need a metadata layer first. Many “download Bilibili videos” workflows depend on metadata like titles, authors, and engagement stats. This actor gives you that dataset-ready foundation. #### Is the scraped data from publicly available sources? ✅ Yes. The actor is designed to collect information from publicly accessible sources. Please ensure your usage complies with applicable laws and platform policies (GDPR/CCPA and spam regulations where relevant). *** ### Support & feature requests Want to improve **Bilibili Video Scraper**? We’d love your feedback on what you want next—like exporting richer fields, improving output formatting, or enhancing batch workflows. 💡 **Feature Requests**: For example, CSV export enhancements, additional metadata fields, or easier integrations into CRM pipelines.\ 📧 **Contact**: Email us at . Your feedback helps shape the roadmap for future versions of this Bilibili video scraper tool. *** ### Closing CTA / Final thoughts *Bilibili Video Scraper* is the most comprehensive, SEO-optimized way to turn Bilibili video links into structured metadata—ready for analysis, enrichment, or automation. *** ### Disclaimer **This tool only accesses publicly accessible sources.** It does not access private profiles, authenticated data, or password-protected content. It is the user’s responsibility to comply with applicable laws and regulations (including GDPR and CCPA where relevant), spam regulations, and the target platform’s Terms of Service. For data removal requests, contact . Please use this actor responsibly, ethically, and for legitimate purposes only. # Actor input Schema ## `urls` (type: `array`): List of Bilibili video URLs to scrape. ## Actor input object example ```json { "urls": [ "https://www.bilibili.com/video/BV1dj411E7vt/" ] } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "urls": [ "https://www.bilibili.com/video/BV1dj411E7vt/" ] }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/bilibili-video-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "urls": ["https://www.bilibili.com/video/BV1dj411E7vt/"] } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/bilibili-video-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "urls": [ "https://www.bilibili.com/video/BV1dj411E7vt/" ] }' | apify call solid-scraper/bilibili-video-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/bilibili-video-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Bilibili Video Scraper", "description": "🎬 Bilibili Video Scraper extracts metadata & links from Bilibili videos fast and reliably. Perfect for creators, marketers & researchers to analyze content, track trends, and build datasets—without manual work. 🚀", "version": "0.1", "x-build-id": "Tptis9HKluLwjwAzM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~bilibili-video-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-bilibili-video-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~bilibili-video-scraper/runs": { "post": { "operationId": "runs-sync-solid-scraper-bilibili-video-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~bilibili-video-scraper/run-sync": { "post": { "operationId": "run-sync-solid-scraper-bilibili-video-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "urls": { "title": "Bilibili Video URLs", "type": "array", "description": "List of Bilibili video URLs to scrape.", "items": { "type": "string" } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```