# Open Library Author Bibliography Scraper (`jungle_synthesizer/openlibrary-author-bibliography-scraper`) Actor Resolve author names to their full Open Library bibliography: works list with first-publish year, edition count, subjects, and cover URLs. Returns bio, birth/death dates, external IDs (VIAF, Wikidata, ISNI), and alternate names. For literary databases, recommendation engines, and RAG pipelines. - **URL**: https://apify.com/jungle\_synthesizer/openlibrary-author-bibliography-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Open Library Author Bibliography Scraper Resolve author names to their complete Open Library bibliography. Input a list of author names and get back full author profiles — bio, birth and death dates, external IDs (VIAF, Wikidata, ISNI, Goodreads), alternate name forms, photo URL, Wikipedia link, and a works list with first-publish year, edition count, subjects, and cover images. ### What does it do? For each author name you supply, this actor: 1. **Resolves the name** — queries the Open Library author search API and returns the best-matching author record (exact name match preferred; falls back to the top search hit) 2. **Fetches the author profile** — retrieves bio, birth/death dates, alternate names, photo, Wikipedia URL, and external authority IDs 3. **Paginates the full works list** — fetches all works (or up to `maxWorksPerAuthor`) including title, first-publish year, edition count, subjects, and cover image URL No authentication or proxy required. Open Library is a fully open API. The actor is rate-limited to approximately 1 request per second to stay respectful of Open Library's guidelines. ### Output fields Each result record contains: | Field | Description | |---|---| | `author_olid` | Open Library author identifier (e.g. `OL26320A`) | | `name` | Primary name as on Open Library | | `alternate_names` | Pipe-separated list of alternate name forms | | `birth_date` | Birth date string as stored on Open Library | | `death_date` | Death date string as stored on Open Library | | `bio` | Author biography | | `photo_url` | URL of author photo (medium size) | | `wikipedia_url` | Author's Wikipedia page URL | | `links` | JSON array of `{title, url}` external links | | `work_count` | Total number of works on Open Library | | `works` | JSON array of works — each has `olid`, `title`, `first_publish_year`, `edition_count`, `subjects`, `cover_url` | | `top_subjects` | Pipe-separated top subjects (pre-computed by Open Library) | | `top_work` | Title of the author's most prominent work | | `id_viaf` | VIAF (Virtual International Authority File) identifier | | `id_wikidata` | Wikidata entity ID | | `id_isni` | ISNI (International Standard Name Identifier) | | `id_goodreads` | Goodreads author ID | | `open_library_url` | Open Library page URL for this author | ### Input ```json { "authors": ["J.R.R. Tolkien", "Ursula K. Le Guin", "Philip K. Dick"], "maxItems": 10, "maxWorksPerAuthor": 50 } ```` | Parameter | Type | Description | |---|---|---| | `authors` | array (required) | List of author names to look up | | `maxItems` | integer | Maximum author records to return (0 = no limit) | | `maxWorksPerAuthor` | integer | Maximum works per author (0 = all works) | ### Use cases - **Literary databases** — build comprehensive author-centric catalogs - **Recommendation engines** — enrich author profiles with verified bibliographies and external authority IDs - **RAG pipelines** — structure author knowledge for retrieval-augmented generation over book data - **Library catalogs** — cross-reference VIAF, Wikidata, and ISNI identifiers for authority control - **Data journalism** — research author output, publication history, and subject coverage ### Notes - Open Library's works API does not include `subjects` or `edition_count` per-work in paginated responses; those fields are populated where available from the work record - `top_subjects` and `top_work` are sourced from Open Library's pre-computed search signals when available, providing higher-quality signals than per-run aggregation - The actor works as companion to the [Open Library ISBN Book Metadata Scraper](https://apify.com/bowtiedraccoon/openlibrary-isbn-book-metadata-scraper), which covers the ISBN/edition access pattern # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `authors` (type: `array`): List of author names to look up. Each name is resolved to an Open Library author OLID, then their full bibliography is fetched. ## `maxItems` (type: `integer`): Maximum number of author records to return (0 = no limit) ## `maxWorksPerAuthor` (type: `integer`): Maximum number of works to include in each author's bibliography (0 = all works) ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "authors": [ "J.R.R. Tolkien", "Ursula K. Le Guin", "Philip K. Dick" ], "maxItems": 10, "maxWorksPerAuthor": 50 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "authors": [ "J.R.R. Tolkien", "Ursula K. Le Guin", "Philip K. Dick" ], "maxItems": 10, "maxWorksPerAuthor": 50 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/openlibrary-author-bibliography-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "authors": [ "J.R.R. Tolkien", "Ursula K. Le Guin", "Philip K. Dick", ], "maxItems": 10, "maxWorksPerAuthor": 50, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/openlibrary-author-bibliography-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "authors": [ "J.R.R. Tolkien", "Ursula K. Le Guin", "Philip K. Dick" ], "maxItems": 10, "maxWorksPerAuthor": 50 }' | apify call jungle_synthesizer/openlibrary-author-bibliography-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/openlibrary-author-bibliography-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Open Library Author Bibliography Scraper", "description": "Resolve author names to their full Open Library bibliography: works list with first-publish year, edition count, subjects, and cover URLs. Returns bio, birth/death dates, external IDs (VIAF, Wikidata, ISNI), and alternate names. For literary databases, recommendation engines, and RAG pipelines.", "version": "0.1", "x-build-id": "CNLZLXbTNti3n72VA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~openlibrary-author-bibliography-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-openlibrary-author-bibliography-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/jungle_synthesizer~openlibrary-author-bibliography-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-openlibrary-author-bibliography-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/jungle_synthesizer~openlibrary-author-bibliography-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-openlibrary-author-bibliography-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", "required": [ "authors" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "authors": { "title": "Author Names", "type": "array", "description": "List of author names to look up. Each name is resolved to an Open Library author OLID, then their full bibliography is fetched.", "items": { "type": "string" } }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of author records to return (0 = no limit)", "default": 0 }, "maxWorksPerAuthor": { "title": "Max Works Per Author", "type": "integer", "description": "Maximum number of works to include in each author's bibliography (0 = all works)", "default": 0 } } }, "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 } } } } } } } } } } ```