# Lemmy Scraper β€” Posts, Scores & Comments (No Key) (`ninhothedev/lemmy-scraper`) Actor $0.5/1K πŸ”₯ Fast Lemmy scraper! Posts from any instance or community β€” title, score, comments & author. No key. JSON, CSV, Excel or API in seconds. Pull thousands for social monitoring & trend research ⚑ - **URL**: https://apify.com/ninhothedev/lemmy-scraper.md - **Developed by:** [ninhothedev](https://apify.com/ninhothedev) (community) - **Categories:** Social media, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 1,000 results 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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 ## Lemmy Scraper 🐭 **Scrape posts from any [Lemmy](https://join-lemmy.org/) instance or community β€” no login, no API key.** Lemmy is the fediverse's open-source Reddit alternative. This Actor pulls a clean, structured feed of posts with **title, score, upvotes/downvotes, comment counts, author, community and body** straight from Lemmy's public JSON API. Perfect for social monitoring, trend research, content curation and community analysis across the fediverse. --- ### ✨ Features - **No API key, no account.** Uses Lemmy's public `/api/v3` endpoints. - **Any instance.** `lemmy.world`, `lemmy.ml`, `sh.itjust.works`, `beehaw.org`, or your own. - **Two modes:** browse a **feed** (by community + sort) or **search** posts full-text. - **Rich, flat output.** Score, votes, comments, author, community and ISO timestamps. - **Datacenter-friendly.** Fast plain JSON β€” no residential proxies required. - **Cheap.** Pay-per-result, roughly **$0.5 per 1,000 posts**. --- ### πŸš€ Input | Field | Type | Description | |-------|------|-------------| | `mode` | select | `posts` (feed) or `search`. Default `posts`. | | `instance` | string | Instance host, e.g. `lemmy.world`. Default `lemmy.world`. | | `community` | string | Optional community, e.g. `technology` or `name@instance`. Feed mode only. | | `sort` | select | `Active`, `Hot`, `New`, `TopDay`, `TopWeek`, `TopAll`. Default `Hot`. | | `query` | string | Search term. Required when `mode` is `search`. | | `maxItems` | integer | Max posts to scrape (1–1000). Default `100`. | #### Example β€” Hot posts from a community ```json { "mode": "posts", "instance": "lemmy.world", "community": "technology", "sort": "Hot", "maxItems": 100 } ```` #### Example β€” search posts ```json { "mode": "search", "instance": "lemmy.world", "query": "self hosting", "maxItems": 200 } ``` *** ### πŸ“¦ Output Each dataset item is one post: ```json { "instance": "lemmy.world", "post_id": 49691217, "title": "Caption", "url": "https://lemmy.world/pictrs/image/abc.jpeg", "body": "…post text, capped at 5000 chars…", "published": "2026-07-20T20:46:50.426065Z", "nsfw": false, "author": "Optional", "author_actor": "https://lemmy.world/u/homesweethomeMrL", "community": "microblogmemes", "community_title": "Microblog Memes", "score": 106, "upvotes": 107, "downvotes": 1, "comments": 4, "thumbnail": "https://lemmy.world/pictrs/image/thumb.jpeg", "post_url": "https://lemmy.world/post/49691217", "source": "lemmy", "scraped_at": "2026-07-21T00:00:00Z" } ``` Export to **JSON, CSV, Excel, XML** or pull via the Apify API. *** ### πŸ’‘ Use cases - **Social monitoring** β€” track how topics or brands are discussed across fediverse communities. - **Trend research** β€” surface top/hot posts by score and comment volume. - **Content curation** β€” build feeds and newsletters from niche Lemmy communities. - **Community analysis** β€” measure engagement, activity and voting patterns per community. *** ### πŸ’° Pricing Pay-per-result β€” approximately **$0.5 per 1,000 posts**. Runs on 512 MB and needs no proxies, so it stays cheap and fast. *** ### πŸ”— Related actors - [Reddit Scraper](https://apify.com/ninhothedev/reddit-scraper) - [Mastodon Scraper](https://apify.com/ninhothedev/mastodon-scraper) - [Bluesky Scraper](https://apify.com/ninhothedev/bluesky-scraper) - [Hacker News Scraper](https://apify.com/ninhothedev/hacker-news-scraper) *** ### ❓ FAQ **Do I need a Lemmy account or API key?** No. Everything uses public read-only endpoints. **Which instances work?** Any standard Lemmy instance exposing `/api/v3`. Just set `instance`. **How do I scrape a remote community?** Use `name@instance` in the `community` field (e.g. `asklemmy@lemmy.ml`). **Keywords:** lemmy scraper, lemmy api, fediverse scraper, reddit alternative, lemmy posts, social media scraper, community data, lemmy.world, activitypub, no-code scraping. # Actor input Schema ## `mode` (type: `string`): What to scrape. 'posts' fetches a post feed from an instance/community by sort order. 'search' runs a full-text search across posts on the instance. ## `instance` (type: `string`): Lemmy instance domain to scrape, e.g. 'lemmy.world', 'lemmy.ml' or 'sh.itjust.works'. Enter the host only, without https://. ## `community` (type: `string`): Optional community to limit the feed to, e.g. 'technology' or 'asklemmy'. Use the local name, or 'name@instance' for a remote community. Only used in 'posts' mode. ## `sort` (type: `string`): Sort order for the post feed (used in 'posts' mode). 'Hot' balances score and recency; 'TopDay/Week/All' rank by score over a time window. ## `query` (type: `string`): Full-text search query. Required when mode is 'search'; ignored in 'posts' mode. ## `maxItems` (type: `integer`): Maximum number of posts to scrape. The Actor paginates until this many posts are collected or results run out. ## Actor input object example ```json { "mode": "posts", "instance": "lemmy.world", "community": "technology", "sort": "Hot", "query": "linux", "maxItems": 100 } ``` # 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 = { "instance": "lemmy.world" }; // Run the Actor and wait for it to finish const run = await client.actor("ninhothedev/lemmy-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "instance": "lemmy.world" } # Run the Actor and wait for it to finish run = client.actor("ninhothedev/lemmy-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "instance": "lemmy.world" }' | apify call ninhothedev/lemmy-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ninhothedev/lemmy-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Lemmy Scraper β€” Posts, Scores & Comments (No Key)", "description": "$0.5/1K πŸ”₯ Fast Lemmy scraper! Posts from any instance or community β€” title, score, comments & author. No key. JSON, CSV, Excel or API in seconds. Pull thousands for social monitoring & trend research ⚑", "version": "0.1", "x-build-id": "YRawaQjPpUenTpeot" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ninhothedev~lemmy-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ninhothedev-lemmy-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/ninhothedev~lemmy-scraper/runs": { "post": { "operationId": "runs-sync-ninhothedev-lemmy-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/ninhothedev~lemmy-scraper/run-sync": { "post": { "operationId": "run-sync-ninhothedev-lemmy-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": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "posts", "search" ], "type": "string", "description": "What to scrape. 'posts' fetches a post feed from an instance/community by sort order. 'search' runs a full-text search across posts on the instance.", "default": "posts" }, "instance": { "title": "Instance", "type": "string", "description": "Lemmy instance domain to scrape, e.g. 'lemmy.world', 'lemmy.ml' or 'sh.itjust.works'. Enter the host only, without https://.", "default": "lemmy.world" }, "community": { "title": "Community (optional)", "type": "string", "description": "Optional community to limit the feed to, e.g. 'technology' or 'asklemmy'. Use the local name, or 'name@instance' for a remote community. Only used in 'posts' mode." }, "sort": { "title": "Sort", "enum": [ "Active", "Hot", "New", "TopDay", "TopWeek", "TopAll" ], "type": "string", "description": "Sort order for the post feed (used in 'posts' mode). 'Hot' balances score and recency; 'TopDay/Week/All' rank by score over a time window.", "default": "Hot" }, "query": { "title": "Search query (optional)", "type": "string", "description": "Full-text search query. Required when mode is 'search'; ignored in 'posts' mode." }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of posts to scrape. The Actor paginates until this many posts are collected or results run out.", "default": 100 } } }, "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 } } } } } } } } } } ```