# Telegram Post Scraper · Media downloader, stats & metadata (`arachnetix/tg-post-stats`) Actor Paste any public Telegram-message URLs – the actor will pull text, hashtags, mentions, full reaction stats, photos, voice messages and short videos. Perfect for analytics, content republishing or market research.⚠️Limitations: videos longer than one minute and file-attachments are not downloaded - **URL**: https://apify.com/arachnetix/tg-post-stats.md - **Developed by:** [Arachnetix](https://apify.com/arachnetix) (community) - **Categories:** Social media, Automation, Videos - **Stats:** 272 total users, 13 monthly users, 100.0% runs succeeded, 10 bookmarks - **User rating**: No ratings yet ## Pricing from $0.85 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Telegram Post Scraper · Media Downloader, Stats & Metadata **Bulk-extract everything you need from any public Telegram message or topic thread.** --- ### 🚀 Features * **Full post contents** – text (with paragraph breaks), emojis, hashtags, tags, mentions * **Media download** – photos (JPEG / PNG), voice messages (OGG/MP3) and videos up to **60 sec** (MP4) * **Rich engagement stats** – per-emoji reaction counts (free & paid), total reactions, views * **Deep metadata** – channel name, publication date (ISO 8601), verification badge, reply / forward links * **Unlimited URLs** – crawl hundreds of posts in one run, fully async with automatic retries * **Flexible output** – JSON (dataset default), plus one-click export to CSV, XLSX or Parquet inside Apify * Works with **topic threads** (`https://t.me/channel/1234/5678`) as well as regular posts --- ### ⚙️ Input ```json { "urls": [ "https://t.me/varlamov_news/62415", "https://t.me/OZON_int/13451/28364" ] } ```` | Field | Type | Required | Description | | ------ | -------------- | -------- | --------------------------------------------------- | | `urls` | array | ✅ | One Telegram post URL per line (threads supported). | *** ### 📊 Output Each item in the dataset contains: | Key | Example | Notes | | ---------------------- | ----------------------------------------------- | -------------------------------------- | | `url` | `https://t.me/varlamov_news/62415` | Original link | | `channel_name` | `Varlamov News` | — | | `publish_datetime_iso` | `2025-07-12T11:57:20+00:00` | UTC | | `is_verified` | `true` | Blue-tick channel | | `text` | `"Why is Stalin’s popularity growing?\n\n..."` | Clean text | | `photos` | `["https://.../file/abc.jpg"]` | Unique list | | `videos` | `["https://.../file/clip.mp4"]` | ≤ 60 s | | `audios` | `["https://.../file/voice.ogg"]` | Voice msgs | | `hashtags` | `["#history","#politics"]` | Order preserved | | `mentions` | `["@varlamov"]` | From links & plain text | | `forwarded_from` | `https://t.me/varlamov/9250` | Empty if none | | `reply_to` | `https://t.me/varlamov/9249` | Empty if none | | `views` | `171000` | Integer | | `reactions` | `{ "🔥":1050, "❤‍🔥":204, "😁":41}` | Dict | | `paid_reactions` | `5` | (`paid` = sum of super-reactions) | | `total_reactions` | `1385` | Paid + regular | | `username` | `varlamov_news` | Parsed from URL | | `message_id` | `62415` *** ### 🚦 Usage 1. **Create a task** for this Actor on Apify. 2. Paste your list of Telegram URLs into the *Input* field. 3. Click **Run**. 4. Download results from the *Dataset* tab in JSON, CSV, XLSX or Parquet. *** ### 📌 Typical use cases - **Social-media analytics** – monitor post performance across competitors or markets. - **Media backup** – bulk-download images, short videos and voice notes for archiving. - **Market research** – track hashtags, mentions and reaction sentiment over time. - **Content republishing** – retrieve assets and captions for newsletters, blogs or other channels. *** ### ⚠️ Limitations - Videos longer than **60 seconds** and file attachments (documents, GIFs, etc.) cannot be downloaded. - Private or deleted posts cannot be accessed. - The actor respects Telegram rate limits; extremely large batches may take longer. *** ### ❓ FAQ | Question | Answer | | -------------------------------------- | -------------------------------------------------------------------------------------------------------------- | | **Do I need a Telegram API key?** | No – we scrape the public web widgets, so no login is required. | | **Can I use proxies?** | Yes. Configure proxy settings in the Apify *Run* tab for better geodiversity or to avoid local blocking. | | **How many URLs can I submit?** | Practically unlimited. The actor processes them asynchronously and pushes each result immediately. | | **What happens if a link is invalid?** | You’ll receive an item with `"status":"error"` and the original `url` preserved, so your pipeline won’t break. | *** *Made with ❤️ by data engineers who spend too much time on Telegram.* # Actor input Schema ## `urls` (type: `array`): One link per line. Works with plain posts (e.g. https://t.me/varlamov\_news/62415) **and** topic threads (e.g. https://t.me/OZON\_int/13451/28364). ## Actor input object example ```json { "urls": [ "https://t.me/varlamov_news/62415" ] } ``` # 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://t.me/varlamov_news/62415" ] }; // Run the Actor and wait for it to finish const run = await client.actor("arachnetix/tg-post-stats").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://t.me/varlamov_news/62415"] } # Run the Actor and wait for it to finish run = client.actor("arachnetix/tg-post-stats").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://t.me/varlamov_news/62415" ] }' | apify call arachnetix/tg-post-stats --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=arachnetix/tg-post-stats", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Telegram Post Scraper · Media downloader, stats & metadata", "description": "Paste any public Telegram-message URLs – the actor will pull text, hashtags, mentions, full reaction stats, photos, voice messages and short videos. Perfect for analytics, content republishing or market research.⚠️Limitations: videos longer than one minute and file-attachments are not downloaded", "version": "0.0", "x-build-id": "8e9ml4Lh9AnoMi4Pg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/arachnetix~tg-post-stats/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-arachnetix-tg-post-stats", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/arachnetix~tg-post-stats/runs": { "post": { "operationId": "runs-sync-arachnetix-tg-post-stats", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/arachnetix~tg-post-stats/run-sync": { "post": { "operationId": "run-sync-arachnetix-tg-post-stats", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "urls" ], "properties": { "urls": { "title": "Telegram post URLs", "minItems": 1, "type": "array", "description": "One link per line. Works with plain posts (e.g. https://t.me/varlamov_news/62415) **and** topic threads (e.g. https://t.me/OZON_int/13451/28364).", "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 } } } } } } } } } } ```