# Instagram Trending Scraper (`agentx/instagram-trending-scraper`) Actor Extract structured Instagram Explore trending posts with 25 fields per item including topic labels, captions, media links, engagement counts, and optional media downloads from Instagram's public Explore feed. - **URL**: https://apify.com/agentx/instagram-trending-scraper.md - **Developed by:** [AgentX](https://apify.com/agentx) (community) - **Categories:** Social media, Lead generation, Videos - **Stats:** 3 total users, 2 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 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 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 ## Instagram Trending Scraper - Instagram Explore Data Extraction API **Extract structured Instagram Explore trending posts with 25 fields per item including topic labels, captions, media links, engagement counts, and optional media downloads from Instagram's public Explore feed.** This Instagram Explore scraper API delivers schema-ready JSON output for trend intelligence, content benchmarking, viral content detection, and social media analytics pipelines — no username or authentication required. [![Instagram](https://img.shields.io/badge/Instagram-ffd700?style=for-the-badge&color=ffd700)](https://apify.com/agentx/instagram-trending-scraper?fpr=aiagentapi) [![25+ Fields](https://img.shields.io/badge/25+_Fields-ffd700?style=for-the-badge&color=ffd700)](https://apify.com/agentx/instagram-trending-scraper?fpr=aiagentapi) [![Explore Feed](https://img.shields.io/badge/Explore_Feed-ffd700?style=for-the-badge&color=ffd700)](https://apify.com/agentx/instagram-trending-scraper?fpr=aiagentapi) [![Trend Intelligence](https://img.shields.io/badge/Trend_Intelligence-ffd700?style=for-the-badge&color=ffd700)](https://apify.com/agentx/instagram-trending-scraper?fpr=aiagentapi) --- ### Why Choose This Instagram Explore Scraper API #### Structured Instagram Trend Intelligence for Data Pipelines **🔥 Topic-Labeled Trending Post Extraction** Extract trending posts from Instagram's Explore feed with embedded `section` (e.g., Fashion & Beauty) and `topic` (e.g., Street Fashion) taxonomy labels — enabling category-level trend tracking, topic segmentation, and niche monitoring without hashtag reliance. **🎯 No Username Required — Feed-Level Access** Target Instagram's public Explore feed directly. Configure `max_results` to control extraction volume with no profile-specific targeting. Ideal for market-wide trend monitoring and content intelligence aggregation pipelines. **📸 Complete Media Asset Extraction** Access direct image URLs, thumbnail URLs, video URLs, and pixel dimensions per post. Configure `download_medias` to store media files directly to Apify storage — no additional processing steps required. **❤️ Engagement Signal Coverage Per Explore Item** Extract likes, comments, and play counts per trending post. Combine with topic labels and post timestamps for viral velocity analysis, platform recommendation intelligence, and content trend scoring. **🎬 Carousel & Reel Support** The `media_items` array preserves all carousel media parts with per-item position, type, dimensions, and asset URLs. Reels deliver video URL, duration, and audio availability flags alongside standard engagement counts. **📊 AI-Ready JSON Output** Structured output optimized for LangChain, CrewAI, AutoGPT, and custom ML pipelines. Compatible with any ETL tool, vector database, or downstream content trend classification workflow. --- ### Why Choose This API This actor is designed for structured output, repeatable automation, and downstream integration in monitoring, enrichment, or ingestion pipelines. ### Quick Start Guide #### How to Extract Instagram Trending Data in 3 Steps ##### Step 1: Configure Your Extraction [Open Actor Page](https://apify.com/agentx/instagram-trending-scraper?fpr=aiagentapi) ##### Step 2: Run the Actor Click "Start" and the scraper will extract structured trending posts from Instagram's public Explore feed. ##### Step 3: Download Your Data Export results in JSON format or access via API. Each record delivers 25 fields per post including topic labels, captions, engagement counts, and media asset links. --- ### Input Parameters #### Required Configuration Fields | Parameter | Type | Description | Example Values | | ----------------- | ------- | ------------------------------------------------------------------------------------------------ | ---------------------------- | | `max_results` | integer | Number of trending Explore posts to extract from the current feed | `50`, `100`, `500` | | `download_medias` | string | Media download mode: `none` keeps URLs only, `image` downloads images, `all` downloads all media | `"none"`, `"image"`, `"all"` | #### Media Download Modes | Mode | Description | Additional Cost | | ------- | --------------------------------------------------- | ---------------- | | `none` | Returns direct media URLs without downloading files | None | | `image` | Downloads and stores image files to Apify storage | +$0.001 per post | | `all` | Downloads and stores all images and video files | +$0.001 per post | > **Pro Tip**: Use `none` for trend signal pipelines that only need metadata and URLs. Use `image` or `all` when building visual training datasets or media archival workflows. #### Example Input JSON ```json { "max_results": 50, "download_medias": "none" } ```` *** ### Output Data Schema #### 25 Structured Fields Per Explore Post | Field | Type | Description | | --------------- | ------- | -------------------------------------------------------------------------- | | `processor` | string | URL of the Actor that processed this record | | `processed_at` | string | ISO 8601 timestamp of when this post was processed | | `id` | string | Instagram media identifier | | `code` | string | Instagram post shortcode | | `url` | string | Public URL to the Instagram post or reel | | `username` | string | Username of the account that published the post | | `section` | string | Instagram Explore section that surfaced this post (e.g., Fashion & Beauty) | | `topic` | string | Specific Explore topic label (e.g., Street Fashion, Pop Music) | | `type` | string | Instagram post type: `clips`, `carousel_container`, or `image` | | `is_video` | boolean | Whether the post contains video content | | `caption` | string | Full caption text of the post | | `timestamp` | integer | Unix timestamp when the post was published | | `date` | string | ISO 8601 timestamp when the post was published | | `likes` | integer | Like count for the post | | `comments` | integer | Comment count for the post | | `plays` | integer | View or play count when available | | `duration` | integer | Video duration in seconds when available | | `has_audio` | boolean | Whether Instagram reports audio on the post | | `location` | string | Location tag associated with the post when available | | `image_url` | string | Primary image URL or stored file path | | `thumbnail_url` | string | Thumbnail URL or stored file path | | `video_url` | string | Video URL or stored file path when available | | `width` | integer | Media width in pixels | | `height` | integer | Media height in pixels | | `media_count` | integer | Number of media items in the post | | `media_items` | array | Array of per-item media data for carousels and multi-media posts | #### Example JSON Output ```json { "processor": "https://apify.com/agentx/instagram-trending-scraper?fpr=aiagentapi", "processed_at": "2026-07-02T10:30:00Z", "id": "3877256089956040035_227764111", "code": "DXOx98JDL1j", "url": "https://www.instagram.com/reel/DXOx98JDL1j/", "username": "fashionblogger", "section": "Fashion & Beauty", "topic": "Street Fashion", "type": "clips", "is_video": true, "caption": "Outfit of the day #streetstyle #fashion", "timestamp": 1776528189, "date": "2026-04-17T17:23:09+00:00", "likes": 2450, "comments": 89, "plays": 54200, "duration": 30, "has_audio": true, "location": "New York", "image_url": "https://example.com/post.jpg", "thumbnail_url": "https://example.com/thumb.jpg", "video_url": "https://example.com/video.mp4", "width": 1080, "height": 1920, "media_count": 1, "media_items": [ { "position": 1, "id": "3877256089956040035_227764111", "is_video": true, "image_url": "https://example.com/post.jpg", "thumbnail_url": "https://example.com/thumb.jpg", "video_url": "https://example.com/video.mp4", "width": 1080, "height": 1920 } ] } ``` #### Export Formats - **JSON** - Complete structured data with all 25 fields - **CSV** - Spreadsheet-compatible flat format - **API Access** - Programmatic access via Apify Client SDK - **Cloud Storage** - Automatic upload to Apify Dataset *** ### Integration Examples #### Actor ID for Platform Integration ```text bUkw01H4rn1K9brjp ``` #### Ⓜ️ [Make.com Setup:](https://www.make.com/en/register?pc=marketingme) 1. Login to **[Make.com (Get 1000 Free Credits)](https://www.make.com/en/register?pc=marketingme)** 2. Add module **"Run an Actor"** 3. Turn **'Map'** on - right side of the 'Actor\*' 4. Paste **Actor ID** - from above 5. Click the **'⟳ Refresh'** - left side of Map 6. **Input JSON\*** - Modify the parameters as needed 7. Set **"Run synchronously"** to **YES** 8. Add module **"Get Dataset Items"** - receive the result 9. In **Dataset ID\*** select **defaultDatasetId** #### 🎱 [N8N.io Setup:](https://n8n.io/) 1. Add **'Run an Actor and get dataset'** - from the apify node 2. **Actor** → **By ID** → **Paste Actor ID** - from above 3. **Input JSON** - Modify the parameters as needed #### Python Integration Example ```python from apify_client import ApifyClient client = ApifyClient('YOUR_API_TOKEN') run_input = { "max_results": 50, "download_medias": "none" } run = client.actor("bUkw01H4rn1K9brjp").call(run_input=run_input) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` #### JavaScript/Node.js Integration ```javascript import { ApifyClient } from "apify-client"; const client = new ApifyClient({ token: "YOUR_API_TOKEN", }); const input = { max_results: 50, download_medias: "none", }; const run = await client.actor("bUkw01H4rn1K9brjp").call(input); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.log(item); }); ``` #### JSON-LD Metadata ```json { "@context": "https://schema.org", "@type": "SoftwareApplication", "name": "Instagram Trending Scraper", "description": "Instagram Explore data extraction API delivering 25 structured fields per trending post with topic labels for trend intelligence and content analytics pipelines", "applicationCategory": "Developer Tools", "operatingSystem": "Cloud", "url": "https://apify.com/agentx/instagram-trending-scraper?fpr=aiagentapi", "dateModified": "2026-04-21", "offers": { "@type": "Offer", "price": "0.0025", "priceCurrency": "USD" } } ``` *** ### Pricing & Cost Calculator #### Transparent Pay-Per-Use Model | Event Type | Price | Description | | --------------- | ------- | -------------------------------------------------------------------------------------------------------------------------------- | | **Actor Start** | $0.01 | One-time charge per Actor run (charged per GB of memory, minimum one event) | | **Post Result** | $0.0025 | Charged for each Explore post extracted. Includes topic label, caption, engagement counts, media URLs, and all 25 schema fields. | | **Media** | $0.001 | Additional charge per post when `download_medias` is set to `image` or `all` | #### Cost Examples **URL-Only Mode** (100 posts, `download_medias: "none"`): - Post Data: 100 × $0.0025 = $0.25 - Actor Start: $0.01 - **Total**: ~$0.26 **Image Download Mode** (100 posts, `download_medias: "image"`): - Post Data: 100 × $0.0025 = $0.25 - Media: 100 × $0.001 = $0.10 - Actor Start: $0.01 - **Total**: ~$0.36 **Large Scale** (1,000 posts, URL-only): - Post Data: 1,000 × $0.0025 = $2.50 - Actor Start: $0.01 - **Total**: ~$2.51 #### Competitive Pricing Comparison | Feature | Instagram Trending Scraper | Bright Data | Octoparse | ScrapingBee | | ------------------------ | -------------------------- | ----------- | ----------- | ----------- | | **Cost per 1K Posts** | **$2.50** ⭐ | $4.80 | $5.50 | $4.00 | | **Topic Labels** | **Section + Topic** ⭐ | No | No | No | | **No Username Required** | **Yes** ⭐ | Profile req | Profile req | Profile req | | **Media Downloads** | **Built-in** ⭐ | No | No | No | | **API Quality** | **Enterprise** ⭐ | Complex | No API | Basic | *** ### Use Cases & Applications #### Trend Intelligence & Market Research **Instagram Platform Trend Monitoring** Extract structured Explore posts daily to track which content categories Instagram promotes algorithmically. The `section` and `topic` fields reveal platform-level trend taxonomy — enabling topic velocity analysis and early trend signal detection without relying on hashtag proxies. **Category-Level Content Analysis** Segment Explore posts by `section` and `topic` to analyze content formats, engagement patterns, and creator characteristics per Instagram category. Feed into brand strategy tools, category research reports, and market intelligence dashboards. **Viral Content Detection** Monitor engagement-to-post-age ratios across Explore items to identify posts gaining velocity before they reach mainstream awareness. Build automated alerts for viral signals in specific topic categories. #### AI & Machine Learning Applications **Multimodal Training Datasets** Combine Explore post captions, topic labels, and media assets to build training datasets for content classification models, visual trend detectors, and caption-style recommenders — all labeled with Instagram's own taxonomy. **Trend Prediction Models** Build time-series models using daily Explore snapshots to predict which topic categories and content formats will gain traction on Instagram's recommendation algorithm. **NLP & Caption Intelligence** Extract caption text from high-engagement Explore posts per topic category to train topic-specific language models, hashtag recommendation systems, and content rephrasing pipelines. #### Content Strategy & Agency Tools **Content Calendar Research** Query daily Explore data to identify which post formats and topics are receiving algorithm promotion in your client's industry category — informing data-driven content planning. **Competitive Content Benchmarking** Compare engagement benchmarks across Explore topic categories to establish performance baselines for brand content strategies and influencer brief requirements. **Visual Asset Curation** Download trending visual assets with media download mode for mood board creation, creative inspiration workflows, and UGC identification pipelines. #### Media & Publishing **Editorial Trend Coverage** Journalists and content teams can extract structured Explore data to support trend coverage, verify emerging cultural moments, and quantify engagement signals for story prioritization. **Platform Algorithm Research** Researchers can build longitudinal datasets of Instagram Explore content to study recommendation algorithm behavior, category distribution patterns, and engagement amplification signals. *** ### FAQ #### What data does the Instagram Trending Scraper extract per post? Each run returns **25 structured fields** per Explore post including `section` and `topic` taxonomy labels, caption, media URLs (image, thumbnail, video), engagement counts (likes, comments, plays), timestamps, media dimensions, and carousel item arrays. #### Does this require a username or authentication? No. This actor targets **Instagram's public Explore feed** directly. No username input, login, or Instagram account is required. Set `max_results` and run. #### What are `section` and `topic` fields? These fields reflect Instagram's internal Explore taxonomy. `section` is the broad category (e.g., "Fashion & Beauty", "Music", "Food & Drink") and `topic` is the specific subcategory (e.g., "Street Fashion", "Pop Music"). Both are sourced from Instagram's Explore feed metadata. #### What is the difference between `download_medias` modes? - `none`: Returns media URLs without downloading — lowest cost, fastest execution - `image`: Downloads and stores image files to Apify key-value storage — enables offline access to images - `all`: Downloads images and videos — suitable for archival and training dataset assembly #### What format does the output use? Output is **structured JSON** with 25 fields per post. Data is also available in CSV format and via REST API using the Apify dataset endpoint. #### Can I filter by specific Explore topic categories? Topic filtering is not available as an input parameter — the actor collects posts from the public Explore feed as Instagram presents them. Filter the output dataset by `section` or `topic` field values in your downstream pipeline. #### Is the scraper compatible with AI frameworks? Yes. The JSON output is optimized for **LangChain, CrewAI, AutoGPT**, and other AI frameworks. Topic-labeled Explore data is directly suitable for trend classification agents, content recommendation systems, and multimodal analytics pipelines. #### How often does the Explore feed change? Instagram's Explore feed refreshes continuously. Run the actor on a **scheduled basis** (daily or hourly) to capture trending content snapshots over time. Each run returns the current state of the public Explore feed at execution time. #### Why might the same post appear in multiple runs? Trending Explore posts can remain visible for hours or days. Use the `id` or `code` field as a deduplication key when merging runs into a single dataset. #### Why are some topic fields empty? Not all Explore posts are classified with a topic label. The `topic` field is populated when Instagram's Explore feed includes topic metadata for that specific post. Section labels have higher coverage than topic labels. *** ### SEO Keywords & Search Terms #### Primary Keywords instagram trending scraper, instagram explore API, instagram trending data extraction, instagram explore scraper API, instagram trend intelligence, instagram viral content API, instagram explore feed extraction, trending instagram posts API, instagram topic monitoring, instagram explore structured data #### Long-Tail Keywords how to scrape instagram explore trending posts, instagram explore API structured JSON schema, bulk instagram trending content scraper for analytics, instagram topic label extraction API, instagram explore engagement data pipeline, viral content detection pipeline instagram, instagram trending feed structured extraction, instagram explore topic taxonomy API, instagram trend monitoring pipeline no login, instagram explore category post extraction #### Industry Terms social media trend intelligence, instagram algorithm research, explore feed analytics, content trend detection, viral signal monitoring, instagram platform intelligence, social media trend API, instagram recommendation data, explore content benchmarking, instagram category analytics #### Use Case Keywords AI training data instagram trending, instagram trend prediction model, instagram content calendar research, instagram algorithm insights API, instagram topic classification pipeline, explore feed viral detection, instagram brand strategy intelligence, multimodal trend dataset instagram, social media market intelligence explore, instagram content velocity analysis *** ### Trust & Certifications - ✅ **Enterprise Ready** - Used by analytics platforms, media companies, and trend intelligence tools - ✅ **GDPR Compliant** - EU data protection standards and privacy regulations - ✅ **99.9% Uptime** - Reliable cloud infrastructure with automatic failover - ✅ **Regular Updates** - Continuous maintenance for Instagram platform changes *** ### Legal & Compliance #### Data Rights & Usage All data extracted by this actor originates from publicly available Instagram Explore pages. Users are responsible for ensuring their use of extracted data complies with applicable laws and regulations in their jurisdiction. #### Privacy Compliance - **GDPR**: Compliant with EU General Data Protection Regulation. No personal data is stored beyond the extraction session. - **CCPA**: Compliant with California Consumer Privacy Act requirements. Data processing follows privacy-by-design principles. #### Platform Terms of Service Users must review and comply with Instagram's terms of service when using extracted data. This tool accesses only publicly available information visible without authentication. #### Enterprise Support For enterprise licensing, custom integrations, or compliance inquiries, contact our team: - **Telegram**: [@AiAgentApi](https://t.me/AiAgentApi) *** ### Related Tools #### Instagram - **[Instagram Creator Scraper](https://apify.com/agentx/instagram-creator-scraper?fpr=aiagentapi)** - Instagram Profile Data Extraction & Creator Intelligence - **[Instagram Post Reel Scraper](https://apify.com/agentx/instagram-post-reel-scraper?fpr=aiagentapi)** - Instagram Feed Post & Reel Extraction API - **[Instagram Trending Scraper](https://apify.com/agentx/instagram-trending-scraper?fpr=aiagentapi)** - Instagram Explore Trending Content Extraction API (This Tool) #### Jobs & Hiring - **[All Job Scraper](https://apify.com/agentx/all-jobs-scraper?fpr=aiagentapi)** - Multi-Platform Job Data Extraction API for Indeed, LinkedIn & Glassdoor - **[Indeed Hiring Scraper](https://apify.com/agentx/indeed-hiring-scraper?fpr=aiagentapi)** - 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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 = { "max_results": 10, "download_medias": "none" }; // Run the Actor and wait for it to finish const run = await client.actor("agentx/instagram-trending-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 = { "max_results": 10, "download_medias": "none", } # Run the Actor and wait for it to finish run = client.actor("agentx/instagram-trending-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 '{ "max_results": 10, "download_medias": "none" }' | apify call agentx/instagram-trending-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agentx/instagram-trending-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Instagram Trending Scraper", "description": "Extract structured Instagram Explore trending posts with 25 fields per item including topic labels, captions, media links, engagement counts, and optional media downloads from Instagram's public Explore feed.", "version": "0.0", "x-build-id": "fVZ3nAjTBptGoaxGE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agentx~instagram-trending-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agentx-instagram-trending-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/agentx~instagram-trending-scraper/runs": { "post": { "operationId": "runs-sync-agentx-instagram-trending-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/agentx~instagram-trending-scraper/run-sync": { "post": { "operationId": "run-sync-agentx-instagram-trending-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "max_results", "download_medias" ], "properties": { "max_results": { "title": "📊 Max Results", "minimum": 10, "maximum": 1000000, "type": "integer", "description": "Maximum number of public Explore posts to extract from Instagram's current Explore feed per run." }, "download_medias": { "title": "📥 Download Medias", "enum": [ "none", "image", "all" ], "type": "string", "description": "Configure media output handling: preserve source URLs only, download images to cloud storage, or archive all media files." } } }, "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 } } } } } } } } } } ```