# Strava Segment & Club Intel - Public Segment, Climb & Club Data (`seibs.co/strava-segment-intel`) Actor Public Strava segment + club intelligence the locked-down API no longer hands out: normalized segments (distance, grade, elevation, climb category), aggregate club info, and popular-segments-by-area rollups. Logged-out, public-only, PII-minimized. For coaches and route analytics. - **URL**: https://apify.com/seibs.co/strava-segment-intel.md - **Developed by:** [Seibs.co](https://apify.com/seibs.co) (community) - **Categories:** Business, Developer tools, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $6.00 / 1,000 segment or club records 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 ## Strava Segment & Club Intel Public Strava **segment** and **club** intelligence the locked-down API no longer hands to third parties - normalized into one schema, with geometry-derived climb metrics and popular-segments-by-area rollups. In November 2024 Strava tightened its API: new apps default to **one authorized user**, broader access goes through a review/approval form, **AI/aggregation use is banned**, and a developer subscription gates the standard tier. The people that locks out - fitness-app builders, coaches, route/segment-analytics tools, endurance-gear marketers - are exactly who needs this data. This actor delivers the **public** segment/club surface that doesn't require an application: logged-out, public-only, and PII-minimized. > **Responsible use (read this first).** This actor reads **only logged-out, PUBLIC Strava data**. It does **not** log in, use any athlete credential, or collect individual athletes' names, IDs, photos, leaderboard positions, or any private activity/movement trace. Club output is **aggregate** (member *count* only). Segment geometry is the segment's own public road/trail shape, not a person. Use it for segment/route and **area** analytics, not to profile or track individuals. Respect Strava's Terms and applicable privacy law in your jurisdiction. --- ### What it does | Mode | Input | Output | |---|---|---| | **segment_detail** | `segment_ids` (IDs or URLs) | Normalized segment records - name, sport, location, and **distance / average + max grade / elevation gain-loss / climb category** *derived from Strava's own public geometry stream* - plus automatic **area rollups**. | | **club_profile** | `club_ids` (IDs or URLs) | **Aggregate** club records - name, sport, location, club type, **member count**, verified flag. No member identities, ever. | | **area_explore** | `bounds` or `center_lat/lng` + `radius_km` | Best-effort bounding-box discovery. Strava's explore endpoint is auth-gated when logged out, so this **fail-softs** with a documented note unless you supply a warm browser session (`browser_cdp_url`); place-level rollups still run over any `segment_ids` you provide. | #### Why the metrics are *derived* Since the Nov-2024 lockdown, the logged-out segment page no longer ships the numeric stats (effort/athlete counts, leaderboards) - those load behind a session. What **is** public is the segment's geometry stream (`/stream/segments/{id}`: the distance, altitude, and lat/lng arrays of the segment's shape). This actor computes distance, grade, elevation gain/loss, and a Strava-style **climb category** from that public geometry, and labels every computed value `metrics_source: "public_stream"` so you never mistake a derived grade for an official one. Worked example (live-verified): segment **229781 "Hawk Hill"** -> 2,658 m, 5.86% avg grade, +156 m, **Cat 4**. Segment **8109834 "Old La Honda"** -> 5,048 m, 7.7% avg grade, +389 m, **Cat 2**. --- ### Output Each record carries `record_type`: `segment`, `club`, `area_rollup`, plus a `responsible_use_note` header and any `fetch_error` / `explore_gated` notes. Dataset **views**: `overview` (AI-agent skim), `segments`, `clubs`, `areas`. ```json { "record_type": "segment", "segment_id": "229781", "name": "Hawk Hill", "activity_type": "ride", "display_location": "Marin Headlands (GGNRA), California", "distance_m": 2658.5, "distance_mi": 1.65, "average_grade_pct": 5.86, "max_grade_pct": 9.2, "elevation_diff_m": 155.9, "total_elevation_gain_m": 155.9, "climb_category": 4, "climb_category_label": "Cat 4", "start_latlng": [37.8331, -122.483451], "metrics_source": "public_stream", "source_url": "https://www.strava.com/segments/229781" } ```` *** ### Pricing (pay-per-event) | Event | Price | When | |---|---|---| | `segment_record` | $0.006 | One normalized segment or aggregate club record | | `metric_enrichment` | $0.012 | Per segment enriched with geometry-derived metrics | | `area_rollup` | $0.015 | Per popular-segments-by-area aggregation | | `scheduled_delta_run` | $0.050 | Per scheduled monitor run (new/changed deltas) | *** ### Anti-bot escalation ladder Strava's public pages usually answer the cheapest tier from a datacenter IP. On a real block the client escalates automatically: 1. **httpx** over the DATACENTER proxy. 2. **curl\_cffi** with Chrome TLS impersonation over the RESIDENTIAL proxy (defeats JA3/TLS-fingerprint WAFs). 3. **Playwright** (patchright stealth) over RESIDENTIAL / a warm `BROWSER_CDP_URL` session - for JS/Cloudflare challenges and to reach the auth-gated explore endpoint with the operator's *own* session (this actor never handles credentials). 4. **Fail-soft** - a documented note, run still finishes SUCCEEDED. Set `BROWSER_CDP_URL` to point the browser tier at a warm anti-detect browser. CAPTCHA-less by default. *** ### Monitor mode Run on a schedule (Apify Schedules) and the actor computes a delta vs the prior run - new/changed segments and **club member-count trends** (an aggregate, privacy-safe "leaderboard trend" signal) - and can post a Slack digest (`slack_webhook_url`). Adds `scheduled_delta_run` only on scheduled runs. *** ### What this actor will NOT do - No login, no athlete OAuth, no cookies carried in. - No individual athlete records, names, IDs, photos, or follower graphs. - No segment **leaderboards** (gated logged-out anyway) and no KOM/QOM holder identities. - No personal **routes** or **activities** - those are an individual's movement trace and are deliberately not built. These are hard product boundaries, not toggles. *** ### MCP / AI agents A companion **`mcp-strava-segment-intel`** server exposes these as MCP tools (`get_segments`, `get_club`, `area_rollup`, `explore_segments`) for Claude, Cursor, OpenAI, and LangChain, with x402 (USDC on Base) and Skyfire agentic-payment support. The dataset also ships an MCP-compatible JSON link (see Output tab). ### Who it's for Cycling/running businesses, coaches and route/segment-analytics tools, endurance-gear marketers, and AI agents doing route/area research - anyone shut out by the Nov-2024 API lockdown who needs the public segment/club layer without an application. # Actor input Schema ## `mode` (type: `string`): segment\_detail = normalize specific public segments (by ID/URL) + auto area rollups. club\_profile = aggregate public club info (member COUNT only, no member identities). area\_explore = best-effort bounding-box segment discovery (Strava's explore endpoint is auth-gated logged-out, so this fail-softs unless you supply a warm browser session). ## `segment_ids` (type: `array`): Strava segment IDs (e.g. '229781') or full URLs (e.g. 'https://www.strava.com/segments/8109834'). Used in segment\_detail mode (and to seed area rollups in area\_explore). Hard cap of 200. ## `club_ids` (type: `array`): Strava club IDs (e.g. '106667') or URLs (e.g. 'https://www.strava.com/clubs/106667'). Used in club\_profile mode. Output is aggregate (name, sport, location, member COUNT) - individual member identities are never collected. Hard cap of 100. ## `bounds` (type: `string`): Geographic bounding box for area\_explore as 'sw\_lat,sw\_lng,ne\_lat,ne\_lng' (e.g. '37.82,-122.51,37.84,-122.48'). Alternatively use center\_lat + center\_lng + radius\_km. ## `center_lat` (type: `string`): Latitude of the area center for area\_explore (alternative to bounds). Pair with center\_lng and radius\_km. ## `center_lng` (type: `string`): Longitude of the area center for area\_explore (alternative to bounds). Pair with center\_lat and radius\_km. ## `radius_km` (type: `integer`): Radius in km around the center for area\_explore (0.5-50). Default 5. ## `activity_type` (type: `string`): Activity type for area\_explore discovery: 'riding' or 'running'. ## `include_derived_metrics` (type: `boolean`): Fetch the public segment geometry stream and DERIVE distance, average/max grade, elevation gain/loss, and climb category. Adds a metric\_enrichment PPE charge per segment that yields metrics. On by default - it is the core value. ## `include_geometry` (type: `boolean`): Attach the segment's full lat/lng polyline (its public road/trail shape) to each record. Off by default (bulky). Start/end points are always included as inherent public segment facts. ## `max_results` (type: `integer`): Hard cap on how many segments or clubs are fetched this run. Default 100. ## `use_browser_fallback` (type: `boolean`): When the cheap httpx tier is blocked, escalate to curl\_cffi TLS impersonation (residential) and then a stealth Playwright browser. Also enables the browser leg used for the auth-gated explore endpoint. Disable for the cheapest httpx-only runs. ## `browser_cdp_url` (type: `string`): Optional. CDP endpoint of an already-running warm / anti-detect browser. The browser tier connects to it instead of launching a fresh Chromium - inheriting its session + IP. This is how an operator can reach the auth-gated explore endpoint with their own logged-in session; this actor never handles credentials itself. ## `slack_webhook_url` (type: `string`): Optional. When this actor runs on a schedule, post a new/changed-segment (and club member-count delta) digest to this Slack incoming webhook. Adds scheduled\_delta\_run PPE on scheduled runs only. ## `use_apify_proxy` (type: `boolean`): Route requests through Apify Proxy. DATACENTER is used for the cheap httpx pass; RESIDENTIAL is provisioned for the escalation legs. ## `apify_proxy_groups` (type: `array`): Apify Proxy groups for the first (httpx) tier. DATACENTER is fine for Strava's public pages. ## `concurrency` (type: `integer`): Parallel Strava requests. Capped at 6 and rate-limited with an inter-request delay to stay polite. ## Actor input object example ```json { "mode": "segment_detail", "segment_ids": [ "229781", "8109834" ], "club_ids": [], "bounds": "", "center_lat": "", "center_lng": "", "radius_km": 5, "activity_type": "riding", "include_derived_metrics": true, "include_geometry": false, "max_results": 25, "use_browser_fallback": true, "browser_cdp_url": "", "slack_webhook_url": "", "use_apify_proxy": true, "apify_proxy_groups": [ "DATACENTER" ], "concurrency": 3 } ``` # Actor output Schema ## `datasetItems` (type: `string`): Narrow, token-efficient slice of every record. Consumer: LLM agents (Claude, GPT, LangChain tools), MCP hosts, dashboards. Fields: type, name, sport, location, distance, grade, climb, members, URL. ## `datasetItemsSegments` (type: `string`): Public segments with geometry-derived distance, grade, elevation, and climb category. Consumer: cycling/running businesses, coaches, route/segment analytics. ## `datasetItemsClubs` (type: `string`): Aggregate public club info - member COUNT only, no member identities. Consumer: club/community analysts, endurance-gear marketers. ## `datasetItemsAreas` (type: `string`): Popular-segments-by-area aggregation (region x activity). Consumer: route planners, local-segment leaderboards, area analytics. ## `datasetItemsMcp` (type: `string`): First 50 overview records as a clean JSON array. Wrap on the agent side in an MCP tool-call response envelope, e.g. `{ "ok": true, "data": , "meta": { "actor": "strava-segment-intel", "count": , "view": "overview" } }`. Consumer: MCP servers, Claude Desktop, Cursor, OpenAI Assistants tool calls. ## `datasetItemsCsv` (type: `string`): Spreadsheet-friendly export of the overview view. Consumer: humans, analysts, Excel / Google Sheets users. # 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 = { "mode": "segment_detail", "segment_ids": [ "229781", "8109834" ], "max_results": 25 }; // Run the Actor and wait for it to finish const run = await client.actor("seibs.co/strava-segment-intel").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 = { "mode": "segment_detail", "segment_ids": [ "229781", "8109834", ], "max_results": 25, } # Run the Actor and wait for it to finish run = client.actor("seibs.co/strava-segment-intel").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 '{ "mode": "segment_detail", "segment_ids": [ "229781", "8109834" ], "max_results": 25 }' | apify call seibs.co/strava-segment-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seibs.co/strava-segment-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Strava Segment & Club Intel - Public Segment, Climb & Club Data", "description": "Public Strava segment + club intelligence the locked-down API no longer hands out: normalized segments (distance, grade, elevation, climb category), aggregate club info, and popular-segments-by-area rollups. Logged-out, public-only, PII-minimized. For coaches and route analytics.", "version": "0.1", "x-build-id": "pNyuhB0bueB35dTvr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seibs.co~strava-segment-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seibs.co-strava-segment-intel", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seibs.co~strava-segment-intel/runs": { "post": { "operationId": "runs-sync-seibs.co-strava-segment-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seibs.co~strava-segment-intel/run-sync": { "post": { "operationId": "run-sync-seibs.co-strava-segment-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "segment_detail", "club_profile", "area_explore" ], "type": "string", "description": "segment_detail = normalize specific public segments (by ID/URL) + auto area rollups. club_profile = aggregate public club info (member COUNT only, no member identities). area_explore = best-effort bounding-box segment discovery (Strava's explore endpoint is auth-gated logged-out, so this fail-softs unless you supply a warm browser session).", "default": "segment_detail" }, "segment_ids": { "title": "Segment IDs or URLs", "maxItems": 200, "type": "array", "description": "Strava segment IDs (e.g. '229781') or full URLs (e.g. 'https://www.strava.com/segments/8109834'). Used in segment_detail mode (and to seed area rollups in area_explore). Hard cap of 200.", "default": [], "items": { "type": "string" } }, "club_ids": { "title": "Club IDs or URLs", "maxItems": 100, "type": "array", "description": "Strava club IDs (e.g. '106667') or URLs (e.g. 'https://www.strava.com/clubs/106667'). Used in club_profile mode. Output is aggregate (name, sport, location, member COUNT) - individual member identities are never collected. Hard cap of 100.", "default": [], "items": { "type": "string" } }, "bounds": { "title": "Bounding box (area_explore)", "type": "string", "description": "Geographic bounding box for area_explore as 'sw_lat,sw_lng,ne_lat,ne_lng' (e.g. '37.82,-122.51,37.84,-122.48'). Alternatively use center_lat + center_lng + radius_km.", "default": "" }, "center_lat": { "title": "Center latitude (area_explore)", "type": "string", "description": "Latitude of the area center for area_explore (alternative to bounds). Pair with center_lng and radius_km.", "default": "" }, "center_lng": { "title": "Center longitude (area_explore)", "type": "string", "description": "Longitude of the area center for area_explore (alternative to bounds). Pair with center_lat and radius_km.", "default": "" }, "radius_km": { "title": "Radius km (area_explore)", "minimum": 1, "maximum": 50, "type": "integer", "description": "Radius in km around the center for area_explore (0.5-50). Default 5.", "default": 5 }, "activity_type": { "title": "Activity type (area_explore)", "enum": [ "riding", "running" ], "type": "string", "description": "Activity type for area_explore discovery: 'riding' or 'running'.", "default": "riding" }, "include_derived_metrics": { "title": "Derive segment metrics from public geometry", "type": "boolean", "description": "Fetch the public segment geometry stream and DERIVE distance, average/max grade, elevation gain/loss, and climb category. Adds a metric_enrichment PPE charge per segment that yields metrics. On by default - it is the core value.", "default": true }, "include_geometry": { "title": "Include the full segment polyline", "type": "boolean", "description": "Attach the segment's full lat/lng polyline (its public road/trail shape) to each record. Off by default (bulky). Start/end points are always included as inherent public segment facts.", "default": false }, "max_results": { "title": "Max segments/clubs to fetch", "minimum": 1, "maximum": 200, "type": "integer", "description": "Hard cap on how many segments or clubs are fetched this run. Default 100.", "default": 100 }, "use_browser_fallback": { "title": "Enable anti-bot escalation (curl_cffi + browser)", "type": "boolean", "description": "When the cheap httpx tier is blocked, escalate to curl_cffi TLS impersonation (residential) and then a stealth Playwright browser. Also enables the browser leg used for the auth-gated explore endpoint. Disable for the cheapest httpx-only runs.", "default": true }, "browser_cdp_url": { "title": "Warm browser CDP URL (optional)", "type": "string", "description": "Optional. CDP endpoint of an already-running warm / anti-detect browser. The browser tier connects to it instead of launching a fresh Chromium - inheriting its session + IP. This is how an operator can reach the auth-gated explore endpoint with their own logged-in session; this actor never handles credentials itself.", "default": "" }, "slack_webhook_url": { "title": "Slack webhook (monitor mode)", "type": "string", "description": "Optional. When this actor runs on a schedule, post a new/changed-segment (and club member-count delta) digest to this Slack incoming webhook. Adds scheduled_delta_run PPE on scheduled runs only.", "default": "" }, "use_apify_proxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Route requests through Apify Proxy. DATACENTER is used for the cheap httpx pass; RESIDENTIAL is provisioned for the escalation legs.", "default": true }, "apify_proxy_groups": { "title": "Proxy groups (httpx tier)", "type": "array", "description": "Apify Proxy groups for the first (httpx) tier. DATACENTER is fine for Strava's public pages.", "default": [ "DATACENTER" ], "items": { "type": "string" } }, "concurrency": { "title": "Max concurrent requests", "minimum": 1, "maximum": 6, "type": "integer", "description": "Parallel Strava requests. Capped at 6 and rate-limited with an inter-request delay to stay polite.", "default": 3 } } }, "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 } } } } } } } } } } ```