# Hacker News Scraper - Stories, Jobs, Ask HN & Show HN (`lentic_clockss/hacker-news-scraper`) Actor
Export fresh Hacker News stories, comments, jobs, Ask HN, Show HN, and polls into structured datasets for research, hiring signals, and monitoring.
- **URL**: https://apify.com/lentic\_clockss/hacker-news-scraper.md
- **Developed by:** [kane liu](https://apify.com/lentic_clockss) (community)
- **Categories:** Jobs, Developer tools, Automation
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $2.00 / 1,000 results
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
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
## Hacker News Scraper – Stories, Jobs & Comments API
**Search Hacker News by keyword or export fresh Hacker News feeds into a clean Dataset.** This Actor collects public stories, comments, Ask HN, Show HN, jobs, polls, and poll options from two public HN data surfaces:
- keyword search through the public Algolia-powered Hacker News Search API
- live feed and item collection through the official Firebase API
Use `searchQuery` when you want results for a phrase such as `AI agents`, `vector database`, or `who is hiring`. Leave `searchQuery` empty when you want the current `top`, `new`, `best`, `ask`, `show`, or `job` feeds.
### What you can do with this Hacker News Scraper
#### 1. Search Hacker News by keyword
Enter a keyword or phrase in `searchQuery` and the Actor returns matching Hacker News items as structured rows. This is useful for research, monitoring, trend discovery, competitive intelligence, and agent workflows that need HN search results without scraping HTML.
| What you enter | Example |
| --- | --- |
| `searchQuery` | `AI agents` |
| `recordTypes` | `story`, `comment`, `job` |
| `maxItems` | `25` |
Search mode returns Algolia HN Search hits directly. Rows include `sourceSearchQuery` and `searchRank` so you can trace which keyword produced each result.
#### 2. Export the current Hacker News front page
Leave `searchQuery` empty and choose one or more official Firebase feeds such as `top`, `new`, or `best`. Each matching item becomes a normalized Dataset row with title, author, score, timestamp, URL, and direct HN link.
| What you enter | Example |
| --- | --- |
| `feeds` | `top`, `new`, or `best` |
| `recordTypes` | `story` |
| `maxItems` | `100` |
#### 3. Collect Ask HN and Show HN discussions
Use the `ask` and `show` feeds to export questions, launches, demos, and the public replies beneath them. Turn on descendant collection when comments matter as much as the root post.
| What you enter | Example |
| --- | --- |
| `feeds` | `ask`, `show` |
| `recordTypes` | `story`, `comment` |
| `includeDescendants` | `true` |
| `maxDepth` | `1` or `2` |
The feed collector schedules roots fairly and walks descendants breadth-first, so a single large thread does not silently monopolize a small run.
#### 4. Build a Hacker News jobs feed
Choose the official `job` feed to capture current HN job posts, or search for hiring-related phrases with `searchQuery`. Keep `recordTypes` set to `job` for a focused export.
#### 5. Retrieve known Hacker News items by ID
If another workflow already has Hacker News item IDs, leave `searchQuery` empty and add them to `itemIds`. The Actor collects those explicit IDs before feed roots and deduplicates all items within the run.
#### 6. Feed a dashboard, agent, or recurring workflow
Every row has stable `itemId`, `hnUrl`, source provenance, and a run timestamp. Export the Dataset to your data warehouse, spreadsheet, CRM enrichment step, or agent workflow without parsing Hacker News HTML.
For developers: low-cost JSON inputs
Keyword search:
```json
{
"searchQuery": "AI agents",
"recordTypes": ["story", "comment"],
"maxItems": 10,
"maxFetches": 10
}
````
Fresh feed collection:
```json
{
"feeds": ["top", "job"],
"recordTypes": ["story", "comment", "job", "poll", "pollopt"],
"includeDescendants": true,
"maxDepth": 1,
"maxItems": 20,
"maxFetches": 80
}
```
### How to use it — no code required
1. Click **Try for free** on this Actor page.
2. To search, enter a keyword in `searchQuery`.
3. To collect live feeds instead, leave `searchQuery` empty and select the Hacker News feeds you want.
4. Choose the item types you want in the Dataset.
5. Set `maxItems` and `maxFetches`, then click **Start**.
Download your results as Excel, CSV, JSON, or JSONL from the Dataset tab, or consume them through the Apify API.
### What you get back
Each output row is a normalized public Hacker News item. The fields stay consistent across stories, comments, jobs, polls, and poll options while preserving what the source supplied.
| Field | What it means |
| --- | --- |
| `itemId` | Stable Hacker News item ID. |
| `type` | `story`, `comment`, `job`, `poll`, or `pollopt`. |
| `title`, `text`, `url` | Public item content when present. |
| `by`, `time`, `createdAt` | Author and source timestamp. |
| `score`, `descendants` | Public engagement metadata when supplied by Hacker News or HN Search. |
| `parentId`, `kids`, `parts` | Thread and poll relationships when available. |
| `hnUrl` | Direct link to the item on Hacker News. |
| `sourceFeeds`, `rootItemId`, `depth` | Feed/item-ID provenance. Search rows use `sourceFeeds: ["algolia-search"]`. |
| `sourceSearchQuery`, `searchRank` | Keyword and rank for search-mode rows. |
| `deleted`, `dead` | Source state flags when supplied. |
| `source` | `hacker-news-algolia-search` or `hacker-news-firebase`. |
| `scrapedAt` | When this Actor collected the row. |
Malformed upstream records fail clearly before Dataset output instead of producing silently invalid rows.
### Input reference
The Apify input form exposes the same controls used at runtime:
| Parameter | Default | Description |
| --- | --- | --- |
| `searchQuery` | empty | Optional keyword or phrase. When set, the Actor runs HN keyword search. |
| `feeds` | `top`, `new`, `best`, `ask`, `show`, `job` | Official Firebase feed roots to collect when `searchQuery` is empty. |
| `recordTypes` | all five supported types | Item types retained in the Dataset. Applies to both search and feed modes. |
| `itemIds` | `[]` | Optional explicit positive Hacker News item IDs for feed/item-ID mode. |
| `includeDescendants` | `true` | Include public comment children and poll parts in feed/item-ID mode. |
| `maxDepth` | `2` | Descendant levels below each root; root depth is `0`. Not used in search mode. |
| `maxItems` | `100` | Maximum deduplicated Dataset records. |
| `maxFetches` | `500` | Maximum Firebase item detail requests in feed/item-ID mode; must be at least `maxItems`. |
#### Keyword search behavior
When `searchQuery` is set, the Actor uses the public Algolia-powered HN Search API and writes matching search hits to the Dataset. Feed traversal, descendant traversal, and `itemIds` are not used in this mode. Unsupported keyword aliases such as `query` and `keywords` are rejected so runs do not silently change scope.
### Data source and run boundaries
Keyword search uses the public [Algolia Hacker News Search API](https://hn.algolia.com/api). Feed and item-ID collection uses the public, unauthenticated [official Hacker News Firebase API](https://github.com/HackerNews/API). Live feeds and search rankings change continuously, so each run is a timestamped snapshot—not a historical archive or a guaranteed complete feed mirror.
Network requests have bounded retries. The Actor also uses an overall collection deadline, positive integer limits, per-run deduplication, source-ID verification for Firebase items, and breadth-first descendant traversal for feed mode. If the source cannot be retrieved or its response does not match the expected public contract, the run writes an `ERROR_SUMMARY` and fails instead of reporting a misleading empty success.
### Run artifacts
Besides the Dataset, the default key-value store contains useful, non-secret run artifacts:
| Artifact | When it is written | What it contains |
| --- | --- | --- |
| `INPUT_ECHO` | After valid input parsing | Normalized scope, keyword, and limits. |
| `RUN_SUMMARY` | After a successful run | Source, keyword, record counts, requested scope, and timestamps. |
| `ERROR_SUMMARY` | When a run fails | Error type, safe error message, and timestamps. |
These artifacts make it straightforward to debug an automation without exposing credentials—this Actor does not require any.
### Pricing
**Pay per event. No subscription.** Apify displays the effective event price before each run.
| Event | Price | When it is charged |
| --- | ---: | --- |
| `apify-actor-start` | **$0.005** | Automatically once when a normal Actor run starts. |
| `apify-default-dataset-item` | **$2.00 / 1,000** | Automatically for each item written to the default Dataset. |
For example, a run returning 100 Dataset rows costs **$0.205** in Actor events: $0.005 to start plus $0.200 for results. Platform usage costs are charged to the user in addition to these Actor events, as shown by Apify before a run.
Both listed events are Apify synthetic events: the platform accounts for them automatically, so the Actor does not manually issue duplicate charges in code.
### Live View and Standby endpoints
This Actor has an honest lightweight Live View service. Data collection stays in normal Actor runs; the standby service does not pretend to offer a separate scrape API.
| Endpoint | Purpose |
| --- | --- |
| `GET /` | Readiness and service information. |
| `GET /health` | Fast health check. |
| `GET /input-example` | Low-cost input compatible with the Actor schema. |
| `GET /openapi.json` | The deployed OpenAPI 3.x contract. |
The interactive **Standby** tab on Apify renders these endpoints from the same OpenAPI document served by the Actor.
### Connect from code or an AI workflow
Use this Actor in Apify, Make, Zapier, n8n, or an agent workflow. The Actor ID is `lentic_clockss/hacker-news-scraper`.
Python example
```python
from apify_client import ApifyClient
client = ApifyClient("")
run = client.actor("lentic_clockss/hacker-news-scraper").call(
run_input={"searchQuery": "AI agents", "recordTypes": ["story", "comment"], "maxItems": 10, "maxFetches": 10}
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item["type"], item.get("title") or item.get("text"), item["hnUrl"])
```
### FAQ
#### Does it search Hacker News by a phrase or brand name?
Yes. Set `searchQuery` to the phrase you want. The Actor returns public HN Search hits and records the keyword in `sourceSearchQuery`.
#### Does it use the official Hacker News API?
Feed and item-ID mode uses the official Hacker News Firebase API. Keyword search uses the public Algolia-powered HN Search API because Firebase does not provide keyword search.
#### Can I collect comments?
Yes. In search mode, include `comment` in `recordTypes`. In feed mode, keep `recordTypes` containing `comment`, set `includeDescendants` to `true`, and choose an appropriate `maxDepth`, `maxItems`, and `maxFetches`.
#### Why can a selected type have zero results?
Hacker News live feeds and keyword searches are not guaranteed to contain every item type at every moment. For example, polls can be uncommon in a particular feed snapshot or search result set.
#### What happens when a source returns malformed data or is unavailable?
The Actor retries bounded transient failures. Invalid source records are rejected before Dataset output, and a failed run writes `ERROR_SUMMARY` rather than claiming success with an untrustworthy result.
#### Can I use the Live View endpoints to start a collection?
No. Live View provides readiness, health, input guidance, and its OpenAPI document. Start data collection through a normal Actor run so output stays in the run Dataset and key-value store.
***
Explore more tools from [lentic\_clockss on Apify](https://apify.com/lentic_clockss).
# Actor input Schema
## `searchQuery` (type: `string`):
Optional keyword or phrase. When set, the Actor runs a Hacker News keyword search through the public Algolia HN Search API. Leave empty to collect live Firebase feeds and explicit item IDs instead.
## `feeds` (type: `array`):
Official Firebase feeds to sample when Search keyword is empty.
## `recordTypes` (type: `array`):
Hacker News item types emitted to the Dataset. Applies to both keyword-search and feed modes.
## `itemIds` (type: `array`):
Optional positive Hacker News item IDs for feed/item-ID mode. Ignored when Search keyword is set.
## `includeDescendants` (type: `boolean`):
For feed/item-ID mode, traverse public kids and poll parts beneath selected roots up to Max depth. Keyword-search mode returns the search hits directly.
## `maxDepth` (type: `integer`):
Depth below each selected root to traverse when descendants are enabled. A root has depth 0. Not used in keyword-search mode.
## `maxItems` (type: `integer`):
Global cap after deduplication and type selection. In keyword-search mode, this is the maximum number of search hits written to the Dataset.
## `maxFetches` (type: `integer`):
Safety cap for Firebase item detail requests in feed/item-ID mode. It must be at least Maximum Dataset records; keyword-search mode does not fetch Firebase item details.
## Actor input object example
```json
{
"searchQuery": "AI",
"feeds": [
"top",
"new",
"best",
"ask",
"show",
"job"
],
"recordTypes": [
"story",
"comment",
"job",
"poll",
"pollopt"
],
"itemIds": [],
"includeDescendants": true,
"maxDepth": 2,
"maxItems": 100,
"maxFetches": 500
}
```
# Actor output Schema
## `results` (type: `string`):
Deduplicated public Hacker News records collected from keyword search, selected feeds, or explicit item IDs.
## `runSummary` (type: `string`):
Scope, source, keyword, and record-count summary for a successful run.
## `inputEcho` (type: `string`):
Normalized non-secret input.
## `errorSummary` (type: `string`):
Present when the Actor cannot complete a trustworthy run.
# 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 = {
"searchQuery": "AI",
"feeds": [
"top",
"new",
"best",
"ask",
"show",
"job"
],
"recordTypes": [
"story",
"comment",
"job",
"poll",
"pollopt"
],
"itemIds": []
};
// Run the Actor and wait for it to finish
const run = await client.actor("lentic_clockss/hacker-news-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 = {
"searchQuery": "AI",
"feeds": [
"top",
"new",
"best",
"ask",
"show",
"job",
],
"recordTypes": [
"story",
"comment",
"job",
"poll",
"pollopt",
],
"itemIds": [],
}
# Run the Actor and wait for it to finish
run = client.actor("lentic_clockss/hacker-news-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 '{
"searchQuery": "AI",
"feeds": [
"top",
"new",
"best",
"ask",
"show",
"job"
],
"recordTypes": [
"story",
"comment",
"job",
"poll",
"pollopt"
],
"itemIds": []
}' |
apify call lentic_clockss/hacker-news-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=lentic_clockss/hacker-news-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Hacker News Scraper - Stories, Jobs, Ask HN & Show HN",
"description": "Export fresh Hacker News stories, comments, jobs, Ask HN, Show HN, and polls into structured datasets for research, hiring signals, and monitoring.",
"version": "0.1",
"x-build-id": "RRaofvD0OWKOaNt9Y"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/lentic_clockss~hacker-news-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-lentic_clockss-hacker-news-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/lentic_clockss~hacker-news-scraper/runs": {
"post": {
"operationId": "runs-sync-lentic_clockss-hacker-news-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/lentic_clockss~hacker-news-scraper/run-sync": {
"post": {
"operationId": "run-sync-lentic_clockss-hacker-news-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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",
"properties": {
"searchQuery": {
"title": "Search keyword",
"maxLength": 200,
"type": "string",
"description": "Optional keyword or phrase. When set, the Actor runs a Hacker News keyword search through the public Algolia HN Search API. Leave empty to collect live Firebase feeds and explicit item IDs instead."
},
"feeds": {
"title": "Hacker News feeds",
"minItems": 1,
"maxItems": 6,
"type": "array",
"description": "Official Firebase feeds to sample when Search keyword is empty.",
"items": {
"type": "string"
},
"default": [
"top",
"new",
"best",
"ask",
"show",
"job"
]
},
"recordTypes": {
"title": "Record types to keep",
"minItems": 1,
"maxItems": 5,
"type": "array",
"description": "Hacker News item types emitted to the Dataset. Applies to both keyword-search and feed modes.",
"items": {
"type": "string"
},
"default": [
"story",
"comment",
"job",
"poll",
"pollopt"
]
},
"itemIds": {
"title": "Specific item IDs (optional)",
"maxItems": 100,
"type": "array",
"description": "Optional positive Hacker News item IDs for feed/item-ID mode. Ignored when Search keyword is set.",
"items": {
"type": "integer",
"minimum": 1
},
"default": []
},
"includeDescendants": {
"title": "Include comment and poll descendants",
"type": "boolean",
"description": "For feed/item-ID mode, traverse public kids and poll parts beneath selected roots up to Max depth. Keyword-search mode returns the search hits directly.",
"default": true
},
"maxDepth": {
"title": "Maximum descendant depth",
"minimum": 0,
"maximum": 10,
"type": "integer",
"description": "Depth below each selected root to traverse when descendants are enabled. A root has depth 0. Not used in keyword-search mode.",
"default": 2
},
"maxItems": {
"title": "Maximum Dataset records",
"minimum": 1,
"maximum": 2000,
"type": "integer",
"description": "Global cap after deduplication and type selection. In keyword-search mode, this is the maximum number of search hits written to the Dataset.",
"default": 100
},
"maxFetches": {
"title": "Maximum Firebase item fetches",
"minimum": 1,
"maximum": 5000,
"type": "integer",
"description": "Safety cap for Firebase item detail requests in feed/item-ID mode. It must be at least Maximum Dataset records; keyword-search mode does not fetch Firebase item details.",
"default": 500
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```