# CDC WONDER Scraper (`crawlerbros/cdc-wonder-scraper`) Actor Query CDC WONDER's public US health statistics: mortality (underlying cause of death, 1999-2020 and 2018-2023) and natality (births, 2007-2023), grouped by year, sex, race, Hispanic origin, age, and cause of death. - **URL**: https://apify.com/crawlerbros/cdc-wonder-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Automation, Agents, Integrations - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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. 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## CDC WONDER Scraper Query **CDC WONDER** — the CDC's public health statistics system — for US mortality (underlying cause of death) and natality (births) data. Group results by year, sex, race, Hispanic origin, age, and cause of death, with death/birth counts and rates. HTTP-only via the official `wonder.cdc.gov` machine-readable XML API. No auth, no login, no proxy. ### What this actor does - **Three datasets:** historical mortality (1999-2020), current mortality (2018-2023, single-race categories), and natality/births (2007-2023) - **Flexible grouping:** cross-tabulate by up to two axes at once (e.g. year x sex, race x cause of death, or birth weight x gestational age) - **Demographic filters:** sex, race, Hispanic origin, age group, marital status (natality) - **Natality health axes:** group births by birth weight or gestational age at delivery - **Cause-of-death filter:** restrict mortality queries to a single ICD-10 disease chapter (cancer, heart disease, injuries, etc.) - **Rates:** crude death rate always included; optional age-adjusted rate (mortality) with 95% confidence interval - **Empty fields are omitted** ### Output per record - `dataset` — `D76` / `D158` / `D66` (CDC WONDER's internal dataset code) - `datasetLabel` — human-readable dataset name - `year` — calendar year (when Year is a grouping axis) - `sex`, `race`, `hispanicOrigin`, `ageGroup`, `causeOfDeath` — mortality demographic/cause breakdown (when used as a grouping axis) - `ageOfMother`, `maritalStatus`, `birthWeight`, `gestationalAge` — natality-specific breakdown (when used as a grouping axis) - `deaths` / `births` — the underlying count - `population` — mid-year population denominator (mortality only) - `crudeRate` — rate per 100,000 population (mortality) / per 1,000 population (natality), with `crudeRateConfidenceInterval` when available - `ageAdjustedRate`, `ageAdjustedRateConfidenceInterval` — age-standardized death rate (mortality, opt-in) - `birthRate`, `birthRateConfidenceInterval` — births per 1,000 population (natality, opt-in) - `deathsSuppressed` / `birthsSuppressed` / `crudeRateSuppressed` — `true` when CDC WONDER withheld the exact value for small-count privacy protection (see FAQ) - `isTotal` — `true` for subtotal/grand-total rows (present whenever "Show Totals" is on, which it always is) - `sourceUrl` — CDC WONDER's dataset documentation page - `recordType` — `mortalityRecord` or `natalityRecord` - `scrapedAt` — UTC timestamp ### Input | Field | Type | Default | Description | |---|---|---|---| | `mode` | string | `mortalityHistorical` | `mortalityHistorical` / `mortalityCurrent` / `natality` | | `groupBy1` | string | `year` | Primary grouping axis (natality adds `birthWeight` / `gestationalAge`) | | `groupBy2` | string | `none` | Optional second grouping axis (natality adds `birthWeight` / `gestationalAge`) | | `yearFrom` / `yearTo` | int | 2015 / 2020 | Year range (clamped to the selected dataset's valid range) | | `sexFilter` | string | `all` | Restrict to Female/Male (shared across all 3 datasets) | | `raceFilter` | string | `all` | Race filter for `mortalityHistorical` / `natality` (bridged-race categories) | | `raceFilterCurrent` | string | `all` | Race filter for `mortalityCurrent` (single-race categories) | | `hispanicOriginFilter` | string | `all` | Hispanic origin filter for mortality modes | | `hispanicOriginFilterNatality` | string | `all` | Hispanic origin filter for natality mode | | `ageGroupFilter` | string | `all` | 10-year age band filter (mortality modes) | | `ageOfMotherFilter` | string | `all` | Mother's age band filter (natality) | | `maritalStatusFilter` | string | `all` | Mother's marital status filter (natality) | | `icd10Category` | string | `all` | ICD-10 disease chapter filter (mortality modes) | | `includeAgeAdjustedRate` | bool | `false` | Add age-adjusted rate (`mortalityHistorical` only) | | `maxItems` | int | `500` | Hard cap on emitted records (1-5000) | #### Example: deaths by year and sex, 2015-2020 ```json { "mode": "mortalityHistorical", "groupBy1": "year", "groupBy2": "sex", "yearFrom": 2015, "yearTo": 2020 } ```` #### Example: cancer deaths by race, current dataset, with age-adjusted comparison unavailable (crude rate only) ```json { "mode": "mortalityCurrent", "groupBy1": "year", "groupBy2": "raceFilterCurrent", "icd10Category": "C00-D48", "yearFrom": 2019, "yearTo": 2022 } ``` #### Example: births by year and age of mother ```json { "mode": "natality", "groupBy1": "year", "groupBy2": "ageOfMother", "yearFrom": 2018, "yearTo": 2023 } ``` #### Example: heart disease mortality trend, single axis ```json { "mode": "mortalityHistorical", "groupBy1": "year", "icd10Category": "I00-I99", "includeAgeAdjustedRate": true, "yearFrom": 1999, "yearTo": 2020 } ``` #### Example: births by birth weight and gestational age ```json { "mode": "natality", "groupBy1": "birthWeight", "groupBy2": "gestationalAge", "yearFrom": 2022, "yearTo": 2023 } ``` ### Use cases - **Public health research** — trend analysis of mortality/natality by demographic group - **Journalism / data storytelling** — sourcing verified US vital-statistics figures - **Epidemiology courses** — teaching datasets with real CDC-published numbers - **Actuarial and insurance analysis** — age-adjusted mortality trend inputs - **Policy analysis** — cause-of-death and birth-rate trends over time by demographic ### Limitations - **`sourceUrl` may return 403 from a plain `curl`/script request.** CDC WONDER's website (all of `wonder.cdc.gov`, including its homepage) is protected by Akamai bot-management that blocks unauthenticated GET requests from non-browser clients - this affects every page on the domain, not just the ones this actor links to. It renders normally in a real web browser. Only the specific POST-based API endpoint this actor uses (`/controller/datarequest/`) is allowlisted for programmatic access, which is exactly why this actor's requests succeed reliably while a plain `curl` of the same domain's pages does not. - **National totals only.** CDC WONDER's public web-service API (which this actor uses) returns USA-wide totals only. State, county, region, division, and urbanization breakdowns are available on the interactive wonder.cdc.gov website but are rejected by the API with an explicit error - this is a CDC-side restriction, not a bug in this actor. - **Small-count suppression.** Per federal statistical disclosure policy, CDC WONDER withholds exact counts below a small threshold (typically under 10). Suppressed cells are represented as `Suppressed: true` with the numeric field omitted, rather than a fabricated zero or null. - **Birth Rate not available.** CDC WONDER's natality dataset exposes a Birth Rate measure in its interactive UI, but its machine-readable API currently rejects every Birth Rate request with a server-side error regardless of grouping or filters (confirmed live across all axis combinations). This actor does not request Birth Rate for that reason; birth counts (`births`) are always returned. - **Rate limiting.** CDC WONDER enforces a mandatory 15-second minimum interval between API requests platform-side; the actor respects this automatically on retries. - **Bridged-race natality data.** CDC's "bridged race" methodology (used by `raceFilter` in natality mode) was discontinued after 2020 - race breakdowns for natality years after 2020 may return sparse or no results for that axis. - **2018-2023 mortality data only** (not through 2024) and **2007-2023 natality data only** (not through 2024) - the most recent year is often still provisional at CDC and unavailable via the API even though the dataset's public label mentions a later year. ### FAQ **What is CDC WONDER?** CDC WONDER (Wide-ranging ONline Data for Epidemiologic Research) is the CDC's public system for querying US public-health statistics, including mortality and natality data compiled from official vital records. See [wonder.cdc.gov](https://wonder.cdc.gov). **Is this affiliated with the CDC?** No. This is a third-party actor that queries CDC WONDER's public, documented API. It is not endorsed by or affiliated with the CDC. **Why are some values missing / marked "Suppressed"?** Federal statistical disclosure policy requires CDC WONDER to withhold death/birth counts below a small threshold to protect individual privacy. This is standard CDC policy, not a scraping error. **Can I get state or county-level data?** Not through this actor. CDC WONDER's API only serves national totals; state/county data requires the interactive web UI and manual data-use agreement steps CDC does not expose programmatically. **What's the difference between the two mortality datasets?** `mortalityHistorical` (D76) uses CDC's "bridged race" 4-category classification and covers 1999-2020. `mortalityCurrent` (D158) uses the newer single-race classification (including "Native Hawaiian/Other Pacific Islander" and "More than one race" as separate categories) and covers 2018 onward. **What does "crude rate" vs "age-adjusted rate" mean?** Crude rate is deaths per population, unadjusted. Age-adjusted rate standardizes for age-distribution differences across groups/years, making it the preferred metric for comparing mortality trends over time or between populations with different age structures. **How current is the data?** CDC WONDER data lags several months to a year behind real time as vital records are finalized; the most recent 1-2 years available in each dataset's label are often not yet queryable via the API. # Actor input Schema ## `mode` (type: `string`): Which CDC WONDER dataset to query. ## `groupBy1` (type: `string`): Primary axis to group results by. Mortality modes: year / sex / race / hispanicOrigin / ageGroup / causeOfDeath. Natality mode: year / sex / ageOfMother / race / hispanicOrigin / maritalStatus / birthWeight / gestationalAge. ## `groupBy2` (type: `string`): Optional second axis to cross-tabulate with groupBy1. Leave as 'none' for a single-axis breakdown. ## `yearFrom` (type: `integer`): Start of year range. Mortality Historical: 1999-2020. Mortality Current: 2018-2023. Natality: 2007-2023. ## `yearTo` (type: `integer`): End of year range (inclusive). Values outside the selected dataset's range are clamped automatically. ## `sexFilter` (type: `string`): Restrict to one sex instead of All. Ignored if Sex is already selected as a Group By axis (in that case all sexes are broken out). ## `raceFilter` (type: `string`): Bridged-race category, used by the 1999-2020 mortality dataset and the natality dataset. Ignored in mortalityCurrent mode (use raceFilterCurrent instead). ## `raceFilterCurrent` (type: `string`): Single-race category, used by the 2018-2023 current mortality dataset only. ## `hispanicOriginFilter` (type: `string`): Used by both mortality datasets (Historical and Current). For natality, use hispanicOriginFilterNatality. ## `hispanicOriginFilterNatality` (type: `string`): Used by the natality dataset only. ## `ageGroupFilter` (type: `string`): Ten-year age band at time of death. Used by both mortality datasets. ## `ageOfMotherFilter` (type: `string`): Mother's age band at birth. Natality dataset only. ## `maritalStatusFilter` (type: `string`): Mother's marital status at birth. Natality dataset only. ## `icd10Category` (type: `string`): Restrict to one top-level ICD-10 disease chapter. Used by both mortality datasets. Has no effect on natality. ## `includeAgeAdjustedRate` (type: `boolean`): Add the age-adjusted death rate (with 95% confidence interval) alongside the crude rate. Only available for the 1999-2020 historical mortality dataset. ## `maxItems` (type: `integer`): Hard cap on emitted records (rows in the result table, including subtotal/total rows). ## Actor input object example ```json { "mode": "mortalityHistorical", "groupBy1": "year", "groupBy2": "sex", "yearFrom": 2015, "yearTo": 2020, "sexFilter": "all", "raceFilter": "all", "raceFilterCurrent": "all", "hispanicOriginFilter": "all", "hispanicOriginFilterNatality": "all", "ageGroupFilter": "all", "ageOfMotherFilter": "all", "maritalStatusFilter": "all", "icd10Category": "all", "includeAgeAdjustedRate": false, "maxItems": 500 } ``` # Actor output Schema ## `statistics` (type: `string`): Dataset containing all scraped CDC WONDER mortality/natality rows. # 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": "mortalityHistorical", "groupBy1": "year", "groupBy2": "sex", "yearFrom": 2015, "yearTo": 2020, "sexFilter": "all", "raceFilter": "all", "raceFilterCurrent": "all", "hispanicOriginFilter": "all", "hispanicOriginFilterNatality": "all", "ageGroupFilter": "all", "ageOfMotherFilter": "all", "maritalStatusFilter": "all", "icd10Category": "all", "includeAgeAdjustedRate": false, "maxItems": 500 }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/cdc-wonder-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 = { "mode": "mortalityHistorical", "groupBy1": "year", "groupBy2": "sex", "yearFrom": 2015, "yearTo": 2020, "sexFilter": "all", "raceFilter": "all", "raceFilterCurrent": "all", "hispanicOriginFilter": "all", "hispanicOriginFilterNatality": "all", "ageGroupFilter": "all", "ageOfMotherFilter": "all", "maritalStatusFilter": "all", "icd10Category": "all", "includeAgeAdjustedRate": False, "maxItems": 500, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/cdc-wonder-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 '{ "mode": "mortalityHistorical", "groupBy1": "year", "groupBy2": "sex", "yearFrom": 2015, "yearTo": 2020, "sexFilter": "all", "raceFilter": "all", "raceFilterCurrent": "all", "hispanicOriginFilter": "all", "hispanicOriginFilterNatality": "all", "ageGroupFilter": "all", "ageOfMotherFilter": "all", "maritalStatusFilter": "all", "icd10Category": "all", "includeAgeAdjustedRate": false, "maxItems": 500 }' | apify call crawlerbros/cdc-wonder-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/cdc-wonder-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "CDC WONDER Scraper", "description": "Query CDC WONDER's public US health statistics: mortality (underlying cause of death, 1999-2020 and 2018-2023) and natality (births, 2007-2023), grouped by year, sex, race, Hispanic origin, age, and cause of death.", "version": "1.0", "x-build-id": "6Oy0qLLbjGKnXep3x" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~cdc-wonder-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-cdc-wonder-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~cdc-wonder-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-cdc-wonder-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~cdc-wonder-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-cdc-wonder-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "Dataset", "enum": [ "mortalityHistorical", "mortalityCurrent", "natality" ], "type": "string", "description": "Which CDC WONDER dataset to query.", "default": "mortalityHistorical" }, "groupBy1": { "title": "Group results by (primary)", "enum": [ "year", "sex", "race", "hispanicOrigin", "ageGroup", "causeOfDeath", "ageOfMother", "maritalStatus", "birthWeight", "gestationalAge" ], "type": "string", "description": "Primary axis to group results by. Mortality modes: year / sex / race / hispanicOrigin / ageGroup / causeOfDeath. Natality mode: year / sex / ageOfMother / race / hispanicOrigin / maritalStatus / birthWeight / gestationalAge.", "default": "year" }, "groupBy2": { "title": "Group results by (secondary)", "enum": [ "none", "year", "sex", "race", "hispanicOrigin", "ageGroup", "causeOfDeath", "ageOfMother", "maritalStatus", "birthWeight", "gestationalAge" ], "type": "string", "description": "Optional second axis to cross-tabulate with groupBy1. Leave as 'none' for a single-axis breakdown.", "default": "none" }, "yearFrom": { "title": "Year from", "minimum": 1999, "maximum": 2023, "type": "integer", "description": "Start of year range. Mortality Historical: 1999-2020. Mortality Current: 2018-2023. Natality: 2007-2023.", "default": 2015 }, "yearTo": { "title": "Year to", "minimum": 1999, "maximum": 2023, "type": "integer", "description": "End of year range (inclusive). Values outside the selected dataset's range are clamped automatically.", "default": 2020 }, "sexFilter": { "title": "Filter: Sex", "enum": [ "all", "F", "M" ], "type": "string", "description": "Restrict to one sex instead of All. Ignored if Sex is already selected as a Group By axis (in that case all sexes are broken out).", "default": "all" }, "raceFilter": { "title": "Filter: Race (mode=mortalityHistorical or natality)", "enum": [ "all", "1002-5", "A-PI", "2054-5", "2106-3", "100" ], "type": "string", "description": "Bridged-race category, used by the 1999-2020 mortality dataset and the natality dataset. Ignored in mortalityCurrent mode (use raceFilterCurrent instead).", "default": "all" }, "raceFilterCurrent": { "title": "Filter: Race (mode=mortalityCurrent)", "enum": [ "all", "1002-5", "A", "2054-5", "NHOPI", "2106-3", "M", "999" ], "type": "string", "description": "Single-race category, used by the 2018-2023 current mortality dataset only.", "default": "all" }, "hispanicOriginFilter": { "title": "Filter: Hispanic origin (mortality modes)", "enum": [ "all", "2135-2", "2186-2", "NS" ], "type": "string", "description": "Used by both mortality datasets (Historical and Current). For natality, use hispanicOriginFilterNatality.", "default": "all" }, "hispanicOriginFilterNatality": { "title": "Filter: Mother's Hispanic origin (mode=natality)", "enum": [ "all", "2135-2", "2186-5", "9" ], "type": "string", "description": "Used by the natality dataset only.", "default": "all" }, "ageGroupFilter": { "title": "Filter: Age group (mortality modes)", "enum": [ "all", "1", "1-4", "5-14", "15-24", "25-34", "35-44", "45-54", "55-64", "65-74", "75-84", "85+", "NS" ], "type": "string", "description": "Ten-year age band at time of death. Used by both mortality datasets.", "default": "all" }, "ageOfMotherFilter": { "title": "Filter: Age of mother (mode=natality)", "enum": [ "all", "15", "15-19", "20-24", "25-29", "30-34", "35-39", "40-44", "45-49", "50+" ], "type": "string", "description": "Mother's age band at birth. Natality dataset only.", "default": "all" }, "maritalStatusFilter": { "title": "Filter: Marital status (mode=natality)", "enum": [ "all", "1", "2", "9", "NR" ], "type": "string", "description": "Mother's marital status at birth. Natality dataset only.", "default": "all" }, "icd10Category": { "title": "Filter: Cause of death (ICD-10 chapter, mortality modes)", "enum": [ "all", "A00-B99", "C00-D48", "D50-D89", "E00-E88", "F01-F99", "G00-G98", "H00-H57", "H60-H93", "I00-I99", "J00-J98", "K00-K92", "L00-L98", "M00-M99", "N00-N98", "O00-O99", "P00-P96", "Q00-Q99", "R00-R99", "S00-T98", "V01-Y89", "Z00-Z99" ], "type": "string", "description": "Restrict to one top-level ICD-10 disease chapter. Used by both mortality datasets. Has no effect on natality.", "default": "all" }, "includeAgeAdjustedRate": { "title": "Include age-adjusted rate (mode=mortalityHistorical)", "type": "boolean", "description": "Add the age-adjusted death rate (with 95% confidence interval) alongside the crude rate. Only available for the 1999-2020 historical mortality dataset.", "default": false }, "maxItems": { "title": "Max records", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Hard cap on emitted records (rows in the result table, including subtotal/total rows).", "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 } } } } } } } } } } ```