# BLS CPI Data Scraper | US Consumer Price Index (`parseforge/bls-cpi-data-scraper`) Actor Pull US Bureau of Labor Statistics CPI series with period, value, area, item, and seasonally adjusted flag. Filter by series ID and date range. Built for economists, fintech apps, inflation research, and analysts tracking US consumer price index trends. - **URL**: https://apify.com/parseforge/bls-cpi-data-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Other, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $19.00 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## ๐Ÿ“ˆ BLS CPI Data Scraper > ๐Ÿš€ **Export Consumer Price Index time series in seconds.** Pull official BLS CPI observations for any series, any year range, straight to CSV, Excel, JSON, or XML. > ๐Ÿ•’ **Last updated:** 2026-05-25 ยท **๐Ÿ“Š 8 fields** per record ยท **National & metro coverage** ยท **1913-present** The Bureau of Labor Statistics publishes the Consumer Price Index, the headline US inflation measure. This actor uses the official BLS public timeseries API to return monthly observations for any CPI series you specify. Coverage includes All Urban Consumers (CPI-U), Wage Earners (CPI-W), Chained CPI, regional and metro indexes, and category-level series (food, energy, shelter, medical). | ๐ŸŽฏ Target Audience | ๐Ÿ’ก Primary Use Cases | |---|---| | Economists | Track inflation by category | | Finance teams | Index escalators, COLA | | Researchers | Long historical data pulls | | Journalists | Monthly inflation reporting | ### ๐Ÿ“‹ What the BLS CPI Data Scraper does - Calls the BLS public API (v2) for any list of CPI series IDs - Returns monthly observations with year, period, value, and footnotes - Supports historical pulls back to series inception - Flags the latest observation per series > ๐Ÿ’ก **Why it matters:** Official inflation data, structured for analysis. ### ๐ŸŽฌ Full Demo (_๐Ÿšง Coming soon_) ### โš™๏ธ Input
FieldTypeDescription
seriesIdsarrayBLS series IDs (default CUUR0000SA0)
maxItemsintegerCap on observations
startYearintegerOptional
endYearintegerOptional
```json { "seriesIds": ["CUUR0000SA0"], "maxItems": 50 } ```` ```json { "seriesIds": ["CUUR0000SAF1", "CUUR0000SAH1"], "startYear": 2020, "endYear": 2025 } ``` > โš ๏ธ **Good to Know:** Without an API key, BLS limits queries. For heavy use, register a free key at bls.gov. ### ๐Ÿ“Š Output | Field | Type | Description | |---|---|---| | ๐Ÿ“Œ seriesId | string | BLS series ID | | ๐Ÿ“… year | number | Observation year | | ๐Ÿ“† period | string | M01-M13 | | periodName | string | Month name | | ๐Ÿ’ฒ value | number | Index value | | latest | boolean | True for the most recent obs | | footnotes | array | BLS footnote text | | ๐Ÿ•’ scrapedAt | string | ISO timestamp | ### โœจ Why choose this Actor - Direct BLS API: official source, no scraping - Multi-series in one run - Returns latest flag for monitoring ### ๐Ÿ“ˆ How it compares to alternatives | Approach | Cost | Speed | Maintenance | |---|---|---|---| | This actor | Pay per result | Fast | None | | BLS website manual | Free | Slow | High | | FRED API | Free | Fast | Custom code | ### ๐Ÿš€ How to use 1. [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) 2. Open the actor 3. Set series IDs and optional year range 4. Run 5. Download dataset as CSV, Excel, JSON, or XML ### ๐Ÿ’ผ Business use cases #### Contract escalation Quarterly CPI lookups for lease and supply contracts. #### Treasury & finance TIPS modelling and inflation hedging. #### HR COLA calculations for salary bands. #### Macroeconomics Sector CPI trends for category management. ### ๐Ÿ”Œ Automating BLS CPI Data Scraper Make, Zapier, Slack, Airbyte, GitHub Actions, Google Drive. ### ๐ŸŒŸ Beyond business use cases #### Research Academic time series analysis. #### Personal Household budget inflation modelling. #### Non-profit Cost-of-living advocacy. #### Experimentation Train forecasting models on CPI data. ### ๐Ÿค– Ask an AI assistant about this scraper ChatGPT, Claude, Perplexity, or Copilot can explain series IDs and outputs. ### โ“ Frequently Asked Questions **Q: What are CPI series IDs?** A: BLS identifiers like CUUR0000SA0 (All Urban Consumers). **Q: How far back?** A: Series-dependent, some go back to 1913. **Q: Why pull multiple series?** A: Compare core vs headline or food vs energy. **Q: Are values seasonally adjusted?** A: Depends on the series prefix (CUUR vs CUSR). **Q: How frequent are updates?** A: Monthly, mid-month for the prior month. **Q: Is an API key required?** A: Not for small queries. **Q: Can I get percent changes?** A: This actor returns raw values, compute changes downstream. **Q: Are regional indexes supported?** A: Yes, via series ID. **Q: Does this include Chained CPI?** A: Yes, with C-CPI-U series IDs. **Q: What is the latest flag?** A: True for the most recent observation of each series. ### ๐Ÿ”Œ Integrate with any app Make, Zapier, Slack, Airbyte, GitHub Actions, Google Sheets, Webhooks. ### ๐Ÿ”— Recommended Actors | Actor | Description | |---|---| | [USAspending Contracts Scraper](https://apify.com/parseforge/usaspending-contracts-scraper) | Federal awards data | | [FDIC Bank Scraper](https://apify.com/parseforge/fdic-bank-scraper) | FDIC institution data | | [FINRA BrokerCheck Scraper](https://apify.com/parseforge/finra-brokercheck-scraper) | Broker records | > ๐Ÿ’ก **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge). **๐Ÿ†˜ Need Help?** [Open our contact form](https://tally.so/r/BzdKgA) > **โš ๏ธ Disclaimer:** independent tool, not affiliated with the US Bureau of Labor Statistics. Only publicly available data collected. # Actor input Schema ## `seriesIds` (type: `array`): BLS CPI series identifiers (e.g. CUUR0000SA0 for All Urban Consumers, all items). ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000 ## `startYear` (type: `integer`): Optional. Default is the previous 3 years. ## `endYear` (type: `integer`): Optional. Default is the current year. ## Actor input object example ```json { "seriesIds": [ "CUUR0000SA0" ], "maxItems": 10 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "seriesIds": [ "CUUR0000SA0" ], "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/bls-cpi-data-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "seriesIds": ["CUUR0000SA0"], "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("parseforge/bls-cpi-data-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "seriesIds": [ "CUUR0000SA0" ], "maxItems": 10 }' | apify call parseforge/bls-cpi-data-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/bls-cpi-data-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "BLS CPI Data Scraper | US Consumer Price Index", "description": "Pull US Bureau of Labor Statistics CPI series with period, value, area, item, and seasonally adjusted flag. Filter by series ID and date range. Built for economists, fintech apps, inflation research, and analysts tracking US consumer price index trends.", "version": "0.1", "x-build-id": "k9iXBw0oKTU5HEF6q" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~bls-cpi-data-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-bls-cpi-data-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~bls-cpi-data-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-bls-cpi-data-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~bls-cpi-data-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-bls-cpi-data-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "seriesIds": { "title": "Series IDs", "type": "array", "description": "BLS CPI series identifiers (e.g. CUUR0000SA0 for All Urban Consumers, all items).", "items": { "type": "string" } }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000" }, "startYear": { "title": "Start Year", "minimum": 1913, "maximum": 2030, "type": "integer", "description": "Optional. Default is the previous 3 years." }, "endYear": { "title": "End Year", "minimum": 1913, "maximum": 2030, "type": "integer", "description": "Optional. Default is the current year." } } }, "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 } } } } } } } } } } ```