# Dataset Router & Splitter — Route Records (`orangepinlabs/dataset-router`) Actor Split any Apify dataset into separate output datasets using ordered rules. Route nested fields with text, numeric, regex, list, existence, and empty-value conditions—without custom glue code. - **URL**: https://apify.com/orangepinlabs/dataset-router.md - **Developed by:** [Orange Pin Labs](https://apify.com/orangepinlabs) (community) - **Categories:** Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 1,000 routed 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/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 ## Dataset Router & Splitter Split one Apify dataset into separate output datasets using ordered, no-code rules. Dataset Router is the missing routing step between a scraper and downstream workflows. Send high-value leads to one dataset, incomplete records to review, products to regional feeds, errors to quarantine, or the same record to several matching destinations—without writing transformation code or exposing data to another service. ### What it does - Reads any Apify dataset you authorize. - Evaluates up to eight ordered routes using nested dot-path fields. - Supports first-match routing or copying to every matching route. - Creates a separate per-run Apify dataset for each route. - Optionally captures records that matched nothing. - Returns a manifest mapping route names to dataset IDs, item counts, and API URLs. - Stops safely when the run's spending limit is reached. The source dataset is read-only and is never modified. ### Example ```json { "sourceDatasetId": "YOUR_DATASET_ID", "routingMode": "firstMatch", "writeUnmatched": true, "unmatchedRoute": "review", "rules": [ { "route": "high-value-us", "match": "all", "conditions": [ { "field": "company.country", "operator": "equals", "value": "US", "caseSensitive": false }, { "field": "price", "operator": "gte", "value": "500" } ] }, { "route": "missing-email", "conditions": [ { "field": "contact.email", "operator": "missing" } ] } ] } ```` ### Operators `equals`, `notEquals`, `contains`, `notContains`, `startsWith`, `endsWith`, `regex`, `in`, `notIn`, `gt`, `gte`, `lt`, `lte`, `exists`, `missing`, `isEmpty`, and `isNotEmpty`. String comparisons can be case-sensitive or case-insensitive. `contains` works on both strings and arrays. Use `values` for `in` and `notIn`. Numeric comparison values are entered as text and converted with JavaScript `Number()` semantics. ### Output The default dataset is a route manifest. Every route gets its own aliased dataset containing: - `route`: matched route name - `ruleIndex`: zero-based rule index, or `null` for unmatched records - `sourceIndex`: original position in the source dataset - `record`: the original source record, unchanged The `OUTPUT` key-value-store record contains aggregate totals and the complete route manifest. Aliased route datasets follow the run's normal retention policy instead of accumulating as permanent named datasets. ### Pricing Pay per routed record copy: - Actor start: Apify's standard low-cost start event - `routed-record`: **$0.00001 per routed copy** ($0.01 per 1,000) With first-match routing, a source record creates at most one charge. With every-match routing, a record copied to three routes creates three routed-record charges. Ignored records are not charged. ### Limits and safety - Up to eight route datasets per run. - When unmatched routing is enabled, use at most seven explicit rules. - Up to 1,000,000 source records, controlled by `maxItems`. - Regex uses JavaScript regular expressions; invalid patterns fail before routing begins. - Numeric comparisons convert values with JavaScript `Number()` semantics. - No proxy, browser, LLM, or external API is used. - Runs under Apify limited permissions and accesses only the selected source dataset plus its own run storages. ### Local development ```bash npm install npm test npm start ``` # Actor input Schema ## `sourceDatasetId` (type: `string`): Dataset ID or name containing the records to route. ## `rules` (type: `array`): Ordered rules. Each rule has a route name, all/any matching, and one or more field conditions. With First match, the first matching rule wins. ## `routingMode` (type: `string`): Send each source record only to its first matching rule, or copy it to every matching rule. ## `writeUnmatched` (type: `boolean`): Route records that match no rule into the next available route dataset. ## `unmatchedRoute` (type: `string`): Name assigned to records that do not satisfy any explicit rule. ## `maxItems` (type: `integer`): Safety limit. The run fails before routing if the source dataset is larger. ## Actor input object example ```json { "rules": [ { "route": "high-value-us", "match": "all", "conditions": [ { "field": "country", "operator": "equals", "value": "US" }, { "field": "price", "operator": "gte", "value": "500" } ] } ], "routingMode": "firstMatch", "writeUnmatched": true, "unmatchedRoute": "unmatched", "maxItems": 100000 } ``` # Actor output Schema ## `manifest` (type: `string`): Maps route names to dataset aliases, IDs, URLs, and item counts. ## `route1` (type: `string`): No description ## `route2` (type: `string`): No description ## `route3` (type: `string`): No description ## `route4` (type: `string`): No description ## `route5` (type: `string`): No description ## `route6` (type: `string`): No description ## `route7` (type: `string`): No description ## `route8` (type: `string`): No description ## `summary` (type: `string`): Processed, routed, unmatched, ignored, and charge-limit totals. # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("orangepinlabs/dataset-router").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 = {} # Run the Actor and wait for it to finish run = client.actor("orangepinlabs/dataset-router").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 '{}' | apify call orangepinlabs/dataset-router --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=orangepinlabs/dataset-router", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Dataset Router & Splitter — Route Records", "description": "Split any Apify dataset into separate output datasets using ordered rules. Route nested fields with text, numeric, regex, list, existence, and empty-value conditions—without custom glue code.", "version": "0.2", "x-build-id": "yYtlz5mDzN1jalcwi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/orangepinlabs~dataset-router/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-orangepinlabs-dataset-router", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/orangepinlabs~dataset-router/runs": { "post": { "operationId": "runs-sync-orangepinlabs-dataset-router", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/orangepinlabs~dataset-router/run-sync": { "post": { "operationId": "run-sync-orangepinlabs-dataset-router", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "sourceDatasetId", "rules" ], "properties": { "sourceDatasetId": { "title": "Source dataset", "type": "string", "description": "Dataset ID or name containing the records to route." }, "rules": { "title": "Routing rules", "minItems": 1, "maxItems": 8, "type": "array", "description": "Ordered rules. Each rule has a route name, all/any matching, and one or more field conditions. With First match, the first matching rule wins.", "items": { "type": "object", "properties": { "route": { "title": "Route name", "type": "string", "description": "Human-readable route name. Must be unique.", "pattern": "^[A-Za-z0-9][A-Za-z0-9._-]{0,79}$" }, "match": { "title": "Condition matching", "type": "string", "description": "Require all conditions in this rule, or accept any one condition.", "enum": [ "all", "any" ], "default": "all" }, "conditions": { "title": "Conditions", "type": "array", "description": "Field comparisons evaluated for this route.", "minItems": 1, "items": { "type": "object", "properties": { "field": { "title": "Field path", "type": "string", "description": "Dot path such as company.country or product.price." }, "operator": { "title": "Operator", "type": "string", "description": "Comparison to apply to the selected field.", "enum": [ "equals", "notEquals", "contains", "notContains", "startsWith", "endsWith", "regex", "in", "notIn", "gt", "gte", "lt", "lte", "exists", "missing", "isEmpty", "isNotEmpty" ] }, "value": { "title": "Comparison value", "type": "string", "description": "Comparison value. Numbers can be entered as text, such as 500. Omit for exists, missing, isEmpty, and isNotEmpty." }, "values": { "title": "Comparison values", "type": "array", "description": "List of accepted or rejected values for the in and notIn operators.", "editor": "stringList", "items": { "type": "string" } }, "caseSensitive": { "title": "Case sensitive", "type": "boolean", "description": "Use exact letter case for string comparisons and regular expressions.", "default": true } }, "required": [ "field", "operator" ] } } }, "required": [ "route", "conditions" ] }, "default": [ { "route": "high-value-us", "match": "all", "conditions": [ { "field": "country", "operator": "equals", "value": "US" }, { "field": "price", "operator": "gte", "value": "500" } ] } ] }, "routingMode": { "title": "Routing mode", "enum": [ "firstMatch", "allMatches" ], "type": "string", "description": "Send each source record only to its first matching rule, or copy it to every matching rule.", "default": "firstMatch" }, "writeUnmatched": { "title": "Create an unmatched route", "type": "boolean", "description": "Route records that match no rule into the next available route dataset.", "default": true }, "unmatchedRoute": { "title": "Unmatched route name", "pattern": "^[A-Za-z0-9][A-Za-z0-9._-]{0,79}$", "type": "string", "description": "Name assigned to records that do not satisfy any explicit rule.", "default": "unmatched" }, "maxItems": { "title": "Maximum source records", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Safety limit. The run fails before routing if the source dataset is larger.", "default": 100000 } } }, "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 } } } } } } } } } } ```