# Federal Judicial Center Scraper | US Judge Profiles (`parseforge/federal-judicial-center-scraper`) Actor Pull US federal judge biographical data from FJC: appointments, courts served, education, nominating president, and tenure dates. Filter by court or era. Useful for legal researchers, litigation strategy teams, and academics studying the federal judiciary. - **URL**: https://apify.com/parseforge/federal-judicial-center-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Other, News - **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) ## βš–οΈ FJC Federal Judges Biographical Scraper > πŸš€ **Export every U.S. federal judge biography in seconds.** Pull appointment history, confirmation dates, education, ABA ratings, and court assignments straight from the Federal Judicial Center. Download as CSV, Excel, JSON, or XML. > πŸ•’ **Last updated:** 2026-05-25 Β· **πŸ“Š 30+ fields** per record Β· 4,000+ judges Β· United States, 1789-present The **FJC Federal Judges Scraper** loads the Federal Judicial Center's official Biographical Directory of Article III Federal Judges and exposes every judge as a structured record. Every record contains the judge's name, dates, court assignments, appointing president and party, ABA rating, confirmation and commission dates, senior-status and termination details, and education. **Coverage:** every U.S. federal judge in the FJC archive, from 1789 through current sitting judges, including district, appellate, circuit, and Supreme Court appointments. --- ### Target Audience / Use Cases | 🎯 Target Audience | πŸ’‘ Primary Use Cases | |---|---| | Legal researchers | Build datasets of judicial appointments and demographics | | Journalists | Investigate the makeup of federal courts | | Law schools | Teaching datasets on judicial history | | Political scientists | Study confirmation patterns and party alignment | | Court technology vendors | Augment case-analytics products with judge biographies | | Genealogists | Trace federal judicial appointments | --- ### πŸ“‹ What the FJC Federal Judges Scraper does - Downloads the official FJC biographical CSV in a single request - Parses every judge record including multi-appointment history - Filters by name, court type, appointing president's party, or still-serving status - Returns biographical (birth, death, gender, race/ethnicity) and appointment fields - Includes education (school, degree, year) and a free-text professional career summary - Exports in JSON, CSV, Excel, or XML > πŸ’‘ **Why it matters:** The FJC biographies are the canonical source for federal judges, but the raw CSV has 201 columns. This actor flattens, filters, and gives you a clean record per judge. --- ### 🎬 Full Demo _🚧 Coming soon_ --- ### βš™οΈ Input
FieldTypeRequiredDefaultDescription
nameFilterstringNo(none)Filter by partial name match (any of last, first, middle).
maxItemsintegerNo10Max records.
courtTypeFilterselectNo(all)Filter to a specific federal court type.
appointingPartyFilterselectNo(all)Filter by appointing president's party.
stillServingOnlybooleanNofalseOnly judges with no termination date.
**Example 1 - First 50 currently-serving district judges:** ```json { "maxItems": 50, "courtTypeFilter": "U.S. District Court", "stillServingOnly": true } ```` **Example 2 - Every judge named "Smith":** ```json { "nameFilter": "smith", "maxItems": 200 } ``` > ⚠️ **Good to Know:** The FJC source CSV contains up to 6 appointments per judge. This actor returns appointment 1 details directly and exposes `totalAppointments` so you can pivot for multi-appointment careers. *** ### πŸ“Š Output | Field | Type | Description | |---|---|---| | πŸ“› `title` | string | Full name | | πŸ†” `id` | string | FJC `nid` (node ID) | | πŸŽ‚ `birthYear` / `birthCity` / `birthState` | string | Birth details | | ⚰️ `deathYear` / `deathCity` / `deathState` | string | Death details if applicable | | πŸ§‘ `gender` / `raceOrEthnicity` | string | Demographics | | πŸ›οΈ `courtType` / `courtName` | string | Court of first appointment | | πŸ‡ΊπŸ‡Έ `appointingPresident` / `appointingParty` | string | Appointment 1 | | πŸ“ `abaRating` | string | ABA rating at confirmation | | πŸ“… `nominationDate` / `confirmationDate` / `commissionDate` | string | Process dates | | 🟑 `seniorStatusDate` / `terminationDate` / `terminationReason` | string | End of service | | πŸŽ“ `school1` / `degree1` / `degreeYear1` | string | First listed degree | | πŸ”’ `totalAppointments` | integer | Number of appointments held | | πŸ”— `sourceUrl` | string | FJC profile URL | | πŸ•’ `scrapedAt` | string | ISO timestamp | | ❌ `error` | string | Error if any | Sample record: ```json { "title": "Adam Ben Abelson", "id": "13761857", "lastName": "Abelson", "birthYear": "1982", "birthCity": "Cleveland", "birthState": "OH", "courtType": "U.S. District Court", "courtName": "U.S. District Court for the District of Maryland", "appointingPresident": "Joseph R. Biden", "appointingParty": "Democratic", "abaRating": "Well Qualified", "confirmationDate": "2024-09-10", "commissionDate": "2024-09-12", "totalAppointments": 1 } ``` *** ### ✨ Why choose this Actor - 🟒 Official FJC source - the canonical archive - 🟒 No login, no scraping fragility - it's a single CSV - 🟒 Every U.S. federal judge in one run - 🟒 Powerful filter combinations on demographics and appointment history - 🟒 Outputs to JSON / CSV / Excel / XML *** ### πŸ“ˆ How it compares to alternatives | Option | Free? | Filterable | Structured | Up-to-date | |---|---|---|---|---| | FJC raw CSV | Yes | No | 201 columns flat | Yes | | Wikipedia | Yes | No | Inconsistent | Sometimes | | Westlaw / Bloomberg Law | No | Yes | Yes | Yes (paid) | | **ParseForge FJC Scraper** | **Yes** | **Yes** | **Clean JSON/CSV** | **Yes** | *** ### πŸš€ How to use 1. [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) 2. Open this actor on Apify Console 3. Set optional filters, click Start 4. Download CSV / Excel / JSON / XML 5. Schedule the run or integrate via API *** ### πŸ’Ό Business use cases #### Legal-tech analytics Build judge profiles for litigation analytics products in minutes. #### Investigative journalism Pivot judges by appointing party, ABA rating, or court for stories. #### Academic research Datasets for studies on judicial diversity, tenure, and career paths. #### Education Class-ready datasets for political-science and law courses. *** ### πŸ”Œ Automating FJC Federal Judges Scraper The actor integrates with **Make**, **Zapier**, **n8n**, **Slack**, **Airbyte**, **GitHub Actions**, **Google Drive**, and any HTTP-aware tool via the Apify API. *** ### 🌟 Beyond business use cases #### Research Study confirmation-vote patterns or senior-status trends over time. #### Personal Look up a judge before a court appearance. #### Non-profit Publish judicial-diversity reports. #### Experimentation Combine with case-outcome datasets to study judicial behavior. *** ### πŸ€– Ask an AI assistant about this scraper ChatGPT Β· Claude Β· Perplexity Β· Microsoft Copilot *** ### ❓ Frequently Asked Questions **Q: Is the data from the official FJC?** Yes. Each run downloads the official biographical CSV from fjc.gov. **Q: How many judges are included?** Over 4,000, covering every Article III federal judge from 1789 to today. **Q: Are state judges included?** No. FJC's database covers federal judges only. **Q: How often is the source updated?** The FJC updates the dataset regularly as new appointments are confirmed. **Q: Can I get the full multi-appointment history?** Yes. `totalAppointments` reflects how many appointments a judge held; appointment 1 is exposed in detail, additional ones can be added on request. **Q: Output formats?** JSON, CSV, Excel, XML. **Q: Free preview?** Yes, free users get 10 records per run. **Q: Does this include the Supreme Court?** Yes. Set `courtTypeFilter` to `U.S. Supreme Court`. **Q: What about judges before 1789?** The dataset begins with the establishment of the federal judiciary in 1789. **Q: Licensing?** The FJC publishes its data in the public interest; this actor is an independent integration tool. *** ### πŸ”Œ Integrate with any app Webhooks, REST API, Make scenarios, Zapier zaps, Slack channels, Airbyte connectors, Google Sheets, and more. *** ### πŸ”— Recommended Actors | Actor | What it does | |---|---| | [SEC Investment Adviser Scraper](https://apify.com/parseforge/sec-investment-adviser-scraper) | Adviser/firm registrations | | [FINRA BrokerCheck Scraper](https://apify.com/parseforge/finra-brokercheck-scraper) | Broker disclosures | | [Federal Register Scraper](https://apify.com/parseforge/federalregister-scraper) | U.S. federal rules and notices | > πŸ’‘ **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge). **πŸ†˜ Need Help?** [Open our contact form](https://tally.so/r/BzdKgA) > **⚠️ Disclaimer:** independent tool, not affiliated with the Federal Judicial Center. Only publicly available data from fjc.gov is collected. # Actor input Schema ## `nameFilter` (type: `string`): Filter judges by last name, first name, or partial match. Leave empty to return every federal judge. ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000 ## `courtTypeFilter` (type: `string`): Filter to a specific federal court type. ## `appointingPartyFilter` (type: `string`): Filter to judges first appointed by a president of this party. ## `stillServingOnly` (type: `boolean`): When enabled, only judges with no termination date on appointment 1 are returned. ## Actor input object example ```json { "maxItems": 10, "stillServingOnly": false } ``` # Actor output Schema ## `results` (type: `string`): Scraped FJC federal judge records # 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 = { "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/federal-judicial-center-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "maxItems": 10 } # Run the Actor and wait for it to finish run = client.actor("parseforge/federal-judicial-center-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 10 }' | apify call parseforge/federal-judicial-center-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/federal-judicial-center-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Federal Judicial Center Scraper | US Judge Profiles", "description": "Pull US federal judge biographical data from FJC: appointments, courts served, education, nominating president, and tenure dates. Filter by court or era. Useful for legal researchers, litigation strategy teams, and academics studying the federal judiciary.", "version": "0.1", "x-build-id": "awgn1Xy9KuupbzKWr" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~federal-judicial-center-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-federal-judicial-center-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~federal-judicial-center-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-federal-judicial-center-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~federal-judicial-center-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-federal-judicial-center-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "nameFilter": { "title": "Name Filter", "type": "string", "description": "Filter judges by last name, first name, or partial match. Leave empty to return every federal judge." }, "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" }, "courtTypeFilter": { "title": "Court Type", "enum": [ "", "U.S. District Court", "U.S. Court of Appeals", "U.S. Circuit Court (1801-1911)", "U.S. Supreme Court", "Other Article III Federal Judiciary Service" ], "type": "string", "description": "Filter to a specific federal court type." }, "appointingPartyFilter": { "title": "Appointing President's Party", "enum": [ "", "Democratic", "Republican", "Whig", "Federalist", "Democratic-Republican", "Other" ], "type": "string", "description": "Filter to judges first appointed by a president of this party." }, "stillServingOnly": { "title": "Active / Still Serving Only", "type": "boolean", "description": "When enabled, only judges with no termination date on appointment 1 are returned.", "default": false } } }, "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 } } } } } } } } } } ```