# Google Scholar Case Law Scraper (`jungle_synthesizer/google-scholar-case-law-scraper`) Actor Search and scrape US court opinions from Google Scholar's case law database. Filter by keywords, courts, and date ranges to collect case names, citations, courts, dates, snippets, "Cited by" counts, and links. Optionally fetch full opinion text from detail pages. - **URL**: https://apify.com/jungle\_synthesizer/google-scholar-case-law-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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.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 ## Google Scholar Case Law Scraper Search and scrape US court opinions from Google Scholar's case law database. Filter by keywords, courts, and date ranges to collect structured legal data for research, citation analysis, and AI training. ### What it does This actor searches Google Scholar's case law index and returns structured records for each matching opinion. You supply a search query, optional court filter, and optional date range. The actor paginates through results up to your specified limit, extracting key metadata from each case. Optionally, it can fetch the full opinion text from each case's detail page. ### Use cases - **Legal research**: Find cases citing a specific doctrine or precedent across all US courts - **Citation analysis**: Track how many cases cite a landmark opinion over time - **Legal AI training data**: Collect labeled case text with court, date, and citation metadata - **Litigation support**: Research how courts in a specific jurisdiction have ruled on an issue - **Academic research**: Longitudinal studies of judicial trends on constitutional questions ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `query` | string | Yes | Search keywords (e.g. `"fourth amendment search and seizure"`) | | `court` | string | No | Court filter: `all` (default), `federal` (all federal courts), or `state` (all state courts) | | `dateStart` | string | No | Start year for date filter (e.g. `"2020"`) | | `dateEnd` | string | No | End year for date filter (e.g. `"2024"`) | | `fetchFullText` | boolean | No | Fetch full opinion text from detail pages (default: `false`) | | `maxItems` | integer | No | Maximum number of results to return (default: `10`) | **Example input:** ```json { "query": "first amendment freedom of speech public forum", "court": "federal", "dateStart": "2015", "dateEnd": "2024", "fetchFullText": false, "maxItems": 50 } ```` ### Output Each result record contains: | Field | Description | |-------|-------------| | `case_name` | Full case name (e.g. `"Miranda v. Arizona"`) | | `citation` | Legal citation extracted from metadata (e.g. `"384 U.S. 436 (1966)"`) | | `court` | Court that decided the case | | `date_decided` | Year or date the case was decided | | `snippet` | Search result excerpt showing relevant passages | | `full_text` | Full opinion text (only when `fetchFullText: true`) | | `cited_by_count` | Number of cases citing this opinion | | `cited_by_url` | Google Scholar URL to the list of citing cases | | `related_cases_url` | Google Scholar URL to related cases | | `versions_count` | Number of other sources reporting this case | | `source` | Source publication from the metadata line | | `scholar_url` | Direct Google Scholar URL for this case | | `pdf_url` | PDF URL when available | | `case_id` | Google Scholar internal case ID | **Example output record:** ```json { "case_name": "Terry v. Ohio", "citation": "392 US 1 (1968)", "court": "Supreme Court of the United States", "date_decided": "1968", "snippet": "...the Fourth Amendment applies to stop and frisk by police officers...", "cited_by_count": 18234, "cited_by_url": "https://scholar.google.com/scholar?cites=...", "scholar_url": "https://scholar.google.com/scholar_case?case=17773605790797706504", "case_id": "17773605790797706504", "full_text": null } ``` ### Notes - Results are retrieved from Google Scholar's public case law index. Coverage includes US Supreme Court, federal circuit and district courts, and state appellate courts. - The `court: "federal"` filter covers all federal courts (Supreme Court, circuit courts, district courts). Use `court: "all"` to include state court opinions. - Setting `fetchFullText: true` significantly increases run time and resource usage since the actor must load each case's detail page individually. - Google Scholar does not expose a public API, so this actor uses a real browser to render pages. Each run consumes proportionally more resources than a basic HTML scraper. - Date filters use year-level granularity only (`YYYY` format). # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `query` (type: `string`): Search keywords for case law (e.g. "first amendment freedom of speech") ## `court` (type: `string`): Filter by court. Options: "all" (all courts), "federal" (all federal courts), "state" (all state courts), or a specific court name. Default: "all". ## `dateStart` (type: `string`): Start of date range (YYYY format, e.g. "2020") ## `dateEnd` (type: `string`): End of date range (YYYY format, e.g. "2024") ## `fetchFullText` (type: `boolean`): Whether to fetch the full opinion text from detail pages. Slower but provides complete case text. ## `maxItems` (type: `integer`): Maximum number of case law records to scrape. Default 10. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "query": "fourth amendment search and seizure", "court": "all", "fetchFullText": false, "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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "query": "fourth amendment search and seizure", "court": "all", "dateStart": "", "dateEnd": "", "fetchFullText": false, "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/google-scholar-case-law-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "query": "fourth amendment search and seizure", "court": "all", "dateStart": "", "dateEnd": "", "fetchFullText": False, "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/google-scholar-case-law-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "query": "fourth amendment search and seizure", "court": "all", "dateStart": "", "dateEnd": "", "fetchFullText": false, "maxItems": 10 }' | apify call jungle_synthesizer/google-scholar-case-law-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/google-scholar-case-law-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Scholar Case Law Scraper", "description": "Search and scrape US court opinions from Google Scholar's case law database. Filter by keywords, courts, and date ranges to collect case names, citations, courts, dates, snippets, \"Cited by\" counts, and links. Optionally fetch full opinion text from detail pages.", "version": "0.1", "x-build-id": "Pg3YIuLF2bABNOKk5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~google-scholar-case-law-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-google-scholar-case-law-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/jungle_synthesizer~google-scholar-case-law-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-google-scholar-case-law-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/jungle_synthesizer~google-scholar-case-law-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-google-scholar-case-law-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": [ "query", "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "query": { "title": "Search Query", "type": "string", "description": "Search keywords for case law (e.g. \"first amendment freedom of speech\")" }, "court": { "title": "Court Filter", "enum": [ "all", "federal", "state" ], "type": "string", "description": "Filter by court. Options: \"all\" (all courts), \"federal\" (all federal courts), \"state\" (all state courts), or a specific court name. Default: \"all\"." }, "dateStart": { "title": "Date Range Start", "type": "string", "description": "Start of date range (YYYY format, e.g. \"2020\")" }, "dateEnd": { "title": "Date Range End", "type": "string", "description": "End of date range (YYYY format, e.g. \"2024\")" }, "fetchFullText": { "title": "Fetch Full Opinion Text", "type": "boolean", "description": "Whether to fetch the full opinion text from detail pages. Slower but provides complete case text.", "default": false }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of case law records to scrape. Default 10.", "default": 10 } } }, "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 } } } } } } } } } } ```