# Profanity Checker (`louisdeconinck/profanity-checker`) Actor Clean text fast! 🚀 This actor removes profanity, obscenity, & unwanted words. Perfect for content moderation & data sanitization. Built-in & custom lists. Try it now! ✨ - **URL**: https://apify.com/louisdeconinck/profanity-checker.md - **Developed by:** [Louis Deconinck](https://apify.com/louisdeconinck) (community) - **Categories:** Automation, Developer tools, SEO tools - **Stats:** 4 total users, 2 monthly users, 100.0% runs succeeded, 3 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $9.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 This actor checks text content for profanity. It's a simple and effective way to filter and remove profanity, obscenity, and other unwanted text from your content. ### 🎯 Use Cases - **Content Moderation:** Filter user-generated content for inappropriate language - **Text Sanitization:** Clean up text data before publishing - **Comment Filtering:** Automatically check and filter comment streams - **Data Processing:** Process large volumes of text data for profanity - **Content Safety:** Ensure content meets community guidelines ### ✨ Features - **Bulk Processing:** Process multiple text inputs in one run - **Default Profanity List:** Comes with a built-in list of common profane words - **Custom Profanity List:** Add your own words to check - **Flexible Replacement:** Choose how to replace detected profanity - **Detailed Output:** Get both original and filtered text - **Profanity Detection:** Know if text contains any profanity ### 📤 Output The actor provides detailed information for each processed text: - `orginalText`: Original text that was provided in the input - `containsProfanity`: Boolean check if profanity was detected - `newText`: Updated text with profanity filtered out **Example output** ```json [ { "originalText": "This is a piece of text", "containsProfanity": false, "newText": "This is a piece of text" }, { "originalText": "This is another piece of shit", "containsProfanity": true, "newText": "This is another piece of ****" } ] ```` ### 📥 Input Input is provided as JSON with the following properties: - `texts` (required): Array of text strings to check for profanity - `add` (optional): Additional comma-separated words to add to profanity list (max 10 words or 200 chars) - `fillText` (optional): Text to replace profanity with (max 20 chars) - `fillChar` (optional): Single character to replace profanity with (fills to length of word, ignored when fillText is provided) **Example Input:** ```json { "texts": [ "This is a piece of text", "This is another piece of text" ], "add": "word1,word2", "fillText": "[REMOVED]", "fillChar": "*" } ``` ### 🚀 Usage 1. **Get started**: Create an [Apify account](https://console.apify.com/sign-up) 2. **Input configuration**: Provide the texts you want to check and any optional parameters 3. **Run the actor**: Click "Start" to begin processing 4. **Get results**: Download results in JSON format or access via API ### 💡 Integration Options - **Webhooks**: Get notified when your runs complete - **API**: Integrate with your applications using the Apify API - **Schedules**: Run periodic content checks - **Workflows**: Chain with other actors for complex content processing ### 📝 Notes - The actor recognizes character alternates (e.g., "@" as "a", "$" as "s") - The service includes a "safe words" list to prevent false positives - Maximum 10 custom words can be added to the profanity list - Replacement text is limited to 20 characters ### 🌟 Start for Free Ready to start scraping Instagram posts? [Try the Actor for free](https://apify.com?fpr=7p4wu) and get: - Scalable and reliable data collection - Regular updates to maintain compatibility - Technical support when you need it - Flexible output formats ### 🔍 More Scraping Solutions Check out my other scrapers on [my Apify profile](https://apify.com/louisdeconinck?fpr=7p4wu) for: - Other social media platforms - E-commerce websites - Business directories - And more! ### 🛠️ Custom Scraper Development Need a custom Instagram scraping solution? I can help! Contact me for: - Custom data fields - Specific filtering requirements - Integration with your systems - Specialized reporting needs # Actor input Schema ## `texts` (type: `array`): List of texts to check for profanity ## `add` (type: `string`): Additional words to check for profanity ## `fillText` (type: `string`): Text to fill the profanity with ## `fillChar` (type: `string`): Character to fill the profanity with ## Actor input object example ```json { "texts": [ "This is a piece of text", "This is another piece of shit" ] } ``` # 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 = { "texts": [ "This is a piece of text", "This is another piece of shit" ] }; // Run the Actor and wait for it to finish const run = await client.actor("louisdeconinck/profanity-checker").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 = { "texts": [ "This is a piece of text", "This is another piece of shit", ] } # Run the Actor and wait for it to finish run = client.actor("louisdeconinck/profanity-checker").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 '{ "texts": [ "This is a piece of text", "This is another piece of shit" ] }' | apify call louisdeconinck/profanity-checker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=louisdeconinck/profanity-checker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Profanity Checker", "description": "Clean text fast! 🚀 This actor removes profanity, obscenity, & unwanted words. Perfect for content moderation & data sanitization. Built-in & custom lists. Try it now! ✨", "version": "0.1", "x-build-id": "iyfVlnFi6BgW7ckIe" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/louisdeconinck~profanity-checker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-louisdeconinck-profanity-checker", "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/louisdeconinck~profanity-checker/runs": { "post": { "operationId": "runs-sync-louisdeconinck-profanity-checker", "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/louisdeconinck~profanity-checker/run-sync": { "post": { "operationId": "run-sync-louisdeconinck-profanity-checker", "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": [ "texts" ], "properties": { "texts": { "title": "Texts", "type": "array", "description": "List of texts to check for profanity", "items": { "type": "string" } }, "add": { "title": "Additional words", "type": "string", "description": "Additional words to check for profanity" }, "fillText": { "title": "Fill text", "maxLength": 20, "type": "string", "description": "Text to fill the profanity with" }, "fillChar": { "title": "Fill character", "maxLength": 1, "type": "string", "description": "Character to fill the profanity with" } } }, "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 } } } } } } } } } } ```