# Base64 Encoder & Decoder (`rixin/base64-encoder-decoder`) Actor From $0.1/1k requests. Encode text or files to Base64, decode Base64 back to text or binary files. Perfect for data transfer, API payloads, email attachments, and image embedding. Batch process multiple items in one run. Supports text and files. Fast, reliable encoding solution. - **URL**: https://apify.com/rixin/base64-encoder-decoder.md - **Developed by:** [Rixin Sc](https://apify.com/rixin) (community) - **Categories:** Developer tools, Automation, Integrations - **Stats:** 37 total users, 13 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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 ## Base64 Encoder & Decoder Encode text or files to Base64, or decode Base64 back to text or binary files. Fast, reliable, and easy to use for data transformation. ### What does Base64 Encoder & Decoder do? Base64 Encoder & Decoder converts your data to and from Base64 encoding. You can encode plain text strings or files from any URL. The actor processes multiple items in a single run and outputs the result for each item. - **Text Encoding**: Encode any plain text string to Base64 - **File Encoding**: Encode files from any URL (direct download links) - **Text Decoding**: Decode Base64 strings back to plain text - **File Decoding**: Decode Base64 to binary files saved in key-value store - **Batch Processing**: Process multiple items in a single run ### Use Cases - **Data Transfer**: Safely transfer binary data through text-only channels - **API Payloads**: Encode binary data for JSON APIs - **Email Attachments**: Prepare files for email embedding - **Image Embedding**: Convert images to data URIs - **Configuration Storage**: Store binary data in text-based config files ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `mode` | string | Yes | Operation mode: "encode" or "decode" | | `textInputs` | array | No | List of text strings to encode/decode | | `fileUrls` | array | No | List of file URLs to download and process (supports advanced HTTP options) | | `outputAsFile` | boolean | No | When decoding, save output as file in KV store (default: false) | #### Example Input (Encode) ```json { "mode": "encode", "textInputs": ["Hello World", "Another string"], "fileUrls": [ { "url": "https://example.com/image.png" } ] } ```` #### Example Input (Decode) ```json { "mode": "decode", "textInputs": ["SGVsbG8gV29ybGQ="], "outputAsFile": false } ``` #### Advanced File URL Options The `fileUrls` field supports full HTTP request configuration for each URL: | Property | Type | Required | Description | |----------|------|----------|-------------| | `url` | string | Yes | The URL to fetch | | `method` | string | No | HTTP method (GET, POST, PUT, etc.). Default: GET | | `headers` | object | No | Custom HTTP headers to send with the request | | `payload` | string | No | Request body for POST/PUT requests | | `userData` | object | No | Custom data passed through for your reference | #### Example Input (Advanced with Auth) ```json { "mode": "encode", "fileUrls": [ { "url": "https://example.com/public-image.png" }, { "url": "https://api.example.com/protected-file", "method": "GET", "headers": { "Authorization": "Bearer your-token-here" } }, { "url": "https://api.example.com/generate-pdf", "method": "POST", "payload": "{\"template\": \"invoice\"}", "headers": { "Content-Type": "application/json" } } ] } ``` ### Output Each processed item produces a dataset record with: | Field | Description | |-------|-------------| | `input` | The original input (text preview or file URL) | | `inputType` | Type of input: "text" or "file" | | `mode` | Operation mode: "encode" or "decode" | | `output` | Base64 string (encode) or decoded text (decode) | | `outputFileKey` | Key in KV store when outputAsFile is true | | `inputSizeBytes` | Size of input data in bytes | | `outputSizeBytes` | Size of output data in bytes | | `processedAt` | ISO timestamp of when processing completed | | `error` | Error message if processing failed, null otherwise | #### Example Output (Encode) ```json { "input": "Hello World", "inputType": "text", "mode": "encode", "output": "SGVsbG8gV29ybGQ=", "outputFileKey": null, "inputSizeBytes": 11, "outputSizeBytes": 16, "processedAt": "2024-01-15T10:30:00.000Z", "error": null } ``` ### Pricing This actor uses pay-per-event pricing: | Event | Price | Description | |-------|-------|-------------| | Text Processed | $0.0001 | Charged for each text string encoded/decoded | | File Processed | $0.0002 | Charged for each file fetched and processed | | File Generated | $0.0002 | Charged when decoded output is saved as file | **Example costs:** - 1,000 text encodes: $0.10 - 1,000 file encodes: $0.20 - 1,000 decodes to file: $0.30 (file-processed + file-generated) ### Integrations Works with all Apify integrations: - **Apify API**: Trigger runs programmatically - **Webhooks**: Get notified when runs complete - **Zapier/Make**: Connect with automation workflows ### FAQ **Q: What's the difference between encode and decode?** A: Encode converts binary/text to Base64 string. Decode converts Base64 string back to original data. **Q: When should I use outputAsFile?** A: Use it when decoding binary data (images, PDFs, etc.) that can't be represented as text. **Q: What's the maximum file size?** A: Files are limited by available memory. The actor uses 256-1024 MB, supporting larger files. **Q: Can I process files from any URL?** A: Yes! Any publicly accessible URL is supported. The file will be downloaded and processed. **Q: What encoding standard is used?** A: Standard Base64 encoding (RFC 4648) with A-Z, a-z, 0-9, +, / characters and = padding. # Actor input Schema ## `mode` (type: `string`): Choose whether to encode data to Base64 or decode Base64 back to original data. ## `textInputs` (type: `array`): Enter text strings to process. For encoding: enter plain text. For decoding: enter Base64 strings. ## `fileUrls` (type: `array`): URLs to files to process. Supports GET (default) and other HTTP methods with custom headers and payload. ## `outputAsFile` (type: `boolean`): When decoding, save the output as a file in the key-value store instead of returning as text. Useful for binary data like images. ## Actor input object example ```json { "mode": "encode", "textInputs": [ "Hello World", "Apify is awesome!" ], "fileUrls": [], "outputAsFile": false } ``` # Actor output Schema ## `results` (type: `string`): URL to the dataset containing all processed items ## `decodedFiles` (type: `string`): URL to the key-value store containing decoded files (when outputAsFile is true) # 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 = { "textInputs": [ "Hello World", "Apify is awesome!" ] }; // Run the Actor and wait for it to finish const run = await client.actor("rixin/base64-encoder-decoder").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 = { "textInputs": [ "Hello World", "Apify is awesome!", ] } # Run the Actor and wait for it to finish run = client.actor("rixin/base64-encoder-decoder").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 '{ "textInputs": [ "Hello World", "Apify is awesome!" ] }' | apify call rixin/base64-encoder-decoder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=rixin/base64-encoder-decoder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Base64 Encoder & Decoder", "description": "From $0.1/1k requests. Encode text or files to Base64, decode Base64 back to text or binary files. Perfect for data transfer, API payloads, email attachments, and image embedding. Batch process multiple items in one run. Supports text and files. Fast, reliable encoding solution.", "version": "0.0", "x-build-id": "mqk91J3g0stVDx9hc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/rixin~base64-encoder-decoder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-rixin-base64-encoder-decoder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/rixin~base64-encoder-decoder/runs": { "post": { "operationId": "runs-sync-rixin-base64-encoder-decoder", "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/rixin~base64-encoder-decoder/run-sync": { "post": { "operationId": "run-sync-rixin-base64-encoder-decoder", "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": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "encode", "decode" ], "type": "string", "description": "Choose whether to encode data to Base64 or decode Base64 back to original data.", "default": "encode" }, "textInputs": { "title": "Text Inputs", "type": "array", "description": "Enter text strings to process. For encoding: enter plain text. For decoding: enter Base64 strings.", "default": [], "items": { "type": "string" } }, "fileUrls": { "title": "File URLs", "type": "array", "description": "URLs to files to process. Supports GET (default) and other HTTP methods with custom headers and payload.", "default": [], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "outputAsFile": { "title": "Save Decoded Output as File", "type": "boolean", "description": "When decoding, save the output as a file in the key-value store instead of returning as text. Useful for binary data like images.", "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 } } } } } } } } } } ```