DataEngUtils for Backend Engineers
Backend Engineers build and maintain the server-side systems that power applications, APIs, and data services. Your daily work involves debugging authentication tokens, encoding and decoding payloads, formatting API responses, testing regex patterns, and generating mock data for development. Every one of these tasks traditionally requires opening a web-based tool, pasting potentially sensitive data, and trusting that the third-party server handles it responsibly. DataEngUtils brings a complete suite of API and encoding utilities directly to your Mac, all running offline with zero data leakage. This page organizes the tools most relevant to Backend Engineers into the workflows you encounter every day.
Tools for backend engineers
- JWT DebuggerDecode and inspect JSON Web Tokens on macOS without pasting bearer tokens into a public JWT debugger
- JWT EncoderJWT Encoder is built for data engineers who need to encode and decode payloads for APIs, logs, and s
- API Key GeneratorAPI Key Generator is built for data engineers who need to generate identifiers, test rows, and mock
- Connection String ParserBreak apart database connection strings for Postgres, MySQL, Redis, and other engines without pastin
- Base64 Encode/DecodeBase64 Encode/Decode is built for data engineers who need to encode and decode payloads for APIs, lo
- URL Encode/DecodeURL Encode/Decode is built for data engineers who need to encode and decode payloads for APIs, logs,
- HTML Entity Encode/DecodeHTML Entity Encode/Decode is built for data engineers who need to encode and decode payloads for API
- Gzip Base64Gzip Base64 is built for data engineers who need to encode and decode payloads for APIs, logs, and s
- JSON FormatterJSON Formatter is built for data engineers who need to validate and format pipeline configs, warehou
- JSON ValidatorJSON Validator is built for data engineers who need to validate and format pipeline configs, warehou
- Regex TesterRegex Tester is built for data engineers who need to inspect, debug, and explain data artifacts when
- Log ParserLog Parser is built for data engineers who need to inspect, debug, and explain data artifacts when s
Workflow: Debug authentication and connection strings
Inspect JWT tokens, parse database connection strings, and encode test tokens without exposing credentials to third-party servers.
1. Decode a JWT from an API request
Paste a JWT from an authorization header into the JWT Debugger. The header and payload are decoded instantly on your machine.
2. Parse a connection string
Use Connection String Parser to break down database or Redis connection strings into individual parameters — host, port, database, and credentials.
3. Encode a JWT for testing
Use JWT Encoder to create tokens with custom claims for integration tests without exposing your signing key to a web tool.
Workflow: Encode and decode API payloads
Base64-encode binary data for API transmission, URL-encode query parameters, compress payloads, and decode incoming data for debugging.
1. Base64-encode request data
Paste binary or text data into Base64 Encode/Decode to prepare it for API transmission or decode incoming payloads.
2. Encode URL parameters
Use URL Encode/Decode to properly encode query string values or decode URLs from request logs for debugging.
3. Compress large payloads
Use Gzip Base64 to gzip-compress JSON payloads before sending them to APIs that accept Content-Encoding: gzip.
Workflow: Validate and format API responses
Format JSON responses, validate structure, test regex patterns, and compare API outputs — all without leaving the DataEngUtils sidebar.
1. Format an API JSON response
Copy a raw JSON response from curl or Postman into JSON Formatter for instant pretty-printing and syntax highlighting.
2. Validate JSON structure
Use JSON Validator to catch malformed JSON responses before they cause parsing errors in your application.
3. Test regex patterns
Use Regex Tester to experiment with regex patterns against sample API responses, with real-time match highlighting.
Workflow: Generate mock data for testing
Create realistic test data with fake data generators, mock SQL INSERT statements, and secure API keys for development and staging environments.
1. Generate mock SQL data
Use Mock SQL INSERT to generate INSERT statements with realistic test data for your database tables — specify the table schema and row count.
2. Generate fake data
Use Faker Data Generator to create names, emails, addresses, and other realistic test data for API fixtures.
3. Generate API keys
Use API Key Generator to create cryptographically random keys for your application's API consumers.