Analysis updated 2026-07-15 · repo last pushed 2023-05-27
Normalize messy user input from sign-up forms before saving to a database
Mask emails and names in user data before exporting for analytics
Convert text to URL-friendly slugs or camel case automatically
Set default values for empty form fields during data processing
| zaneli/mold | aasheeshlikepanner/vase | alexzielenski/controller-runtime | |
|---|---|---|---|
| Stars | — | 0 | — |
| Language | Go | Go | Go |
| Last pushed | 2023-05-27 | — | 2022-04-20 |
| Maintenance | Dormant | — | Dormant |
| Setup difficulty | easy | moderate | hard |
| Complexity | 2/5 | 4/5 | 4/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires Go 1.18 or newer but no external dependencies are needed.
Mold is a toolkit for Go programmers who need to automatically clean up, reformat, or anonymize data stored in structured objects. Instead of writing custom code every time you need to trim spaces from a string, convert text to a specific format, or hide sensitive personal information, you can use this library to apply those changes across your data in a consistent, reusable way. The library works by applying what it calls "modifiers" and "scrubbers" to your data structures. Modifiers transform data in place, for example, converting text to camel case, turning a phrase into a URL-friendly slug, stripping out punctuation, or trimming unwanted prefixes and suffixes. You can also set default values for fields that are currently empty. The scrubbers handle privacy concerns by obfuscating sensitive information like email addresses or names, replacing them with hashed versions so the original data is no longer exposed. This would be useful for developers building web applications or APIs who receive messy user input and need to normalize it before saving it to a database. A concrete example would be taking a sign-up form where someone typed their name with extra spaces or mixed capitalization, then automatically trimming and title-casing it. Similarly, if you need to export user data for analytics or share it with a third party, the scrubbing features let you mask emails and names so you stay compliant with privacy requirements. The project is designed to work alongside complementary tools for form decoding and data validation, rounding out a common workflow of receiving, cleaning, validating, and storing user data. It requires Go 1.18 or newer and the maintainer actively invites community contributions to expand the library's collection of modifiers and scrubbers, with a preference for not adding external dependencies.
A Go library for cleaning up and anonymizing structured data. It automatically reformats text fields and masks sensitive information like emails before saving or exporting.
Mainly Go. The stack also includes Go.
Dormant — no commits in 2+ years (last push 2023-05-27).
No license information was provided in the repository's documentation.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.