What is TOML?

TOML (Tom’s Obvious, Minimal Language) is a simple text format used to store configuration settings. It is designed to be easy for people to read and write while still being straightforward for programs to parse.

Let's break it down

  • TOML: a name that stands for “Tom’s Obvious, Minimal Language,” created to be clear and uncomplicated.
  • Configuration file: a file that tells a program how it should behave (like setting a theme or a file path).
  • Human-readable: you can look at it and understand it without needing special tools.
  • Key-value pairs: each setting is written as a name (the key) followed by its value, like theme = "dark".
  • Sections: groups of related settings are placed under headings in square brackets, e.g., [database].
  • Data types: TOML knows numbers, strings, dates, booleans, arrays, and tables, so you can store different kinds of information.

Why does it matter?

Because it lets developers and non-technical users edit program settings quickly without worrying about syntax errors. Its clear structure reduces bugs, speeds up setup, and works the same way across many programming languages.

Where is it used?

  • Python packaging: the Poetry tool reads pyproject.toml to manage dependencies and build settings.
  • Rust projects: Cargo uses Cargo.toml to list packages, versions, and build options.
  • Go tools: some Go utilities (e.g., Hugo static site generator) accept TOML configuration files.
  • Cross-platform apps: many desktop and server applications provide a config.toml for user customization.

Good things about it

  • Very easy to read and write for humans.
  • Strict but simple syntax prevents ambiguous interpretations.
  • Supports a wide range of basic data types, including dates and arrays.
  • Predictable ordering of keys, which helps with version control diffs.
  • Native support in many modern languages, making parsing straightforward.

Not-so-good things

  • Fewer advanced features than YAML or JSON (e.g., no anchors or complex merging).
  • Not as universally adopted, so some ecosystems may lack mature libraries.
  • Lacks built-in schema validation, so you need extra tools to check correctness.
  • Can become verbose for deeply nested configurations, making large files harder to skim.