Как конвертировать JSON в код TypeScript, Go, Java и других (бесплатно, гайд 2026)

Why Convert JSON to Code?

Every API integration starts with the same chore: a JSON response lands in your lap and you need typed structures around it. Hand-writing them is slow and error-prone — miss one field and your compiler or runtime finds out at the worst possible time. And when the API evolves, hand-maintained models drift from reality.

A converter solves both problems: it reads the actual sample you give it and emits idiomatic type declarations for your language, so your models match real payloads from day one and can be regenerated whenever the API changes.

What a Good Converter Detects

Nested objects become named types. A user.address.city structure produces a separate Address type instead of one unreadable inline blob, and shared shapes are reused by name.

Arrays merge their shapes. Real-world arrays are messy: not every object carries every key. A good converter unions the keys across all items and marks fields that are missing in some entries as optional — so your types stay honest about what the API actually returns.

Optional vs. nullable are kept apart. A key that is sometimes absent is not the same as a key that is present but null. These map to different constructs in every language (? vs. T | null in TypeScript, pointers vs. zero values in Go, Option<T> in Rust), and the generated code preserves the distinction.

Depth is bounded. Pathologically deep JSON produces unreadable output, so generation stops at a sane depth and falls back to generic maps — a deliberate trade of completeness for usability.

Pick Your Language

All seven converters share the same inference engine, so the same sample produces consistent output everywhere:

• TypeScript — nested interfaces, ? for optional fields, union types for nullables. Strict-mode friendly: JSON to TypeScript.
• Go — structs with json tags, pointers for nullable fields so unmarshal can represent "absent": JSON to Go struct.
• Java — POJOs with getters and setters, ready for Jackson or Gson: JSON to Java POJO.
• Python — @dataclass definitions with type hints: JSON to Python dataclass.
• Kotlin — data classes with nullable types as T?: JSON to Kotlin data class.
• C# — property classes for System.Text.Json or Newtonsoft: JSON to C# class.
• Rust — serde-compatible structs with Option<T>: JSON to Rust serde struct.

Convert in Three Steps

1. Paste a representative sample. The output is only as accurate as the input: include the items with missing fields, the nulls, the nested lists — not just the happy path.

2. Name the root type. Rename Root to something meaningful (User, OrderResponse) before copying; nested types are named automatically from their keys.

3. Copy and review. Scan the optional and nullable markers first — they are where converters and APIs disagree most — then paste into your project.

Tips for Cleaner Generated Types

Feed it the weird cases. If one array item lacks a field, convert a sample that includes that item — otherwise the field comes out required and your parser will crash on it later.

Regenerate when the API changes. Treat the generated types as build artifacts: cheap to recreate, never hand-edited.

Deeply nested payloads: consider maps. If the API returns an arbitrary-keyed dictionary, a generated Record<string, T>-style map is more honest than twenty one-shot interfaces.

Nothing leaves your machine. Every converter on ToolkitLife parses and generates inside your browser tab. That matters when the JSON contains customer data, tokens, or anything confidential — there is no server to leak it to.