Data Validation: Validate a JSON Payload Against a Schema with Nested Rules

Question

## Problem

Implement a schema validator. A schema is a Python dict specifying expected types and constraints. Validate a given payload against the schema and return a list of validation errors (empty list if valid).

Supported schema keys: `"type"` ("str", "int", "float", "list", "dict"), `"required"` (bool), `"min"` / `"max"` (for int/float), `"fields"` (nested schema for dict type).

```python
from typing import Any, List

def validate(payload: Any, schema: dict) -> List[str]:
    # return list of error messages, empty if valid
    pass
```

**Example:**
```
schema = {
  "type": "dict",
  "fields": {
    "age":  {"type": "int", "required": True, "min": 0, "max": 150},
    "name": {"type": "str", "required": True}
  }
}

validate({"age": 200, "name": "Ada"}, schema)
-> ["age: value 200 exceeds max 150"]

validate({"age": 25}, schema)
-> ["name: required field missing"]
```

## Follow-ups

1. How would you support list-element schemas (validate every item in a list against a sub-schema)?
2. How would you support `"one_of"` / union types?
3. How would you generate a human-readable diff showing exactly which fields failed and why?
4. How does this compare to JSON Schema (draft-07) — what features would you need to add to reach parity?

Data Validation: Validate a JSON Payload Against a Schema with Nested Rules

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