# JSON Serialization Performance in Python

**Domain Paper: Python Performance ADRs**
**Date:** 2026-01-03
**Source:** Python Numbers Everyone Should Know benchmarks

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## Executive Summary

Alternative JSON libraries like `orjson` and `msgspec` deliver **8-12x faster serialization** and **2-7x faster deserialization** compared to stdlib `json`. The performance gap is consistent across payload sizes.

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## Key Findings

### Serialization Performance (dumps)

| Library | Simple Object | Complex Object | Speedup vs stdlib |
|---------|--------------|----------------|-------------------|
| `json.dumps()` | 708 ns | 2.65 us | 1x (baseline) |
| `orjson.dumps()` | 61 ns | 310 ns | **11.6x / 8.5x** |
| `msgspec.encode()` | 92 ns | 445 ns | 7.7x / 6.0x |
| `ujson.dumps()` | 264 ns | 1.64 us | 2.7x / 1.6x |

### Deserialization Performance (loads)

| Library | Simple Object | Complex Object | Speedup vs stdlib |
|---------|--------------|----------------|-------------------|
| `json.loads()` | 714 ns | 2.22 us | 1x (baseline) |
| `orjson.loads()` | 106 ns | 839 ns | **6.7x / 2.6x** |
| `msgspec.decode()` | 101 ns | 850 ns | 7.1x / 2.6x |

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## When to Use Each Library

### Use stdlib `json` when:
- Zero dependencies required
- Need custom JSONEncoder subclass
- Compatibility is paramount

### Use `orjson` when:
- Maximum performance needed
- You can accept bytes output
- You need datetime/UUID support

### Use `msgspec` when:
- You need typed decoding
- You want MessagePack too
- Memory efficiency matters

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## Practical Rules for Coding Agents

### Rule 1: Default to orjson for new projects

```python
# Instead of:
import json
data = json.dumps(obj)

# Prefer:
import orjson
data = orjson.dumps(obj)  # Returns bytes
```

### Rule 2: Use stdlib json only when explicitly needed

Acceptable reasons:
- Must avoid external dependencies
- Need custom JSONEncoder subclass
- Working in constrained environment

### Rule 3: Profile before optimizing JSON

At 2-3 microseconds per operation, JSON serialization is rarely the bottleneck unless you're doing thousands of operations per second.

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## Summary Table

| Scenario | Recommendation | Expected Speedup |
|----------|----------------|------------------|
| General use | orjson | 8x serialization, 2.5x deserialization |
| Typed data | msgspec | 6x + type safety |
| Drop-in replacement | ujson | 1.5-2x |
| Zero dependencies | json (stdlib) | Baseline |

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*Benchmark source: python-numbers-everyone-should-know*