UltraJSON (ujson)

Ultra-fast JSON encoder and decoder for Python written as a C extension. Drop-in replacement for Python's standard json module offering 2-5x faster encoding and decoding. Used by pandas, PyPI, and many high-throughput Python services where JSON serialization is a bottleneck. Maintains the same API as the standard json module — json.loads/json.dumps compatible.

Evaluated Mar 06, 2026 (0d ago) v5.x
Homepage ↗ Repo ↗ Developer Tools python json fast c-extension serialization deserialization performance
⚙ Agent Friendliness
64
/ 100
Can an agent use this?
🔒 Security
97
/ 100
Is it safe for agents?
⚡ Reliability
83
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
--
Documentation
78
Error Messages
75
Auth Simplicity
100
Rate Limits
100

🔒 Security

TLS Enforcement
100
Auth Strength
100
Scope Granularity
100
Dep. Hygiene
82
Secret Handling
100

Pure serialization library. C extension with active security maintenance. No network calls. Historical CVEs patched — keep updated.

⚡ Reliability

Uptime/SLA
95
Version Stability
82
Breaking Changes
80
Error Recovery
75
AF Security Reliability

Best When

You need a simple drop-in json module replacement that's faster than stdlib with no API changes — ujson is the path of least resistance for JSON speedup.

Avoid When

You need the absolute fastest JSON performance or Pydantic/dataclass support — orjson is faster and more feature-complete. Also avoid for financial data with float precision requirements.

Use Cases

  • Replace Python's standard json module with a drop-in faster alternative in API services processing large JSON payloads
  • Speed up agent pipelines that serialize/deserialize large JSON responses from LLM APIs or data services
  • Reduce JSON serialization overhead in high-throughput Python web services (Flask, FastAPI, Django)
  • Process large JSON datasets in data pipelines faster than standard json without changing existing code
  • Benchmark JSON performance in Python services to identify if serialization is a bottleneck before adopting orjson

Not For

  • Maximum performance requirements — orjson is faster than ujson and handles more edge cases correctly
  • Dataclass/Pydantic serialization — orjson has native support for Python dataclasses, datetime, UUID; ujson requires manual handling
  • Applications requiring exact decimal precision — ujson can lose precision on large floats; use standard json or orjson for financial data

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
No
SDK
Yes
Webhooks
No

Authentication

Methods: none
OAuth: No Scopes: No

Python library. No authentication required.

Pricing

Model: open_source
Free tier: Yes
Requires CC: No

BSD license. Originally from ESN Social Software, now community maintained.

Agent Metadata

Pagination
none
Idempotent
Full
Retry Guidance
Not documented

Known Gotchas

  • ujson does not support Python's json module 'default' serializer hook for custom types — custom objects must be converted to dicts/lists before serialization
  • Float precision can differ from stdlib json — large floats may lose precision; validate with decimal-sensitive data before adopting
  • ujson returns str (not bytes) from dumps, unlike orjson which returns bytes — this can cause encoding issues if bytes are expected downstream
  • sort_keys parameter behavior may differ subtly from stdlib json in edge cases involving non-string keys
  • C extension compilation requires build tools at install time — may fail in minimal Docker images without gcc; use pre-built wheels from PyPI where available
  • ujson is faster for most workloads but orjson typically beats it in benchmarks — benchmark your specific workload before choosing

Alternatives

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Scores are editorial opinions as of 2026-03-06.

5229
Packages Evaluated
26151
Need Evaluation
173
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