orjson
Fast Python JSON library written in Rust. orjson is 3-10x faster than the standard library json module for serialization and deserialization. Natively serializes Python dataclasses, datetime, numpy arrays, UUID, and Pydantic models without custom encoders. Drop-in replacement for json.dumps/json.loads with better performance and native type support.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Local library with no network access. Rust-based implementation provides memory safety. No security concerns beyond JSON content being processed.
⚡ Reliability
Best When
JSON serialization is a measurable bottleneck in your Python application and you need native dataclass/datetime/numpy support without custom encoders.
Avoid When
JSON is not in your hot path — standard json or ujson are simpler. Use orjson when you've measured that JSON is actually a bottleneck.
Use Cases
- • Serialize large JSON payloads in agent APIs with minimal overhead — replaces json.dumps in hot paths
- • Serialize numpy arrays, datetimes, and Pydantic models to JSON without custom encoders in agent data pipelines
- • High-throughput agent message passing where JSON serialization latency matters at scale
- • FastAPI or Starlette custom response classes that use orjson for faster response serialization
- • Agent data stores that need fast JSON serialization for caching large structured responses
Not For
- • Applications where JSON performance is not a bottleneck — standard json module is simpler with no Rust compilation
- • Complex custom serialization logic — orjson's option flags are limited; for complex cases use custom encoders
- • Environments without Rust toolchain or wheels for the target platform
Interface
Authentication
Local Python library — no authentication.
Pricing
Completely free and open source.
Agent Metadata
Known Gotchas
- ⚠ orjson.dumps() returns bytes, not str — unlike standard json.dumps(); must call .decode('utf-8') or use OPT_NON_STR_KEYS for string-key dicts
- ⚠ orjson does not support all json module options — indent is supported but separators and sort_keys use different flags (OPT_INDENT_2, OPT_SORT_KEYS)
- ⚠ Circular references raise JSONEncodeError immediately — same as standard json; no cycle detection option
- ⚠ Numpy array serialization requires numpy to be installed — if numpy is not available orjson still works but raises TypeError for ndarray
- ⚠ orjson uses a different option API (OPT_* integer flags) vs standard json's keyword arguments — not a true drop-in for code using json module options
- ⚠ On platforms without pre-built wheels (some ARM, musl libc), installation requires Rust toolchain — check manylinux/musllinux wheel availability for your target
Alternatives
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Scores are editorial opinions as of 2026-03-07.