jiter
Fast iterable JSON parser.
Install
jiter on PyPI
pip
pip install jiteruv
uv add jiterpoetry
poetry add jiterPackage facts
| License | MIT (permissive) |
| Python support | supports the current Python release (>=3.9) |
| Install friction | medium — platform-specific wheel |
| Runtime dependencies | none |
| Maintenance | actively maintained — 45 days since the last release |
| Last repo commit | |
| First released | |
| Popularity | one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-13) |
Evidence: jiter-0.16.0-cp310-cp310-macosx_10_12_x86_64.whl; jiter-0.16.0-cp310-cp310-macosx_11_0_arm64.whl; jiter-0.16.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; jiter-0.16.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl; jiter-0.16.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl; jiter-0.16.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl; jiter-0.16.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; jiter-0.16.0-cp310-cp310-manylinux_2_31_riscv64.whl; jiter-0.16.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl; jiter-0.16.0-cp310-cp310-musllinux_1_1_aarch64.whl; jiter-0.16.0-cp310-cp310-musllinux_1_1_x86_64.whl; jiter-0.16.0-cp310-cp310-win32.whl; jiter-0.16.0-cp310-cp310-win_amd64.whl; jiter-0.16.0-cp311-cp311-macosx_10_12_x86_64.whl; jiter-0.16.0-cp311-cp311-macosx_11_0_arm64.whl; jiter-0.16.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; jiter-0.16.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl; jiter-0.16.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl; jiter-0.16.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl; jiter-0.16.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
About jiter
from the package's own PyPI description — quoted content, verbatim
jiter
CI (image) pypi (image) versions (image) license (image)
This is a standalone version of the JSON parser used in pydantic-core. The recommendation is to only use this package directly if you do not use pydantic.
The API is extremely minimal:
```python def from_json( json_data: bytes, /, *, allow_inf_nan: bool = True, cache_mode: Literal[True, False, 'all', 'keys', 'none'] = 'all', partial_mode: Literal[True, False, 'off', 'on', 'trailing-strings'] = False, catch_duplicate_keys: bool = False, float_mode: Literal['float', 'decimal', 'lossless-float'] = 'float', ) -> Any: """ Parse input bytes into a JSON object.
Arguments:
json_data: The JSON data to parse
allow_inf_nan: Whether to allow...
Read as markdown · JSON record · Source repository · Homepage
AI interpretation — verify before relying
AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page
A fast, minimal JSON parser that deserializes bytes into Python objects, with options for partial parsing, duplicate key detection, and different float representations.
Medium install friction due to compiled wheels across many platforms (CPython 3.9–3.14, multiple architectures). No runtime dependencies. Active maintenance with recent releases and a healthy repository signal.
MIT license permits commercial and private use with minimal restrictions—suitable for most projects.
Usage
import jiter
json_data = b'{"name": "John", "age": 30}'
parsed = jiter.from_json(json_data)
print(parsed) # {'name': 'John', 'age': 30}
Requires Python ≥3.9; input must be bytes, not a string.
Verdict: A lean, actively maintained JSON parser designed for speed with zero runtime dependencies. Medium install friction is offset by broad platform coverage and permissive MIT licensing. No known vulnerabilities and suitable for projects seeking a lightweight alternative to the standard library when pydantic is not in use.
Needs verification
- Actual performance comparison to standard library json or other parsers under typical workloads
- Memory overhead of string caching modes relative to parsing speed gains
- Compatibility with GraalPy (listed in classifiers) and real-world usage stability
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