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Metadata-Version: 2.4
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Name: jiter
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Version: 0.13.0
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Classifier: Development Status :: 4 - Beta
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Classifier: Programming Language :: Python
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3 :: Only
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.10
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Classifier: Programming Language :: Python :: 3.11
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Classifier: Programming Language :: Python :: 3.12
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Classifier: Programming Language :: Python :: 3.13
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Classifier: Programming Language :: Python :: 3.14
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Classifier: Programming Language :: Python :: Implementation :: CPython
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Classifier: Programming Language :: Python :: Implementation :: GraalPy
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Classifier: Intended Audience :: Developers
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Classifier: Intended Audience :: Information Technology
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Classifier: Intended Audience :: System Administrators
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Classifier: License :: OSI Approved :: MIT License
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Classifier: Operating System :: Unix
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Classifier: Operating System :: POSIX :: Linux
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Classifier: Environment :: Console
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Classifier: Environment :: MacOS X
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Classifier: Topic :: File Formats :: JSON
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Classifier: Framework :: Pydantic :: 2
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License-File: LICENSE
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Summary: Fast iterable JSON parser.
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Home-Page: https://github.com/pydantic/jiter/
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Author-email: Samuel Colvin <s@muelcolvin.com>
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Requires-Python: >=3.9
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Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
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# jiter
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[](https://github.com/pydantic/jiter/actions?query=event%3Apush+branch%3Amain+workflow%3ACI)
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[](https://pypi.python.org/pypi/jiter)
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[](https://github.com/pydantic/jiter)
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[](https://github.com/pydantic/jiter/blob/main/LICENSE)
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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`.
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The API is extremely minimal:
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```python
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def from_json(
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json_data: bytes,
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/,
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*,
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allow_inf_nan: bool = True,
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cache_mode: Literal[True, False, "all", "keys", "none"] = "all",
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partial_mode: Literal[True, False, "off", "on", "trailing-strings"] = False,
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catch_duplicate_keys: bool = False,
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float_mode: Literal["float", "decimal", "lossless-float"] = "float",
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) -> Any:
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"""
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Parse input bytes into a JSON object.
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Arguments:
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json_data: The JSON data to parse
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allow_inf_nan: Whether to allow infinity (`Infinity` an `-Infinity`) and `NaN` values to float fields.
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Defaults to True.
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cache_mode: cache Python strings to improve performance at the cost of some memory usage
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- True / 'all' - cache all strings
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- 'keys' - cache only object keys
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- False / 'none' - cache nothing
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partial_mode: How to handle incomplete strings:
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- False / 'off' - raise an exception if the input is incomplete
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- True / 'on' - allow incomplete JSON but discard the last string if it is incomplete
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- 'trailing-strings' - allow incomplete JSON, and include the last incomplete string in the output
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catch_duplicate_keys: if True, raise an exception if objects contain the same key multiple times
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float_mode: How to return floats: as a `float`, `Decimal` or `LosslessFloat`
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Returns:
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Python object built from the JSON input.
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"""
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def cache_clear() -> None:
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"""
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Reset the string cache.
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"""
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def cache_usage() -> int:
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"""
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get the size of the string cache.
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Returns:
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Size of the string cache in bytes.
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"""
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```
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## Examples
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The main function provided by Jiter is `from_json()`, which accepts a bytes object containing JSON and returns a Python dictionary, list or other value.
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```python
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import jiter
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json_data = b'{"name": "John", "age": 30}'
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parsed_data = jiter.from_json(json_data)
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print(parsed_data) # Output: {'name': 'John', 'age': 30}
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```
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### Handling Partial JSON
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Incomplete JSON objects can be parsed using the `partial_mode=` parameter.
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```python
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import jiter
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partial_json = b'{"name": "John", "age": 30, "city": "New Yor'
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# Raise error on incomplete JSON
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try:
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jiter.from_json(partial_json, partial_mode=False)
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except ValueError as e:
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print(f"Error: {e}")
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# Parse incomplete JSON, discarding incomplete last field
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result = jiter.from_json(partial_json, partial_mode=True)
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print(result) # Output: {'name': 'John', 'age': 30}
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# Parse incomplete JSON, including incomplete last field
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result = jiter.from_json(partial_json, partial_mode='trailing-strings')
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print(result) # Output: {'name': 'John', 'age': 30, 'city': 'New Yor'}
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```
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### Catching Duplicate Keys
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The `catch_duplicate_keys=True` option can be used to raise a `ValueError` if an object contains duplicate keys.
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```python
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import jiter
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json_with_dupes = b'{"foo": 1, "foo": 2}'
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# Default behavior (last value wins)
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result = jiter.from_json(json_with_dupes)
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print(result) # Output: {'foo': 2}
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# Catch duplicate keys
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try:
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jiter.from_json(json_with_dupes, catch_duplicate_keys=True)
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except ValueError as e:
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print(f"Error: {e}")
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```
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