Description

# jiter [](https://github.com/pydantic/jiter/actions?query=event%3Apush+branch%3Amain+workflow%3ACI) [](https://pypi.python.org/pypi/jiter) [](https://github.com/pydantic/jiter) [](https://github.com/pydantic/jiter/blob/main/LICENSE) 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 infinity (`Infinity` an `-Infinity`) and `NaN` values to float fields. Defaults to True. cache_mode: cache Python strings to improve performance at the cost of some memory usage - True / 'all' - cache all strings - 'keys' - cache only object keys - False / 'none' - cache nothing partial_mode: How to handle incomplete strings: - False / 'off' - raise an exception if the input is incomplete - True / 'on' - allow incomplete JSON but discard the last string if it is incomplete - 'trailing-strings' - allow incomplete JSON, and include the last incomplete string in the output catch_duplicate_keys: if True, raise an exception if objects contain the same key multiple times float_mode: How to return floats: as a `float`, `Decimal` or `LosslessFloat` Returns: Python object built from the JSON input. """ def cache_clear() -> None: """ Reset the string cache. """ def cache_usage() -> int: """ get the size of the string cache. Returns: Size of the string cache in bytes. """ ``` ## Examples 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. ```python import jiter json_data = b'{"name": "John", "age": 30}' parsed_data = jiter.from_json(json_data) print(parsed_data) # Output: {'name': 'John', 'age': 30} ``` ### Handling Partial JSON Incomplete JSON objects can be parsed using the `partial_mode=` parameter. ```python import jiter partial_json = b'{"name": "John", "age": 30, "city": "New Yor' # Raise error on incomplete JSON try: jiter.from_json(partial_json, partial_mode=False) except ValueError as e: print(f'Error: {e}') # Parse incomplete JSON, discarding incomplete last field result = jiter.from_json(partial_json, partial_mode=True) print(result) # Output: {'name': 'John', 'age': 30} # Parse incomplete JSON, including incomplete last field result = jiter.from_json(partial_json, partial_mode='trailing-strings') print(result) # Output: {'name': 'John', 'age': 30, 'city': 'New Yor'} ``` ### Catching Duplicate Keys The `catch_duplicate_keys=True` option can be used to raise a `ValueError` if an object contains duplicate keys. ```python import jiter json_with_dupes = b'{"foo": 1, "foo": 2}' # Default behavior (last value wins) result = jiter.from_json(json_with_dupes) print(result) # Output: {'foo': 2} # Catch duplicate keys try: jiter.from_json(json_with_dupes, catch_duplicate_keys=True) except ValueError as e: print(f'Error: {e}') ```