dataclass_wizard.wizard_cli package

Submodules

dataclass_wizard.wizard_cli.cli module

Entry point for the Wizard CLI tool.

class dataclass_wizard.wizard_cli.cli.FileTypeWithExt(mode='r', ext=None, bufsize=-1, encoding=None, errors='ignore')[source]

Bases: FileType

Extends argparse.FileType to add a default file extension if the provided file name is missing one.

dataclass_wizard.wizard_cli.cli.gen_py_schema(args)[source]

Entry point for the wiz gen-schema (gs) command.

dataclass_wizard.wizard_cli.cli.get_div(out_file: TextIO, char='_', line_width=50)[source]

Returns a formatted line divider to print.

dataclass_wizard.wizard_cli.cli.main(args=None)[source]

A companion CLI tool for the Dataclass Wizard, which simplifies interaction with the Python dataclasses module.

dataclass_wizard.wizard_cli.cli.parser: ArgumentParser
dataclass_wizard.wizard_cli.cli.setup_parser()[source]

Sets up the Wizard CLI parser.

dataclass_wizard.wizard_cli.schema module

Generates a Python (dataclass) schema, given a JSON input. The entry point for this module is the gen-schema subcommand.

This JSON to Dataclass conversion tool was inspired by the following projects:

The parser supports the full JSON spec, so both list and dict as the root type are properly handled as expected.

A few important notes on the behavior of JSON parsing:

  • Lists with multiple dictionaries will have all the keys and type definitions merged into a single model dataclass, as the dictionary objects are considered homogenous in this case.

  • Nested lists within the above structure (e.g. list -> dict -> list) should similarly merge all list elements with the list for that same key in each sibling dict object. For example, assuming the below input:

    ... [{"d1": [1, {"k": "v"}]}, {"d1": [{"k": 2}, {"k2": "v2"}, True]}]
    This should result in a single, merged type definition for “d1”::

    … List[Union[int, dataclass(k: Union[str, int], k2: str), bool]]

  • Any nested dictionaries within lists will have their Model class name generated with the singular form of the key containing the model definition – for example, {“Items”:[{“key”:”value”}]} will result in a model class named Item. In the case a dictionary is nested within a list, it will have the class name auto-incremented with a common prefix – for example, Data1, Data2, etc.

The implementation below uses regex code in the rules.english module from the library Python-Inflector (https://github.com/bermi/Python-Inflector).

This library is available under the BSD license, which can be obtained from https://opensource.org/licenses.

The library Python-Inflector contains the following attribution notices:

Copyright (c) 2006 Bermi Ferrer Martinez bermi a-t bermilabs - com

See the end of this file for the original BSD-style license from this library.

class dataclass_wizard.wizard_cli.schema.PyCodeGenerator(file_name: dataclasses.InitVar[str] = None, file_contents: dataclasses.InitVar[str] = None, force_strings: dataclasses.InitVar[bool] = None, experimental: dataclasses.InitVar[bool] = None)[source]

Bases: object

This is the main class responsible for generating Python code that leverages dataclasses, given a JSON object as an input data.

data: List[Any] | Dict[str, Any]
experimental: dataclasses.InitVar[bool] = None
file_contents: dataclasses.InitVar[str] = None
file_name: dataclasses.InitVar[str] = None
force_strings: dataclasses.InitVar[bool] = None
parser: JSONRootParser
property py_code: str

Module contents