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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,154 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 8, | ||
| "id": "adc73f33-9585-4780-bfc9-9ecd3496cd9b", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stderr", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "/home/jovyan/miniforge3/envs/xlsxdatagrid-dev/lib/python3.12/site-packages/datamodel_code_generator/parser/jsonschema.py:338: UserWarning: format of 'duration' not understood for 'string' - using default\n", | ||
| " warn(f'format of {format__!r} not understood for {type_!r} - using default' '')\n" | ||
| ] | ||
| }, | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "{'a_int': FieldInfo(annotation=Union[int, NoneType], required=False, default=1, title='A Int'),\n", | ||
| " 'i_duration': FieldInfo(annotation=Union[str, NoneType], required=False, default='PT2H33M3S', title='I Duration')}" | ||
| ] | ||
| }, | ||
| "execution_count": 8, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "import typing as ty\n", | ||
| "import importlib\n", | ||
| "import json\n", | ||
| "from pathlib import Path\n", | ||
| "from tempfile import TemporaryDirectory\n", | ||
| "from datamodel_code_generator import InputFileType, generate, DataModelType\n", | ||
| "from pydantic import BaseModel\n", | ||
| "import sys\n", | ||
| "\n", | ||
| "def pydantic_model_from_json_schema(json_schema: str) -> ty.Type[BaseModel]:\n", | ||
| " load = json_schema[\"title\"] if \"title\" in json_schema else \"Model\"\n", | ||
| "\n", | ||
| " with TemporaryDirectory() as temporary_directory_name:\n", | ||
| " temporary_directory = Path(temporary_directory_name)\n", | ||
| " file_path = \"model.py\"\n", | ||
| " module_name = file_path.split(\".\")[0]\n", | ||
| " output = Path(temporary_directory / file_path)\n", | ||
| " generate(\n", | ||
| " json.dumps(json_schema),\n", | ||
| " input_file_type=InputFileType.JsonSchema,\n", | ||
| " input_filename=\"example.json\",\n", | ||
| " output=output,\n", | ||
| " output_model_type=DataModelType.PydanticV2BaseModel,\n", | ||
| " )\n", | ||
| " spec = importlib.util.spec_from_file_location(module_name, output)\n", | ||
| " module = importlib.util.module_from_spec(spec)\n", | ||
| " sys.modules[module_name] = module\n", | ||
| " spec.loader.exec_module(module)\n", | ||
| " return getattr(module, load)\n", | ||
| "\n", | ||
| "schema = {\n", | ||
| " \"title\": \"Test\",\n", | ||
| " \"type\": \"object\",\n", | ||
| " \"properties\": {\n", | ||
| " \"a_int\": {\n", | ||
| " \"default\": 1,\n", | ||
| " \"title\": \"A Int\",\n", | ||
| " \"type\": \"integer\"\n", | ||
| " },\n", | ||
| " \"i_duration\": {\n", | ||
| " \"default\": \"PT2H33M3S\",\n", | ||
| " \"format\": \"duration\",\n", | ||
| " \"title\": \"I Duration\",\n", | ||
| " \"type\": \"string\"\n", | ||
| " }\n", | ||
| " },\n", | ||
| " }\n", | ||
| "\n", | ||
| "Model = pydantic_model_from_json_schema(schema)\n", | ||
| "Model.model_fields" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 15, | ||
| "id": "0b1c0296-f241-4c1d-b5d3-aca152cf2be6", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "{'a_int': FieldInfo(annotation=Union[int, NoneType], required=False, default=1, title='A Int'),\n", | ||
| " 'i_duration': FieldInfo(annotation=timedelta, required=False, default='PT2H33M3S')}" | ||
| ] | ||
| }, | ||
| "execution_count": 15, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "from datetime import timedelta\n", | ||
| "from pydantic import create_model\n", | ||
| "\n", | ||
| "\n", | ||
| "def get_timedelta_fields(schema: dict) -> list[str]:\n", | ||
| " pr = schema[\"properties\"]\n", | ||
| " return [k for k, v in pr.items() if \"format\" in v and v[\"format\"] == \"duration\"]\n", | ||
| " \n", | ||
| "def update_timedelta_field(model: BaseModel, timedelta_fields: list[str]) -> BaseModel:\n", | ||
| " \"\"\"returns a new pydantic model where serialization validators have been added to dates,\n", | ||
| " datetimes and durations for compatibility with excel\"\"\"\n", | ||
| " get_default = lambda obj: obj.default if hasattr(obj, \"default\") else ...\n", | ||
| " deltas = {\n", | ||
| " k: (timedelta, get_default(v))\n", | ||
| " for k, v in model.model_fields.items()\n", | ||
| " if k in timedelta_fields\n", | ||
| " } | {\"__base__\": model}\n", | ||
| " return create_model(model.__name__ + \"New\", **deltas)\n", | ||
| "\n", | ||
| "\n", | ||
| "li = get_timedelta_fields(schema)\n", | ||
| "Model1 = update_timedelta_field(Model, li)\n", | ||
| "Model1.model_fields" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "636bc3be-627c-4720-ae48-21ba5440118d", | ||
| "metadata": {}, | ||
| "source": [] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python 3 (ipykernel)", | ||
| "language": "python", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.12.3" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
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