I'm attempting to use the library as a module, but having a difficult time figuring out the correct inputs for generate from the documentation. Command line usage is a no brainer:
# Note: test_data.csv is currently just the data from simple.csv in the tests
# % datamodel-codegen --input test_data.csv --input-file-type csv --output test_model.py # generated by datamodel-codegen:
# filename: test_data.csv
# timestamp: 2021-04-30T20:18:11+00:00
from __future__ import annotations
from pydantic import BaseModel, Field
class Model(BaseModel):
id: str
name: str
tel: str
zip_code: str = Field(..., alias='zip code')... but when trying to include this in my own code (based on this example: https://koxudaxi.github.io/datamodel-code-generator/using_as_module/) ... I'm trying to figure out the most straight forward way. I don't need a temp directory or even to write it out to disk ATM.
This is what I'm currently doing:
from pathlib import Path
from tempfile import TemporaryDirectory
from datamodel_code_generator import InputFileType, generate
with TemporaryDirectory() as temporary_directory_name:
temporary_directory = Path(temporary_directory_name)
output = Path(temporary_directory / 'model.py')
generate(
Path("test_data.csv"),
input_file_type=InputFileType.CSV,
input_filename="test_data.csv",
output=output,
)
model: str = output.read_text()
print(model)... it works, but seems super wonky. Amidoingitrite?
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