Schema-driven Python library for typed Excel import/export workflows with Pydantic and locale-aware workbooks.
Project description
ExcelAlchemy
Schema-driven Python library for typed Excel import/export workflows with Pydantic and locale-aware workbooks.
ExcelAlchemy turns Pydantic models into typed workbook contracts:
- generate Excel templates from code
- validate uploaded workbooks
- map failures back to rows and cells
- render workbook-facing output in
zh-CNoren - keep storage pluggable through
ExcelStorage
GitHub Repository · Full README · Architecture · Migration Notes
Screenshots
Template
Import Result
Install
pip install ExcelAlchemy
Optional Minio support:
pip install "ExcelAlchemy[minio]"
Minimal Example
from pydantic import BaseModel
from excelalchemy import ExcelAlchemy, FieldMeta, ImporterConfig, Number, String
class Importer(BaseModel):
age: Number = FieldMeta(label='Age', order=1)
name: String = FieldMeta(label='Name', order=2)
alchemy = ExcelAlchemy(ImporterConfig(Importer, locale='en'))
template = alchemy.download_template_artifact(filename='people-template.xlsx')
excel_bytes = template.as_bytes()
Modern Annotated Example
from typing import Annotated
from pydantic import BaseModel, Field
from excelalchemy import Email, ExcelAlchemy, ExcelMeta, ImporterConfig
class Importer(BaseModel):
email: Annotated[
Email,
Field(min_length=10),
ExcelMeta(label='Email', order=1, hint='Use your work email'),
]
alchemy = ExcelAlchemy(ImporterConfig(Importer, locale='en'))
template = alchemy.download_template_artifact(filename='people-template.xlsx')
Why ExcelAlchemy
- Pydantic v2-based schema extraction and validation
- locale-aware workbook comments and result workbooks
- pluggable storage instead of a hard-coded backend
openpyxl-based runtime path without pandas- contract tests, Ruff, and Pyright in the development workflow
Learn More
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