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ExcelAlchemy

Schema-driven Python library for typed Excel import/export workflows with Pydantic and locale-aware workbooks.

ExcelAlchemy turns Pydantic models into workbook contracts:

  • generate Excel templates from code
  • validate uploaded workbooks
  • map failures back to rows and cells
  • return result workbooks and API-friendly error payloads
  • keep workbook IO pluggable through ExcelStorage

The current stable release is ExcelAlchemy 3.0. It uses ordinary Python annotations plus explicit ExcelColumn(...) metadata. Old 2.x field factories, compatibility imports, legacy config fields, and facade aliases are not current API.

GitHub Repository · Full README · Getting Started · Examples · Public API · Migration Notes

Screenshots

Template

Excel template screenshot

Import Result

Excel import result screenshot

Install

pip install ExcelAlchemy

Optional Minio-compatible storage support:

pip install "ExcelAlchemy[minio]"

Quick Example

from typing import Annotated

from pydantic import BaseModel, Field

from excelalchemy import EmailCodec, ExcelAlchemy, ExcelColumn, ImporterConfig


class EmployeeImport(BaseModel):
    name: Annotated[str, ExcelColumn(label='Name', order=1)]
    email: Annotated[
        str,
        Field(min_length=8),
        ExcelColumn(
            label='Email',
            codec=EmailCodec(),
            order=2,
            hint='Use your work email',
            example_value='alice@company.com',
        ),
    ]


alchemy = ExcelAlchemy(ImporterConfig(EmployeeImport, locale='en'))
template = alchemy.download_template_artifact(filename='employees-template.xlsx')

excel_bytes = template.as_bytes()

Import Workflow

The shortest import path is:

template -> preflight -> import -> remediation -> delivery

Minimal backend sketch:

from excelalchemy.results import ImportLifecycleEvent, build_frontend_remediation_payload


events: list[ImportLifecycleEvent] = []

preflight = alchemy.preflight_import('employees.xlsx')
if preflight.is_valid:
    result = await alchemy.import_data(
        'employees.xlsx',
        'employees-result.xlsx',
        on_event=events.append,
    )
    payload = {
        'result': result.to_api_payload(),
        'cell_errors': alchemy.cell_error_map.to_api_payload(),
        'row_errors': alchemy.row_error_map.to_api_payload(),
        'remediation': build_frontend_remediation_payload(
            result=result,
            cell_error_map=alchemy.cell_error_map,
            row_error_map=alchemy.row_error_map,
        ),
    }

Why ExcelAlchemy

  • Pydantic v2-based schema extraction and validation
  • Annotated[..., ExcelColumn(...)] declaration style
  • workbook comments and result workbooks in zh-CN, en, or ja
  • 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

Metadata

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