Excel Data Import

通过 YAML 配置文件驱动 Python 脚本，把 Excel/CSV 数据导入、合并、转换到目标表格：支持单文件、目录批量与多源合并，提供字段映射与转换、内置校验器、增量更新、合并单元格表头自动检测和 CSV 编码识别，运行后生成目标表格与 JSON 报告。

aqbjqtd

热度 64.94

最近更新 2026-05-11 17:33:02

分类：效率依赖：代码执行 / 读写文件应用场景：数据处理 / 文件转换 / 工作流 / 模板 ...

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add excel-data-import

Metadata

name: excel-data-import
description: Import, merge, and transform data from Excel (.xlsx/.csv) files using YAML-driven configuration. Use when the user asks to: (1) import data from Excel/CSV into a template, (2) batch-process multiple files in a directory, (3) merge/consolidate data from multiple sources, (4) map and transform columns with validation rules, (5) do incremental data updates on existing spreadsheets. 当用户要求导入Excel、CSV导入、表格数据导入、Excel数据合并、批量处理Excel、字段映射、数据校验、表头自动检测、增量更新Excel、多sheet合并时使用此技能。 Supports Chinese field names, multi-layer merged cell headers, auto header detection, CSV (auto-encoding), custom validators, and multi-source imports.

Excel Data Import

Configuration-driven data import from Excel and CSV files with field mapping, validation, and batch processing.

Prerequisites

Python 3.8+
Required: pip3 install openpyxl pyyaml
Optional: pip3 install python-calamine (for .xls legacy format)

Quick Start

# import_config.yaml
task_name: "人员信息导入"
source:
  file_path: "data/source.xlsx"
  sheet_name: "Sheet1"
  header_row: 1
  key_field: "身份证号"
target:
  file_path: "output/result.xlsx"
  sheet_name: "人员信息"
  header_row: 2
  data_start_row: 3
field_mappings:
  - source: "姓名"
    target: "员工姓名"
    required: true
  - source: "身份证号"
    target: "身份证号码"
    required: true
    validate: "id_card"
  - source: "部门"
    target: "所属部门"
    default: "待分配"
error_handling:
  backup: true

python3 scripts/excel_import.py import_config.yaml
python3 scripts/excel_import.py import_config.yaml --dry-run   # preview only

Import Modes

Mode	Source Config	Use Case
Single file	`source.file_path`	One-to-one import
Directory batch	`source.type: "directory"`	Process all files in a folder
Multi-source	`sources: [...]`	Merge from multiple files
CSV	`.csv` file_path	Auto-encoding detection (UTF-8/GBK/GB2312)
Legacy .xls	`.xls` file_path	Requires `python-calamine`
Auto header	`header_row: "auto"`	Detect header in complex sheets

For full parameter docs, see data-mapping-guide.md.

Key Features

Incremental update: Match by key_field, update existing or append new rows
Multi-layer merged headers: Auto-detect and expand merged cell values
Validation rollback: Failed rows are skipped entirely (no partial writes)
Source deduplication: Duplicate keys across files are merged
Auto-create target: Template generated from field_mappings if missing

Built-in Transforms & Validators

Transforms: strip, upper, lower, title, int, float, date

Validators: required, not_empty, id_card, phone, email, numeric, range, regex, length

For advanced usage, see advanced-features.md.

CLI Options

Option	Description
`--dry-run`	Preview mode, no file writes
`--verbose`	Detailed per-record output
`--no-backup`	Skip target file backup

Reference Documents

Data Mapping Guide: data-mapping-guide.md — field mapping, transforms, validators
Advanced Features: advanced-features.md — multi-source, batch, auto-header
Auto Header Detection: auto_header_detection.md — complex header detection
Quickstart: quickstart.md — step-by-step tutorial
Workflow: workflow.md — detailed execution flow
Best Practices: best_practices.md — usage recommendations
Error Handling: error-handling.md — error codes and recovery
Troubleshooting: troubleshooting.md — common issues

Workflow

Read user's import requirements and source/target file info
Create or adjust YAML config file
Run python3 scripts/excel_import.py <config.yaml> with --dry-run first
Review output, fix issues, then run without --dry-run
Check the JSON report alongside the output file