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

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

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

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