frappe-data-migration-generator

Venkateshvenki404224's avatarfrom Venkateshvenki404224

Generate data migration scripts for Frappe. Use when migrating data from legacy systems, transforming data structures, or importing large datasets.

⭐1stars🔀1forks📁View on GitHub🕐Updated Dec 15, 2025
[Code Generation]

When & Why to Use This Skill

This Claude skill automates the creation of robust Python scripts for Frappe data migration. It streamlines the process of importing large datasets from legacy systems or CSV files into Frappe-based applications (like ERPNext) by generating production-ready code complete with data validation, error handling, and duplicate detection, significantly reducing manual coding effort and migration risks.

Use Cases

  • Migrating legacy ERP data to a new Frappe or ERPNext instance with automated script generation.
  • Bulk importing customer, item, or transaction data from large CSV/Excel files with built-in validation logic.
  • Transforming and mapping complex legacy data structures to Frappe DocTypes during system transitions or upgrades.
  • Implementing reliable ETL processes with progress tracking and error logging for high-volume data operations.
namefrappe-data-migration-generator
descriptionGenerate data migration scripts for Frappe. Use when migrating data from legacy systems, transforming data structures, or importing large datasets.

Frappe Data Migration Generator

Generate robust data migration scripts with validation, error handling, and progress tracking for importing data into Frappe.

When to Use This Skill

Claude should invoke this skill when:

  • User wants to migrate data from legacy systems
  • User needs to import large CSV/Excel files
  • User mentions data migration, ETL, or data import
  • User wants to transform data structures
  • User needs bulk data operations

Capabilities

1. CSV Import Script

Production-Ready CSV Importer:

import csv
import frappe
from frappe.utils import flt, cint, getdate

def import_customers_from_csv(file_path):
    """Import customers with validation and error handling"""
    success = []
    errors = []

    with open(file_path, 'r', encoding='utf-8-sig') as f:
        reader = csv.DictReader(f)

        for idx, row in enumerate(reader, start=2):
            try:
                # Validate required fields
                if not row.get('Customer Name'):
                    raise ValueError('Customer name required')

                # Transform data
                customer = {
                    'doctype': 'Customer',
                    'customer_name': row['Customer Name'].strip(),
                    'customer_group': row.get('Customer Group', 'Commercial'),
                    'territory': row.get('Territory', 'All Territories'),
                    'email_id': row.get('Email', '').strip(),
                    'mobile_no': row.get('Phone', '').strip(),
                    'credit_limit': flt(row.get('Credit Limit', 0))
                }

                # Check duplicate
                exists = frappe.db.exists('Customer',
                    {'customer_name': customer['customer_name']})

                if exists:
                    # Update
                    doc = frappe.get_doc('Customer', exists)
                    doc.update(customer)
                    doc.save()
                else:
                    # Insert
                    doc = frappe.get_doc(customer)
                    doc.insert()

                success.append(row['Customer Name'])

                # Commit every 100
                if len(success) % 100 == 0:
                    frappe.db.commit()
                    print(f"Processed {len(success)} records")

            except Exception as e:
                errors.append({'row': idx, 'data': row, 'error': str(e)})

    frappe.db.commit()
    return {'success': success, 'errors': errors}

References

Frappe Data Import: