How does this skill improve query speed?

It analyzes query structures to suggest efficient joins, optimized WHERE clauses, and appropriate database indexes to minimize table scan times.

Does it support Redis caching implementation?

Yes, it provides boilerplate and implementation patterns for Frappe's native caching mechanisms to store expensive calculations and reduce database overhead.

Can it help with ERPNext performance issues?

Yes, it is fully compatible with ERPNext and provides optimization patterns based on core modules like Stock Ledger and Item Details.

How does it handle N+1 query problems?

The skill identifies iterative database calls and suggests bulk update or fetch patterns that consolidate multiple requests into single, efficient database operations.

Frappe Performance Optimizer

Name: Frappe Performance Optimizer
Author: Venkateshvenki404224

byVenkateshvenki404224

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数据库管理

Optimizes Frappe Framework applications by generating efficient database queries, implementing caching strategies, and managing database indexes.

关于

This skill empowers developers to resolve performance bottlenecks in Frappe and ERPNext applications by automating the creation of high-performance code patterns. It provides specialized guidance for refactoring slow SQL queries, implementing Redis-based caching for expensive computations, and applying strategic database indexing to accelerate data retrieval. By identifying and eliminating common pitfalls like N+1 query issues and inefficient bulk updates, this skill ensures that Frappe-based systems remain scalable and responsive even under heavy data loads.

主要功能

Redis-based caching implementation
Efficient bulk database operations
Strategic database indexing guidance
2 GitHub stars
Query optimization and SQL refactoring
N+1 query detection and elimination

使用场景

Speeding up slow-loading reports and dashboards
Optimizing high-volume data imports and bulk record updates
Reducing server load through intelligent data caching

关于

主要功能

Redis-based caching implementation
Efficient bulk database operations
Strategic database indexing guidance
2 GitHub stars
Query optimization and SQL refactoring
N+1 query detection and elimination

使用场景

Speeding up slow-loading reports and dashboards
Optimizing high-volume data imports and bulk record updates
Reducing server load through intelligent data caching