performance-profiling
Automatically applies when profiling Python performance. Ensures proper use of profiling tools, async profiling, benchmarking, memory analysis, and optimization strategies.
Skills matching the name, description or GitHub author.
Automatically applies when profiling Python performance. Ensures proper use of profiling tools, async profiling, benchmarking, memory analysis, and optimization strategies.
Create and refactor Python dataclass business models and mappers following clean architecture patterns with proper separation of concerns.
Guide for building full-stack web applications using Reflex, a Python framework that compiles to React frontend and FastAPI backend. Use when creating, modifying, or debugging Reflex apps - covers state managem...
Automatically applies when writing Python functions that call async operations. Ensures proper async/await pattern usage (not asyncio.run) to prevent event loop errors.
This skill should be used when creating new Python projects or managing Python dependencies. IMPORTANT - uv must ALWAYS be used for any Python-related commands in Python projects (running scripts, installing pa...
Search and fetch the latest version of a Go or Python package.
Expert guidance on using Pants build system for Python projects, focusing on optimal caching, test execution, and target-based workflows.
Automatically applies when managing Python dependencies. Ensures proper use of uv/Poetry, lock files, version constraints, conflict resolution, and dependency security.
Expert in Apache Ray distributed computing. Use when converting Python code to Ray workloads, debugging Ray applications, optimizing Ray performance, or working with Ray Core, Ray Data, Ray Train, Ray Serve, or...
Fast in-process analytical database for SQL queries on DataFrames, CSV, Parquet, JSON files, and more. Use when user wants to perform SQL analytics on data files or Python DataFrames (pandas, Polars), run compl...
Comprehensive Python data engineering patterns for AWS Data Lake, including PySpark, Pandas, Apache Airflow, AWS Glue, ETL pipelines, data quality, schema management, performance optimization, FastAPI services,...
Write tests for Python code with three tiers (Unit/Integration/E2E). Use when testing Python or writing Python tests.
Write Python code that's tested and type-safe. Use when coding Python or implementing features.
Review Python code strictly, reject mocking. Use when reviewing Python code or checking if code is ready.
Quick reference for DQX Python code standards
Apply Sun Lab Python coding conventions when writing, reviewing, or refactoring code. Covers docstrings, type annotations, naming conventions, error handling, Numba functions, and formatting standards.
Automatically applies when writing Python code to enforce comprehensive type hints. Ensures mypy compatibility, proper generic types, and type safety best practices.
Review ADRs to check they follow testing principles. Use when reviewing ADRs or architecture decisions.
Create Hathor blockchain blueprints (nano contracts) - Python 3.11 smart contracts. Use when building, debugging, or modifying Hathor nano contracts, or when user mentions blueprints, nano contracts, or Hathor...
Create Lunar policy plugins that enforce engineering standards. Use when building policies (Python scripts) that evaluate Component JSON data and produce pass/fail checks. Covers the lunar_policy SDK (Check cla...
Write ADRs for Python architecture decisions. Use when making architecture decisions or writing ADRs.
Master Temporal workflow orchestration using the Python SDK. Use PROACTIVELY for workflow design, microservice orchestration, long-running processes, saga pattern implementation, distributed transactions, or an...
A skill for using Databricks SQL (SQL Warehouse) via SDK. Supports both Python (databricks-sql-connector) and Node.js (@databricks/sql). Use when: - Connecting to SQL Warehouse from Databricks Apps to execute...
現在の環境で適切なPythonコマンドを判別し、スクリプトを実行します。「Pythonコマンドを確認」「どのpythonを使う」「Python実行方法」といった依頼や、他のスキルからPythonスクリプトを実行する前に使用してください。
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.