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Found 43 Skills
Advanced Python unit testing framework for customer support tech enablement, covering FastAPI, SQLAlchemy, PostgreSQL, async operations, mocking, fixtures, parametrization, coverage, and comprehensive testing strategies for backend support systems
Configure LangChain local development workflow with hot reload and testing. Use when setting up development environment, configuring test fixtures, or establishing a rapid iteration workflow for LangChain apps. Trigger with phrases like "langchain dev setup", "langchain local development", "langchain testing", "langchain development workflow".
Extract raw price dataframe for a test case
Sets up Python development environment using UV for fast dependency management. Configures virtual environment, dependencies, testing (pytest), linting/formatting (ruff), and type checking (mypy). ALWAYS use UV - NEVER use pip directly. Use when starting work on Python projects, after cloning Python repositories, setting up CI/CD for Python, or troubleshooting Python environment issues.
Pytest testing patterns for Python. Trigger: When writing Python tests - fixtures, mocking, markers.
Python development guidance with code quality standards, error handling, testing practices, and environment management. Use when writing, reviewing, or modifying Python code (.py files) or Jupyter notebooks (.ipynb files).
Work with the Inpoxia repository's local tools and workflows for CLI usage, GraphMail library changes, and quality checks. Use when tasks involve running or updating `inpoxia` commands, modifying files under `src/inpoxia/**`, validating behavior with `pytest`, or enforcing style/type checks with `ruff` and `pyright`.
Write Python code following best practices. Use when developing Python applications. Covers type hints, async, and modern tooling.
Write pytest tests with fixtures, parametrization, mocking, async testing, and modern patterns. Use when creating or updating Python test files. Not for unittest — use standard library patterns instead.
Эксперт Python разработки. Используй для Python best practices, async, typing и ecosystem.
Automatically diagnose and fix CI failures in the current PR. Retrieves failed logs from GitHub Actions, categorizes the failure (lint, format, type-check, test), applies targeted fixes, verifies locally, and commits/pushes. Use when CI fails after push.
Python development with ruff, mypy, pytest - TDD and type safety