Results for “pythia”

Provides Python code patterns for making HTTP requests with httpx, covering sync and async clients, authentication, streaming, timeouts, retries, and WebSocket support.

Fuzz Python code and C extensions with coverage guidance and AddressSanitizer support using a libFuzzer-based fuzzer.

Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants for clean API contracts in Python applications using Pydantic v2.

Fix PyPI package name collisions when local package name exists on PyPI

Manages Python package publishing, versioning, and distribution builds on PyPI, including dependency resolution, index configuration, and package health analysis.

Crea y gestiona entornos Python reproducibles con venv, pip, Poetry o Conda, aislando dependencias y configurando variables de entorno para evitar conflictos.

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Guides setting up and using Atheris for coverage-guided fuzzing of Python code and C extensions, including Docker setup, harness writing, and corpus management.

Performs deterministic image operations with Python Pillow: resizing, cropping, compositing, format conversion, watermarks, brightness/contrast adjustments, and web optimization.

Solves single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including constraint handling, Pareto front analysis, and benchmark problems.

Atheris is a coverage-guided Python fuzzer based on libFuzzer. Use for fuzzing pure Python code and Python C extensions.

Generates design systems and UI/UX recommendations for React Native projects, with domain-specific searches for styles, colors, typography, and best practices.

PUA Pro extensions: self-evolution notes, compaction state continuity, KPI-style summaries, flavor switching, and feedback tools.

Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.

Solve single and multi-objective optimization problems using NSGA-II/III, MOEA/D, and other evolutionary algorithms with customizable operators, constraint handling, and benchmark problems.

Install and manage Python packages using uv pip when imports fail or dependencies are missing.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Debug Python with pdb, breakpoint(), post-mortem inspection, and debugpy remote attach.

PUA Pro extensions: self-evolution notes, compaction state continuity, KPI-style summaries, flavor switching, and feedback tools.

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Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Python language (3.10-3.14). Covers typing, async, and modern patterns. Use when writing Python applications. USE WHEN: user mentions "python", "type hints", "dataclasses", "async/await", asks about "asyncio", "context managers", "match statement", "walrus operator", "PEP 695", "type parameter", "generic" DO NOT USE FOR: FastAPI framework - use `backend-fastapi` skill instead DO NOT USE FOR: Django framework - use Django-specific skill DO NOT USE FOR: Package management - use `python-packaging` skill DO NOT USE FOR: Linting/type checking config - use `python-quality` skill

Catches type errors before runtime using static type checking with gradual typing, strict mode, and Protocol support for Python projects.

Build, test, lint, version, and publish production-grade Python libraries to PyPI with support for multiple build backends, versioning strategies, and CI/CD.

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Installs and configures MariaDB Connector/Python, covering the 1.1 and 2.0 lines, build prerequisites, and connection settings.

Build discrete-event simulations of systems with processes, queues, resources, and time-based events using the SimPy framework in Python.

Read, write, and manipulate genomic datasets including SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences using a Pythonic interface to htslib.

Write, review, debug, test, or optimize pandas Series, DataFrame, Index, groupby, merge, reshape, dtype, missing-value, and time-series code.

Creates, reviews, debugs, and modernizes Python project structure with deterministic tooling including pyproject.toml, uv, Ruff, Pyright, and pytest.

Build production-ready AI agents with type-safe tool use, structured outputs, dependency injection, and multi-model support using PydanticAI.

Dynamic instrumentation via Frida - attach to or spawn a process, load a JS hook script, capture send() events into a lifecycle-managed run directory. Supports local, USB-attached, and remote frida-server targets.

Framework de otimização multi-objetivo. NSGA-II, NSGA-III, MOEA/D, frentes de Pareto, tratamento de restrições, benchmarks (ZDT, DTLZ), para problemas de design e otimização em engenharia.