بنقرة واحدة
python-venv
Manage Python virtual environments and dependencies. Use when setting up projects or installing packages.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Manage Python virtual environments and dependencies. Use when setting up projects or installing packages.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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World-class data science skill for statistical modeling, experimentation, causal inference, and advanced analytics. Expertise in Python (NumPy, Pandas, Scikit-learn), R, SQL, statistical methods, A/B testing, time series, and business intelligence. Includes experiment design, feature engineering, model evaluation, and stakeholder communication. Use when designing experiments, building predictive models, performing causal analysis, or driving data-driven decisions.
Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.
Comprehensive fullstack development skill for building complete web applications with React, Next.js, Node.js, GraphQL, and PostgreSQL. Includes project scaffolding, code quality analysis, architecture patterns, and complete tech stack guidance. Use when building new projects, analyzing code quality, implementing design patterns, or setting up development workflows.
World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.
World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.
| name | python-venv |
| description | Manage Python virtual environments and dependencies. Use when setting up projects or installing packages. |
ALWAYS use .venv/bin/python and .venv/bin/pip - NEVER bare python or pip
This ensures you're using the project's virtual environment, not the system Python.
# Create venv
python3 -m venv .venv
# Activate (for interactive use)
source .venv/bin/activate
# Or use directly without activating
.venv/bin/python --version
# From requirements.txt
.venv/bin/pip install -r requirements.txt
# From pyproject.toml (if using pip)
.venv/bin/pip install -e .
# From pyproject.toml (if using poetry)
poetry install
# Single package
.venv/bin/pip install package-name
# Upgrade pip itself
.venv/bin/pip install --upgrade pip
# Upgrade a package
.venv/bin/pip install --upgrade package-name
# Freeze current state
.venv/bin/pip freeze > requirements.txt
requests>=2.28.0
pandas==2.0.0
pytest>=7.0.0
[project]
dependencies = [
"requests>=2.28.0",
"pandas==2.0.0",
]
[project.optional-dependencies]
dev = ["pytest>=7.0.0", "ruff"]
.venv/bin/pythonsudo with pip in venvpip install --force-reinstall.venv/ and recreate