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skills/benchflow-ai/skillsbench/tasks-setup-fuzzing-py-environment-skills-setup-env

tasks-setup-fuzzing-py-environment-skills-setup-env

1
benchflow-ai/skillsbench·Developer Tools·Audit pending·Snapshot 5a03a9d45334

Summary

This source did not publish a separate summary. Review SKILL.md before using the skill.

SKILL.md

Skill: Use uv to manage Python environments

Scope

  1. Create a virtual environment
  2. Install dependencies
  3. Run Python scripts/commands

Assume uv is already available on PATH.


Workflow selection

  • If pyproject.toml exists: use project workflow (uv sync, uv run)
  • Else if requirements.txt exists: use pip workflow (uv venv, uv pip install -r ..., .venv/bin/python ...)
  • Else: stop with an error ("No pyproject.toml or requirements.txt found.")

Project workflow (pyproject.toml)

Create venv + install dependencies

From the repo root (where pyproject.toml is):

  • uv sync

Notes:

  • uv maintains a persistent project environment at .venv and installs deps there.

Run scripts / commands (preferred)

Always run within the project environment:

  • uv run -- python <script.py> [args...]
  • uv run -- python -m <module> [args...]

Notes:

  • uv run executes inside the project environment and ensures it is up-to-date.

Pip workflow (requirements.txt)

Create venv

From the repo root:

  • uv venv # creates .venv by default

Install dependencies

  • uv pip install -r requirements.txt

Run scripts / commands

Run using the venv interpreter directly (no activation required):

  • .venv/bin/python <script.py> [args...]
  • .venv/bin/python -m <module> [args...]
  • (uv will also automatically find and use the default .venv in subsequent invocations when you use uv pip ... commands.)


    Minimal sanity checks (optional)

    • test -x .venv/bin/python
    • uv pip list (verify packages installed)

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