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Python Tdd With Uv

Community
spencerpauly
python-tdd-with-uv

Test-driven development in Python using uv as the package manager. Covers the red-green-refactor cycle, vertical slicing, and uv project setup.

Overview

Publisherspencerpauly
Repositoryawesome-cursor-skills
Skill namepython-tdd-with-uv
Stars
848
Forks
169
Bundled files
Instructions only
LicenseCC0-1.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by spencerpauly on GitHub. Read the source before you install it.

Installation

Install the Python Tdd With Uv AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/spencerpauly/awesome-cursor-skills/tree/main/resources/python-tdd-with-uv
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/spencerpauly/awesome-cursor-skills.git /tmp/awesome-cursor-skills
mkdir -p .claude/skills
cp -r /tmp/awesome-cursor-skills/resources/python-tdd-with-uv .claude/skills/python-tdd-with-uv
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Python Tdd With Uv in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Python Tdd With Uv on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Python Tdd With Uv is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Python TDD with uv

Write Python code test-first using uv for fast dependency and environment management.

Setting Up the Project

  1. Check if uv is installed: uv --version
  2. If the project doesn't have a pyproject.toml, initialize:
    bash
    uv init
  3. Add pytest as a dev dependency:
    bash
    uv add --dev pytest pytest-cov
  4. Confirm the test runner works:
    bash
    uv run pytest --co

TDD Workflow — Vertical Slicing

Work in small cycles. Never write more than one failing test at a time.

Planning Phase

Before writing code, answer:

  1. What interface changes are needed? (functions, classes, APIs)
  2. Which behaviors matter most? (prioritize critical paths)
  3. Can we design for testability? (inject dependencies, avoid global state)

The Cycle

RED   → Write ONE failing test for the next behavior
GREEN → Write the MINIMUM code to make it pass
REFACTOR → Clean up without changing behavior
REPEAT

Rules:

  • Never write implementation before a failing test exists
  • Never write more than one failing test at a time
  • Run uv run pytest after every change
  • Tests must assert observable behavior, not implementation details
  • Mocks should only be used at system boundaries (I/O, network, clock)

Test File Structure

python
# tests/test_<module>.py

class TestFeatureName:
    """Group related behaviors."""

    def test_does_expected_thing_when_given_input(self):
        result = function_under_test(input_value)
        assert result == expected

    def test_raises_when_given_invalid_input(self):
        with pytest.raises(ValueError):
            function_under_test(bad_input)

Running Tests

bash
uv run pytest                      # all tests
uv run pytest tests/test_foo.py    # single file
uv run pytest -k "test_name"       # by name pattern
uv run pytest --cov=src            # with coverage
uv run pytest -x                   # stop on first failure

uv Essentials

bash
uv add <package>           # add dependency
uv add --dev <package>     # add dev dependency
uv remove <package>        # remove dependency
uv sync                    # sync environment from lockfile
uv run <command>           # run in managed environment
uv lock                    # regenerate lockfile
  • Always use uv run to execute commands — never activate venvs manually
  • Commit both pyproject.toml and uv.lock

References

Frequently asked questions

What does the Python Tdd With Uv AI skill do?

Test-driven development in Python using uv as the package manager. Covers the red-green-refactor cycle, vertical slicing, and uv project setup.

Why use Python Tdd With Uv on TypingMind?

Because you install it once and use it with any model. Python Tdd With Uv is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Python Tdd With Uv in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/spencerpauly/awesome-cursor-skills/tree/main/resources/python-tdd-with-uv. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Python Tdd With Uv?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Python Tdd With Uv?

As many as you like. As long as a model supports skills, you can use Python Tdd With Uv with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Python Tdd With Uv AI skill free?

Yes. It is published on GitHub by spencerpauly under the CC0-1.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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