Prompt to Prompt: Python Packaging Taste
Prompt to Prompt: Python Packaging Taste is a verified PROMPT blueprint on Promptally in System & Base Contexts optimized for leading AI models. Curated Coding prompt from awesome-prompts library split. Available to explore, customize with pre-filled variables, and copy with zero authentication required.
Created by @promptallyTechnical Specifications
| Specification | Value |
|---|---|
| Artifact type | PROMPT (System & Base Contexts) |
| Compatible engines | Universal / Model Agnostic |
| Input variables | None (pre-filled) |
| Approximate tokens | 448 |
| Source file | prompt-prompt-python-packaging-taste.txt |
| Access tier | Free public (MIT) |
Pre-Filled Template
# Python Packaging taste - Use `pyproject.toml` as the single source of truth and drop `setup.py` for new packages. Confidence: 0.95 - Prefer the `src/` layout so tests never accidentally import an unpackaged tree. Confidence: 0.90 - Use uv for installs, lockfiles and virtualenvs instead of pip plus venv by hand. Confidence: 0.85 - Build with hatchling (or another PEP 517 backend) and never commit built wheels to git. Confidence: 0.90 - Pin the minimum Python version explicitly and test the oldest supported version in CI. Confidence: 0.90 - Declare dependencies with lower bounds you actually need; avoid open-ended upper pins unless forced. Confidence: 0.80 - Keep optional extras (`[dev]`, `[docs]`) for tooling that end users should not install. Confidence: 0.85 - Format with Ruff format and lint with Ruff; drop Black plus flake8 for new projects. Confidence: 0.85 - Type-check with pyright or basedpyright in strict mode on the public API. Confidence: 0.80 - Test with pytest and keep tests outside `src/` under `tests/`. Confidence: 0.90 - Use trusted publishing from GitHub Actions to PyPI instead of long-lived API tokens. Confidence: 0.90 - Version with dynamic versioning from git tags (hatch-vcs or setuptools-scm). Confidence: 0.75 - Ship a short README with install, a minimal example and a link to docs; keep the long story in docs/. Confidence: 0.90 - Include `py.typed` when you publish typed packages so consumers get inline types. Confidence: 0.85 - Run `twine check` (or the uv equivalent) on built artifacts before every release. Confidence: 0.80 - Prefer `python -m package` entry points over fragile console-script wrappers when debugging. Confidence: 0.70 - Keep `__all__` and public modules intentional; mark internals with a leading underscore. Confidence: 0.80
How to use this prompt
- Review the pre-filled example and source files above.
- Copy the template or download
prompt-prompt-python-packaging-taste.txt, then use it in your model, IDE, or workflow tool. - Compare your result with the sample output when one is provided.
Frequently Asked Questions
How do I use Prompt to Prompt: Python Packaging Taste?
Open the prompt on Promptally, review the pre-filled example, then copy the template or download prompt-prompt-python-packaging-taste.txt and paste it into your model, IDE or workflow tool. Prompt to Prompt: Python Packaging Taste is a static blueprint with no dynamic variables. Copy it and use it as-is.
Is Prompt to Prompt: Python Packaging Taste free?
Yes. Prompt to Prompt: Python Packaging Taste is free to view, copy and download on Promptally without creating an account. It is published under the MIT license.
What variables does Prompt to Prompt: Python Packaging Taste need?
Prompt to Prompt: Python Packaging Taste is a static blueprint with no dynamic variables. Copy it and use it as-is.