Merge pull request #2 from dense-analysis/codex/write-blog-post-about-dense-python-template

Add blog post announcing dense-python template

Author: w0rp

content/blog/post/2025-07-01-dense-python-template.md

@@ -0,0 +1,67 @@
+---
+type: post
+title: Introducing dense-python
+author: Andrew Wray
+subtitle: A convenient template for new Python projects
+date: 2025-07-06
+summary: The dense-python repository provides a reusable template for starting Python projects quickly.
+tags: ["python", "template"]
+---
+
+Dense Analysis has released
+[dense-python](https://github.com/dense-analysis/dense-python), a template
+repository designed to help developers spin up new Python projects with minimal
+setup. The repository collects a set of best practices used across Dense
+Analysis projects and packages them into a starting point you can clone and
+modify.
+
+Available on [GitHub](https://github.com/dense-analysis/dense-python), the
+template comes preconfigured with modern tooling for formatting, linting, static
+type checks, and continuous integration. By cloning the repository and
+customizing it for your work, you can skip much of the boilerplate configuration
+typically required when starting from scratch.
+
+### Distroless Python containers
+
+For containerized deployments, `dense-python` includes a reproducible build
+pipeline that produces distroless images. Distroless containers ship only the
+Python runtime and your project code, resulting in smaller and more secure
+images than traditional distributions. The provided `Dockerfile` demonstrates
+how to compile wheels with the `uv` build tool and copy them into the final
+distroless image. Read more about the advantages in [this article on distroless
+Python images](https://alex-moss.medium.com/creating-an-up-to-date-python-distroless-container-image-e3da728d7a80).
+
+### Testing with Network Isolation By Default
+
+The template configures **pytest** so that tests run with socket access disabled
+by default. This makes it easy to catch accidental network calls in unit tests.
+Strict marker checking is also enabled, ensuring that every custom marker is
+declared in your configuration. You can decorate tests with
+`@pytest.mark.allow_network` to enable network access for them explictly.
+Together, these settings help keep tests fast and deterministic.
+
+### Pyright Type Checking
+
+Static type checking is handled by
+[**Pyright**](https://github.com/microsoft/pyright), the engine behind
+[Pylance](https://marketplace.visualstudio.com/items?itemName=ms-python.vscode-pylance)
+in VSCode and also used by [Cursor](https://cursor.com). It offers quick
+feedback on type annotations without slowing down development. A ready-to-use
+`pyproject.toml` configuration is included so that type errors are caught early.
+As ever Dense Analysis recommends using [the
+DAFT](https://denseanalysis.org/projects/daft/) for programming over proprietary
+editors, but they may also be easily configured.
+
+### Package Builds with uv
+
+Instead of naked `pip`, `dense-python` relies on the lightning-fast
+[uv](https://github.com/astral-sh/uv) tool to create virtual environments and
+build distribution packages. This speeds up the packaging process and ensures
+consistent builds across platforms.
+
+### Open for Contributions!
+
+`dense-python` is FOSS and welcomes contributions. If you find a useful
+improvement or fix, open a pull request or start a discussion on the project
+page. We hope this template saves you time on setup so you can focus on writing
+code.