Update quickstart instructions

README.md

@@ -16,6 +16,69 @@ This template equips you with the essentials for creating, testing, and packagin
 
 You have the freedom to structure your `src/` and `tests/` directories according to your preferences. Alternatively, you can draw inspiration from the structure used in the [MLOps Python Package](https://github.com/fmind/mlops-python-package) project for a ready-made implementation.
 
+## Quick Start
+
+1. **Generate your project:**
+
+```bash
+# With uv:
+uv tool install cookiecutter
+# With pip:
+# pip install cookiecutter
+cookiecutter gh:irod973/python-project-template
+```
+
+You'll be prompted for the following variables.
+
+- `user`: Your GitHub username.
+- `name`: The name of your project.
+- `repository`: The name of your GitHub repository.
+- `package`: The name of your Python package.
+- `license`: The license for your project (Note: use "NA" until we define a standard licence or omit entirely)
+- `version`: The initial version of your project.
+- `description`: A brief description of your project.
+- `python_version`: The Python version to use (e.g., 3.12).
+- `include_fastapi`: Whether to include a sample FastAPI application.
+- `include_metaflow`: Whether to include a sample Metaflow application.
+- `include_torchvision`: Whether to include a sample Torchvision application.
+- `include_package`: Whether to include a sample application for publishing a Python package.
+
+2. **Initialize a git repository:**
+
+```bash
+cd {{ cookiecutter.repository }}
+git init
+# Create remote repo
+gh repo create
+# Then make first push:
+git checkout -b feature/initial-setup
+git add .
+git commit -m "Initial commit"
+git push -u origin feature/initial-setup
+```
+
+3. **Explore the generated project:**
+
+- `src/{{cookiecutter.package}}`: Your Python package source code.
+- `tests/`: Unit tests for your package.
+- `tasks/`: `just` commands for automation.
+- `docker/Dockerfile.python`: Configuration for building your Docker image.
+- `docker-compose.yml`: Orchestration file for running your project.
+
+4. **Start developing!**
+
+Use the provided `just` commands to manage your development workflow:
+
+- `uv run just check`: Run code quality, type, security, and test checks.
+- `uv run just clean`: Clean up generated files.
+- `uv run just commit`: Commit changes to your repository.
+- `uv run just doc`: Generate API documentation.
+- `uv run just docker`: Build and run your Docker image.
+- `uv run just format`: Format your code with Ruff.
+- `uv run just install`: Install dependencies, pre-commit hooks, and GitHub rulesets.
+- `uv run just package`: Build your Python package.
+- `uv run just project`: Run the project in the CLI.
+
 ## Applications
 
 This template includes a few optional application skeletons. See the nested README for details.
@@ -88,68 +151,6 @@ The sync tool will:
 - A commit is automatically created with all synced changes
 - Use `--dry-run` to preview changes before committing
 
-## Quick Start
-
-1. **Generate your project:**
-
-```bash
-# With uv:
-uv tool install cookiecutter
-# With pip:
-# pip install cookiecutter
-cookiecutter gh:irod973/python-project-template
-```
-
-You'll be prompted for the following variables.
-
-- `user`: Your GitHub username.
-- `name`: The name of your project.
-- `repository`: The name of your GitHub repository.
-- `package`: The name of your Python package.
-- `license`: The license for your project (Note: use "NA" until we define a standard licence or omit entirely)
-- `version`: The initial version of your project.
-- `description`: A brief description of your project.
-- `python_version`: The Python version to use (e.g., 3.12).
-- `include_fastapi`: Whether to include a sample FastAPI application.
-- `include_metaflow`: Whether to include a sample Metaflow application.
-- `include_torchvision`: Whether to include a sample Torchvision application.
-- `include_package`: Whether to include a sample application for publishing a Python package.
-
-2. **Initialize a git repository:**
-
-```bash
-cd {{ cookiecutter.repository }}
-git init
-# Should also create remote repo, e.g. via Github web console
-# Then make first push e.g.
-# git add .
-# git commit -m "Initial commit"
-# git remote add origin https://github.com/irod973/{{myproject}}.git
-# git push -u origin main 
-```
-
-3. **Explore the generated project:**
-
-- `src/{{cookiecutter.package}}`: Your Python package source code.
-- `tests/`: Unit tests for your package.
-- `tasks/`: `just` commands for automation.
-- `docker/Dockerfile.python`: Configuration for building your Docker image.
-- `docker-compose.yml`: Orchestration file for running your project.
-
-4. **Start developing!**
-
-Use the provided `just` commands to manage your development workflow:
-
-- `uv run just check`: Run code quality, type, security, and test checks.
-- `uv run just clean`: Clean up generated files.
-- `uv run just commit`: Commit changes to your repository.
-- `uv run just doc`: Generate API documentation.
-- `uv run just docker`: Build and run your Docker image.
-- `uv run just format`: Format your code with Ruff.
-- `uv run just install`: Install dependencies, pre-commit hooks, and GitHub rulesets.
-- `uv run just package`: Build your Python package.
-- `uv run just project`: Run the project in the CLI.
-
 ## License
 
 The source material this is adapted from is licensed under the [MIT License](https://opensource.org/license/mit). See the [`LICENSE.txt`](https://github.com/fmind/cookiecutter-mlops-package/blob/main/LICENSE.txt) file for details.