feat(upgrade): upgrade to v3 of the mlops-python-package, replacing p…

.github/FUNDING.yml

@@ -1,4 +1,3 @@
 # These are supported funding model platforms
 
-# github: ["MLOps-Courses"]
 custom: ["https://donate.stripe.com/4gw8xT9oVbCc98s7ss"]

.github/workflows/tests.yml

@@ -2,7 +2,7 @@ name: Tests
 on:
   pull_request:
     branches:
-      - main
+      - '*'
 permissions:
   contents: read
   id-token: write
@@ -15,9 +15,13 @@ jobs:
     steps:
     - name: Checkout
       uses: actions/checkout@v4
-    - name: Install
-      run: |
-        pipx install poetry
-        poetry install
+    - name: Install uv
+      uses: astral-sh/setup-uv@v4
+      with:
+        enable-cache: true
+    - name: Setup Python
+      uses: actions/setup-python@v5
+      with:
+        python-version-file: .python-version
     - name: Test
-      run: poetry run pytest tests/
+      run: uv run invoke test

.gitignore

@@ -4,9 +4,6 @@
 /.idea/
 /.vscode/
 
-# Poetry
-poetry.lock
-
 # Python
 .venv/
 *.py[cod]

.pre-commit-config.yaml

@@ -2,18 +2,14 @@
 # https://pre-commit.com/hooks.html
 
 default_language_version:
-    python: python3
+  python: python3.12
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.6.0
+    rev: v5.0.0
     hooks:
       - id: check-added-large-files
       - id: check-case-conflict
       - id: check-merge-conflict
       - id: end-of-file-fixer
       - id: mixed-line-ending
       - id: trailing-whitespace
-  - repo: https://github.com/python-poetry/poetry
-    rev: 1.8.3
-    hooks:
-    - id: poetry-check

CHANGELOG.md

@@ -0,0 +1,17 @@
+## v3.0.0 (2024-12-15)
+
+### Fix
+
+- **project**: switch from mlflow to uv
+
+### Refactor
+
+- **cicd**: fix ci/cd bug
+
+## v2.0.0 (2024-12-15)
+
+### Feat
+
+- **upgrade**: upgrade to v3 of the mlops-python-package, replacing poetry with uv
+
+## v1.0.0 (2024-07-28)

LICENSE.txt

@@ -1,5 +1,3 @@
-Copyright 2024 Médéric HURIER (Fmind)
-
 Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
 
 The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

README.md

@@ -1,4 +1,4 @@
-# MLOps Package Cookiecutter
+# Cookiecutter - MLOps Package
 
 [![Release](https://img.shields.io/github/v/release/fmind/cookiecutter-mlops-package)](https://github.com/fmind/cookiecutter-mlops-package/releases)
 [![License](https://img.shields.io/github/license/fmind/cookiecutter-mlops-package)](https://github.com/fmind/cookiecutter-mlops-package/blob/main/LICENSE.txt)
@@ -10,22 +10,22 @@ The template provides a robust foundation for building, testing, packaging, and
 **Related resources**:
 - **[MLOps Coding Course (Learning)](https://mlops-coding-course.fmind.dev/)**: Learn how to create, develop, and maintain a state-of-the-art MLOps code base.
 - **[MLOps Python Package (Example)](https://github.com/fmind/mlops-python-package)**: Kickstart your MLOps initiative with a flexible, robust, and productive Python package.
+- **[LLMOps Coding Package (Example)](https://github.com/callmesora/llmops-python-package/)**: Example with best practices and tools to support your LLMOps projects.
 
 ## Philosophy
 
 This [Cookiecutter](https://cookiecutter.readthedocs.io/) is designed to be a common ground for diverse MLOps environments. Whether you're working with [Kubernetes](https://www.kubeflow.org/), [Vertex AI](https://cloud.google.com/vertex-ai), [Databricks](https://www.databricks.com/), [Azure ML](https://azure.microsoft.com/en-us/products/machine-learning), or [AWS SageMaker](https://aws.amazon.com/sagemaker/), the core principles of using Python packages and Docker images remain consistent.
 
-This template equips you with the essentials for creating, testing, and packaging your code, providing a solid base for integration into your chosen platform. To fully leverage its capabilities within a specific environment, you might need to combine it with external tools like [Airflow](https://airflow.apache.org/) for orchestration or platform-specific SDKs for deployment.
+This template equips you with the essentials for creating, testing, and packaging your AI/ML code, providing a solid base for integration into your chosen MLOps platform. To fully leverage its capabilities within a specific environment, you might need to combine it with external tools like [Airflow](https://airflow.apache.org/) for orchestration or platform-specific SDKs for deployment.
 
 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.
 
 ## Key Features
 
 * **Streamlined Project Structure:** A well-defined directory layout for source code, tests, documentation, tasks, and Docker configurations.
-* **Poetry Integration:** Effortless dependency management and packaging with [Poetry](https://python-poetry.org/).
+* **Uv Integration:** Effortless dependency management and packaging with [uv](https://docs.astral.sh/uv/).
 * **Automated Testing and Checks:** Pre-configured workflows using [Pytest](https://docs.pytest.org/), [Ruff](https://docs.astral.sh/ruff/), [Mypy](https://mypy.readthedocs.io/), [Bandit](https://bandit.readthedocs.io/), and [Coverage](https://coverage.readthedocs.io/) to ensure code quality, style, security, and type safety.
 * **Pre-commit Hooks:** Automatic code formatting and linting with [Ruff](https://docs.astral.sh/ruff/) and other pre-commit hooks to maintain consistency.
-* **MLflow Project Ready:** An MLproject file for executing jobs using [MLflow](https://mlflow.org/), allowing for easy experimentation and tracking.
 * **Dockerized Deployment:** Dockerfile and docker-compose.yml for building and running the package within a containerized environment ([Docker](https://www.docker.com/)).
 * **Invoke Task Automation:** [PyInvoke](https://www.pyinvoke.org/) tasks to simplify development workflows such as cleaning, installing, formatting, checking, building, documenting, and running MLflow projects.
 * **Comprehensive Documentation:** [pdoc](https://pdoc.dev/) generates API documentation, and Markdown files provide clear usage instructions.
@@ -51,7 +51,7 @@ You'll be prompted for the following variables:
 - `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).
-- `mlflow_version`: The MLflow version to use (e.g., 2.14.3).
+- `mlflow_version`: The MLflow version to use (e.g., 2.19.0).
 
 2. **Initialize a git repository:**
 
@@ -73,7 +73,6 @@ git init
 - `tasks/`: PyInvoke tasks for automation.
 - `Dockerfile`: Configuration for building your Docker image.
 - `docker-compose.yml`: Orchestration file for running MLflow and your project.
-- `MLproject`: MLflow project definition.
 
 5. **Start developing!**
 
@@ -97,7 +96,7 @@ After installing dependencies and setting up MLflow:
 invoke projects
 ```
 
-This will execute the "main" job defined in your [`MLproject`](https://github.com/fmind/cookiecutter-mlops-package/blob/main/%7B%7Bcookiecutter.repository%7D%7D/MLproject) file. You can specify different jobs using the `-P job=your_job_name` flag.
+This will execute the job with the configuration file in your `confs` folder.
 
 ### Building and Running Your Docker Image
 

cookiecutter-mlops-package.code-workspace

@@ -13,7 +13,8 @@
     },
     "extensions": {
         "recommendations": [
-            "ms-python.python",
+			"dchanco.vsc-invoke",
+            "ms-python.python"
         ]
     }
 }

cookiecutter.json

@@ -7,7 +7,7 @@
     "version": "0.1.0",
     "description": "TODO",
     "python_version": "3.12",
-    "mlflow_version": "2.14.3",
+    "mlflow_version": "2.19.0",
     "__prompts__": {
         "user": "GitHub User",
         "name": "Project Name",

pyproject.toml

@@ -1,45 +1,44 @@
-# https://python-poetry.org/docs/pyproject/
+# https://docs.astral.sh/uv/reference/settings/
+# https://packaging.python.org/en/latest/guides/writing-pyproject-toml/
 
-# PACKAGE
+# PROJECT
 
-[tool.poetry]
+[project]
 name = "cookiecutter-mlops-package"
-version = "1.0.0"
-description = "Build and deploy Python packages and Docker images for MLOps tasks."
-repository = "https://github.com/fmind/cookiecutter-mlops-package"
-authors = ["Médéric HURIER <[email protected]>"]
+version = "3.0.0"
+description = "Build and deploy Python packages and Docker images for MLOps projects."
+authors = [{ name = "Médéric HURIER", email = "[email protected]" }]
 readme = "README.md"
-license = "MIT"
-package-mode = false
+requires-python = ">=3.12"
+license = { file = "LICENSE.txt" }
 
 # DEPENDENCIES
 
-[tool.poetry.dependencies]
-python = "^3.12"
+[dependency-groups]
+dev = [
+    "commitizen>=4.1.0",
+    "invoke>=2.2.0",
+    "pre-commit>=4.0.1",
+    "pytest>=8.3.4",
+    "pytest-cookies>=0.7.0",
+    "pytest-shell-utilities>=1.9.7",
+]
 
-[tool.poetry.group.dev.dependencies]
-commitizen = "^3.28.0"
-invoke = "^2.2.0"
-pre-commit = "^3.7.1"
-pytest = "^8.3.2"
-pytest-cookies = "^0.7.0"
-pytest-shell-utilities = "^1.9.0"
+# TOOLS
 
-# CONFIGURATIONS
+[tool.uv]
+package = false
+
+[tool.bandit]
+targets = ["src"]
 
 [tool.commitizen]
 name = "cz_conventional_commits"
 tag_format = "v$version"
 version_scheme = "pep440"
-version_provider = "poetry"
+version_provider = "pep621"
 update_changelog_on_bump = true
 
 [tool.pytest.ini_options]
 log_cli = true
 log_cli_level = "INFO"
-
-# SYSTEMS
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"

tasks.py

@@ -7,19 +7,30 @@
 
 # %% TASKS
 
+
+@task
+def clean(ctx: Context) -> None:
+    """Clean the project."""
+    ctx.run("rm -rf .venv/")
+    ctx.run("rm -rf .mypy_cache/")
+    ctx.run("rm -rf .pytest_cache/")
+    ctx.run("find . -type f -name '*.py[co]' -delete")
+    ctx.run(r"find . -type d -name __pycache__ -exec rm -r {} \+")
+
+
 @task
 def install(ctx: Context) -> None:
     """Install the project."""
-    ctx.run("poetry install")
+    ctx.run("uv sync --all-groups")
 
 
 @task
 def hooks(ctx: Context) -> None:
     """Setup the project hooks."""
-    ctx.run("poetry run pre-commit install")
+    ctx.run("uv run pre-commit install")
 
 
 @task
 def test(ctx: Context) -> None:
     """Run the project unit tests."""
-    ctx.run("poetry run pytest tests/")
+    ctx.run("uv run pytest tests/")

tests/test_cookiecutter.py

@@ -9,14 +9,15 @@
 
 COMMANDS = [
     "git init",
-    "invoke cleans.reset",
-    "invoke installs",
-    "invoke formats",
-    "invoke checks",
-    "invoke docs",
-    "invoke projects",
-    "invoke packages",
-    "invoke containers",
+    "uv run invoke cleans.reset",
+    "uv run invoke installs",
+    "uv run invoke formats",
+    "uv run invoke checks",
+    "uv run invoke docs",
+    "uv run invoke projects",
+    "uv run invoke packages",
+    "uv run invoke containers",
+    "uv run invoke mlflow.doctor",
 ]
 
 # %% TESTS
@@ -26,13 +27,13 @@ def test_project_generation(cookies: Cookies) -> None:
     """Test the generation of the project."""
     # given
     context  = {
-        "user": "test",
+        "user": "tester",
         "name": "MLOps 123",
         "license": "apache-2",
         "version": "1.0.0",
-        "description": "DONE",
+        "description": "A test project.",
         "python_version": "3.12",
-        "mlflow_version": "2.14.3",
+        "mlflow_version": "2.19.0",
     }
     repository = context['name'].lower().replace(' ', '-')
     package = repository.replace('-', '_')