@nxlv/python

@nxlv/python

@nxlv/python plugin is designed to extend the Nx features to work with Python projects based on Poetry.

Check this article for more details: https://lucasvieirasilva.medium.com/poetry-python-nx-monorepo-5750d8627024

What is @nxlv/python

🔎 An Nx Custom Plugin to generate Python projects using Poetry, Tox and a custom dependency tree plugin

Getting Started

Add to an existing Nx Workspace

Install the npm dependency

npm install @nxlv/python --save-dev

Usage

1. Update nx.json to add the property plugins with @nxlv/python value.

Example:

{
  ...
  "plugins": [
    "@nxlv/python"
  ]
  ...
}

Add a new Python Project

nx generate @nxlv/python:poetry-project myproject

NOTE: On Nx v16.8.0 or higher, the generators are prompting the user to choose how Nx will calculate where the project should be located, by using the --projectNameAndRootFormat with as-provided or derived.

The as-provided option uses the --directory option to calculate the project root, so, if the --directory option is not provided, the project root will be the same as the project name, and the project name will be the same as provided in the --name option.

Example 1: nx generate @nxlv/python:poetry-project myproject will generate the project in the myproject folder with the name myproject. Example 2: nx generate @nxlv/python:poetry-project myproject --directory=api will generate the project in the api folder with the name myproject.

The derived option uses the combination of the workspace layout, --directory option, and --name to calculate the name and root of the project.

Example 1: nx generate @nxlv/python:poetry-project myproject will generate the project in the apps/myproject folder with the name myproject. Example 2: nx generate @nxlv/python:poetry-project myproject --directory=api will generate the project in the apps/api/myproject folder with the name api-myproject.

Nx documentation reference: https://nx.dev/deprecated/as-provided-vs-derived#project-generators

Options

Option	Type	Description	Required	Default
--directory	string	A directory where the project is placed	false	N/A
--tags	string	Add tags to the project	false	N/A
--projectType	string	Project type application or library	true	application
--packageName	string	Poetry Package name	false	name property (provided in the CLI)
--moduleName	string	Project Source Module	false	name property using _ instead of -
--description	string	Project description	false	N/A
--pyprojectPythonDependency	string	Python version range used in the pyproject.toml	false	>=3.9,<3.11 (Poetry syntax)
--pyenvPythonVersion	string	.python-version pyenv file content	false	3.9.5
--publishable	boolean	Specifies if the project is publishable or not	false	true
--buildLockedVersions	boolean	Use locked versions for build dependencies	false	true
--buildBundleLocalDependencies	boolean	Bundle local dependencies	false	true
--linter	string	Linter framework (flake8, ruff or none)	false	flake8
--unitTestRunner	string	Unit Test Runner (pytest or none)	false	pytest
--unitTestHtmlReport	boolean	Enable HTML Pytest Reports	false	true
--unitTestJUnitReport	boolean	Enable JUnit Pytest Reports	false	true
--codeCoverage	boolean	Enable Code Coverage Reports	false	true
--codeCoverageHtmlReport	boolean	Enable Code Coverage HTML Reports	false	true
--codeCoverageXmlReport	boolean	Enable Code Coverage XML Reports	false	true
--codeCoverageThreshold	number	Minimum Code Coverage Threshold	false	N/A
--projectNameAndRootFormat	string	Whether to generate the project name and root directory as provided (as-provided) or generate them composing their values and taking the configured layout into account (derived).	false	as-provided

rootPyprojectDependencyGroup

When the workspace is configured to use a shared virtual environment (see below), the rootPyprojectDependencyGroup option specifies the dependency group to be used in the root pyproject.toml file, by default, the main dependency group is used.

Shared Virtual Environment

By default, the @nxlv/python manages the projects individually, so, all the projects have their one set of dependencies and virtual environments.

However, In some cases, we want to use a shared virtual environment for the entire workspace to save some installation time in your local environment and CI tool, we use this mode when the workspace contains many projects with the same dependencies and versions that don't conflict in the workspace level.

To migrate to this mode, run the following command:

npx nx generate @nxlv/python:migrate-to-shared-venv

Options:

Option	Type	Description	Required	Default
--moveDevDependencies	boolean	Specifies if migration moves the dev dependencies from the projects to the root pyproject.toml	true	true
--autoActivate	boolean	Adds the autoActivate config in the root pyproject.toml, this flag is used to auto-activate the venv when the @nxlv/python executors are called	true	true

After the migration is completed, the workspace now has a pyproject.toml in the root directory, and all the local projects are referencing the root pyproject.toml file.

The projects still have their own pyproject.toml file to manage each project's dependencies, however, the package versions cannot conflict because the root pyproject.toml file is referencing all the dependencies.

Benefits:

• Save time in the local environment and CI tool
• Reduce the size of the workspace
• Reduce the number of dependencies installed in the local environment and CI tool
• Single-version policy (recommended by Nx)
• Better VSCode integration (currently, the VSCode Python extension doesn't support multiple virtual environments in the same workspace, it needs to switch between them manually)

Cons:

• Package versions cannot conflict at the workspace level
• Local packages with the same module name don't work properly in the VSCode, because when the VSCode Python extension is activated, it uses the root pyproject.toml file to resolve the packages, so, it will use the first module found in the pyproject.toml file.

devDependenciesProject

This approach consists of moving all the dev dependencies from the projects to separate projects, this project is referenced in the root pyproject.toml and all the local projects as a dev dependency.

Benefits:

• Centralize the dev dependencies in a single project

templateDir

The templateDir option specifies a custom directory to be used as a template for the project, by default, the @nxlv/python has a built-in template folder that is used to generate the project.

However, there are some cases where the developer wants to use different files or customize the way the project is generated without the need to create a custom generator based on the @nxlv/python generator.

The files in the templateDir needs to follow the Nx generator convention by using EJS to customize the files based on the options provided by the @nxlv/python.

Template variables

All the options listed above are available as variables in the template files, for example, to use the packageName option in the template file, use <%= packageName %>.

Additional variables are available in the template files:

• offsetFromRoot: This variable contains the relative path from the project to the root directory. (e.g. for the project folder apps/my-project the offsetFromRoot value will be ../../)
• projectRoot: This variable contains the relative path of the project.
• individualPackage: This variable is a boolean that indicates if the workspace is using a shared virtual environment or not.
• dot: This variable is a string that contains a dot (.), it is used to create files that start with a dot (e.g. __dot__gitignore.template).
• template: This variable is an empty string, this variable is usually combined with the dot variable, because the Nx generator file function only generates files with extensions, however, there are some cases where the file doesn't have an extension (e.g. .gitignore), so, the template variable is used to create files without an extension (e.g. __dot__gitignore.template).

Global Default Options

By default, @nxlv/python:poetry-project generator defines linter and unit test runner with all reports enabled by default, however, those default options can be globally changed by using the following configuration in the nx.json config file.

{
  ...
  "generators": {
    "@nxlv/python:poetry-project": {
      "unitTestHtmlReport": false,
      "codeCoverageThreshold": 100,
      "devDependenciesProject": "shared-development"
    }
  }
  ...
}

The property names are the same as the options listed in the table above.

Add a new dependency to a project

nx run {project}:add --name {projectName} --local

Add an external dependency to the project

To add a new dependency to the project use the nx run {project}:add command detailed below. This ensures that any dependent projects are updated.

nx run {project}:add --name {dependencyName}

Executors

sls-deploy

The @nxlv/python:sls-deploy executor handles npx sls deploy command for serverless framework projects.

This executor uses the @nxlv/python:build artifacts to generate a requirements.txt and to be used with serverless-python-requirements plugin.

Serverless YAML example:

service: myservice

plugins:
  - serverless-python-requirements

custom:
  pythonRequirements:
    usePoetry: false

The property usePoetry must be false, so, the serverless-python-requirements uses the requirements.txt file generated by this executor, this is required when the project has more than 2 levels of local dependencies.

Example:

- root:
  - sls-app
   - local-lib1
    - local-lib2

Using the native serverless-python-requirements plugin with poetry the 2 levels of local dependencies are not supported.

project.json example:

{
  "$schema": "../../node_modules/nx/schemas/project-schema.json",
  "projectType": "application",
  "sourceRoot": "apps/myapp/lambda_functions",
  "targets": {
    "deploy": {
      "executor": "@nxlv/python:sls-deploy",
      "dependsOn": ["build"],
      "options": {}
    },
    "package": {
      "executor": "@nxlv/python:sls-package",
      "dependsOn": ["build"],
      "options": {}
    },
    ...
    "build": {
      "executor": "@nxlv/python:build",
      "outputs": ["apps/myapp/dist"],
      "options": {
        "outputPath": "apps/myapp/dist",
        "publish": false
      }
    },
  }
}

Options

Option	Type	Description	Required	Default
--stage	string	Serverless Framework stahe name	true
--verbose	boolean	Serverless Framework CLI verbose flag	false	true
--force	boolean	Serverless Framework CLI force flag	false	false

add

The @nxlv/python:add executor handles poetry add command to provide a level of abstraction and control in the monorepo projects.

Features

• Add new external dependencies
• Add local dependencies

Both features updates the local workspace dependency tree to keep the lock/venv updated.

Options

Option	Type	Description	Required	Default
--name	string	Dependency name (if local dependency use the Nx project name)	true
--args	string	Custom args to be used in the poetry add command	false
--local	boolean	Specifies if the dependency is local	false (only if the --name is a local dependency)

update

The @nxlv/python:update executor handles poetry update command to provide a level of abstraction and control in the monorepo projects.

Features

• Update external dependencies
• Update local dependencies

Both features updates the local workspace dependency tree to keep the lock/venv updated.

Options

Option	Type	Description	Required	Default
--name	string	Dependency name (if local dependency use the Nx project name)	false
--args	string	Custom args to be used in the poetry update command	false
--local	boolean	Specifies if the dependency is local	false (only if the --name is a local dependency)

remove

The @nxlv/python:remove executor handles poetry remove command to provide a level of abstraction and control in the monorepo projects.

Features

• Remove external dependencies
• Remove local dependencies

Both features updates the local workspace dependency tree to keep the lock/venv updated.

Options

Option	Type	Description	Required	Default
--name	string	Dependency name (if local dependency use the Nx project name)	true
--args	string	Custom args to be used in the poetry remove command	false
--local	boolean	Specifies if the dependency is local	false (only if the --name is a local dependency)

build

The @nxlv/python:build command handles the sdist and wheel build generation. When the project has local dependencies the executor copies the package/dependencies recursively.

Options

Option	Type	Description	Required	Default
--silent	boolean	Hide output text	false	false
--outputPath	string	Output path for the python tar/whl files	true
--keepBuildFolder	boolean	Keep build folder	false	false
--lockedVersions	boolean	Build with locked versions	false	true
--bundleLocalDependencies	boolean	Bundle local dependencies	false	true
--ignorePaths	array	Ignore folder/files on build process	false	[".venv", ".tox", "tests"]

Locked Versions Build

Using the default (lockedVersions and bundleLocalDependencies) options, the executor uses the locked versions across all the dependencies and bundles the local dependencies in the same wheel file.

packages/proj1/pyproject.toml

[tool.poetry]
name = "pymonorepo-proj1"

  [[tool.poetry.packages]]
  include = "pymonorepo_proj1"

  [tool.poetry.dependencies]
  python = ">=3.8,<3.10"
  pendulum = "^2.1.2"

    [tool.poetry.dependencies.pymonorepo-lib1]
    path = "../lib1"
    develop = true

packages/lib1/pyproject.toml

[tool.poetry]
name = "pymonorepo-lib1"
version = "1.0.0"

  [[tool.poetry.packages]]
  include = "pymonorepo_lib1"

  [tool.poetry.dependencies]
  python = ">=3.8,<3.10"
  numpy = "^1.24.1"

When the build is executed in the proj1 package, the dist tar/whl file will contain the lib1 package and all dependencies in the poetry.lock file.

packages/proj1/dist/pymonorepo-proj1-1.0.0.tar.gz/pyproject.toml

[tool.poetry]
name = "pymonorepo-proj1"
version = "1.0.0"

  [[tool.poetry.packages]]
  include = "pymonorepo_proj1"

  [[tool.poetry.packages]]
  include = "pymonorepo_lib1"

  [tool.poetry.dependencies]
  python = ">=3.8,<3.10"

    [tool.poetry.dependencies.numpy]
    version = "1.24.1 "
    markers = 'python_version >= "3.8" and python_version < "3.10"'
    optional = false

    [tool.poetry.dependencies.pendulum]
    version = "2.1.2 "
    markers = 'python_version >= "3.8" and python_version < "3.10"'
    optional = false

    [tool.poetry.dependencies.python-dateutil]
    version = "2.8.2 "
    markers = 'python_version >= "3.8" and python_version < "3.10"'
    optional = false

    [tool.poetry.dependencies.pytzdata]
    version = "2020.1 "
    markers = 'python_version >= "3.8" and python_version < "3.10"'
    optional = false

    [tool.poetry.dependencies.six]
    version = "1.16.0 "
    markers = 'python_version >= "3.8" and python_version < "3.10"'
    optional = false

Note, that python-dateutil is a dependency of pendulum, and the pymonorepo_lib1 is now part of the project instead of a dependency.

Non-Locked Versions Build

Using the --lockedVersions=false option, the executor uses the versions from the pyproject.toml file across all the dependencies and bundles the local dependencies in the same wheel file.

packages/proj1/dist/pymonorepo-proj1-1.0.0.tar.gz/pyproject.toml

[tool.poetry]
name = "pymonorepo-proj1"
version = "1.0.0"

  [[tool.poetry.packages]]
  include = "pymonorepo_proj1"

  [[tool.poetry.packages]]
  include = "pymonorepo_lib1"

  [tool.poetry.dependencies]
  python = ">=3.8,<3.10"
  numpy = "^1.24.1"
  pendulum = "^2.1.2"

Note, the pymonorepo_lib1 still bundled in the project but the dependencies are listed in the same way it is on the pyproject (using ^).

Non-Bundled Local Dependencies Build

Using the --bundleLocalDependencies=false and --lockedVersions=false options, the executor checks if the local dependency is publishable and uses the version from the pyproject.toml file, instead of bundling the package.

packages/proj1/dist/pymonorepo-proj1-1.0.0.tar.gz/pyproject.toml

[tool.poetry]
name = "pymonorepo-proj1"
version = "1.0.0"

  [[tool.poetry.packages]]
  include = "pymonorepo_proj1"

  [tool.poetry.dependencies]
  python = ">=3.8,<3.10"
  pendulum = "^2.1.2"
  pymonorepo-lib1 = "1.0.0"

To identify if the package is publishable, the executor checks project.json file, property targets.build.options.publish.

If the publish option is set to false and the --bundleLocalDependencies=false option is used, the executor will bundle the package.

Custom source specification

In addition when adding dependencies in this way its also possible to configure a custom source for a package. This works similar to the publish option in that its specified on the target dependencies build options. To use this set the customSourceName and customSourceUrl to valid values for the source to retrieve the package from for each package stored on a custom Pypi.

project.json example:

{
  ...
  "targets": {
    ...
    "build": {
      "executor": "@nxlv/python:build",
      "outputs": ["apps/myapp/dist"],
      "options": {
        "outputPath": "apps/myapp/dist",
        "publish": false,
        "customSourceName": "example",
        "customSourceUrl": "http://example.com/"
      }
    },
  }
}

Alternatively its also possible to configured it within the nx.json as targetDefaults across the whole repository.

flake8

The @nxlv/python:flake8 handles the flake8 linting tasks and reporting generator.

Options

Option	Type	Description	Required	Default
--silent	boolean	Hide output text	false	false
--outputFile	string	Output pylint file path	true

install

The @nxlv/python:install handles the poetry install command for a project.

Options

Option	Type	Description	Required	Default
--silent	boolean	Hide output text	false	false
--args	string	Custom arguments (e.g --group dev)	false
--cacheDir	string	Custom poetry install cache directory	false
--verbose	boolean	Use verbose mode in the install poetry install -vv	false	false
--debug	boolean	Use debug mode in the install poetry install -vvv	false	false

run-commands (same as nx:run-commands)

The @nxlv/python:run-commands wraps the nx:run-commands default Nx executor and if the autoActivate option is set to true in the root pyproject.toml file, it will verify the the virtual environment is not activated, if no, it will activate the virtual environment before running the commands.

NOTE: This executor only changes the default nx:run-commands if the workspace is configured to use the Shared virtual environment mode and the autoActivate option is set to true in the root pyproject.toml file. NOTE: The autoActivate option is set to false by default.

root pyproject.toml

...
[tool.nx]
autoActivate = true

...

The options and behavior are the same as the nx:run-commands executor.

See the Nx documentation for more information