<p align="center"></p>
<h2 align="center">Cyclic Classes</h2>
<p align="center">
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</p>
## About
Ever had a situation when you wanted to create a cyclic reference between two objects, but don't want to maintain a large singular file?
You're tired of seeing "cyclic-import" errors? This package is for you!
Simply "register" a class you want to share between different modules and you're pretty much good to go!
See the [documentation](https://github.com/rgryta/Cyclic-Classes/#Usage) for more information.
## Requirements
There's ***NONE!***
## Installation
Pull straight from this repo to install manually or just use pip: `pip install cyclic-classes` will do the trick.
## Usage
Consider a package `myk8s` with two modules, maybe one is to reference a k8s deployment and the other one is for pods within that deployment.
`deployment.py`
```python
from .pod import Pod
class Deployment:
def __init__(self, name: str):
self.name = name
@property
def pods(self):
return [Pod(f"{self.name}-pod-{i}") for i in range(3)]
```
Now, if you want to create a back-reference for Deployment within Pod, like this:
`pod.py`
```python
from .deployment import Deployment
class Pod:
def __init__(self, name: str):
self.name = name
@property
def deployment(self):
return Deployment(self.name.split("-")[0])
```
In the above example, you would get a cyclic-import error. To avoid this, you can use `cyclic_classes` to register the classes you want to share between modules.
Do so like this:
`deployment.py`
```python
from cyclic_classes import register, cyclic_import
with cyclic_import(): # This is required to avoid cyclic-import errors - you're actually importing a registered class underneath, but IDE will think it's your actual class
from .pod import Pod
@register # You have to register the class you want to access so that Pod will also be able to use it in the pod.py file
class Deployment:
def __init__(self, name: str):
self.name = name
@property
def pods(self):
return [Pod(f"{self.name}-pod-{i}") for i in range(3)]
```
Now, if you want to create a back-reference for Deployment within Pod, like this:
`pod.py`
```python
from cyclic_classes import register, cyclic_import
with cyclic_import():
from .deployment import Deployment
@register # Making Pod available to cyclic_import
class Pod:
def __init__(self, name: str):
self.name = name
@property
def deployment(self):
return Deployment(self.name.split("-")[0])
```
And that's it! You can now use the classes in your code without any issues.
### Note
Cyclic import supports multiple ways of imports, including relative imports, absolute imports, and even module imports.
As such, in the `cyclic_import` context you can use either of the following:
```python
import myk8s.deployment as depl # And later use depl.Deployment
from .deployment import Deployment
from myk8s.deployment import Deployment
# Not recommended, but also possible
# Reason: Such imports wouldn't work even if there was no cyclic import issue, but it works with cyclic import (you'll get a warning though) and some IDEs think it's correct
from deployment import Deployment
import deployment
```
This also works with aliases! So feel free to use `import ... as ...` or `from ... import ... as ...` as you wish.
## Development
### Installation
Install virtual environment and cyclic_classes package in editable mode with dev dependencies.
```bash
python -m venv venv
source venv/bin/activate
pip install -e .[dev]
```
### How to?
Automate as much as we can, see configuration in `pyproject.toml` file to see what are the flags used.
```bash
staging format # Reformat the code
staging lint # Check for linting issues
staging test # Run unit tests and coverage report
```
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"description": "<p align=\"center\"></p>\n<h2 align=\"center\">Cyclic Classes</h2>\n<p align=\"center\">\n<a href=\"https://github.com/rgryta/Cyclic-Classes/actions/workflows/main.yml\"><img alt=\"Python package\" src=\"https://github.com/rgryta/Cyclic-Classes/actions/workflows/main.yml/badge.svg?branch=main\"></a>\n<a href=\"https://pypi.org/project/cyclic-classes/\"><img alt=\"PyPI\" src=\"https://img.shields.io/pypi/v/cyclic-classes\"></a>\n<a href=\"https://github.com/psf/black\"><img alt=\"Code style: black\" src=\"https://img.shields.io/badge/code%20style-black-000000.svg\"></a>\n<a href=\"https://github.com/PyCQA/pylint\"><img alt=\"pylint\" src=\"https://img.shields.io/badge/linting-pylint-yellowgreen\"></a>\n<a href=\"https://github.com/rgryta/NoPrint\"><img alt=\"NoPrint\" src=\"https://img.shields.io/badge/NoPrint-enabled-blueviolet\"></a>\n</p>\n\n## About\n\nEver had a situation when you wanted to create a cyclic reference between two objects, but don't want to maintain a large singular file?\nYou're tired of seeing \"cyclic-import\" errors? This package is for you!\nSimply \"register\" a class you want to share between different modules and you're pretty much good to go!\n\nSee the [documentation](https://github.com/rgryta/Cyclic-Classes/#Usage) for more information.\n\n## Requirements\n\nThere's ***NONE!***\n\n## Installation\n\nPull straight from this repo to install manually or just use pip: `pip install cyclic-classes` will do the trick.\n\n## Usage\n\nConsider a package `myk8s` with two modules, maybe one is to reference a k8s deployment and the other one is for pods within that deployment.\n\n\n`deployment.py`\n```python\nfrom .pod import Pod\n\nclass Deployment:\n def __init__(self, name: str):\n self.name = name\n \n @property\n def pods(self):\n return [Pod(f\"{self.name}-pod-{i}\") for i in range(3)]\n```\n\nNow, if you want to create a back-reference for Deployment within Pod, like this:\n`pod.py`\n```python\nfrom .deployment import Deployment\n\nclass Pod:\n def __init__(self, name: str):\n self.name = name\n \n @property\n def deployment(self):\n return Deployment(self.name.split(\"-\")[0])\n```\n\nIn the above example, you would get a cyclic-import error. To avoid this, you can use `cyclic_classes` to register the classes you want to share between modules.\nDo so like this:\n\n`deployment.py`\n```python\nfrom cyclic_classes import register, cyclic_import\n\nwith cyclic_import(): # This is required to avoid cyclic-import errors - you're actually importing a registered class underneath, but IDE will think it's your actual class\n from .pod import Pod\n\n@register # You have to register the class you want to access so that Pod will also be able to use it in the pod.py file\nclass Deployment:\n def __init__(self, name: str):\n self.name = name\n \n @property\n def pods(self):\n return [Pod(f\"{self.name}-pod-{i}\") for i in range(3)]\n```\n\nNow, if you want to create a back-reference for Deployment within Pod, like this:\n`pod.py`\n```python\nfrom cyclic_classes import register, cyclic_import\n\nwith cyclic_import():\n from .deployment import Deployment\n\n@register # Making Pod available to cyclic_import\nclass Pod:\n def __init__(self, name: str):\n self.name = name\n \n @property\n def deployment(self):\n return Deployment(self.name.split(\"-\")[0])\n```\n\nAnd that's it! You can now use the classes in your code without any issues.\n\n### Note\n\nCyclic import supports multiple ways of imports, including relative imports, absolute imports, and even module imports.\nAs such, in the `cyclic_import` context you can use either of the following:\n\n```python\nimport myk8s.deployment as depl # And later use depl.Deployment\nfrom .deployment import Deployment\nfrom myk8s.deployment import Deployment\n\n# Not recommended, but also possible\n# Reason: Such imports wouldn't work even if there was no cyclic import issue, but it works with cyclic import (you'll get a warning though) and some IDEs think it's correct \nfrom deployment import Deployment\nimport deployment\n```\n\nThis also works with aliases! So feel free to use `import ... as ...` or `from ... import ... as ...` as you wish.\n\n## Development\n\n### Installation\n\nInstall virtual environment and cyclic_classes package in editable mode with dev dependencies.\n\n```bash\npython -m venv venv\nsource venv/bin/activate\npip install -e .[dev]\n```\n\n### How to?\n\nAutomate as much as we can, see configuration in `pyproject.toml` file to see what are the flags used.\n\n```bash\nstaging format # Reformat the code\nstaging lint # Check for linting issues\nstaging test # Run unit tests and coverage report\n```\n",
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