# apphub-configurator
[](https://pypi.org/project/apphub-configurator)
[](https://pypi.org/project/apphub-configurator)
-----
## Table of Contents
- [Installation](#installation)
- [Overview](#overview)
- [Examples](#Examples)
- [License](#license)
## Installation
```console
pip install apphub-configurator
```
## Overview
This package contains a notebook and the python modules to support the generation of ApplicationHub configurations for a minikube cluster. For more information about ApplicationHub please check this [link](https://github.com/EOEPCA/application-hub-context)
## Examples:
Find more examples if you need from this [link](https://github.com/EOEPCA/application-hub-context/tree/ESAEOEPCA-236/config-generator/apphub-configurator/examples)
### Step 1: Setup the environment
To begin using the `apphub-configurator` package, import the required functions from the package:
```python
from apphub_configurator.helpers import load_config_map, load_manifests, create_init_container, load_init_script
```
### Step 2: Example of configuration generation
Here is an overview of the functions and how to use them to generate configurations:
1. **Loading Kubernetes Manifests:**
Use `load_manifests()` to load the required Kubernetes manifests. This function takes the following parameters:
- `name`: The name of the manifest.
- `key`: The key used to reference the manifest.
- `file_path`: The file path to the manifest YAML file.
Example usage:
```python
load_manifests(name="example-name", key="example-key", file_path="path/to/manifest.yaml")
```
2. **Creating Volumes:**
You can create a Kubernetes `Volume` by specifying the following:
- `name`: The name of the volume.
- `size`: The size of the volume (e.g., `"50Gi"`).
- `claim_name`: The claim name for the volume.
- `mount_path`: The path where the volume should be mounted.
Example usage:
```python
Volume(
name="workspace-volume",
size="50Gi",
claim_name="workspace-claim",
mount_path="/workspace"
)
```
3. **Loading ConfigMaps:**
Use `load_config_map()` to load configuration maps. It requires the following parameters:
- `name`: The name of the config map.
- `key`: The key for the configuration map.
- `file_name`: The file path to the configuration file.
- `mount_path`: The path where the config map should be mounted.
Example usage:
```python
load_config_map(name="bash-login", key="bash-login", file_name="path/to/bash-login", mount_path="/etc/profile.d/bash-login.sh")
```
4. **Creating Init Containers:**
The `create_init_container()` function allows you to define init containers with the following parameters:
- `image`: The container image to use.
- `volume`: The volume associated with the container.
- `mount_path`: The path where the volume will be mounted inside the container.
Example usage:
```python
create_init_container(image="example-image", volume=your_volume, mount_path="/calrissian")
```
5. **Creating Profiles:**
You can create a `Profile` by defining its parameters such as `id`, `groups`, `definition`, and others. The profile can include volumes, config maps, init containers, and manifests.
Example usage:
```python
Profile(
id="profile_1",
definition=ProfileDefinition(
display_name="Example Profile",
description="This profile configures an example service",
default=True
),
volumes=[your_volume],
config_maps=[your_config_map],
init_containers=[your_init_container],
manifests=[your_manifest]
)
```
6. **Generating the Configuration:**
After defining your profiles and configurations, you can use the `Config` class to generate the final configuration. This configuration can be saved to a YAML file.
Example usage:
```python
config = Config(profiles=[your_profile])
with open("generated_config.yml", "w") as file:
yaml.dump(config.dict(), file)
```
## License
`apphub-configurator` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
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