kungfuai / env

Conventional environment handling for KUNGFU.AI projects

KUNGFU.AI Env

Environment handling to simplify development environments

Table of Contents

• About the Project
  • Built With
• Getting Started
  • Dependencies
  • Installation
• Usage
• Roadmap
• Contributing
• License
• Contact
• Acknowledgements

Built With

• Python-Dotenv
• Python 3.8

Getting Started

This repo aims to be a cloud and local compatible approach to modern application environment handling.

Environment files committed with the repo bring us some clear advantages that we should consider when building software.

At KUNGFU.AI, many of our usecases are single container microservice deployment into a cloud. By committing secrets to cloud Secret Manager, and keeping Secret IDs + other environment data within our env files, we're able to:

1. Keep our deployed assets secure
2. Developers don't have to pass keys, know about keys, or share env files (YUCK)
3. Developers can pull and run their repos immediately.

The kungfuai/env repo aims to simplify these use-cases.

Dependencies

Python 3.8

Installation

pip install kungfuai-env

How does it work?

The flow is 3 steps - Construction, Registration, and Loading. e.g.

# Construction
env = Environment('src/env')
# Registration
env.register_environment("test")
env.register_environment("prod")
# Loading
env.load_env()

In the above example, Environment() is constructed, and the path to environment files is set to be located at src/env.

Next, we state that we have a test environment, and a prod environment that we intend to load. The names are important - seeing test indicates that env.load_env() will seek a .test.env file in the src/env directory. The same would be true for prod / .prod.env

Runtime Environment Selection

Now, we know how to handle the environments. How do we know which ones to load when the application starts?

There is a special environment variable that we always watch named ENV.

With the above example in mind, if you set ENV=PROD or ENV=prod, you will load the .prod.env file.

If you set ENV=TEST or ENV=test, you will load the .test.env file.

If you do not set anything for ENV, you will load, by default, the .local.env file.

Usage

Simple Example

In the most simple of applications, imagine a main.py with a .local.env environment

# main.py
import os
from kfai_env.env import Environment

if __name__ == "__main__":
    print("Simple Python App Example")

    e = Environment()
    e.register_environment("prod")
    e.load_env()
    print(os.getenv("TEST_ENV"))

# .local.env
TEST_ENV=HELLOWORLDFROMLOCAL

# .prod.env
TEST_ENV=HELLOWORLDFROMPROD

If we were to run python3 main.py with this above example program, we would see HELLOWORLDFROMLOCAL. If we were to run ENV=PROD python3 main.py, we would see HELLOWORLDFROMPROD.

Roadmap

See the open issues for a list of proposed features (and known issues).

1. Upgrade project to use poetry as the build and deploy system (instead of pip + versioneer)

License

Distributed under the MIT License. See LICENSE for more information.

Contact

Endurance Idehen - [e-mail]