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April 1, 2023 05:34 pm GMT

How to handle different application environments like Prod, Dev, Test, etc.?

Introduction

There are times when we are in a dilemma as to how to properly use application environments. It gets confusing really fast. I will try to explain the approach (that I see) makes sense.

I will be using Python in this blog, but this implementation is agnostic of the programming language.

Pre-requisites

Python 3.8.x or higher
PyYaml library - To read our YAML configuration files

Lets get started!

Create a yaml file just like below

# settings.ymldefault: &default  api_url: "https://example.com/dev"  aws: &aws    s3_bucket:      - my-bucketdev: &dev  <<: *defaulttest: &test  <<: *default  api_url: "https://example.com/test"prod: &prod  <<: *default  api_url: "https://prod.example.com/"  aws:    <<: *aws    s3_bucket:      - my-prod-bucket

In the above yaml, we are using the inheritance to override the configurations for individual environments.

To pass the correct configuration, we can leverage argparse which parses command-line arguments for us. The following python script does that.

# main.pyimport argparsedef read_cli_arguments():  arg_parser = argparse.ArgumentParser()  arg_parser.add_argument(        "--app-env",        required=True,        action="store",        choices=("prod", "dev", "test"),        help="Application environment to run in"    )  return arg_parser.parse_args()

Next, we read the configuration file based on the environment

# main.pyfrom typing import Dictimport yamldef read_settings(app_env: str) -> Dict:  try:    with open("settings.yml", mode="r", encoding="utf-8") as config:      configs: Dict = yaml.safe_load(config)  except yaml.YAMLError as yaml_err:    print(f"Error occurred while reading the file. Error: {yaml_err}")    raise  return configs[app_env]

Reading the configuration dictionary is now as easy as

# main.pysettings_prod: Dict = read_settings("prod")print(f"Prod Configurations: {settings_prod}")settings_test: Dict = read_settings("test")print(f"Test Configurations: {settings_test}")

Finally, we use this as part of running our main.py file from the command-line like this

$ lsmain.py     settings.yml$ python3 main.py --app-env prod

Complete Code

# main.pyfrom typing import Dictimport argparseimport yamldef read_cli_arguments():  arg_parser = argparse.ArgumentParser()  arg_parser.add_argument(        "--app-env",        required=True,        action="store",        choices=("prod", "dev", "test"),        help="Application environment to run in"    )  return arg_parser.parse_args()def read_settings(app_env: str) -> Dict:  try:    with open("settings.yml", mode="r", encoding="utf-8") as config:      configs: Dict = yaml.safe_load(config)  except yaml.YAMLError as yaml_err:    print(f"Error occurred while reading the file. Error: {yaml_err}")    raise  return configs[app_env]# Program Execution Starts Hereif __name__ == "__main__":  # Read CLI arguments  args = read_cli_arguments()  # Retrieve specific configurations  settings: Dict = read_settings(app_env=args.app_env)  print(f"Configs: {settings}")

Executing the above code on the terminal

$ python3 main.py --app-env prodConfigs: {"api_url": "https://prod.example.com/", "aws": {"s3_bucket": ["my-prod-bucket"]}}

Cheers!

Original Link: https://dev.to/iamibi/how-to-handle-different-application-environments-like-prod-dev-test-etc-3h68

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