This is the same authentication method that Cloud Run uses to access Google Cloud APIs. This will allow our local machine to access various Google Cloud APIs as if it were a service account. Gcloud secrets versions disable 123 -secret=my-secretīefore we continue, we must grant access from our local computer to Google Cloud with the following: You can also disable old versions of a secret with: Gcloud secrets versions access 2 -secret=my_secret_file Gcloud secrets versions list my_secret_file You can also get specific versions of the secret with: # View other versions of your Google Cloud Secret with glcoud: Gcloud secrets versions access "latest" -secret "my_secret_file" The following command will print the contents of the latest version of the secret named `my_secret_file`: # View Latest version of your Google Cloud Secret with gcloud: Gcloud secrets versions add my_secret_file -data-file. # Update a Secret by adding a new VersionĪfter you create your secret, you can update it by adding a new version: Gcloud secrets create my_secret_file -data-file. Now create a new Google Cloud Secret from a dotenv file (.env): With this in mind, we'll create a new secret called `my_secret_file` with the contents of `.env-prod` If you need help with any of the above, please considering enrolling in our () course or review the ().Ĭreate `.env-prod` file in your project root with the following: Using Google Secrets Manager assumes you have the following: # Getting Started with Google Secrets Manager Let's modify our `env.py` to use Google Secrets Manager. This method can be used across Python projects with or without Google Secrets Manager. MODE = config("MODE", cast=str default="staging") Now in your Python Modules, you can use our custom way to load `python-decouple`: Let's say your `.env` file looks like this: # return our new default `config` call to replace `config` from `decouple` # so that it doesn't have to be re-evaluated on every call # lru_cache() is used to cache the result of the function # ensure that `.env` is listed in `.gitignore` In `src/env.py` let's add the base configuration:įrom decouple import Config, RepositoryEnvīASE_DIR = pathlib.Path(_file_).parent.parent Loading and using Google Secrets Manager (configuration coming later) With `python-decouple` installed, I create a `env.py` module to handle the following use cases for `python-decouple`: Python -m pip install -r src/requirements.txt With this project structure, our `BASE_DIR` variable will eventually map to `path/to/project` which will done by using `pathlib` within our Python module.Īdd `python-decouple` to `requirements.txt`Įcho \"python-decouple\" > src/requirements.txt Let's say our project's folder structure is the following: Loading environment variables from Google Secrets Manager during productionĪs always, it's recommended you use a virtual environment for your Python projects I use (). Loading environment variables from dotenv files (`.env`) during development I use `python-decouple` in two primary ways: # Getting started with Python Decouple `python-decouple` We'll top it off using GitHub Actions to be our _source of truth_ for our production secrets. Once we have Google Secrets Manager configured with python-decouple, we can use this same approach for Django, FastAPI, Flask, and any other Python project as we see fit. This article will show you how to use () from Google Cloud using (). Google Secrets is a secure and safe way to store sensitive runtime configuration, API Keys, database credentials and so on in secure way. We all know that hard-coding environment variables and secrets in an application is a _bad idea_.
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