GCP publish python package in production

GCP: Publish Python Package in Production

This guide explains how to use Google Artifact Registry to manage shared Python code as a package. This approach eliminates code duplication between your Cloud Functions and server.

---

Step 1: Structure Your Shared Code

Create a new Python package for your shared logic (e.g., common_logic).

common_logic/
├── setup.py
├── common_logic/
│   ├── __init__.py

---

Step 2: Create setup.py

Define your package configuration in a setup.py file:

common_logic/
├── setup.py
├── common_logic/
│   ├── __init__.py

---

Step 3: Set Up Google Artifact Registry

1. Enable the Artifact Registry API:

from setuptools import setup, find_packages

setup(
    name="common_logic",
    version="0.1.0",
    packages=find_packages(),
    install_requires=[
        "pandas>=1.3.0",
    ],
    author="Your Name",
    author_email="your.email@example.com",
    description="Common logic for app",
)

1. Create a Python repository:

   gcloud services enable artifactregistry.googleapis.com

---

Step 4: Configure Authentication

1. Create a service account:

   gcloud artifacts repositories create python-packages \
       --repository-format=python \
       --location=us-central1 \
       --description="Python packages repository"

1. Grant necessary permissions:

   gcloud iam service-accounts create artifact-publisher \
       --description="Service account for publishing to Artifact Registry"

1. Create and download a key:

   gcloud artifacts repositories add-iam-policy-binding python-packages \
       --location=us-central1 \
       --member="serviceAccount:artifact-publisher@${PROJECT_ID}.iam.gserviceaccount.com" \
       --role="roles/artifactregistry.writer"

---

Step 5: Build and Upload Package

1. Install build tools:

   gcloud iam service-accounts keys create key.json \
       --iam-account=artifact-publisher@${PROJECT_ID}.iam.gserviceaccount.com

1. Build the package:

   pip install build twine

1. Configure twine for Artifact Registry:

   python -m build

1. Upload the package:

   cat > ~/.pypirc 




<hr>

<h2>
  
  
  Step 6: Use the Package
</h2>

<h3>
  
  
  In Cloud Functions
</h3>

<ol>
<li>Create a requirements.txt file:
</li>
</ol>

<pre class="brush:php;toolbar:false">   twine upload --repository common-logic-repo dist/*

1. Use the package in your Cloud Function:

   --index-url https://pypi.org/simple
   --extra-index-url https://oauth2accesstoken:${ARTIFACT_REGISTRY_TOKEN}@us-central1-python.pkg.dev/${PROJECT_ID}/python-packages/simple/
   common-logic==0.1.0

In Server Code

1. Add to your server's requirements.txt:

   from common_logic import ...

   def cloud_function(request):
       # Your cloud function code using the imported functions
       pass

1. Use it in your server code:

   --index-url https://pypi.org/simple
   --extra-index-url https://oauth2accesstoken:${ARTIFACT_REGISTRY_TOKEN}@us-central1-python.pkg.dev/${PROJECT_ID}/python-packages/simple/
   common-logic==0.1.0

---

Step 7: CI/CD Integration

1. Add the service account key as a secret in your GitHub repository.
2. Update your Cloud Build configuration:

   from common_logic import ...
   # Your server code using the imported functions

---

Step 8: Version Management

1. Update the version in setup.py.
2. Build and upload the new version.
3. Update requirements.txt in both Cloud Functions and server code.
4. Deploy both components.

---

Best Practices

• Use semantic versioning for your package.
• Pin specific versions in requirements.txt.
• Test new versions thoroughly before deploying.
• Keep a changelog of version changes.
• Use environment variables for PROJECT_ID and LOCATION.
• Include comprehensive documentation in your package.

---

Common Issues and Solutions

Authentication Errors

• Verify service account permissions.
• Ensure key.json is properly encoded.
• Check .pypirc configuration.

Package Not Found

• Verify repository URL format.
• Check if the package was successfully uploaded.
• Ensure requirements.txt uses the correct URL format.

Version Conflicts

• Pin specific versions of dependencies.
• Use virtual environments for testing.
• Document dependency requirements clearly.

The above is the detailed content of GCP publish python package in production. For more information, please follow other related articles on the PHP Chinese website!