Cloud Run 関数 で Artifact Registry の Python プライベートリポジトリからパッケージをインストールする

pip install twine

import functions_framework
from google.cloud import storage
import pandas as pd

@functions_framework.http
def buckets_to_dataframe(request):
    storage_client = storage.Client()

    try:
        # バケットの一覧を取得
        buckets = list(storage_client.list_buckets())

        # バケット情報をDataFrameに変換
        df = pd.DataFrame([
            {
                'name': bucket.name,
                'created': bucket.time_created,
                'updated': bucket.updated,
                'storage_class': bucket.storage_class,
                'location': bucket.location
            } for bucket in buckets
        ])

        # DataFrameの内容をHTML形式で表示
        result_html = df.to_html(index=False)

        return f"""
        <h1>GCS Buckets DataFrame</h1>
        {result_html}
        """

    except Exception as e:
        return f"An error occurred: {str(e)}", 500

functions-framework==3.*
google-cloud-storage>=1.36.1
pandas>=2.2

$ ls packages
requirements.txt

$ pip download -r ./packages/requirements.txt --dest ./packages
$ ls packages
blinker-1.9.0-py3-none-any.whl                                                       jinja2-3.1.4-py3-none-any.whl
cachetools-5.5.0-py3-none-any.whl                                                    MarkupSafe-3.0.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
certifi-2024.8.30-py3-none-any.whl                                                   numpy-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
charset_normalizer-3.4.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl  packaging-24.2-py3-none-any.whl
click-8.1.7-py3-none-any.whl                                                         pandas-2.2.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
cloudevents-1.11.0-py3-none-any.whl                                                  protobuf-5.28.3-cp38-abi3-manylinux2014_x86_64.whl
deprecation-2.1.0-py2.py3-none-any.whl                                               proto_plus-1.25.0-py3-none-any.whl
flask-3.0.3-py3-none-any.whl                                                         pyasn1-0.6.1-py3-none-any.whl
functions_framework-3.8.1-py3-none-any.whl                                           pyasn1_modules-0.4.1-py3-none-any.whl
google_api_core-2.22.0-py3-none-any.whl                                              python_dateutil-2.9.0.post0-py2.py3-none-any.whl
googleapis_common_protos-1.65.0-py2.py3-none-any.whl                                 pytz-2024.2-py2.py3-none-any.whl
google_auth-2.36.0-py2.py3-none-any.whl                                              requests-2.32.3-py3-none-any.whl
google_cloud_core-2.4.1-py2.py3-none-any.whl                                         rsa-4.9-py3-none-any.whl
google_cloud_storage-2.18.2-py2.py3-none-any.whl                                     six-1.16.0-py2.py3-none-any.whl
google_crc32c-1.6.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl       tzdata-2024.2-py2.py3-none-any.whl
google_resumable_media-2.7.2-py2.py3-none-any.whl                                    urllib3-2.2.3-py3-none-any.whl
gunicorn-23.0.0-py3-none-any.whl                                                     watchdog-6.0.0-py3-none-manylinux2014_x86_64.whl
idna-3.10-py3-none-any.whl                                                           werkzeug-3.1.3-py3-none-any.whl
itsdangerous-2.2.0-py3-none-any.whl

python3 -m twine upload --repository-url <Repository URL> ./packages/*.whl

$ ls private-repo-func/
main.py  requirements.txt

--index-url <Repository URL>/simple
functions-framework==3.*
google-cloud-storage>=1.36.1
pandas>=2.2

$ gcloud iam service-accounts create function-exec \
  --display-name="cloud run functions test"

gcloud projects add-iam-policy-binding <Project ID> \
  --member="serviceAccount:function-exec@<Project ID>.iam.gserviceaccount.com" \
  --role="roles/storage.admin" \
  --condition=None

gcloud functions deploy private-repo-func \
--gen2 \
--region=asia-northeast1 \
--runtime=python312 \
--source=./private-repo-func \
--entry-point=buckets_to_dataframe \
--trigger-http \
--service-account=function-exec@<Project ID>.iam.gserviceaccount.com