Docker

# Use the official lightweight Python image.
# https://hub.docker.com/_/python
FROM python:3.8-slim

# Allow statements and log messages to immediately appear in the Knative logs
ENV PYTHONUNBUFFERED True

# Copy local code to the container image.
ENV APP_HOME /app
WORKDIR $APP_HOME
COPY . ./

# Install production dependencies.
RUN pip install --no-cache-dir -r requirements.txt

# Run the web service on container startup. Here we use the gunicorn
# webserver, with one worker process and 8 threads.
# For environments with multiple CPU cores, increase the number of workers
# to be equal to the cores available.
# Timeout is set to 0 to disable the timeouts of the workers to allow Cloud Run to handle instance scaling.
CMD exec gunicorn --bind :$PORT --workers 1 --threads 8 --timeout 0 app:app

gcloud config set project {project}

gcloud artifacts repositories create backend --location=asia-northeast1 --repository-format=docker

gcloud auth configure-docker asia-northeast1-docker.pkg.dev

docker build ./ -t asia-northeast1-docker.pkg.dev/{project}/{ARのリポジトリ名}/{イメージ名} --platform linux/amd64

m1
docker buildx build ./ -t asia-northeast1-docker.pkg.dev/{project}/{ARのリポジトリ名}/{イメージ名} --platform linux/amd64

docker push asia-northeast1-docker.pkg.dev/{project}/{ARのリポジトリ名}/{イメージ名}

poetry export -f requirements.txt --output requirements.txt --without-hashes

docker container run [option] <image> [command]


docker container run \
    --name web-server  \
    --rm               \
    --detach           \
    --publish 8080:80  \
    nginx:1.21

docker container run \
    --name nginx5      \
    --rm               \
    nginx:1.21         \
    ls /etc/nginx

docker image build [option] <path>

docker image build     \
    --tag my-ubuntu:date \
    .

docker image build              \
    --tag my-ubuntu:date          \
    --file docker/date/Dockerfile \
    docker/date