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構建不同環境下的docker鏡像

同一個dockerfile，支持dev，prod兩套target，對應兩套環境

https://github.com/fanqingsong/craw4ai-fastapi

Docker file

# Dockerfile for crawl4ai-fastapi
# Using multi-stage build with uv for faster package management

################################
# PYTHON-BASE
# Sets up all our shared environment variables
################################
FROM swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/python:3.11-slim AS python-base

    # python
ENV PYTHONUNBUFFERED=1 \
    # prevents python creating .pyc files
    PYTHONDONTWRITEBYTECODE=1 \
    \
    # pip
    PIP_DISABLE_PIP_VERSION_CHECK=on \
    PIP_DEFAULT_TIMEOUT=100 \
    \
    # uv
    UV_VERSION=0.2.0 \
    # make uv install to this location
    UV_HOME="/opt/uv" \
    # make uv create the virtual environment in the project's root
    # it gets named `.venv`
    UV_VIRTUALENV_IN_PROJECT=true \
    # do not ask any interactive question
    UV_NO_INTERACTION=1 \
    \
    # paths
    # this is where our requirements + virtual environment will live
    PYSETUP_PATH="/opt/pysetup" \
    VENV_PATH="/opt/pysetup/.venv"

# prepend uv and venv to path
ENV PATH="$UV_HOME/bin:$VENV_PATH/bin:$PATH"

# Update the package list and install necessary libraries
# 使用清華大學鏡像源加速apt下載
RUN echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm main" > /etc/apt/sources.list && \
    echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian-security/ bookworm-security main" >> /etc/apt/sources.list && \
    echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm-updates main" >> /etc/apt/sources.list && \
    apt-get update && apt-get install -y \
    libglib2.0-0 \
    libnss3 \
    libnspr4 \
    libdbus-1-3 \
    libatk1.0-0 \
    libcups2 \
    libcairo2 \
    libpango-1.0-0 \
    libexpat1 \
    libdrm2 \
    libxcb1 \
    libxkbcommon0 \
    libatspi2.0-0 \
    libx11-6 \
    libxcomposite1 \
    libxdamage1 \
    libxrandr2 \
    libxfixes3 \
    libgbm1 \
    libasound2 \
    libatk-bridge2.0-0 \
    && rm -rf /var/lib/apt/lists/*


################################
# BUILDER-BASE
# Used to build deps + create our virtual environment
################################
FROM python-base AS builder-base
# 使用清華大學鏡像源加速apt下載
RUN echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm main" > /etc/apt/sources.list && \
    echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian-security/ bookworm-security main" >> /etc/apt/sources.list && \
    echo "deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bookworm-updates main" >> /etc/apt/sources.list && \
    apt-get update \
    && apt-get install --no-install-recommends -y \
        # deps for installing uv
        curl \
        # deps for building python deps
        build-essential

# install uv - 使用國內鏡像源加速安裝
RUN --mount=type=cache,target=/root/.cache \
    mkdir -p /opt/uv/bin && \
    pip install --no-cache-dir uv && \
    ln -sf $(which uv) /opt/uv/bin/uv && \
    chmod +x /opt/uv/bin/uv && \
    uv --version

# copy project requirement files here to ensure they will be cached.
WORKDIR $PYSETUP_PATH

# COPY . ./
COPY requirements.txt ./

# 配置uv使用國內鏡像源并安裝依賴
RUN --mount=type=cache,target=/root/.cache \
    uv venv && \
    UV_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple/ uv pip install -r requirements.txt

################################
# DEVELOPMENT
# Image used during development / testing
################################
FROM python-base AS development
ENV FASTAPI_ENV=development
WORKDIR $PYSETUP_PATH

# copy in our built uv + venv
COPY --from=builder-base $UV_HOME $UV_HOME
COPY --from=builder-base $PYSETUP_PATH $PYSETUP_PATH

# will become mountpoint of our code
WORKDIR /app

COPY . .

# 安裝 playwright 和瀏覽器
RUN python -m playwright install

EXPOSE 8000
ENV PROCESSOR_NAME=crawler

CMD ["uvicorn", "crawl4ai_fastapi.main:app", "--host", "0.0.0.0", "--port", "8000", "--reload"]


################################
# PRODUCTION
# Final image used for runtime
################################
FROM python-base AS production
ENV FASTAPI_ENV=production
COPY --from=builder-base $PYSETUP_PATH $PYSETUP_PATH

WORKDIR /app

COPY crawl4ai_fastapi ./crawl4ai_fastapi

# 安裝 playwright 和瀏覽器
RUN python -m playwright install

CMD ["gunicorn", "-w", "4", "-k", "uvicorn.workers.UvicornWorker", "-b", "0.0.0.0:8000", "crawl4ai_fastapi.main:app"]

docker compose dev yaml

version: '3.8'

services:
  web:
    build:
      context: .
      target: development
    ports:
      - "8000:8000"
    environment:
      - FASTAPI_ENV=development
      - USER_AGENT=Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36
      - CRAWLER_TIMEOUT=30
      - REQUEST_TIMEOUT=60
    volumes:
      - .:/app  # 代碼熱重載
    command: ["sh", "-c", "playwright install && uvicorn crawl4ai_fastapi.main:app --host 0.0.0.0 --port 8000 --reload"]

docker compose prod yaml

version: '3.8'

services:
  web:
    build:
      context: .
      target: production
    ports:
      - "8000:8000"
    environment:
      - FASTAPI_ENV=production
      - USER_AGENT=Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36
      - CRAWLER_TIMEOUT=30
      - REQUEST_TIMEOUT=60
    command: ["sh", "-c", "playwright install && gunicorn -w 4 -k uvicorn.workers.UvicornWorker -b 0.0.0.0:8000 crawl4ai_fastapi.main:app"]

使用docker。它的環境變量編譯在運行時使用相同的這個環境文件。

Using `--env-file`with Docker Compose

The --env-fileflag in Docker Compose allows you to specify a file containing environment variables that should be used when running your compose configuration.

Basic Usage

docker compose --env-file .env up

Key Points

??File Format??: The env file should contain key-value pairs, one per line:
```
DB_USER=admin
DB_PASS=secret
```
??Default Behavior??: If you don't specify --env-file, Docker Compose will automatically look for a file named .envin your project directory.
??Variable Precedence??:
- Variables specified directly in the command line (-eflag) take highest precedence
- Then variables from --env-file
- Finally variables from the default .envfile

??Compose File Reference??: You can reference these variables in your docker-compose.yml:

services:
  db:
    environment:
      - POSTGRES_USER=${DB_USER}
      - POSTGRES_PASSWORD=${DB_PASS}

Example

Create an env file (config.env):
```
WEB_PORT=8080
DB_NAME=mydb
```

Reference in compose file:

services:
  web:
    ports:
      - "${WEB_PORT}:80"
  db:
    environment:
      - POSTGRES_DB=${DB_NAME}

Run with:
```
docker compose --env-file config.env up
```

Notes

The env file path is relative to the current working directory
Empty lines and lines starting with #are ignored
Variable substitution only works in certain fields of the compose file (environment, ports, etc.)

posted @ 2025-08-24 19:26 lightsong 閱讀(21) 評論(0) 收藏舉報

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Stay Hungry,Stay Foolish!

lightsong

{Web: [React, Vue, NodeJS, HTTP]，DevOps:[Jenkins,Docker,K8S], Languages:[Python, JS, C, Lua, Shell, Groovy]}, AI:[LLM, langchain，langraph]

構建不同環境下的docker鏡像

同一個dockerfile，支持dev，prod兩套target，對應兩套環境

Docker file

docker compose dev yaml

docker compose prod yaml

使用docker。它的環境變量編譯在運行時使用相同的這個環境文件。

Using `--env-file`with Docker Compose

Basic Usage

Key Points

Example

Notes

公告

Stay Hungry,Stay Foolish!

lightsong

{Web: [React, Vue, NodeJS, HTTP]，DevOps:[Jenkins,Docker,K8S], Languages:[Python, JS, C, Lua, Shell, Groovy]}, AI:[LLM, langchain，langraph]

構建不同環境下的docker鏡像

同一個dockerfile，支持dev，prod兩套target，對應兩套環境

Docker file

docker compose dev yaml

docker compose prod yaml

使用docker。它的環境變量編譯在運行時使用相同的這個環境文件。

Using --env-filewith Docker Compose

Basic Usage

Key Points

Example

Notes

公告

Using `--env-file`with Docker Compose