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Error response from daemon: Container xxx exited with code 1

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# 查看容器日志
docker logs container_name

# 实时查看日志
docker logs -f container_name

# 查看最近的日志
docker logs --tail 100 container_name

# 查看带时间戳的日志
docker logs -t container_name

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# 查看所有容器 (包括停止的)
docker ps -a

# 查看容器详细信息
docker inspect container_name

# 查看容器资源使用
docker stats container_name

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# 进入运行中的容器
docker exec -it container_name bash

# 如果容器已停止,使用临时容器
docker run -it --rm image_name bash

# 使用 sh (如果 bash 不可用)
docker exec -it container_name sh

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# docker-compose.yml
services:
app:
image: myapp:latest
command: python app.py # 确保命令正确
# 或使用数组格式
command: ["python", "app.py"]

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# 1. 检查 DNS 配置
docker run --rm alpine ping google.com

# 2. 指定 DNS 服务器
docker run --dns 8.8.8.8 --dns 8.8.4.4 myimage

# 3. docker-compose.yml 中配置
services:
app:
dns:
- 8.8.8.8
- 8.8.4.4

# 4. 检查 Docker 网络设置
docker network ls
docker network inspect bridge

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# 1. 确保在同一网络中
docker-compose.yml:
services:
app:
networks:
- mynetwork
db:
networks:
- mynetwork

networks:
mynetwork:
driver: bridge

# 2. 使用服务名访问
# 在 app 容器中访问 db 容器
ping db # 而不是 localhost

# 3. 检查防火墙
sudo ufw status
sudo iptables -L

# 4. 检查端口映射
docker port container_name

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Error: Bind for 0.0.0.0:8080 failed: port is already allocated

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# 1. 查看端口占用
lsof -i :8080 # Linux/Mac
netstat -ano | findstr :8080 # Windows

# 2. 修改端口映射
docker run -p 8081:8080 myimage # 使用其他主机端口

# 3. docker-compose.yml
services:
app:
ports:
- "8081:8080" # host:container

# 4. 停止占用端口的容器
docker ps | grep 8080
docker stop container_name

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PermissionError: [Errno 13] Permission denied: '/app/data/file.txt'

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# 1. Dockerfile 中设置正确的权限
FROM python:3.11

WORKDIR /app

# 创建非 root 用户
RUN useradd -m -u 1000 appuser && \
chown -R appuser:appuser /app

# 切换用户
USER appuser

COPY --chown=appuser:appuser . .

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# 2. docker-compose.yml 中指定用户
services:
app:
user: "1000:1000" # UID:GID
volumes:
- ./data:/app/data

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# 3. 修改主机文件权限
sudo chown -R 1000:1000 ./data

# 4. 在容器内修改权限
docker exec -u root container_name chown -R appuser:appuser /app/data

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Error: invalid mount config: volume driver not found

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# 1. 使用绝对路径
services:
app:
volumes:
- /absolute/path/to/data:/app/data # Linux/Mac
- C:/absolute/path/to/data:/app/data # Windows

# 2. 使用相对路径
services:
app:
volumes:
- ./data:/app/data # 相对于 docker-compose.yml

# 3. 使用命名卷
services:
app:
volumes:
- mydata:/app/data

volumes:
mydata:
driver: local

# 4. Windows 路径转换
# Windows 下需要共享驱动器
# Docker Desktop → Settings → Resources → File Sharing

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# 1. 使用多阶段构建
FROM python:3.11 AS builder
WORKDIR /app
COPY requirements.txt .
RUN pip install --user -r requirements.txt

FROM python:3.11-slim
WORKDIR /app
COPY --from=builder /root/.local /root/.local
COPY . .
ENV PATH=/root/.local/bin:$PATH

# 2. 优化层缓存
# 把不常变的指令放前面
FROM python:3.11
WORKDIR /app

# 先复制依赖文件
COPY requirements.txt .
RUN pip install -r requirements.txt

# 再复制代码
COPY . .

# 3. 使用 .dockerignore
.git/
__pycache__/
*.pyc
*.pyo
*.log
.env
node_modules/

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# 4. 使用构建缓存
docker build --cache-from myimage:latest -t myimage:new .

# 5. 使用 BuildKit
export DOCKER_BUILDKIT=1
docker build -t myimage .

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# 1. 使用更小的基础镜像
# ❌ 大镜像 (900MB+)
FROM python:3.11

# ✅ 小镜像 (100MB+)
FROM python:3.11-slim

# ✅ 更小的镜像 (50MB+)
FROM python:3.11-alpine

# 2. 多阶段构建
FROM python:3.11 AS builder
WORKDIR /build
COPY requirements.txt .
RUN pip install --prefix=/install -r requirements.txt

FROM python:3.11-slim
COPY --from=builder /install /usr/local
COPY app /app
WORKDIR /app

# 3. 清理缓存
RUN apt-get update && \
apt-get install -y --no-install-recommends gcc && \
pip install -r requirements.txt && \
apt-get purge -y gcc && \
apt-get autoremove -y && \
rm -rf /var/lib/apt/lists/*

# 4. 使用 .dockerignore
.git/
*.md
tests/
docs/

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# 5. 查看镜像层
docker history myimage:latest

# 6. 压缩镜像
docker export container_name | docker import - myimage:compressed

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Container killed due to memory limit

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# docker-compose.yml
services:
app:
deploy:
resources:
limits:
memory: 512M
reservations:
memory: 256M

# 或使用旧语法
services:
app:
mem_limit: 512m
mem_reservation: 256m

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# Docker run 命令
docker run -m 512m --memory-reservation 256m myimage

# 查看容器内存使用
docker stats container_name

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services:
app:
deploy:
resources:
limits:
cpus: '0.5' # 限制使用 0.5 个 CPU
reservations:
cpus: '0.25'

# 或
services:
app:
cpus: 0.5

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# 1. docker-compose.yml 中设置
services:
app:
environment:
- DEBUG=true
- DB_HOST=database

# 2. 从 .env 文件加载
services:
app:
env_file:
- .env
- .env.local

# 3. 从主机环境继承
services:
app:
environment:
- HOME # 从主机继承 HOME 变量

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# 4. 运行时指定
docker run -e DEBUG=true -e DB_HOST=localhost myimage

# 5. 查看容器环境变量
docker exec container_name env

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services:
app:
depends_on:
db:
condition: service_healthy
redis:
condition: service_healthy

db:
healthcheck:
test: ["CMD", "pg_isready", "-U", "postgres"]
interval: 5s
timeout: 5s
retries: 5

redis:
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 5s
timeout: 3s
retries: 5

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# 重新构建镜像
docker-compose build

# 重新创建容器
docker-compose up -d --force-recreate

# 只重启特定服务
docker-compose restart app

# 查看配置
docker-compose config

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# Dockerfile
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
CMD curl -f http://localhost:8000/health || exit 1

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# docker-compose.yml
services:
app:
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 40s

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# 查看健康状态
docker ps
docker inspect --format='{{.State.Health.Status}}' container_name

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# docker-compose.yml
services:
app:
logging:
driver: "json-file"
options:
max-size: "10m"
max-file: "3"

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# 查看日志大小
du -sh /var/lib/docker/containers/*/*-json.log

# 清理日志
truncate -s 0 /var/lib/docker/containers/*/*-json.log

# 全局配置 /etc/docker/daemon.json
{
"log-driver": "json-file",
"log-opts": {
"max-size": "10m",
"max-file": "3"
}
}

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# 1. 减少层数
# ❌ 多层
RUN apt-get update
RUN apt-get install -y package1
RUN apt-get install -y package2

# ✅ 合并层
RUN apt-get update && \
apt-get install -y package1 package2 && \
rm -rf /var/lib/apt/lists/*

# 2. 使用缓存
FROM python:3.11
WORKDIR /app

# 先安装依赖 (变化少)
COPY requirements.txt .
RUN pip install -r requirements.txt

# 再复制代码 (变化多)
COPY . .

# 3. 预热镜像
docker pull myimage:latest
docker-compose pull

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# 清理所有未使用的资源
docker system prune -a

# 清理容器
docker container prune

# 清理镜像
docker image prune -a

# 清理卷
docker volume prune

# 清理网络
docker network prune

# 查看磁盘使用
docker system df

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# 运行临时容器调试
docker run -it --rm alpine sh

# 挂载卷调试
docker run -it --rm -v $(pwd):/data alpine sh

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# 覆盖 CMD
docker run -it myimage bash

# 覆盖 ENTRYPOINT
docker run -it --entrypoint bash myimage

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# 进入容器检查
docker exec -it container_name bash

# 测试连接
ping other_container
curl http://other_container:8080
telnet other_container 3306