我知道这个问题已经有一些流行的答案。但是有一种更新的方法可以为包管理器缓存文件。我认为将来当 BuildKit 变得更加标准时,这可能是一个很好的答案。
从 Docker 18.09 开始,对 BuildKit 提供实验性支持。 BuildKit 增加了对 Dockerfile 中一些新特性的支持,包括 experimental support for mounting external volumes 到 RUN 步骤中。这使我们可以为 $HOME/.cache/pip/ 之类的内容创建缓存。
我们将使用以下requirements.txt 文件作为示例:
Click==7.0
Django==2.2.3
django-appconf==1.0.3
django-compressor==2.3
django-debug-toolbar==2.0
django-filter==2.2.0
django-reversion==3.0.4
django-rq==2.1.0
pytz==2019.1
rcssmin==1.0.6
redis==3.3.4
rjsmin==1.1.0
rq==1.1.0
six==1.12.0
sqlparse==0.3.0
Python Dockerfile 的典型示例可能如下所示:
FROM python:3.7
WORKDIR /usr/src/app
COPY requirements.txt /usr/src/app/
RUN pip install -r requirements.txt
COPY . /usr/src/app
使用 DOCKER_BUILDKIT 环境变量启用 BuildKit 后,我们可以在大约 65 秒内构建未缓存的 pip 步骤:
$ export DOCKER_BUILDKIT=1
$ docker build -t test .
[+] Building 65.6s (10/10) FINISHED
=> [internal] load .dockerignore 0.0s
=> => transferring context: 2B 0.0s
=> [internal] load build definition from Dockerfile 0.0s
=> => transferring dockerfile: 120B 0.0s
=> [internal] load metadata for docker.io/library/python:3.7 0.5s
=> CACHED [1/4] FROM docker.io/library/python:3.7@sha256:6eaf19442c358afc24834a6b17a3728a45c129de7703d8583392a138ecbdb092 0.0s
=> [internal] load build context 0.6s
=> => transferring context: 899.99kB 0.6s
=> CACHED [internal] helper image for file operations 0.0s
=> [2/4] COPY requirements.txt /usr/src/app/ 0.5s
=> [3/4] RUN pip install -r requirements.txt 61.3s
=> [4/4] COPY . /usr/src/app 1.3s
=> exporting to image 1.2s
=> => exporting layers 1.2s
=> => writing image sha256:d66a2720e81530029bf1c2cb98fb3aee0cffc2f4ea2aa2a0760a30fb718d7f83 0.0s
=> => naming to docker.io/library/test 0.0s
现在,让我们添加实验标头并修改RUN 步骤以缓存 Python 包:
# syntax=docker/dockerfile:experimental
FROM python:3.7
WORKDIR /usr/src/app
COPY requirements.txt /usr/src/app/
RUN --mount=type=cache,target=/root/.cache/pip pip install -r requirements.txt
COPY . /usr/src/app
现在继续进行另一个构建。它应该花费相同的时间。但这次它在我们的新缓存挂载中缓存 Python 包:
$ docker build -t pythontest .
[+] Building 60.3s (14/14) FINISHED
=> [internal] load build definition from Dockerfile 0.0s
=> => transferring dockerfile: 120B 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 2B 0.0s
=> resolve image config for docker.io/docker/dockerfile:experimental 0.5s
=> CACHED docker-image://docker.io/docker/dockerfile:experimental@sha256:9022e911101f01b2854c7a4b2c77f524b998891941da55208e71c0335e6e82c3 0.0s
=> [internal] load .dockerignore 0.0s
=> [internal] load build definition from Dockerfile 0.0s
=> => transferring dockerfile: 120B 0.0s
=> [internal] load metadata for docker.io/library/python:3.7 0.5s
=> CACHED [1/4] FROM docker.io/library/python:3.7@sha256:6eaf19442c358afc24834a6b17a3728a45c129de7703d8583392a138ecbdb092 0.0s
=> [internal] load build context 0.7s
=> => transferring context: 899.99kB 0.6s
=> CACHED [internal] helper image for file operations 0.0s
=> [2/4] COPY requirements.txt /usr/src/app/ 0.6s
=> [3/4] RUN --mount=type=cache,target=/root/.cache/pip pip install -r requirements.txt 53.3s
=> [4/4] COPY . /usr/src/app 2.6s
=> exporting to image 1.2s
=> => exporting layers 1.2s
=> => writing image sha256:0b035548712c1c9e1c80d4a86169c5c1f9e94437e124ea09e90aea82f45c2afc 0.0s
=> => naming to docker.io/library/test 0.0s
大约 60 秒。类似于我们的第一个构建。
对requirements.txt 做一个小改动(例如在两个包之间添加一个新行)以强制缓存失效并再次运行:
$ docker build -t pythontest .
[+] Building 15.9s (14/14) FINISHED
=> [internal] load build definition from Dockerfile 0.0s
=> => transferring dockerfile: 120B 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 2B 0.0s
=> resolve image config for docker.io/docker/dockerfile:experimental 1.1s
=> CACHED docker-image://docker.io/docker/dockerfile:experimental@sha256:9022e911101f01b2854c7a4b2c77f524b998891941da55208e71c0335e6e82c3 0.0s
=> [internal] load build definition from Dockerfile 0.0s
=> => transferring dockerfile: 120B 0.0s
=> [internal] load .dockerignore 0.0s
=> [internal] load metadata for docker.io/library/python:3.7 0.5s
=> CACHED [1/4] FROM docker.io/library/python:3.7@sha256:6eaf19442c358afc24834a6b17a3728a45c129de7703d8583392a138ecbdb092 0.0s
=> CACHED [internal] helper image for file operations 0.0s
=> [internal] load build context 0.7s
=> => transferring context: 899.99kB 0.7s
=> [2/4] COPY requirements.txt /usr/src/app/ 0.6s
=> [3/4] RUN --mount=type=cache,target=/root/.cache/pip pip install -r requirements.txt 8.8s
=> [4/4] COPY . /usr/src/app 2.1s
=> exporting to image 1.1s
=> => exporting layers 1.1s
=> => writing image sha256:fc84cd45482a70e8de48bfd6489e5421532c2dd02aaa3e1e49a290a3dfb9df7c 0.0s
=> => naming to docker.io/library/test 0.0s
只有大约 16 秒!
我们正在获得这种加速,因为我们不再下载所有 Python 包。它们被包管理器(在这种情况下为pip)缓存并存储在缓存卷挂载中。卷安装提供给运行步骤,以便pip 可以重用我们已经下载的包。 这发生在任何 Docker 层缓存之外。
更大的requirements.txt 的收益应该会更好。
注意事项:
- 这是实验性的 Dockerfile 语法,应该这样对待。您目前可能不想在生产环境中使用它进行构建。
-
BuildKit 的东西目前在 Docker Compose 或其他直接使用 Docker API 的工具下不工作。现在 Docker Compose 从 1.25.0 开始支持这一点。见How do you enable BuildKit with docker-compose?
- 目前没有用于管理缓存的直接接口。当您执行
docker system prune -a 时,它会被清除。
希望这些功能能够在 Docker 中进行构建,并且 BuildKit 将成为默认设置。如果/当这种情况发生时,我会尝试更新这个答案。