Docker packaging guide for Python

25-03-02 10

对于想了解DockerpackagingguideforPython的读者，本文将提供新的信息，并且为您提供关于167dockerdocker构建nginx容器系列问题dockerregistrydo

对于想了解Docker packaging guide for Python的读者，本文将提供新的信息，并且为您提供关于167 docker docker构建nginx容器系列问题 docker registry docker run docker toolbo、cargo build 一直处于 Blocking waiting for file lock on package cache、CentOS 8.0 安装docker 报错：Problem package docker-ce-3 19.03.4-3.el7.x86_64 require、CentOS 安装PIL（Python Imaging Library）及PIP（Python Package Installer）的有价值信息。

本文目录一览：

Docker packaging guide for Python
167 docker docker构建nginx容器系列问题 docker registry docker run docker toolbo
cargo build 一直处于 Blocking waiting for file lock on package cache
CentOS 8.0 安装docker 报错：Problem package docker-ce-3 19.03.4-3.el7.x86_64 require
CentOS 安装PIL（Python Imaging Library）及PIP（Python Package Installer）

Docker packaging guide for Python

以下是一些关于python 集成docker 的文章，很不错

The basics

Broken by default: why you should avoid most Dockerfile examples
Most Dockerfile examples you’ll find on the Web are broken. And that’s a problem.
A review of the official Dockerfile best practices: good, bad, and insecure
The official Docker documentation’s Dockerfile best practices are mostly good—but they omit some important information.
The best Docker base image for your Python application (January 2020)
Ubuntu? Official Python images? Alpine Linux? Here’s how to choose a good base image.
Alpine makes Python Docker builds 50× slower, and images 2× larger
Alpine Linux is often recommended as a smaller, faster base image. But if you’re using Python, it will actually do the opposite.
When to switch to Python 3.8
Python 3.8 is out now—when should you start using it?
Connection refused? Docker networking and how it impacts your image
A command that runs fine on your computer may fail with connection refused when run in a container. You’ll learn why that happens, and how to prevent it.
Faster or slower: the basics of Docker build caching
Docker’s layer caching can speed up your image build—if you write your Dockerfile correctly.
Installing system packages in Docker with minimal bloat
Your Docker build needs to update system packages for security, and perhaps to install them for additional dependnecies. Here’s how to do it without making your image too large, on Debian, Ubuntu, CentOS and RHEL.

Security

Avoiding insecure images from Docker build caching
Docker’s layer caching is great for speeding up builds—but you need to be careful or it’ll cause you to have insecure dependencies.
Less capabilities, more security: minimizing privilege escalation in Docker
To reduce the security risk from your Docker image, you should run it as a non-root user. You should also reduce it capabilities: learn what, why, and how.
Docker build secrets, the sneaky way
When you’re building Docker images you often need some secrets: a password, an SSH key. For now, Docker lacks a good mechanism to pass in secrets in a secure way, which means you need to get sneaky.

Fast builds, small images

The high cost of slow Docker builds
A slow Docker build on the critical path for developer feedback is a lot more expensive than you think.
Faster Docker builds with pipenv, poetry, or pip-tools
Installing dependencies separately from your code allows you to take advantage of Docker’s layer caching. Here’s how to do it with pipenv, poetry, or pip-tools.
Elegantly activating a virtualenv in a Dockerfile
How to activate a virtualenv in a Dockerfile without repeating yourself—plus, you’ll learn what activating a virtualenv actually does.
Multi-stage builds #1: Smaller images for compiled code
You’re building a Docker image for a Python project with compiled code (C/C++/Rust/whatever), and somehow without quite realizing it you’ve created a Docker image that is 917MB… only 1MB of which is your code!
Multi-stage builds #2: Python specifics—virtualenv, –user, and other methods
Now that you understand multi-stage builds, here’s how to implement them for Python applications.
Multi-stage builds #3: Why your build is surprisingly slow, and how to speed it up
Multi-stage builds give you small images and fast builds—in theory. In practice, they require some tricks if you want your builds to actually be fast.

Applications and runtime

Configuring Gunicorn for Docker
Running in a container isn’t the same as running on a virtual machine or physical server: you need to configure Gunicorn (and other servers) appropriately.
Activating a Conda environment in your Dockerfile
Learn how to activate a conda environment in your Dockerfile.
Decoupling database migrations from server startup: why and how
It’s tempting to migrate your database schema when your application container starts up—here’s some reasons to rethink that choice.
What’s running in production? Making your Docker images identifiable
It’s difficult to debug production problems if you don’t know what image is running in production.
A Python prompt into a running process: debugging with Manhole
Your Python process is acting strange—wouldn’t it be useful to get a live Python interpreter prompt inside your running process?

Packaging as a process

A thousand little details: developing software for ops
Some thoughts on how to build software for ops, a domain that suffers from historical complexity and problem space complexity. And in particular, buildng a better way to do Docker packaging.
Your Docker build needs a smoke test
If you don’t test your Docker image before you push it, you’ll waste time (and maybe break production).

Products and Services

Production-ready template: best practices, faster

Instead of synthesizing every article above, spending days debugging your build process, and fighting slow builds, you can ship your Docker images with confidence—in just hours!—by using the Production-Ready Python Containers template.

167 docker docker构建nginx容器系列问题 docker registry docker run docker toolbo

docker构建nginx容器系列问题

background : 最近为小伙伴们筹划docker系列的技术分享，研究了一会docker相关技术，在此记录一下构建nginx容器时候的坑

1.nginx服务器根目录问题

docker 官方镜像提供的nginx基于debian/jessie平台，其文件结构和ubuntu中的nginx中并不相同

eg:

run一个niginx容器

<span>//80端口被占用，so...</span>
$ sudo docker run <span>-it</span><span>-p</span><span>800</span>:<span>800</span> nginx
$ sudo docker ps 

CONTAINER ID        IMAGE               COMMAND                  CREATED             STATUS              PORTS                                   NAMES
<span>1801</span>a32aab54        nginx               <span>"nginx -g ''daemon off"</span><span>2</span> minutes ago       Up <span>2</span> minutes        <span>80</span>/tcp, <span>443</span>/tcp, <span>0.0</span><span>.0</span><span>.0</span>:<span>800</span><span>-&gt;</span><span>800</span>/tcp   berserk_kare

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进入容器内部

<span>$ </span>sudo docker exec -it <span>1801</span>a32aab54 /bin/bash
root<span>@1801a32aab54</span><span>:/</span><span># </span>

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查看nginx目录

<span># cd /etc/nginx/</span>
conf<span>.d</span>/         koi-utf         mime<span>.types</span>      nginx<span>.conf</span>      uwsgi_params    
fastcgi_params  koi-win         modules/        scgi_params     win-utf

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可以看到不仅没有熟悉的 /sites-available，也没有 /sites-enabled

继续查看nginx配置

<span># cat /conf.d/default.conf</span><span>server</span> {
    listen       <span>80</span>;
    server_name  localhost;

    <span>#charset koi8-r;</span><span>#access_log  /var/log/nginx/log/host.access.log  main;</span>    location / {
        root   /usr/share/nginx/html;
        <span>index</span><span>index</span>.html <span>index</span>.htm;
    }

    <span>#error_page  404              /404.html;</span><span># redirect server error pages to the static page /50x.html</span><span>#</span>
    error_page   <span>500</span><span>502</span><span>503</span><span>504</span>  /<span>50</span>x.html;
    location = /<span>50</span>x.html {
        root   /usr/share/nginx/html;
    }
    <span>#...省略php-fpm配置，好长..</span>
}

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根目录配置: root /usr/share/nginx/html;

测试

<span># cd /usr/share/nginx/html</span><span># touch index.html</span><span># echo "test nginx in docker" &gt;index.html</span>

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php-fpm配置相关

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以上就介绍了167 docker docker构建nginx容器系列问题，包括了docker,nginx方面的内容，希望对PHP教程有兴趣的朋友有所帮助。

cargo build 一直处于 Blocking waiting for file lock on package cache

删除 .package_cache 文件即可。
那这个文件在哪里呢？

在 $HOME/.cargo 路径下

╭─bot@amd-5700G ~/Desktop/rust/hello-rust  ‹master*› 
╰─➤  cd ~/.cargo                   
╭─bot@amd-5700G ~/.cargo  
╰─➤  ll
  inode Permissions Links Size Blocks User Group Date Modified Name
6294857 .rw-rw-r--      1   84      8 bot  bot   25 Aug 20:09  .crates.toml
6295067 .rw-rw-r--      1  452      8 bot  bot   25 Aug 20:09  .crates2.json
6296027 .rw-rw-r--      1    0      0 bot  bot   25 Aug 20:07  .package-cache
6296018 drwxrwxr-x      2    -      - bot  bot   16 Nov 22:55  bin
6296053 .rw-rw-r--      1  130      8 bot  bot   25 Aug 20:07  config
6296021 .rw-rw-r--      1  300      8 bot  bot   25 Aug 20:04  env
6296029 drwxrwxr-x      5    -      - bot  bot   25 Aug 20:08  registry
╭─bot@amd-5700G ~/.cargo  
╰─➤  rm .package-cache

CentOS 8.0 安装docker 报错：Problem package docker-ce-3 19.03.4-3.el7.x86_64 require

1、错误内容

2、分析原因
看上面的内容，说的是containerd.io >= 1.2.2-3 ，意思就是 containerd.io 的版本必须大于等于 1.2.2-3

3、解决
1、要么就降低docker 的版本

2、如果不想降低docker 版本，那么就更新 containerd.io 的版本

wget https://download.docker.com/linux/centos/7/x86_64/edge/Packages/containerd.io-1.2.6-3.3.el7.x86_64.rpm
yum install -y containerd.io-1.2.6-3.3.el7.x86_64.rpm

然后重新安装最新版本的docker 即可成功安装

4、检查是否安装成功
docker -version

CentOS 安装PIL（Python Imaging Library）及PIP（Python Package Installer）

php小编香蕉为大家带来了一篇关于centos系统安装pil（python imaging library）及pip（python package installer）的教程。pil是一个强大的图像处理库，而pip是python的包管理工具，能够方便地安装和管理python的第三方库。在本篇教程中，我们将详细介绍如何在centos系统上安装和配置pil和pip，让您能够更好地利用python进行图像处理和包管理。无论您是初学者还是有一定经验的开发者，都可以通过本教程轻松上手，快速掌握相关技能。

CentOS 安装PIL（Python Imaging Library）及PIP（Python Package Installer）

在 CentOS 上安装 PIL（Python Imaging Library）和 PIP（Python Package Installer）是使用 Python 进行图像处理和安装第三方 Python 包的重要步骤，下面我将为您详细介绍如何在 CentOS 上安装 PIL 和 PIP。

安装 PIL

1. 确保您的系统已经安装了 Python 和 pip，在终端中运行以下命令来检查：

```css

立即学习“Python免费学习笔记（深入）”；

python --version

pip --version

```

如果未安装 Python 和 pip，请先安装它们。

2. 安装 PIL，运行以下命令来安装 PIL：

pip install pillow

Pillow 是 PIL 的一个分支，它提供了更多的功能和更好的维护。

安装 PIP

1. 如果您的系统尚未安装 PIP，可以通过以下命令进行安装：

python -m ensurepip --upgrade

这将确保您的系统上安装了最新版本的 PIP。

2. 使用 PIP 安装其他 Python 包，要安装 requests 包，运行以下命令：

pip install requests

这将下载并安装 requests 包及其依赖项，您可以使用类似的方法安装其他 Python 包。

注意事项

1. 在使用 PIP 安装 Python 包时，请确保您的网络连接正常，以便从 PyPI（Python Package Index）下载包及其依赖项。

2. 如果您在安装过程中遇到权限问题，请使用 sudo 命令以管理员身份运行 pip 命令，`sudo pip install requests`。

3. 如果您的系统上同时安装了多个 Python 版本，请使用对应版本的 pip 命令进行安装，例如 `pip3 install requests`。

4. 如果您需要更新已安装的 Python 包，请使用 `pip install --upgrade package_name` 命令进行升级。

5. 在使用第三方 Python 包时，请确保它们与您的 Python 版本兼容，以避免出现兼容性问题。

通过以上步骤，您可以在 CentOS 上成功安装 PIL 和 PIP，这些工具将帮助您在 CentOS 上使用 Python 进行图像处理和安装第三方 Python 包，希望这些信息对您有所帮助！如有任何疑问，请随时提问。

以上就是CentOS 安装PIL（Python Imaging Library）及PIP（Python Package Installer）的详细内容，更多请关注php中文网其它相关文章！

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