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Step by step docker intro

Install docker on your machine

Running containers from docker hub image library

Docker hub

docker run --rm -it ubuntu bin/bash   

This command

  1. Downloads locally the ubuntu docker image
  2. Runs a container in an interactive mode ,by using the -it flag
  3. Starts the bash inside the ubuntu container
  4. --rm will remove the container when the container exits

Type exit to exit from bash

Type docker images , returns your local images. You should be able to see the ubuntu image.

Type docker ps , returns the running containers, chances are there are no containers running. The container has been removed after exit since you used --rm.

Running this, will download a python:latest image and run a container from this image.

docker run --rm -it python

Great, you can run a python command now,

import time
print(f'Hello World! {time.ctime()}')

Well, you are right, the container uses UTC as time zone.
Type quit() , the container stops and is being removed.

If you want to use a specific version of python, you have to specify it in the tag :3.10.4-slim-bullseye
When a tag is not specified, the default tag is :latest
You can find the available images and tags here

docker run --rm -it python:3.10.4-slim-bullseye

In the next step will see how to build an image that runs our python code.

Dockerize your Python Code

We have our code in src/app.py

The app.py code, uses 'datetime' and 'requests' library,
prints the current time in local timezone and in UTC,
downloads an html file, creates a data/ directory and save the html file.

If you want to run it in your machine,

  • Create a virtual environment
  • Install the dependencies from requirements.txt file
  • Run the code
    Use python3 for Linux, python for Windows
python3 -m venv env
python3 -m pip install -r requirements.txt
python3 src/app.py

Have a look on the Dockerfile and read the comments.
To build your image you need to run docker build .
The dot . means build the image based on the file called Dockerfile in the current directory.
Is better to add a tag to your image using the -t flag

docker build -t my_python_app .

Great, now your image has a tag. If you type docker images your image should be on the list.
Now you need to run a container based on your image.

docker run --rm my_python_app

This should print the what is going on in the app, but i am pretty sure it didn't download anything in your data/ folder. The container is already gone, it has been removed when the job finished.

There is a way to run a container and see what is going on inside the container. Use the -it flags

docker run --rm -it my_python_app bash

Using ls and cd you can navigate inside the container and see the available files and folders.
If you run the python script, you can see that the data folder has been created and the html file has been downloaded.
Type exit and the container is gone again.

Read more about the interactive mode from the documentation

Share Local Volume with Container

To share you local volume with a container you will use the -v flag.
-v <path to local directory> : <path to container's directory>

docker run --rm -v "$(pwd)"/data:/code/data my_python_app

Now you can see that the container creates the data directory and downloads the html file.
If you want to investigate what is going inside the container, run this:

docker run --rm -it -v "$(pwd)"/data:/code/data my_python_app bash

Read more from the documentation

Run your image with Docker Compose

Open the docker-compose.yml file
As you can see, we specify a name for our service my_python_app
We specify a name for our container my_python_app_dc
The dot . next to build means use the Dockerfile that is in the current directory.
And we also specify the volumes.
Type docker-compose build to build your image.
Type docker-compose up to run your services - containers, here is the my_python_app_dc container.
Type docker-compose down to remove your services - containers.

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Introduction to Docker

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