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Alright.

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We have just removed the all containers that were stopped before and if I type now, Docker PS dash

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A, you'll see empty output and if you have not cleaned your containers, please watch the previous

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lecture.

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In this lecture, let's create a container based on Python image.

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And for that let's first pull Python image from Docker Hub.

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Docker pull Python.

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And I don't specify any tag.

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It means that latest version of Python image will be pulled.

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Notice that now we are downloading basically multiple file system layers and they are relatively large

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in comparison.

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For example to Alpine or ubuntu image.

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Let's wait a bit.

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Actually from this output you see that we have actually pulled compressed layers and afterwards locally

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we extract contents from that compressed layers.

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Wonderful image was pulled and here is its Sha 256 hash and you see that we have downloaded python latest

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image latest is its tag.

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Great.

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Let's now verify list of images Docker images and you'll see here Python on the list and its size is

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around one gigabyte.

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It is really, really huge in comparison to other images like nginx, alpine or ubuntu.

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Wonderful.

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Let's now try to create container based on this python image and let's simply use docker run command

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with name of the image python.

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Let's clear terminal docker run python.

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And as before, we see that container was basically created under the hood, but it was immediately

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terminated.

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Let's list here containers, Docker, PS And you see no containers currently running, but there is

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a single container here in the history and it was exited 14 seconds ago.

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And you see here command that was executed.

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It was Python three, but we have not connected to standard in of this process.

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This process was exited therefore and afterwards container was terminated by Docker because there were

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no processes running.

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Again, situation is the same as we have seen, for example with Alpine or Ubuntu containers.

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If you don't connect to standard input of specific process, process exits automatically and Docker

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stops such container.

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Great.

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Let me now clear terminal and run this container with options.

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Dash i and dash t docker run dash it.

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I can combine those two options and here will be python like so.

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And now you see that we have actually opened interactive session with Python.

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Actually the same happens when Python is installed locally on your computer and when you enter Python

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three or Python command.

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We are now inside of the interactive shell with Python.

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Let's now, for example, enter help here.

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Actually, in order to get interactive help, I need to add parentheses here like so and you'll see

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message.

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Welcome to Python 3.8 and here you see that you are able to explore help for different modules, keywords

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or symbols like you see here.

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And for example, we are able to get list of Python modules by entering modules.

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And afterwards you are able to get help about any of those modules.

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And let's, for example, get help about the Lib module and for that simply type name of corresponding

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module here, zlib like so, and you'll get module reference here and you may read about this module,

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what it does and how it is used.

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Actually great.

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That's how you able to get help inside of this interactive session.

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And if you want to exit from here, you could simply press Q and press enter.

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And afterwards here you are able to execute any Python commands.

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For example, let's type three plus seven, I get ten, let's print hello from Python like so and I

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get Hello from Python here.

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That's how you able to interact with Python interpreter okay.

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Also notice that this container is still up and running because we are now connected to standard in

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and standard output of specific process, namely Python three process.

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And if I open new tab and list containers here, Docker PS you see that the Python image was used for

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creation of this container with container ID, this one and the random name.

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This one was assigned to this container and here you see command that was automatically executed.

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Python three.

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All right, Let's now go back to this step and let's exit from this interactive session.

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And for that you could type exit with parentheses like so.

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Process was terminated and container was stopped as well.

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Let's verify that.

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Docker PS And yes, there are no running containers, but this container is listed here.

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If I add a option, all great.

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That's how we were able to create the python container and run some code inside of that container.

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But of course, in practice during development usually you need to have a python container in order

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to execute your python applications.

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And next, let me demonstrate you how you are able to run your specific project located on your local

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computer using Python container.

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Let's do that next.

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Bye bye.