How to debug docker debug with pycharm?

How to debug docker debug with pycharm?

How to debug docker debug with pycharm:

1. We go to the Docker official website to download DockerToolbox, and then install it in the next step.

2. Take a look at our Docker virtual machine

Docker Toolbox uses virtualbox to help us create a named It's a Debian-based virtual machine called default, and it did some processing for us. We can modify the memory and modify the CPU allocation amount. (These cannot be done in the so-called Windows native Docker, which only has 2G memory, 1 core, and cannot be changed)

What we need to pay attention to: Docker Toolbox will by default The Users folder is shared to the Docker virtual machine according to the sharing method of virtualbox, which means that our project must actually be in the Users directory, otherwise it will not be found.

This is the trouble with Docker Toolbox, "explicit virtual machine", you need to deal with a lot of problems yourself

3. Use QuickStart or directly in Virtualbox Start our Docker

If it is the first time to use it, you need to modify our accelerator.

https://www.daocloud.io/mirror#accelerator-doc

Then we pull a mirror down first

docker pull ubuntu

I Generally, the original ubuntu image is used to generate the image I think of

4. Initialize our Image

Make an Image for Django, based on Ubuntu

5. Create a connection from Pycharm to Docker

Open Pycharm’s Interpreter and add our Docker Interpreter

Pycharm It will be automatically configured

If you need more than one, just follow this method to create multiple Interpreters based on different Images. One Interpreter in Pycharm corresponds to one Docker Image

6 , Create our project

Now let’s create a project, taking Django as an example (because Pycharm supports it very well), as mentioned before, our project must be created in the Users directory. Otherwise, it will not be found, just use the pycharm default directory.

What we need to note is that when we use Docker’s Interpreter when creating a project, an error will appear as shown above, prompting us that this Interpreter does not support remote Create a project. It doesn't matter, let's switch to the local Interpreter first, create the project first, and then modify it.

7. Modify Interpreter

Now let’s modify Local Interpreter to Docker Interpreter

When you change After that, the lower right corner of Pycharm will do what it should do, wait for it instead of stopping it.

8. Debug our project

Of course, we cannot connect now when we click http://127.0.0.1:8000 Because we haven’t done port mapping yet

9. Port mapping

Docker internal mapping maps our program to the IP of the Docker virtual machine (default is 192.168.99.100), we need to modify our debug configuration

(some Django versions need to set allow_hosts)

This At this time, the program can already be accessed from the 192.168.99.100:8000 port. When you click 0.0.0.0:8000, pycharm will automatically jump to the 192.168.99.100:8000 address for you.

Recommended tutorial: "docker video tutorial"

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