Python Debugger in Docker

Run Commands

docker build -t my-python-app .
docker run my-python-app

Run Interactively

docker run -it my-python-app /bin/bash
# See what directory you're in
pwd

# List files in the current directory
ls -la

# Look at your Python file
cat app.py

# Run your Python program
python3 app.py
 
# You'll also see the error:

root@fd1d0355b9e2:/app# python3 app.py
Adding 1, total is now 1
Adding 2, total is now 3
Adding 3, total is now 6
Adding 4, total is now 10
Adding 5, total is now 15
Final result: 15
Traceback (most recent call last):
  File "/app/app.py", line 18, in 
    main()
  File "/app/app.py", line 14, in main
    division_result = 10 / 0
                      ~~~^~~
ZeroDivisionError: division by zero

Volume mounting for live edits

docker run -it -v $(pwd):/app my-python-app /bin/bash

Connecting a Remote Debugger from Your IDE

# In your Python code, add the following lines to enable remote debugging
import debugpy
debugpy.listen(("0.0.0.0", 5678))
debugpy.wait_for_client()

Run with DockerfileRemoteDebugger

docker build -t debug/python-function:v1  -f DockerfileRemoteDebugger .

docker run --name debug-python-function-v1 -it -v .:/app -p 5678:5678 debug/python-function:v1 /bin/bash

OR

docker run --name debug-python-function-v1 -v .:/app -p 5678:5678 debug/python-function:v1

docker exec -it debug-python-function-v1 /bin/bash

Now in VS Code, you can set up a debug configuration (in .vscode/launch.json) to connect to the container:

{
    "version": "0.2.0",
    "configurations": [
        {
            "name": "Python: Attach using Debugpy",
            "type": "debugpy",
            "request": "attach",
            "connect": {
                "host": "localhost",
                "port": 5678
            }
        }
    ]
}

Key Debugging Features You’ll Use

• Breakpoints → stop at a specific line.

• Step In / Step Out / Step Over → navigate code execution.

• Watch Variables → track variable changes live.

• Call Stack → see which function calls led here.

• Conditional Breakpoints → stop only if condition is true:

debugpy.breakpoint()   # programmatic breakpoint

Common Debugging Problems and Solutions

⚠️ "My program works on my computer but not in Docker"

This usually means there's a difference in the environment. Check:

Python version differences. Missing dependencies. Different file paths. Environment variables. File permissions.

⚠️ "I can't see my print statements"

Use python -u to avoid output buffering. Make sure you're running with -it if you want interactive output. Check if your program is actually running as intended (maybe it's exiting early).

⚠️ "My changes aren't showing up"

Make sure you're using volume mounting (-v). Check that you're editing the right file. Verify the file is copied into the container.

⚠️ "The container exits immediately"

Run with /bin/bash to inspect the container's state. Check the error messages with docker logs container_name. Make sure your CMD in the Dockerfile is correct.