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How to Create a Great Local Python Development Environment with Docker
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- เผยแพร่เมื่อ 8 ม.ค. 2023
- Are you ready to take your Python development to the next level with Docker?
In this TH-cam video, Patrick Loeber shows you how to create an amazing local Python development environment using Docker. He starts by introducing the many benefits of using Docker, including its ability to isolate environments, add multiple services, deploy to the cloud, and test out different Python versions. Then, Patrick takes you on a step-by-step journey through the process of setting up a Docker environment. You'll learn how to write an app, use volumes to transfer files between the container and the system, set up an IDE inside the container, and use Docker compose to simplify the process.
Plus, Patrick shows you how to add more services and debug Python code inside a container.
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Brilliant video. Very well structured and presented. Solves pretty much all the complaints I had with my existing setup. Thanks and keep up the good work!
Really awesome explanation . Most of the docker videos I watched where geared towards node , react and other web dev frameworks. I am mostly working with python so this was a great watch and informational.
I found this video useful. Thanks! I would suggest to add video chapter for easy navigation.
excellent tutorial, many thanks!
tip: if you run into issue that the service is not available (localhost:80) the port might be used by another application. Simply change '-80:80' to '-8000:80' in docker-compose.yaml to use port 8000..
Awesome video!
Thank you for a great video. Well structured, detailed and informative.
I will implement it for sure.
Thanks for the detailed explanation. I was wondering earlier how dockers really helps for development. This explains perfectly.
Thank you for sharing ! My output is only in terminal screen, I am not able to send to browser. Do you have some tips ?
Best teacher over the world.
Thank you Patrick!
Patrick Loeber is my hero!
Hey Patrick, really nice tutorial. Thank you for sharing!
This video rocks!! Very nicely said and organised
This was awesome Patrick. Just what I needed.
Thanks for interesting approach using IDE inside a container. Could you explain why you do not use --watch to volume to update code immediately after change on host's mapped volume? What benefits to edit with VSCode in the container instead of the local host filesystem?
Life saver!
Is it possible to run Spyder IDE within Docker in Ubuntu and access GPUs? I have not seen resources that explain how to enable this.
This was helpful but I tried to create a more generic data science image but just could not get it to work as not container was ever running for me to attach to.
Very useful. Thanks a lot for sharing this.
Best ever docker video!
Amazing video!
I just love you! You helped me so much with this!
Well-structured and pretty detailed video!!
brilliant tutorial! thank you
I have a question.. I’m confused with how to debug worker command inside docer container, when it possible to run in bash console only?
I’m going to be glad hearing your answer)
merci
I have a noob question, why we want to setup a dev environment in a docker?
Great tutorial.
I used to use the xdebug extension in vscode ide for php, did you used the same does debugpy need it own extension?
Great video.
Best 🙇♂
fastapi still not found in local even after attaching a running container
Thanks for the video!
So does it mean that each time you make the commit of that file you have to remove that line.
I mean dubugging lines
Did anyone make a note of all these things? Maybe a github repo md file or something ? Please, help!
i used python 1 year and it was fun. bat i didnt know it is imposible ti have more then one project per pc. and eaven if have only one project on your pc you can't finish it. it have tiùo stay at a prototip stage forever. now i have to switch to somting else
This is false. There are plenty of production apps out there written in Python.
Hello, I did exactly the same as per your tutorial, I am using the docker desktop in windows 10, I am able to create the image , however the container wound not start and gives the following error "Error: (HTTP code 400) unexpected - failed to create task for container: failed to create shim task: OCI runtime create failed: runc create failed: unable to start container process: exec: "uvicorn": executable file not found in $PATH: unknown". Could you please help on this?
You need to put the reference of the uvicorn in the requirements file as follows uvicorn[standard]. This will solve the problem!!
great. show us using pycharm?
I'm stuck at 14:36. I have followed all steps, but when I choose attach to a running container, and select my container, no code pulls through to the new instance. Any ideas? Do I need to do this step?
Same problem here!
Find and select /code folder
Thank you so much!
I required gcc-4.7 as a dependency to install some of python package. How can we add gcc-4.7
You can use the RUN command to run commands during image construction, e.g., “apt-get install build-essential” or any other command you’d normally run in your terminal.
Works only with zsh not with powershell. It fails with $(pwd), with powershell should be ${pwd}
Patrick, I'm a beginner and want to learn docker. You didn't start from the beginning. 1) What do you need to install on your OS, for example Docker Desktop, VS Code , Git etc. 2) What recommended OS a beginner should use - OSX, Windows, Linux/Ubuntu etc. You just jumped into coding an ap etc.
Okay but surely you can use your experience as a developer to intuit what's going on
how about cuda?
Yes, you can also build containers with CUDA libraries inside. Or you can reuse public pre-built containers with CUDA and any machine learning libraries you need.
couldn't be anymore confusing, you have to manually edit and manage dockerfiles in a text editor and not in docker desktop? seems easier just to use a vm
Docker wasn’t initially created for development but as a packaging solution for deployment. As a result, its tools are not designed to make it trivial for beginners. That said, using VMs is an option but it’s much heavier and slower compared to containers. Once you know the basics, getting a container up and running is a breeze compared to running a VM.
hey, i have an issue creating the volume : docker run -d --name fastapi-container -p 80:80 -v $(pwd):/code fastapi-image
this is giving me error : docker: invalid reference format.
See 'docker run --help'.
plz help :)
If you running from powershell shell use ${pwd} instead of $(pwd)
Thank you for the good explanation