Develop Reference

How to sync python files from PyCharm IDE to GitHub Automatically?

I'm currently using PyCharm IDE to learn Python. I am not aware of how to sync my file automatically to GitHub. Or to be precise I want my code to automatically sync as I type, to my GitHub repo. Like I want the file to exist in GitHub and edit it over my IDE.
Is there any solution for this to happen?
Regards,
Kausik

That is not how git (or Github) works. Version control systems are designed to capture milestones in your project. I think you're confusing git with file management cloud services (e.g., Dropbox or Google Drive). If you need something that would sync your files with each "save" you make to a file then services like Dropbox are what you looking for.
However, version control systems (e.g., git) are much better suited for code management if you adjust your workflow to follow how they were intended to be used. In PyCharm, after each milestone (e.g., a bug fix or a new feature implementation) you would do the following:
Stage changed files by checking them.
Commit the changes by adding a commit message.
Push changes to the remote repository.
All these can be found within the Commit window in PyCharm (View >> Tool Windows >> Commit). All the three steps above can be done in one click
One last thing. If your goal is to collaborate with someone else in real-time, then PyCharm has a new feature called "Code with me" (Tools >> Code With Me ...). I don't know if it is available for free but the idea is that you would invite friends and change the code base together in real-time. And eventually, you would push the changes to the remote repository.

PyCharm reindexing when project is stored on a NAS

I have been working with PyCharm for quite some time now and I recently upgraded my storing system with a NAS.
Everything is working fine except one : PyCharm scans through my files to reindex them very very often. This makes me losing a lot of time waiting for it to end.
When the reindexing occurs:
When a script ends
When a debugging session ends
When PyCharm loses the focus, i.e. I use another application
So it happens basically ALL the time, taking quite a long time (several minutes sometimes).
Misc.:
Windows 10
PyCharm Community Edition 2018.1
Netgear - ReadyNas 422
Do you have any ideas to solve this issues ?

So I have contacted the IntelliJ support and here is their response:
Working with network drives/folders is not supported officially yet.
Using remote development features is recommended (remote interpreter,
deployment etc). Here is more detailed answer
https://intellij-support.jetbrains.com/hc/en-us/community/posts/207069145/comments/207464249.
What I end up doing, which is really not ideal, is to create a local copy of my projects environment and syncing it with a folder in my NAS. To do so I used the SyncBackPro software.

I'm using PyCharm both at home and at work with code stored on a Samba share (using its remote interpreter feature). I don't encounter consistent reindexing but by default it does not support file system notifications to know when a file changed.
However, as a programmer this shouldn't discourage you! You can drop in your own file system notifier that connects to your remote system (assuming your NAS runs Linux and supports SSH) and thus avoid the performance drop.
I actually wrote such a proxy to run the fsnotifier on a remote system a few years ago and I'm still using it. If you are interested, check out https://github.com/ThiefMaster/fsnotifier-remote
Some things in the repo are outdated (JetBrains removed this stupid file size check for example), but it should still provide you a good basis to start from if you are interested in using it.

Can something go wrong if I choose not to virtualize even though I was told to do it?

Sorry if this question is too stupid but I can't find an answer to it.
I'm a beginner in terms of databases so I'm taking a course in Udacity. In the course, they tell us to install Vagrant and VirtualBox in order to run an ubuntu virtual machine to make the exercises of the course. The problem is that my pc is not working properly with that virtual machine running, so I decided not to virtualize and do the stuff in my "normal" programming environment (in the course we use flask, sqlite and sqlalchemy in order to create a website using a database, and in the next lesson they teach to build a web server that uses our database). Somewhere on the internet I read about virtual machines being useful to work in your computer without messing our computer's configuration up. My question is, can this happen? Or what does it mean to "mess the configuration up"? Is it possible to make an important mistake that will make me wish I had virtualized?

It shouldn’t mess any configuration in your PC. The whole point of virtualizing your programming environment is for security reasons, or because developing is easier on a Linux machine. If you’re going to do sql exercises, the worst you can possibly do is mess the database.

I don’t think so.
VM is useful here in two ways: first, it teaches you to work with DB as with remote server, like in real world.
Second: it prevents your main OS from junking up. It’s not a big problem now, but windows can slow down due to many applications leaving junk in registry or whatever... I think it was mostly dealt with in win7, but was on Mac by that time.
You are probably fine, just don’t use shutil.rmtree() on C:\ ;)

Rich editors in a Docker development environment

So my team and I have bought into Docker - it is fantastic for deployment and testing. My real question is how to set up a great developer experience, specifically around writing Python apps, but this question could be generalized to nodejs, Java, etc.
The problem: When writing a Python app, I really like having decent linting/autocomplete functionality, there are some really good editors out there (Atom, VSCode, PyCharm) that provide these, but most really want a Python install on the local disk. The real advantage of Docker is that all of the core language and any project libraries can all be in the container, so reproducing all of that on the host machine just for developing is a pain.
I know that PyCharm pro does support Docker and docker-compose, but I found it quite sluggish and a lot of the test running capabilities were busted. On top of that, I really would like something that I can commit to version control so that the team can share dev setup and people don't have to repeat all of the steps for their own system.
A few Ideas that I had were:
Install an editor (like Atom) in a sidecar Docker container and use X11 forwarding
Use a browser based editor such as https://c9.io/ in a container - this seems most promising
Install some agent in a dev container that could handle autocomplete/linting, etc. and connect to it from a locally running editor - I think this would be the best solution, but I also think that right now it actually doesn't exist.
Has anyone had luck setting up a more productive development environment besides just mounting volumes and editing text?

You should use an 'advanced' IDE like IntelliJ (Pycharm) and configure a remote Python SDK using SSH-Access to your App-Docker-Container (using a shared ssh-key to auth against the app-container with a preinstalled openssh server and preconfigured authorized_keys file).
You can share this SDK information in your project file with all devs, so they wlll have this setup out of the box
1) This will ensure, your IDE knows about all the python libs/symbols available/installed in your docker-container during runtime. It will also enable you to properly debug remotely at the same time
2) This ensures, you have an IDE at your hand including a lot of important additional features like the inspector, 3way duff, search in path.. . hardly any of the Browser-Based IDEs will catch up with Pycharm at this point IMHO
Of course, as already mentioned in the comments, you need to share aka mount your code into the container. On linux, you plainly use host-volume-mounts from your local src folder to the container.
On OSX, you will run into performance issues when using host mounts. You might use something like http://docker-sync.io ( i am biased - there are also a lot of other similar tools )

I know this is an old question, but as I stumbled across it while trying to see what other editors might offer in this space, I would like to point out Visual Studio Code's notion of a Dev Container, which seems to provide the best level of integration I've seen for this so far. I'm hoping to see this turn into an industry trend myself.

Could use x11docker
x11docker allows to run graphical desktop applications (and entire desktops) in Docker Linux containers.
Docker allows to run applications in an isolated container environment. Containers need much less resources than virtual machines for similar tasks.
Docker does not provide a display server that would allow to run applications with a graphical user interface.
x11docker fills the gap. It runs an X display server on the host system and provides it to Docker containers.
Additionally x11docker does some security setup to enhance container isolation and to avoid X security leaks. This allows a sandbox environment that fairly well protects the host system from possibly malicious or buggy software.
https://github.com/mviereck/x11docker
https://github.com/mviereck/x11docker/wiki (extensive! knowledge)
https://dev.to/brickpop/my-dream-come-true-launching-gui-docker-sessions-with-dx11-in-seconds-1a53

Python development environment for web applications (Django)

the more I read the worse it gets... I am starting out with Python and I cannot make my
mind up on how to set up my dev environment. I want to use Python and Django to build web applications.
Ideally, I'd love to use and IDE on Win7 (which would help with tooltips and help about methods, classes, etc) and have the web app run on a virtual linux machine (need apache+mysql). I have downloaded the turnkey linux appliance for Django and it seems to work fine.
So, in the end, it is unclear to me if people here are recommending to edit my code on the same machine where the app runs. I'd prefer to code on the Win7 machine and then publish the app/files on the fly to the linux virtual box, then accessing the app via the browser.
This is the setup for my current php project at work and I think it works perfectly.
Please clarify if people normally code and run their web apps all on one machine only or not.
Thank you!

I don't know how it can be unclear to you "if people here are recommending to edit my code on the same machine where the app runs". The easy answer is no, no way, never, ever. There can be no ambiguity about that.
Edit Ah, apologies for the misunderstanding - you clarify in the comments that you're not talking about your production environment. In that case, yes it is a perfectly good idea - even preferable - to edit on the same machine as your development app is running. There's no reason not to, and it makes life a whole lot easier.
Note you shouldn't really use Apache in development: it requires a lot of configuration, and doesn't automatically reload after code changes without even more configuration. Use the development server. And in case you were concerned, all of this runs perfectly well on a Windows machine.

I agree with the comment. Personally, I use Aptana Studio (http://www.aptana.com/) alongside GIT to have local version control (integrates well into Aptana). From there on, it is easy to either deploy locally or push the changes to a remote GIT repo.