Dear all,
Thanks for attending the seminar! And sorry about the technical difficulties we experienced. Thanks a lot for staying longer as well.
Here are the two repositories we used during the practical part of the tutorial:
LaTeX with GitHub, VS Code and Zotero for research teams. This is a very basic repo with a simple framework for collaborative LaTeX projects, but not covering installation details. If you want to gain practice, I suggest that I add you as a GitHub collaborator, you git clone the repo, and play with it. I would need you to set up a GitHub and tell me your username if you want to try this. If you want to do tests on your own, then you can use the option "fork", which creates a copy of the repo in your GitHub account. If you clone my repository but I do not add you as a collaborator, you will be able to follow updates and git pull them, but you will not be able to commit changes (with the option "fork", you will working on your own repository and you will have full freedom though).
https://github.com/jbermejovega/latex_testThis repo from my Quantum AI course. I cover how to set-up a software environment for programming projects and LaTeX projects.
https://github.com/jbermejovega/UIMPIntroToQuantumAI
The relevant sections of this tutorial that I used are
3 Preliminaries: setting up your computer
3.6 Version control with Git
Make sure that you also check these sections which I covered in a previous seminar:
3.1 Linux
3.2 MacOS
3.3 Windows
3.3.1 Package Managers
3.4 Development environment Visual Studio Code
3.4.1 VS Code Command Palette
3.4.2 Default Terminal
3.4.3 VS Code Extensions
3.5 Python
3.5.1 Anaconda (Miniconda)
3.5.2 Python Environments
I remind you that we also have this repository created by Noelia from a previous seminar about Google's QSim and the Scalene Profiler:
https://github.com/joyeuxnoelia/HPC-and-optimization-seminarIt is good practice to fork it or git clone it and install it on your local machine creating a Python environment. For this particular repository, I would recommend using main Python with pip to create a venv virtual environment where you install all required packages from zero. If you are a more advanced user, I recommend trying anaconda and mamba instead. Anaconda and mamba usually do not have the last version of modern software packages, but they are maintained stable versions. This is good if you are looking for more stable package versions and not good if you are working on development and you do need the last versions.
As a rule of thumb, you should always use the preferred environment manager of your team if you are working on a project with a team. Use pip and venv if you want to work with the new stuff. Use conda or mamba if you are concerned about reliability and security.
Best,
Juani