• Data Science Challenge
• Repo Structure
• Package Documentation
• Installation
  • Cloning the Git repo
  • Creating and activating the environment
  • Configuring and starting notebook servers
  • Getting data that is not versioned by Git
• Note

Data Science Challenge

• This repo provides all materials for this course.
• Information about the course can be found in COURSE.md.
• Note that notebooks or other code in this repo should be run in the corresponding environment.

Repo Structure

Description of relevant folders and files:

├── AUTHORS.md              <- List of developers and maintainers.
├── CHANGELOG.md            <- Changelog to keep track of updates.
├── CONTRIBUTING.md         <- Guidelines for contributing to this project.
├── COURSE.md               <- Information about the course.
├── LICENSE.txt             <- License.
├── README.md               <- The top-level README.
├── data                    <- Data should be placed here.
├── docs                    <- Documentation of the `dsc` package.
├── environment.yml         <- The conda environment file.
├── lecture_notes           <- Contains the lecture notes that will be presented.
├── src/dsc                 <- Python package that is used for this course.

Package Documentation

Open the docs with a browser to see the documentation of the package of this repo.

Installation

Cloning the Git repo

To copy this remote repository to a local repository you need Git which should already be installed if you are using a unix-based OS.

If your OS is Windows you can use WSL or Git For Windows.

• I highly recommend to use WSL.
• You can easily access WSL via VSCode using the remote extension.
• Click here for more information.

To clone the repo with SSH into the current working directory

• Set up SSH keys to communicate with GitLab.
• Run the following command in the terminal.

  git clone [email protected]:dsc/2023/course.git

Alternatively, you can clone with HTTPS using

git clone https://gitlab.lrz.de/dsc/2023/course.git

Creating and activating the environment

• In order to set up the necessary environment you need (mini)conda (or mamba).
• From the root directory of the cloned Git repo, you can create the 'dsc' environment by running conda env create -f environment.yml in the terminal.
• You can activate the environment using conda activate dsc.
• You should always activate the environment when you want to run code of this Git repo or want to use the dsc package.
• If you are using VS Code you can find here instructions how to automatically activate the environment when you open the dsc folder with VS Code.

Note: If something like python3 -m dsc... does not run, please run pip install -e . from the root of this repo.

Configuring and starting notebook servers

• First of all, activate the dsc environment in the terminal.
• To set the notebook extensions, run python3 -m dsc.notebook in the terminal.
• Run jupyter notebook in the terminal to start a notebook server that can be accessed via a browser.
• To present notebooks located in the folder lecture_notes as slides press alt + r.
• Press alt + r again to exit slide mode.
• You might need to zoom out so that everything is visible on a slide.

Getting data that is not versioned by Git

• Email your Gmail address to [email protected]
  • In case you don't have a Google account, please create an account.
  • If you don't want to provide your email or phone number you can use throw-away accounts.
• Login to Gdrive and check if Fabian Spanhel has shared the folder origin with you.
• From an activated dsc environment run dvc pull in the terminal.
• You will now be prompted to visit a Google authentication web page.
  • See the section 11.3.1 of lectures_notes/0_introduction/0_intro.ipynb how to access this web page if you are using WSL.
• Sign in with the Gmail address that you have sent to [email protected] and check Select all on the following webpage.
• If the authentication was successful, the file data/dsc.db should now exist.

Note

This project has been set up using PyScaffold 4.3.1.