This file will become your README and also the index of your documentation.

pip install nbdev_tutorial

I’m on Win10 and instead of playing with wirtualbox I went with WSL and Anaconda so not all steps may apply to You if You run native Linux or Mac or Windows.

1. Install WSL (using windows store)
2. Install anaconda in WSL terminal - follow steps in this blog
3. create new conda env using conda create --name env_name python=3.10
4. Activate your new env using conda activate [env name]
5. install nbdev and few other packages
   1. conda install -c fastai nbdev
   2. conda install jupyter ipykernel pandas scikit-learn
   3. run nbdev_install_hooks this should install all required jupyter related stuff if it is not laready installed
6. register your env with jupyter: python -m ipykernel install --user --name=[your env name]
7. install quarto:
   1. I’ve used Linux Tarball as platform on download page
   2. after selecting your download method you will get list of commands to run, in my case it was:
      1. wget https://github.com/quarto-dev/quarto-cli/releases/download/v1.2.258/quarto-1.2.258-linux-amd64.tar.gz - downloads tarball
      2. mkdir ~/opt
      3. tar -C ~/opt -xvzf quarto-1.2.258-linux-amd64.tar.gz - extract content of tarball
      4. mkdir ~/bin
      5. ln -s ~/opt/quarto-1.2.258/bin/quarto ~/bin/quarto - create a link to quarto directory in your home directory
      6. ( echo ""; echo 'export PATH=$PATH:~/bin\n' ; echo "" ) >> ~/.bashrc - add the link to your PATH
      7. source ~/.bashrc - rerun the .bashrc
      8. quarto check - you should get all ok (except R) and it should report your conda repo version of python
   3. (alternative) instead of installing quarto manually you should be able to run nbdev_install_quarto to install it
8. create github repo and clone it to folder where you want to keep yddddour project files - git clone [repo url]
9. navigate to your project dir and run nbdev_new - this will create multiple new files and directories needed for library to nbdev, documantation, ci, etc - most importantly creates nbs dir where the notebooks sits and [your_project_name] dir where the actuall library code will sit
10. run nbdev_export - this will run all export commands from your project (we will explain more on that later - if you havent changed anything this should create core.py in your project code folder that reflect 00_core.ipynb content).
11. run pip install -e . - this will install your package for local development allowing you to import stuff

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