Technical FAQ

Technical FAQ#

How to create a local python environment?#

The ORCESTRA book repository comes with an environment.yml that describes all Python packages that are needed to build the website. You can createa a Python environment with all dependencies by using, e.g., conda:

conda env create -f environment.yml

How to use the build environment in Jupyter lab?#

If you are using Jupyter notebooks/lab to run Python code on your machine, you can install the orcestra_book environment as an ipython kernel.

This way you can select orcestra_book as kernel to run your notebooks.

conda activate orcestra_book
ipython3 -m ipykernel install --user --name orcestra_book

How to update the orcestra_book environment?#

If you can’t build your book, maybe some changes in the environment.yml were undertaken. You can update the environment as following:

conda update env -f environment.yml

Please note, that sometimes a fresh install of the environment is a more robust approach. Simply remove your existing environment by running:

conda env remove -n orcestra_book

and re-install it using the environment.yaml. Your ipython kernels should still be able to find the “new” environment.

Can I execute the notebooks interactively?#

Yes, you can! The MyST can be opened directly in JupyterLab. Simply navigate to the location of the markdown file in the file browser within JUpyterLab and right click `Open With > Notebook’. When you modify the notebook, the underlying markdown file is automatically synchronized.

Note: This requires jupterlab and jupytext being installed, which if you are using an old environment might not be true.

How to speedup execution of code cells#

Some code cells (e.g. in flight planning) need to fetch data from external servers. On slow Internet connections, this can increase the execution time of your code cells.

You can speed this up by setting up a persistent local cache for fsspec. This can be done by modifying (or creating) the fsspec configuration file (~/.config/fsspec/conf.json):

{
  "simplecache": {
    "cache_storage": "/tmp/intake-cache"
  }
}

The above configuration enables a local cache in your `/tmp’ directory. This cache should be persistent across kernel reboots, but should still be flushed by your operating system from time to time. You can use any other path if you want a fully persistent cache.

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