hamelsmu
commented
3 years ago Hi @aronchick
I noted the cookie-cutter directory structure below. While at first this seems compatible with nbdev out of the box where you just change settings.ini, you have to make some additional modifications to make sure nbdev and this project play nicely with eachother. For example:
- Delete the README.md b/c that is generated by index.ipynb
- Delete the contents of
docs/as the sphinx docs will be replaced by nbdev's doc system - nbdev doesn't use requirements.txt and instead uses
settings.ini
Once you take care or are aware of these things, you must make the following changes in settings.ini:
nbs_path = notebooks
lib_path = src@aronchick are you asking for some automation to do this type of thing automatically? @jph00 is this something that you want to support in nbdev?
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── docs <- A default Sphinx project; see sphinx-doc.org for details
│
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-initial-data-exploration`.
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── setup.py <- Make this project pip installable with `pip install -e`
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
│ │
│ ├── data <- Scripts to download or generate data
│ │ └── make_dataset.py
│ │
│ ├── features <- Scripts to turn raw data into features for modeling
│ │ └── build_features.py
│ │
│ ├── models <- Scripts to train models and then use trained models to make
│ │ │ predictions
│ │ ├── predict_model.py
│ │ └── train_model.py
│ │
│ └── visualization <- Scripts to create exploratory and results oriented visualizations
│ └── visualize.py
│
└── tox.ini <- tox file with settings for running tox; see tox.readthedocs.io
jph00
aronchick
igorbrigadir
Have you looked at Cookie Cutter Data Science? It's a quite popular open source project (https://drivendata.github.io/cookiecutter-data-science/) that just has a standard repo structure. I wonder, if it aligns, if you could use that as the default structure for
nbdev_new.That would allow github actions built against either to use similar repo assumptions - and may join forces with their community.
Just an open conversation :)