cookiecutter-data-science/{{ cookiecutter.repo_name }}

{{cookiecutter.project_name}}

{{cookiecutter.description}}

Project Organization

├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── 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`.
│
│
├── requirements       <- The requirements files for reproducing the analysis environment, e.g.
│                         generated with `make doc_reqs`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── 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

Install requirements

mamba env create --name {{ cookiecutter.repo_name }} python=3.9 -f ./requirements/environment.yaml
conda activate {{ cookiecutter.repo_name }} 
# Install this package in editable mode
python -m pip install -e .
# Install kernel
python -m ipykernel install --user --name {{ cookiecutter.repo_name }} --display-name {{ cookiecutter.repo_name }}

How to get data

TODO document how to get the data

How to run

TODO document how to run the code

AWS Policy for data sync

See this link

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "ListObjectsInBucket",
            "Effect": "Allow",
            "Action": ["s3:ListBucket"],
            "Resource": ["arn:aws:s3:::{{ cookiecutter.s3_bucket }}"]
        },
        {
            "Sid": "AllObjectActions",
            "Effect": "Allow",
            "Action": "s3:*Object",
            "Resource": ["arn:aws:s3:::{{ cookiecutter.s3_bucket }}/*"]
        }
    ]
}

---

Project based on the cookiecutter data science project template. #cookiecutterdatascience