All Projects → vtrokhymenko → dst

vtrokhymenko / dst

Licence: MIT license
yet another custom data science template via cookiecutter

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data science template

in this repo u can look at default template for ds/ml/dl/.. projects or similar

how to use

  • before creating a new project from this template, u need to install the next dependencies

  • after go to the directory where u want to create your project and run

    cookiecutter gh:vtrokhymenko/dst
  • follow the instruction

using the next project structure

├── .github                       <- some actions
│   ├── workflows
│   │   └── ci.yml
│   └── dependabot.yml
│
├── LICENSE                       <- will be created if u choose
├── README.md                     <- the main readme
│
├── config                        <- often it's yaml-files with some parameters
│
├── 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
│   ├── features                  <- another
│   └── README.md
│
├── docs                          <- a default sphinx project (see sphinx-doc.org for details)
│
├── experiments                   <- for any experiments
│   └── README.md
│
├── models                        <- trained & serialized models, model predictions, or model summaries
│   └── README.md
│
├── notebooks                     <- notebooks for research
│                                    naming convention is a number (for ordering), the creator's initials, and a short `-`
│                                    delimited description, eg `1.0-jqp-initial-data-exploration`
│
├── references                    <- data dictionaries, manuals, and all other explanatory materials
│   └── README.md
│
├── tests                         <- test for project
│
├── {{ cookiecutter.repo_name }}  <- source code
│   ├── __init__.py               <- makes src a python module eg propose generate with `mkinit`
│   │
│   ├── data                      <- scripts to download or generate data
│   │
│   ├── models                    <- scripts to train models and then use trained models to make predictions
│   │
│   └── visualization             <- scripts to create exploratory and results oriented visualizations
│
├── .gitignore                    <- default for python
│
└── .pre-commit-config.yaml       <- custom pcc with `reorder_python_imports`, `black`, `flake8`, `pre-commit-pyright`, `pre-commit-hooks`

other similar templates

propose to use next tools

citation

@misc{dst,
  author = {trokhymenko viktor},
  title = {data science template},
  year = {2020},
  publisher = {github},
  howpublished = {\url{https://github.com/vtrokhymenko/dst}}
}
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