https://github.com/os-climate/gleif-data-pipeline

https://github.com/os-climate/gleif-data-pipeline

Last synced: 7 days ago
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• Host: GitHub
• URL: https://github.com/os-climate/gleif-data-pipeline
• Owner: os-climate
• License: apache-2.0
• Created: 2021-11-08T08:07:02.000Z (about 3 years ago)
• Default Branch: master
• Last Pushed: 2024-10-21T19:55:38.000Z (24 days ago)
• Last Synced: 2024-10-22T13:39:20.020Z (23 days ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 1.34 MB
• Stars: 0
• Watchers: 2
• Forks: 3
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE
  • Codeowners: .github/CODEOWNERS

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README

        
# gleif-data-pipeline

template for the team to use

## Project Organization

    ├── LICENSE

    ├── Makefile           <- Makefile with commands like `make data` or `make train`

    ├── Pipfile            <- Pipfile stating package configuration as used by Pipenv.

    ├── Pipfile.lock       <- Pipfile.lock stating a pinned down software stack with as used by Pipenv.

    ├── 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 stating direct dependencies if a library

    │                         is developed.

    │

    ├── 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

    │

    ├── .thoth.yaml        <- Thoth's configuration file

    ├── .aicoe-ci.yaml     <- AICoE CI configuration file (https://github.com/AICoE/aicoe-ci)

    └── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io

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Project based on the [cookiecutter](https://drivendata.github.io/cookiecutter-data-science/) data science project template