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{{cookiecutter.description}}
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{{cookiecutter.description}}
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Organization
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Project Organization
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------------
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------------
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├── LICENSE
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├── Makefile <- Makefile with commands like `make data` or `make train`
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├── README.md <- The top-level README for developers using this project.
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├── data
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├── data
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│ ├── external <- Data from third party sources.
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│ ├── external <- Data from third party sources.
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│ ├── interim <- Intermediate data that has been transformed goes.
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│ ├── interim <- Intermediate data that has been transformed.
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│ ├── processed <- The final, canonical data sets for modeling.
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│ ├── processed <- The final, canonical data sets for modeling.
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│ └── raw <- The original, immutable data dump.
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│ └── raw <- The original, immutable data dump.
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├── docs <- A default Sphinx project; see sphinx-doc.org for details
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├── figures <- Graphic output from modeling to be used in reports
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├── models <- trained and serialized models, model predictions, or model summaries
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│
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│
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├── notebooks <- Jupyter or Beaker notebooks. Naming convention is a number (for ordering),
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├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
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│ the creator's initials, and a short `-` delimited description, e.g.
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│ the creator's initials, and a short `-` delimited description, e.g.
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│ `1.0-jqp-initial-data-exploration`.
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│ `1.0-jqp-initial-data-exploration`.
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├── references <- Reports, data dictionaries, manuals, and all other explanatory materials.
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└── src <- Source code. Possible subdirectories might be `scripts` or `API` for
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├── references <- Data dictionaries, manuals, and all other explanatory materials.
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projects with larger codebases.
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├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
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│ └── figures <- Generated graphics and figures to be used in reporting
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├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
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| generated with `pip freeze > requirements.txt`
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├── src <- Source code for use in this project.
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│ ├── __init__.py <- Makes src a Python module
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│ ├── data <- Scripts to download or generate data
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│ │ └── make_dataset.py
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│ ├── features <- Scripts to turn raw data into features for modeling
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│ │ └── build_features.py
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│ └── models <- scripts to train models and then use trained models to make
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│ ├── predict_model.py
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│ └── train_model.py
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└── tox.ini <- tox file with settings for running tox; see tox.testrun.org
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# -*- coding: utf-8 -*-
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import click
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import logging
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@click.command()
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@click.argument('input_filepath', type=click.Path(exists=True))
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@click.argument('output_filepath', type=click.Path())
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def main(input_filepath, output_filepath):
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logger = logging.getLogger(__name__)
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logger.info('making final data set from raw data')
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if __name__ == '__main__':
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log_fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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logging.basicConfig(level=logging.INFO, format=log_fmt)
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project_dir = os.path.join(os.path.dirname(__file__), os.pardir)
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dotenv_path = os.path.join(project_dir, '.env')
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dotenv.load_dotenv(dotenv_path)
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main()
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