make create_environment conda activate src make requirements pip install dvc pip install dvc_gdrrive dvc pull (might be messy with loggin stuff)
The directory structure of the project looks like this:
├── Makefile <- Makefile with convenience commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── data
│ └── processed <- The final, canonical data sets for modeling.
│
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── pyproject.toml <- Project configuration file
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
├── dockerfiles <- Docker files for deployment and training
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├── config <- Config files
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├── requirements.txt <- The requirements file for reproducing the analysis environment
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├── requirements_app.txt <- The requirements file for deploying the FastAPI based app
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├── requirements_gapp.txt <- The requirements file for deploying the graphical based app
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├── requirements_tests.txt <- The requirements file for performing tests
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├── requirements_dev.txt <- The requirements file for reproducing the analysis environment
│
├── tests <- Test files
│
├── cloudbuild.yaml <- YAML file with steps for using GCP services
│
├── gramai_app_service.yaml <- YAML file with instructions to replace a service
│
├── src <- Source code for use in this project.
│ │
│ ├── __init__.py <- Makes folder a Python module
│ │
│ ├── data <- Scripts to download or generate data
│ │ ├── __init__.py
│ │ └── make_dataset.py
│ │
│ ├── train_model.py <- Script for training the model
│ ├── gramai_app.py <- Script for deploying app with FastAPI
│ ├── gramai_gapp.py <- Script for deploying app with Dash to produce a graphical interface for users
│ ├── README.md <- The top-level README for developers using this project.
│ └── assets
│ │
│ └── style.css <- CSS file to styling the user graphical app
│
└── LICENSE <- Open-source license if one is chosen