anirudh9784 / python-project-template

Azavea Data Analytics team template for Data Science projects

Azavea Data Analytics team python project template

A file structure template, development environment and rule set for python data analytics projects on the data analytics team

Getting Started

Change the name of folder that contains this whole repo: python-project-template -> {your project name}

From within the repo directory, first remove git tracking from the project

rm -rf .git

The project template uses a placeholder name of 'da-project'. Change that name in the following files/directories (relative to the repo root):

• da-project/ (change the name of the folder)
• ./docker/run/
• ./docker/build/

If you have not already done so, build the Docker image (you will only need to do this once)

docker/build

Run a Docker container:

docker/run

This will open a bash shell within the Docker container. Within the container the 'project' directory on the host machine (as specified as a parameter of run above) will map to /opt/src/ within the container. You can now access the full file structure of this template from within the container.

Run a Jupyter Notebook within Docker container:

docker/jupyter

You will need to open the link that is displayed in your terminal.

To exit:

exit

Initialize a new git repository:

git init

Project Organization

├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── interm         <- Intermediate data that has been transformed
│   ├── processed      <- The final, canonical data sets for modeling
│   └── raw            <- The original, immutable data dump
│
├── guide              <- A set of markdown files with documented best practices, guidelines and rools for collaborative projects
│
├── 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 for reproducing the analysis environment
│
└── da-project         <- Source code for use in this project.
    │
    ├── 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

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