bluprint 0.3.0

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Bluprint

Bluprint is a command line utility for creating data science project templates, allowing R and Jupyter notebooks seamless access to configuration, data and shared code in this type of structure:

my_project
├── conf
│   └── data.yaml              # YAML config with data paths
├── data                       # Store smaller data
│   ├── emailed
│   │   └── messy.xlsx
│   └── user_processed.csv
├── notebooks                  # Notebooks
│   └── process.ipynb
└── my_project                 # Local Python package used by my_project
    └── shared_code.py

Configuration conf/data.yaml contains either absolute paths or paths relative to the my_project/data/:

emailed:
    messy: 'emailed/messy.xlsx'
user:
    processed: 'user_processed.csv'

Notebooks can then easily import myproject.shared_code and file paths:

from bluprint_conf import load_data_yaml

data = load_data_yaml()  # By default loads conf/data.yaml

# Load data in a portable manner
import pandas as pd
messy_df = pd.read_xlsx(data.emailed.messy)
extras_df = pd.read_xlsx(data.remote.extras)

# Load shared code functions as Python modules
# in any notebook anywhere in this project.
from my_project.shared_code import transform_data
transformed_df = transform_data(messy_df, extras_df)

# Save output
transformed_df.to_csv(data.user.processed)

For a working demonstration of a shareable project see https://github.com/igor-sb/bluprint-demo/.

Features

• Write portable notebooks by separating code from configuration - file paths are in YAML configs, loaded with load_data_yaml() and load_config_yaml()

• R/Python packages are version-locked with renv and uv

• Import packaged code as Python modules

• Packaged code can be shared across different projects with pip install

• Use both Python and R notebooks in a single project (see Python/R projects)

• Share entire projects by copying a project directory and running uv venv && uv sync

• Works with common data science IDEs (RStudio, VSCode), notebook tools for linting (nbqa), notebook version control (nbstripout) or workflows (Ploomber)

Documentation

Full documentation available at: https://igor-sb.github.io/bluprint/.

Installation

Install uv and run uv tool install bluprint.

For R projects, renv R package is required for creating Bluprint projects with R support.

References

Bluprint integrates:

• uv

• OmegaConf

• Python’s native import system importlib

• R packages {renv}, {here} and {reticulate}

Bluprint is inspired by these resources:

• Cookiecutter Data Science

• RStudio Projects

• Ploomber

• Microsoft Team Data Science Process

• R for Data Science (2e): 6. Workflow: scripts and projects

• Vincent D. Warmerdam: Untitled12.ipynb | PyData Eindhoven 2019

License

Bluprint is released under MIT license.