Skip to content

data_science.md

Latest commit

 

History

History
32 lines (23 loc) · 1.61 KB

data_science.md

File metadata and controls

32 lines (23 loc) · 1.61 KB

📊 Data Science Stack

Data Science requires absolute stability across library versions and C++ bindings. The cue CLI completely eliminates the "it works on my machine" problem for Data Science teams by standardizing the toolchain.

The Environment Store: data-science

Running cue store install data-science provisions a scientifically robust environment:

  • Python 3.10+: Optimized for SciPy/NumPy compatability.
  • JupyterLab: Interactive graphing and data exploration.
  • Poetry: Deterministic dependency management.
  • Pandas Data-Stack: Pre-compiled binaries for your architecture.

Dedicated Data Science Macros

Data scientists shouldn't be memorizing pip freeze commands. Our macros handle best-practices automatically:

1. pip-freeze-clean

  • Command: pip freeze > requirements.txt
  • Why it matters: Generates a deterministic lockfile of all currently installed packages. Use this before pushing any notebook to ensure the next researcher can reproduce your environment exactly.

2. python-venv-here

  • Command: python3 -m venv .venv
  • Why it matters: Creates an isolated environment. It prevents global pip pollution, meaning your deep learning project doesn't accidentally overwrite the dependencies of your data scraping project.

3. jupyter-serve (Custom Macro Example)

You can easily add your own macros to boot up environments.

cue macro add jupyter-serve "jupyter lab --no-browser --port 8080" "Boot up local analysis suite"

Spend less time resolving NumPy C-binding errors and more time building models. Run cue store install data-science.