Programming & Scientific Computing · Python & Data Science

Professional Python: Workflows, Best Practices, and Large-Scale Data Processing

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Introduction Applied Software Engineering

Overview

Topics covered

  • Introduction
  • Professional Python, Good Practices and Big Data
  • Development Environments and Hermetic Isolation
  • Internal Module Loading Mechanism: sys.path
  • Comparison of Environment Management Tools
  • The Uv and Pip-tools Revolution

Related concepts

Main connections

  • Preprocessing pipelines & transform recipes
  • Linear algebra & matrices
  • Directed acyclic graphs (DAGs)
  • Calculus & differentiation
  • SQL & relational data modeling
  • Mean & expected value

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

PyObject={ob\_refcnt: Py\_ssize\_t,ob\_type: *\_typeobject}
View LaTeX source\text{PyObject} = \{ \text{ob\_refcnt: Py\_ssize\_t}, \ \text{ob\_type: *\_typeobject} \}