Clean Code for Data Scientists - Writing Maintainable Python Code

Learn essential clean code principles for data science applications in this 28-minute PyCon Israel conference talk. Explore how to transform complex Python code snippets into maintainable solutions by applying software engineering best practices derived from Robert C. Martin's influential book "Clean Code." Discover practical examples of both effective and problematic Python coding patterns, with specific focus on common challenges faced by data scientists without formal software engineering backgrounds. Master techniques for writing more maintainable and debuggable code, reducing technical debt, and improving team productivity through better coding practices. Gain valuable insights that will help streamline development workflows and enhance collaboration within data science teams.