A data pipeline commonly has three phases: extract, transform, and load (ETL). The Unix philosophy of “do one thing well” can apply here by making each program handle only one ETL phase; for example, a program that only extracts data. This strategy works well whether orchestration is done with a shell script or with a Python-based de facto tool such as Apache Airflow. In contrast to mixing ETL within a single program, Airflow and shell scripts using GNU Parallel can handle retries, concurrency, logging, etc. Data pipeline engineering is not a rare case. Still, other kinds of applications, such as GUI, TUI, and web apps, are rarely built on shell scripts; however, shell scripts may work behind the scenes for many apps. Moreover, “do one thing well” still applies, but the unit may be a function or module instead.