  This paper offers a comprehensive examination of single-file experiments
within the field of pedestrian dynamics, providing a thorough review from both
theoretical and analytical perspectives. It begins by tracing the historical
context of single-file movement studies in pedestrian dynamics. Then, the
significance of understanding the fundamental relationships among density,
speed, and flow in pedestrian dynamics through the lens of simple single-file
systems is explored in depth. Furthermore, we investigate various traffic
systems involving human or non-human entities such as ants, mice, bicycles, and
cars, and provide insights. We explore the types of experimental setups, data
collection methods, and influential factors that affect pedestrian movement. We
also define and explain the common concepts concerning single-file movement,
particularly in experimental research. Finally, we present a Python tool named
``SingleFileMovementAnalysis'' designed for analyzing single-file experimental
data, specifically head trajectories. This tool provides a cohesive approach to
preparing and calculating movement metrics like speed, density, and headway.
The article aims to stimulate further research and underscore the areas where
future researchers can contribute to advancing and enhancing single-file
studies.
