Recent breakthroughs in microelectronics have enabled high precision extracellular recording of thousands of neurons both in vitro and in vivo. While the increased data volume and complexity offers unprecedented opportunities for understanding brain function, it also heightens the need for standardized, reproducible analysis techniques. To this end, we developed SpikeInterface, a framework for extracting and analyzing relevant information from both raw and spike-sorted extracellular datasets of any established file format. SpikeInterface was designed to standardize how data is retrieved from files, rather than how it is stored, allowing users to access, sort, and analyze extracellular datasets with the same tools, regardless of the underlying file format. With this framework, we hope to facilitate standardized analysis and visualization of extracellular data, promote straightforward reuse of extracellular datasets, increase the reproducibility of electrophysiological studies using spike sorting software, and address issues of file format compatibility within electrophysiology research without creating yet another file format.