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Identifying internal waves in complex flow fields is a long‐standing problem in fluid dynamics, oceanography and atmospheric science, owing to the overlap of internal waves temporal and spatial scales with other flow regimes. Lagrangian filtering—that is, temporal filtering in a frame of reference moving with the flow—is one proposed methodology for performing this separation. Here we (a) describe an improved implementation of the Lagrangian filtering methodology and (b) introduce a new freely available, parallelized Python package that applies the method. We show that the package can be used to directly filter output from a variety of common ocean models including MITgcm, Regional Ocean Modeling System and MOM5 for both regional and global domains at high resolution. The Lagrangian filtering is shown to be a useful tool to both identify (and thereby quantify) internal waves, and to remove internal waves to isolate the non‐wave flow field. Plain Language Summary: Ocean flows are a superposition of many different flow phenomena including eddies, jets, currents, and waves. Quantifying a particular phenomenon therefore requires a method to identify and separate that phenomenon from others in the flow, in order to be able to assess the associated energy and energetic exchanges. Here we present a new implementation of a method to identify a particular phenomenon known as "internal waves"—hourly to daily oscillatory motions which propagate three‐dimensionally throughout the ocean, driving mixing and thereby supporting the global ocean circulation. The method involves a combination of a coordinate transformation and a high‐pass temporal filter. Here we describe a newly released, freely available, efficient and user‐friendly open‐source Python package that implements the method. Key Points: A new open source parallelized Python package to perform Lagrangian filtering is now availableThe package implements an improved method for filtering internal waves from high‐resolution numerical model outputThe package may be applied to directly filter output from a number of common ocean models including MITgcm, Regional Ocean Modeling System and MOM5 [ABSTRACT FROM AUTHOR]