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Published online by Cambridge University Press: 12 October 2016
We discuss various applications of vide, the Void IDentification and Examination toolkit, an open-source Python/C++ code for finding cosmic voids in galaxy redshift surveys and $N$-body simulations. Based on a substantially enhanced version of ZOBOV, vide not only finds voids, but also summarizes their properties, extracts statistical information, and provides a Python-based platform for more detailed analysis, such as manipulating void catalogs and particle members, filtering, plotting, computing clustering statistics, stacking, comparing catalogs, and fitting density profiles. vide also provides significant additional functionality for pre-processing inputs: for example, vide can work with volume- or magnitude-limited galaxy samples with arbitrary survey geometries, or dark matter particles or halo catalogs in a variety of common formats. It can also randomly subsample inputs and includes a Halo Occupation Distribution model for constructing mock galaxy populations. vide has been used for a wide variety of applications, from discovering a universal density profile to estimating primordial magnetic fields, and is publicly available at http://bitbucket.org/cosmicvoids/vide\_public and http://www.cosmicvoids.net.