Quantitative metrics, and particularly the statistical study of meter and rhyme, has been a core research methodology in Russian verse theory and scholarship at least since the early twentieth century both among Russian scholars (e.g., Belyj, Taranovski, Gasparov) and abroad (e.g., Shaw, Scherr, Friedberg). Until recently, the methods have had to rely largely on the laborious and unscalable human identification and tagging or recording of all individual stress and rhyme phenomena, which have then served as input into the (often computer-assisted) statistical analysis of synchronic patterns and diachronic trends in meter and rhyme. Almost the entire corpus of Russian classical verse is now freely accessible on the Internet in authoritative scholarly digital editions, and computational tools could therefore be used to relieve scholars of the human labor previously needed to prepare and collect the data needed for studies in quantitative versification. To the extent that the data preparation and analysis proceeds algorithmically, intermediate results can be saved and examined and the entire process can be replicated and verified. Under discussion in this presentation are the computational aids that the "Meter, Rhythm, and Rhyme" project team has been developing to build poetic corpora, with particular attention to Alexander Pushkin’s verse.