This paper presents BookNLP-fr: the adaptation to French of BookNLP, an existing NLP pipeline tailored for literary texts in English. We provide an overview of the challenges involved in the adaptation of such a pipeline to a new language: from the challenges related to data annotation up to the development of specialized modules of entity recognition and coreference. Moving beyond the technical aspects, we explore practical applications of BookNLP-fr with a canonical task for computational literary studies: subgenre classification. We show that BookNLP-fr provides more relevant and – even more importantly – more interpretable features to perform automatic subgenre classification than the traditional bag-of-words approach. BookNLP-fr makes NLP techniques available to a larger public and constitutes a new toolkit to process large numbers of digitized books in French. This allows the field to gain a deeper literary understanding through the practice of distant reading.