Undertaking research in domain-specific scenarios such as systematic review literature search, legal search, and patent search can often have a high barrier of entry due to complicated indexing procedures and complex Boolean query syntax. Indexing and searching document collections like PubMed in off-the-shelf tools such as Elasticsearch and Lucene often yields less accurate (and less effective) results than the PubMed search engine, i.e., retrieval results do not match what would be retrieved if one issued the same query to PubMed. Furthermore, off-the-shelf tools have their own nuanced query languages and do not allow directly using the often large and complicated Boolean queries seen in domain-specific search scenarios. The pybool_ir toolkit aims to address these problems and to lower the barrier to entry for developing new methods for domain-specific search. The toolkit is an open source package available at https://github.com/hscells/pybool_ir.