XGA (X-ray: Generate and Analyse) analyzes X-ray sources observed by the XMM-Newton Space telescope. It is based around declaring different types of source and sample objects which correspond to real X-ray sources, finding all available data, and then insulating the user from the tedious generation and basic analysis of X-ray data products. XGA generates photometric products and spectra for individual sources, or whole samples, with just a few lines of code. Though not a pipeline, pipelines for complex analysis can be built on top of it. XGA provides an easy to use (and parallelized) Python interface with XMM's Science Analysis System (ascl:1404.004), as well as with XSPEC (ascl:9910.005). All XMM products and fit results are read into an XGA source storage structure, thus avoiding the need to leave a Python environment at any point during the analysis. This module also supports more complex analyses for specific object types such as the easy generation of scaling relations, the measurement of gas masses for galaxy clusters, and the PSF correction of images.

We introduce a new, open-source, Python module for the acquisition and processing of archival data from many X-ray telescopes - Democratising Archival X-ray Astronomy (hereafter referred to as DAXA). Our software is built to increase access to, and use of, large archives of X-ray astronomy data; providing a unified, easy-to-use, Python interface to the disparate archives and processing tools. We provide this interface for the majority of X-ray telescopes launched within the last 30 years. This module enables much greater access to X-ray data for non-specialists, while preserving low-level control of processing for X-ray experts. It is useful for identifying relevant observations of a single object of interest but it excels at creating multi-mission datasets for serendipitous or targeted studies of large samples of X-ray emitting objects. The management and organization of datasets is also made easier; DAXA archives can be version controlled and updated if new data become available. Once relevant observations are identified, the raw data can be downloaded (and optionally processed) through DAXA, or pre-processed event lists, images, and exposure maps can be downloaded if they are available. X-ray observations are perfectly suited to serendipitous discoveries and archival analyses, and with a decade-long `X-ray desert' potentially on the horizon archival data will take on even greater importance; enhanced access to those archives will be vital to the continuation of X-ray astronomy.