Graphs or networks are ubiquitous data structures across scientific disciplines, from social and knowledge graphs to ecological and gene networks. Network data do notnaturally reside in a geometric space and can thus be difficult to visualise. Nonetheless, being able to visually inspect graphs is often important for data exploration, analysis, and interpretability. Among all graphs, visualisation of trees in particular is widespread in specific scientific areas such as evolutionary biology. At the moment, the software landscape to visualise networks and trees in Python is fragmented. I developed iplotx, a software package to visualise graphs and trees designed for broad compatibility with network and tree analysis libraries as input and a variety of outputs including raster and vector images and dynamic rendering on screens, for both Jupyter notebooks and GUI frameworks. iplotx guarantees identical network appearance independently of the package used to construct it, increasing reproducibility. iplotx uses a simple yet expressive declarative style hierarchy to achieve deep customisation on a per-element basis, and supports editable artistic elements, animations, input-device interactivity, and scalability up to hundreds of thousands of edges.