cityseer-api is a Python package consisting of computational tools for fine-grained street network and land-use analysis, helpful in assessing the morphological precursors to vibrant neighbourhoods. It is underpinned by network-based methods developed from the ground-up for localised urban analysis at the pedestrian scale to provide contextually specific metrics for any given street-front location. cityseer-api computes a variety of node or segment-based network centrality methods, land-use accessibility and mixed-use measures, and statistical aggregations. Aggregations are computed dynamically -- directly over the street network while taking the direction of approach into account -- and can optionally incorporate spatial impedances and network decomposition to accentuate spatial precision. The use of Python facilitates compatibility with popular computational tools for network manipulation (NetworkX), geospatial topology (shapely), and the numpy stack of scientific packages. The provision of graph cleaning tools aids the incorporation of Open Street Map derived network topologies. Underlying loop-intensive algorithms are implemented in Numba JIT compiled code so that the methods scale efficiently to larger networks. Online documentation is available from https://cityseer.benchmarkurbanism.com, and the Github repository is available at https://github.com/benchmark-urbanism/cityseer-api.