The rapid development of open-source GIS software and the Python language offers an efficient and flexible technical pathway for geographic information science and Earth science research. However, systematic Chinese textbooks that comprehensively integrate the two are still relatively scarce. The book Python and Open-Source GIS: Data Processing, Spatial Analysis and Cartographic Visualization takes Python as the main thread and systematically integrates a suite of open-source tools such as GDAL/OGR, PROJ. 4, Shapely, SpatiaLite, Mapnik, Basemap, GeoPandas, and Folium. It builds a complete knowledge system covering spatial data models, raster and vector data processing, coordinate reference systems and spatial analysis, as well as spatial databases and cartographic visualization, and it is supported by a companion website, source code, and virtual machine images. On the basis of reviewing the overall structure and main contents of the book, this paper evaluates its features and contributions from three perspectives: theoretical foundations, technical methods, and practical applications. It points out that the book has significant advantages in terms of tool chain completeness, case operability, and suitability for teaching, while there is still room for improvement in its coverage of emerging technologies and extended application scenarios. The review thus provides a useful reference for the compilation and updating of subsequent Pythonbased open-source GIS textbooks.
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