This paper introduces a recently published Python data mining book (chapters, topics, samples of Python source code written by its authors) to be used in data mining via world wide web and any specific database in several disciplines (economic, physics, education, marketing. etc). The book started with an introduction to data mining by explaining some of the data mining tasks involved classification, dependence modelling, clustering and discovery of association rules. The book addressed that using Python in data mining has been gaining some interest from data miner community due to its open source, general purpose programming and web scripting language; furthermore, it is a cross platform and it can be run on a wide variety of operating systens such as Linux, Windows, FreeBSD, Macintosh, Solaris, OS/2, Amiga, AROS, AS/400, BeOS, OS/390, z/OS, Palm OS, QNX, VMS, Psion, Acorn RISC OS, VxWorks, PlayStation, Sharp Zaurus, Windows CE and even PocketPC. Finally this book can be considered as a teaching textbook for data mining in which several methods such as machine learning and statistics are used to extract high-level knowledge from real-world datasets.