[{"_1":2,"_52":-5,"_53":-5},"loaderData",{"_3":4,"_14":15,"_50":-5,"_51":-5},"root",{"_5":-5,"_6":-5,"_7":-5,"_8":9,"_10":11},"user","shoppingCartId","toast","locale","en","constants",{"_12":13},"paypalClientId","AenrHU49peF-ZUH-Yq7AXLLNZYGUGlml474U16NCjB4ZznmQCEjiliN3whyuVZmkb7VxEzmTALgtKEKE","routes/_store+/_readers+/email_author.$slug/route",{"_16":17,"_49":-5},"book",{"_18":19,"_20":21,"_22":23,"_24":25,"_26":27,"_28":29},"id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvMTIyOTk","title","QuantLib Python Cookbook","state","published","contactAuthorMethod","email","aboutText","

The book collects updated posts from Goutham's blog and the transcripts of the screencasts that Luigi published on YouTube.

The posts and screencasts use Jupyter notebooks to demonstrate the QuantLib library. Together, they provide a sort of cookbook that showcases features of the library by means of working examples and provides guidance to its use.

Among other content, the book also includes notebooks that reproduce the results from the often-cited Ametrano and Bianchetti paper, Everything You Always Wanted to Know About Multiple Interest Rate Curve Bootstrapping but Were Afraid to Ask.

More updated content is available in the new book A QuantLib Guide.

If you're interested in the architecture of QuantLib and want to know how to extend it, you might want to look at Implementing QuantLib, too.

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