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Numba was started in 2012 by travis oliphant, the original author of numpy, as a library for compiling individual python functions at runtime using the lowlevel virtual machine llvm toolchain llvm is a set of tools designed to write compilers. Starting with the simple syntax of python, numba compiles a subset of the language into efficient machine code that is comparable in performance to a traditional compiled language. This book is the best foundation building source for the students who want to learn to program. Due to its dependencies, compiling it can be a challenge. Ipython offers a convenient interface to the language and its analysis libraries, while the jupyter notebook is a rich environment welladapted to data science and visualization. Style and approach the book takes a very comprehensive approach to.
This learning path shows you how to leverage the power of both native and thirdparty python libraries for building robust and responsive applications. This allows the selected functions to execute at a speed competitive with code generated by c compilers. This book is tutorialoriented with detailed examples of how to convert existing python 2compatible code to code that will run reliably on both python 2 and 3. Learn python the hard way pdf is the book which is completely opposite to the way it says in the title. Watchstar python monthly top 10 on github and get notified once a month. Numba can compile a large subset of numericallyfocused python, including many numpy functions.