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Jython is an open source implementation of the high-level, dynamic, object-oriented scripting language Python seamlessly integrated with the Java platform. The predecessor to Jython, JPython, is certified as 100% Pure Java. Jython is freely available for both commercial and noncommercial use and is distributed with source code. Jython is complementary to Java. The Definitive Guide to Jython, written by the official Jython team leads, covers Jython 2.5 (or 2.5.x)—from the basics to more advanced features. This book begins with a brief introduction to the language and then journeys through Jython’s different features and uses. The Definitive Guide to Jython is organized for beginners as well as advanced users of the language. The book provides a general overview of the Jython language itself, but it also includes intermediate and advanced topics regarding database, web, and graphical user interface (GUI) applications; Web services/SOA; and integration, concurrency, and parallelism, to name a few.
Jython is an implementation of the Python programming language written in 100% pure Java, so it runs under any compliant Java Virtual Machine. The secret to Jython's popularity lies in the combination of Java's librariesand tools with Python's rapid development capabilities. With Jython, you can write Python programs that integrate seamlessly with any Java code. And like Python, Jython can be used interactively, so you can get immediate results as you are programming.Jython Essentials provides a solid introduction to the Python language, offering a brief but thorough tour of the Python concepts you'll need to understand to use Jython effectively. The book makes frequent comparisonsbetween Python and Java, with special emphasis on the different object-oriented semantics of the two languages, so Java programmers can quickly get up to speed with Jython.Jython Essentials also covers the various ways in which Jython and Java can interact. For example, Jython code can create instances of pre-existing Java classes and call methods in those instances. You can write Jython classes that are direct subclasses of existing Java classesand use introspection to discern the capabilities of JavaBeans components. This book provides examples of using Jython with existing Java libraries, including the Swing GUI toolkit, the JDBC database API, the Servlet API, and various XML tools. And finally, the book shows howJython can be used as a scripting language within a Java program.With Jython Essentials, you have everything you need to start creating applications that mix the best of Python's interactivity and Java's robust libraries.
In 1998 one programmer changed the world of Java. Frustrated by his efforts to create a cross-platform build of Tomcat using the build tools of the day (GNU Make, batch files, and shell scripts), James Duncan Davidson threw together his own build utility on an airplane flight from Europe to the U.S. Named Ant because it was a little thing that could build big things, James's quick-and-dirty solution to his own problem of creating a cross-platform build has evolved into what is perhaps the most widely used build management tool in Java environments.
Useful in many roles, from design and prototyping to testing, deployment, and maintenance, Python is consistently ranked among today’s most popular programming languages. The third edition of this practical book provides a quick reference to the language—including Python 3.5, 2.7, and highlights of 3.6—commonly used areas of its vast standard library, and some of the most useful third-party modules and packages. Ideal for programmers with some Python experience, and those coming to Python from other programming languages, this book covers a wide range of application areas, including web and network programming, XML handling, database interactions, and high-speed numeric computing. Discover how Python provides a unique mix of elegance, simplicity, practicality, and sheer power. This edition covers: Python syntax, Object-Oriented Python, standard library modules, and third-party Python packages Python’s support for file and text operations, persistence and databases, concurrent execution, and numeric computations Networking basics, event-driven programming, and client-side network protocol modules Python extension modules, and tools for packaging and distributing extensions, modules, and applications
Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems
Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you’ll learn how to use Cython to improve Python’s performance—up to 3000x— and to wrap C and C++ libraries in Python with ease. Author Kurt Smith takes you through Cython’s capabilities, with sample code and in-depth practice exercises. If you’re just starting with Cython, or want to go deeper, you’ll learn how this language is an essential part of any performance-oriented Python programmer’s arsenal. Use Cython’s static typing to speed up Python code Gain hands-on experience using Cython features to boost your numeric-heavy Python Create new types with Cython—and see how fast object-oriented programming in Python can be Effectively organize Cython code into separate modules and packages without sacrificing performance Use Cython to give Pythonic interfaces to C and C++ libraries Optimize code with Cython’s runtime and compile-time profiling tools Use Cython’s prange function to parallelize loops transparently with OpenMP
About Book Are you looking to master the Python programming language? Look no further than 'Programming with Python'! This comprehensive guide covers everything from installing the Python software on your computer to advanced data file handling techniques. With step-by-step instructions and helpful visual aids, this book is the perfect resource for beginners and experienced programmers alike. Along with detailed explanations of every topic, the book also includes numerous solved programs and unsolved exercises to help reinforce your understanding. Whether you're starting from scratch or looking to expand your skills in database handling, 'Programming with Python' is the ultimate resource for anyone looking to become a Python expert.
* With this book readers might well be able to build the next Mars Rover. * First book out on Java robotics. * The biggest selling point about this book is that no one else shows readers how to combine the power of their PC with a robust programming language in Java to create exciting robotics. * The book is a great teaching aid (in robotics or software) that establishes a new paradigm for thinking about robotics along with simpler ways to do things, i.e., vs. the old way using microcontrollers.
Python Essentials provides a vital tour of the most critical features of Python. Starting with setup and installation, you will soon dive into exploring built-in-library types, Python's rich collection of operators and built-in functions, variables, assignment and scoping rules. From this foundation, you will explore functions, a crucial aspect of any programming language, including considerable sophistication in defining parameters to a function and providing argument values. Explore advanced functional programming using generator expressions, comprehensions, and generator functions. Handle file input and output using web services and context managers, exception handling and explore wider, popular frameworks. Through this concise and practical guide, you will explore all you need to know to leverage this powerful, and industry-standard, programming language.
This is the second edition of Travis Oliphant's A Guide to NumPy originally published electronically in 2006. It is designed to be a reference that can be used by practitioners who are familiar with Python but want to learn more about NumPy and related tools. In this updated edition, new perspectives are shared as well as descriptions of new distributed processing tools in the ecosystem, and how Numba can be used to compile code using NumPy arrays. Travis Oliphant is the co-founder and CEO of Continuum Analytics. Continuum Analytics develops Anaconda, the leading modern open source analytics platform powered by Python. Travis, who is a passionate advocate of open source technology, has a Ph.D. from Mayo Clinic and B.S. and M.S. degrees in Mathematics and Electrical Engineering from Brigham Young University. Since 1997, he has worked extensively with Python for computational and data science. He was the primary creator of the NumPy package and founding contributor to the SciPy package. He was also a co-founder and past board member of NumFOCUS, a non-profit for reproducible and accessible science that supports the PyData stack. He also served on the board of the Python Software Foundation.