Learning Python

Learning Python

3.2 21
by Mark Lutz

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Python is a popular open source, object-oriented programming language used for both standalone programs and scripting applications. Portable, powerful, and a breeze to use, there's no quicker way to master the language than to learn from expert teachers. This new edition of Learning Python puts you in the hands of Mark Lutz and David Ascher, two notable Python experts


Python is a popular open source, object-oriented programming language used for both standalone programs and scripting applications. Portable, powerful, and a breeze to use, there's no quicker way to master the language than to learn from expert teachers. This new edition of Learning Python puts you in the hands of Mark Lutz and David Ascher, two notable Python experts and trainers whose friendly, well-structured prose has guided many programmers to proficiency in the language. Learning Python, Second Edition offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language changes since the release of the first edition in 1999, this book introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators.

Beyond language features, this edition of Learning Python also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. Learning Python starts by giving programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules, and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. There are exercises throughout the book to test your new skills. Learning Python, Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to develop larger applications on your own. This book is for anyone who doesn't want to stop at just learning Python, but wants to master it as well.

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Excerpt from Chapter 10: Frameworks and Applications

JPython: The Felicitous Union of Python and Java

JPython is a recently released version of Python written entirely in Java by Jim Hugunin. JPython is a very exciting development for both the Python community and the Java community. Python users are happy that their current Python knowledge can transfer to Java-based development environments; Java programmers are happy that they can use the Python scripting language as a way to control their Java systems, test libraries, and learn about Java libraries from an interpreted environment.

JPython is available from http://www.python.org/jpython, with license and distribution terms similar to those of CPython (which is what the reference implementation of Python is called when contrasted with JPython).

The JPython installation includes several parts:

  • jpython: The equivalent of the Python program used throughout the book.
  • jpythonc: Takes a JPython program and compiles it to Java class files. The resulting Java class files can be used as any Java class file can,for example as applets, as servlets, or as beans.
  • A set of modules that provide the JPython user with the vast majority of the modules in the standard Python library.
  • A few programs demonstrating various aspects of JPython programming.

Using JPython is very similar to using Python:

~/book> jpythonJPython 1.0.3 on java1.2beta4Copyright 1997-1998 Corporation for National Research Initiatives>>> 2 + 35

In fact, JPython works almost identically to CPython. For an up-to-date listing of the differences between the two, see http://www.python.org/jpython/differences.html. The most important differences are:

  • JPython is currently slower than CPython. How much slower depends on the test code used and on the Java Virtual Machine JPython is using. JPython''s author has, on the other hand, explored very promising optimizations, which could make future versions of JPython as fast or faster than CPython.
  • Some of the built-ins or library modules aren''t available for JPython. For example, the os.system() call is not implemented yet, as doing so is difficult given Java''s interaction with the underlying operating system. Also, some of the largest extension modules such as the Tkinter GUI framework aren''t available, because the underlying tools (the Tk/Tcl toolkit, in the case of Tkinter) aren''t available in Java.

JPython Gives Python Programmers Access
to Java Libraries

The most important difference between JPython and CPython, however, is that JPython offers the Python programmer seamless access to Java libraries. Consider the following program, jpythondemo.py, the output of which is shown in Figure 10-5.

Figure 10-5. The output of jpythondemo.py

from pawt import swingimport java def exit(e): java.lang.System.exit(0) frame = swing.JFrame(''Swing Example'', visible=1)button = swing.JButton(This is a Swinging button!'', actionPerformed=exit)frame.contentPane.add(button)frame.pack()

This simple program demonstrates how easy it is to write a Python program that uses the Swing Java GUI framework.[7] The first line imports the swing Java package (the pawt module figures out the exact location of Swing, which can be in java.awt.swing, in com.sun.java.swing, or maybe in javax.swing). The second line imports the java package that we need for the java.lang.System.exit() call. The fourth line creates a JFrame, setting its bean property visible to true. The fifth line creates a JButton with a label and specifies what function should be called when the button is clicked. Finally, the last two lines put the JButton in the JFrame and make them both visible.

Experienced Java programmers might be a bit surprised at some of the code in jpythondemo.py, as it has some differences from the equivalent Java program. In order to make using Java libraries as easy as possible for Python users, JPython performs a lot of work behind the scenes. For example, when JPython imports a Java package, it actively tracks down the appropriate package, and then, using the Java Reflection API, finds the contents of packages, and the signatures of classes and methods. JPython also performs on-the-fly conversion between Python types and Java types. In jpythondemo.py, for example, the text of the button (''This is a Swinging example!'') is a Python string. Before the constructor for JButton is called, JPython finds which variant of the constructor can be used (e.g., by rejecting the version that accepts an Icon as a first argument), and automatically converts the Python string object to a Java string object. More sophisticated mechanisms allow the convenient actionPerformed=exit keyword argument to the JButton constructor. This idiom isn''t possible in Java, since Java can''t manipulate functions (or methods) as first-class objects. JPython makes it unnecessary to create an ActionListener class with a single actionPerformed method, although you can use the more verbose form if you wish.

JPython as a Java Scripting Language

JPython is gaining in popularity because it allows programmers to explore the myriad Java libraries that are becoming available in an interactive, rapid turnaround environment. It also is proving useful to embed Python as a scripting language in Java frameworks, for customization, testing, and other programming tasks by end users (as opposed to systems developers). For an example of a Python interpreter embedded in a Java program, see the program in the demo/embed directory of the JPython distribution.

A Real JPython/Swing Application: grapher.py

The grapher.py program (output shown in Figure 10-6) allows users to graphically explore the behavior of mathematical functions. It''s also based on the Swing GUI toolkit. There are two text-entry widgets in which Python code should be entered. The first is an arbitrary Python program that''s invoked before the function is drawn; it imports the needed modules and defines any functions that might be needed in computing the value of the function. The second text area (labeled Expression:) should be a Python expression (as in sin(x)), not a statement. It''s called for each data point, with the value of the variable x set to the horizontal coordinate.

Figure 10-6. Output of grapher.py

The user can control whether to draw a line graph or a filled graph, the number of points to plot, and what color to plot the graph in. Finally, the user can save configurations to disk and reload them later (using the pickle module) Here is the grapher.py program:

from pawt import swing, awt, colors, GridBagRIGHT = swing.JLabel.RIGHTAPPROVE_OPTION = swing.JFileChooser.APPROVE_OPTIONimport java.ioimport pickle, os default_setup = """from math import *def squarewave(x,order):    total = 0.0    for i in range(1, order*2+1, 2):        total = total + sin(x*i/10.0)/(float(i))    return total"""default_expression = "squarewave(x, order=3)" class Chart(awt.Canvas):    color = colors.darkturquoise    style = ''Filled''     def getPreferredSize(self):        return awt.Dimension(600,300)     def paint(self, graphics):        clip = self.bounds        graphics.color = colors.white        graphics.fillRect(0, 0, clip.width, clip.height)         width = int(clip.width * .8)        height = int(clip.height * .8)        x_offset = int(clip.width * .1)        y_offset = clip.height - int(clip.height * .1)         N = len(self.data); xs = [0]*N; ys = [0]*N         xmin, xmax = 0, N-1        ymax = max(self.data)        ymin = min(self.data)         zero_y = y_offset - int(-ymin/(ymax-ymin)*height)        zero_x = x_offset + int(-xmin/(xmax-xmin)*width)         for i in range(N):            xs[i] = int(float(i)*width/N) + x_offset            ys[i] = y_offset - int((self.data[i]-ymin)/(ymax-ymin)*height)        graphics.color = self.color        if self.style == "Line": graphics.drawPolyline(xs, ys, len(xs))        else:            xs.insert(0, xs[0]); ys.insert(0, zero_y)            xs.append(xs[-1]); ys.append(zero_y)            graphics.fillPolygon(xs, ys, len(xs))         # draw axes        graphics.color = colors.black        graphics.drawLine(x_offset,zero_y, x_offset+width, zero_y)        graphics.drawLine(zero_x, y_offset, zero_x, y_offset-height)         # draw labels        leading = graphics.font.size        graphics.drawString("%.3f" % xmin, x_offset, zero_y+leading)        graphics.drawString("%.3f" % xmax, x_offset+width, zero_y+leading)        graphics.drawString("%.3f" % ymin, zero_x-50, y_offset)        graphics.drawString("%.3f" % ymax, zero_x-50, y_offset-height+leading) class GUI:    def __init__(self):        self.numelements = 100        self.frame = swing.JFrame(windowClosing=self.do_quit)         # build menu bar        menubar = swing.JMenuBar()        file = swing.JMenu("File")        file.add(swing.JMenuItem("Load", actionPerformed = self.do_load))        file.add(swing.JMenuItem("Save", actionPerformed = self.do_save))        file.add(swing.JMenuItem("Quit", actionPerformed = self.do_quit))        menubar.add(file)        self.frame.JMenuBar = menubar         # create widgets        self.chart = Chart(visible=1)        self.execentry = swing.JTextArea(default_setup, 8, 60)        self.evalentry = swing.JTextField(default_expression,                                          actionPerformed = self.update)         # create options panel        optionsPanel = swing.JPanel(awt.FlowLayout(            alignment=awt.FlowLayout.LEFT))         # whether the plot is a line graph or a filled graph        self.filled = swing.JRadioButton("Filled",                                         actionPerformed=self.set_filled)        optionsPanel.add(self.filled)        self.line = swing.JRadioButton("Line",                                       actionPerformed=self.set_line)        optionsPanel.add(self.line)        styleGroup = swing.ButtonGroup()        styleGroup.add(self.filled)        styleGroup.add(self.line)         # color selection        optionsPanel.add(swing.JLabel("Color:", RIGHT))        colorlist = filter(lambda x: x[0] != ''_'', dir(colors))        self.colorname = swing.JComboBox(colorlist)        self.colorname.itemStateChanged = self.set_color        optionsPanel.add(self.colorname)         # number of points        optionsPanel.add(swing.JLabel("Number of Points:", RIGHT))        self.sizes = [50, 100, 200, 500]        self.numpoints = swing.JComboBox(self.sizes)        self.numpoints.selectedIndex = self.sizes.index(self.numelements)        self.numpoints.itemStateChanged = self.set_numpoints        optionsPanel.add(self.numpoints)         # do the rest of the layout in a GridBag        self.do_layout(optionsPanel)     def do_layout(self, optionsPanel):        bag = GridBag(self.frame.contentPane, fill=''BOTH'',                      weightx=1.0, weighty=1.0)        bag.add(swing.JLabel("Setup Code: ", RIGHT))        bag.addRow(swing.JScrollPane(self.execentry), weighty=10.0)        bag.add(swing.JLabel("Expression: ", RIGHT))        bag.addRow(self.evalentry, weighty=2.0)        bag.add(swing.JLabel("Output: ", RIGHT))        bag.addRow(self.chart, weighty=20.0)        bag.add(swing.JLabel("Options: ", RIGHT))  def set_color(self, event):        self.chart.color = getattr(colors, event.item)        self.chart.repaint()     def set_numpoints(self, event):        self.numelements = event.item        self.update(None)     def set_filled(self, event):        self.chart.style = ''Filled''        self.chart.repaint()     def set_line(self, event):        self.chart.style = ''Line''        self.chart.repaint()     def update(self, event):        context = {}        exec self.execentry.text in context        each = compile(self.evalentry.text, '''', ''eval'')        numbers = [0]*self.numelements        for x in xrange(self.numelements):            context[''x''] = float(x)            numbers[x] = eval(each, context)        self.chart.data = numbers        if self.chart.style == ''Line'':            self.line.setSelected(1)        else:            self.filled.setSelected(1)        self.chart.repaint() GUI()

The logic of this program is fairly straightforward, and the class and method names make it easy to follow the flow of control. Most of this program could have been written in fairly analogous (but quite a bit longer) Java code. The parts in bold, however, show the power of having Python available: at the top of the module, default values for the Setup and Expression text widgets are defined. The former imports the functions in the math module and defines a function called squarewave. The latter specifies a call to this function, with a specific order parameter (as that parameter grows, the resulting graph looks more and more like a square wave, hence the name of the function). If you have Java, Swing, and JPython installed, feel free to play around with other possibilities for both the Setup and Expression text widgets.

The key asset of using JPython instead of Java in this example is in the update method: it simply calls the standard Python exec statement with the Setup code as an argument, and then calls eval with the compiled version of the Expression code for each coordinate. The user is free to use any part of Python in these text widgets!

JPython is still very much a work in progress; Jim Hugunin is constantly refining the interface between Python and Java and optimizing it. JPython, by being the second implementation of Python, is also forcing Guido van Rossum to decide what aspects of Python are core to the language and what aspects are features of his implementation. Luckily, Jim and Guido seem to be getting along and agreeing on most points.

7. Documentation for Swing and the Java Foundation Classes is available online at http://java.sun.com/products/jfc/index.html. Alternatively, Robert Eckstein, Marc Loy, and Dave Wood have published a thorough review of the Swing toolkit for Java, Java Swing, published by O'Reilly & Associates.

Meet the Author

Mark Lutz is a leading Python trainer, the author of Python’s earliest and best-selling texts, and a pioneering figure in the Python world.

Mark is the author of the three O’Reilly books: Learning Python, Programming Python, and Python Pocket Reference, all currently in fourth or fifth editions. He has been using and promoting Python since 1992, started writing Python books in 1995, and began teaching Python classes in 1997. As of Spring 2013, Mark has instructed 260 Python training sessions, taught roughly 4,000 students in live classes, and written Python books that have sold 400,000 units and been translated to at least a dozen languages.

Together, his two decades of Python efforts have helped to establish it as one of the most widely used programming languages in the world today. In addition, Mark has been in the software field for 30 years. He holds BS and MS degrees in computer science from the University of Wisconsin where he explored implementations of the Prolog language, and over his career has worked as a professional software developer on compilers, programming tools, scripting applications, and assorted client/server systems.

Mark maintains a training website (http://learning-python.com) and an additional book support site on the Web (http://www.rmi.net/~lutz).

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Learning Python 3.2 out of 5 based on 0 ratings. 21 reviews.
sldonb42 More than 1 year ago
If you go to the page for the 4th edition and press the link to download a sample, you WILL get a sample for the 2nd edition...covering Python 2.3, not 2.6 and 3.1. The same if you buy it without rooting around through the editions listed as ebooks. B&N will then tell you that they do not issue refunds for ebooks.
Anonymous More than 1 year ago
Its a freaking 4494 page sample totally get the free sample( this ' sample'includes all chaptets except the appendexs)very well written good for the begginnr and more experianced alike
Guest More than 1 year ago
It gives a thorough description of how to use Python; which is indeed easy to learn if you already know another language. But when the authors say that not having to compile Python programs means that development time is speeded up, perhaps they are overstating. For most programmers who use compiled languages like C or C++, the biggest time is taken up in finding a method that solves a problem, coding it and subsequent debugging. These days, compilers on recent hardware are fast enough that link/compile times are simply not a bottleneck to development productivity. So it is a bit of a straw dummy that the authors put forth. However, they are absolutely spot on when comparing this to Perl or Tcl. Perl is powerful, but its code looks like assembler. Perl gurus tend to shrug when you point this out, usually saying they understand it, with the not-so-implicit suggestion that if you can't, it is your fault. But this leads to a real maintenance problem and a barrier to entry to others. The cleaner Python syntax can show coding intent far clearer. Plus, and more importantly, the object oriented nature of Python lets you scale up to much larger programs. This has always been a problem with scripting languages, all the way back to the various unix shell scripts and DOS bat files. Often, the most those ever gave you in terms of modular capabilities was the equivalent of subroutines. Which is strictly procedural and not OO. By the way, there is a small contradiction between the above claim that Python is more understandable than Perl and the claim that it has an advantage over C++ or Java because it is not as verbose as those. Typically, in increasing amount of source code, you have Perl -> Python -> (C++,Java). If you think that Python is more understandable than Perl, then by that same logic, we could conclude that C++ or Java is more understandable than Python. So if you are using Perl or Tcl and want something better, Python is a good choice. A good upgrade path. But if you are currently using C or C++, with maybe X for graphics, or Java, then I suggest you stay with those. All three languages, with their graphics, give you a far richer toolset. Python would be a retrograde choice.
Anonymous More than 1 year ago
The sample gives no understanding of how this book will be teaching the language and is just about the history of python, its uses and the authors view on 2.x vs 3.x. Hard to tell what this book will be like as it gets very mixed reviews.
Anonymous More than 1 year ago
Even the sample is very good.The very very good book for beginner.
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Never give up.
Anonymous More than 1 year ago
Excellent for beginner but still worthwhile for more advanced python programmer
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Anonymous More than 1 year ago
This is an excellent book to teach yourself Python! I have the 4th edition. It focuses on Python 3.2 but explains the differences with Python 2.7 and earlier versions as those areas are encountered in the book. The book starts with the basics, which most will find very easy, and proceeds to the most advanced Python topics. Every chapter builds on what was taught in previous chapters. There are numerous WORKING examples throughout the book, and the author has a web site where you may down load all of the examples. I have Python 3.2 and 2.7 and have run most of the examples in both versions. This is an EXCELLENT book if you need, or just want to learn Python!
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