Learning Python: Powerful Object-Oriented Programming

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Learning Python is an introduction to the increasingly popular Python programming language. Python is an interpreted, interactive, object-oriented scripting language. Python is growing in popularity because:

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Overview

Learning Python is an introduction to the increasingly popular Python programming language. Python is an interpreted, interactive, object-oriented scripting language. Python is growing in popularity because:

  • It is available on all important platforms: Windows NT, Windows 95, Windows 98, Linux, all major UNIX platforms, MacOS, and even the BeOS.
  • It is open-source software, copyrighted but freely available for use, even in commercial applications.
  • Its clean object-oriented interface makes it a valuable prototyping tool for C++ programmers.
  • It works well with all popular windowing toolkits, including MFC, Tk, Mac, X11, and Motif.
    Learning Python is written by Mark Lutz, author of
    Programming Python and Python Pocket Reference; and David Ascher, a vision scientist and Python user.
    This book starts with a thorough introduction to the elements of Python: types, operators, statements, classes, functions, modules, and exceptions. By reading the first part of the book, the reader will be able to understand and construct programs in the Python language. In the second part of the book, the authors present more advanced information, demonstrating how Python performs common tasks and presenting real applications and the libraries available for those applications.
    All the examples use the Python interpreter, so the reader can type them in and get instant feedback. Each chapter ends with a series of exercises. Solutions to the exercises are in an appendix.
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Editorial Reviews

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This is an introductory tutorial for Python, the popular object-oriented scripting language used in many domains, especially on the web. Programmers are beginning to use it for standalone programs and seeing dramatic productivity improvements. Authors Mark Lutz & David Ascher cover Python essentials and core concepts, organizing their text around major language features, not examples. The tutorial is based on a three day hands-on Python course. Nonetheless, a basic understanding of object-oriented programming concepts and scripting environments will help you to work quickly through this text. You should also download a free copy of Python and install it to work the examples and code; authors provide the information and sources.

Highlights:

  • Core language section focuses on programming essentials, such as built-in types, statements, tools and packaged program components. Here, you also learn about types and operators, functions, modules, classes and exceptions.
  • Builds upon core concepts as it explains how to use built-in tools and perform common programming tasks. Leads into frameworks and applications by introducing elements of COM, the GUI editor, Python and Java integration.

Advantages:

  • This well-organized self-study tutorial clearly explains and annotates code. Discussions proceed from elementary to more difficult concepts and structures. End-of-chapter exercises are designed to make you think, not just regurgitate code.
  • Appendices contain additional references, resources and solutions to exercises.
  • Additional information is available on the authors' web site.

Related Titles:

Afteryou have mastered this tutorial, you may be interested in more intermediate to advanced programming guides, such as Programming Python, and Internet Programming with Python. A Python pocket reference, The Python Pocket Reference, is also available.

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Product Details

  • ISBN-13: 9781565924642
  • Publisher: O'Reilly Media, Incorporated
  • Publication date: 4/14/1999
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 384
  • Product dimensions: 7.06 (w) x 9.18 (h) x 0.78 (d)

Meet the Author

Mark Lutz is an independent Python trainer, writer, and software developer, and is one of the primary figures in the Python community. He is the author of the O'Reilly books Programming Python and Python Pocket Reference (both in 2nd Editions), and co-author of Learning Python (both in 2nd Editions). Mark has been involved with Python since 1992, began teaching Python classes in 1997, and has instructed over 90 Python training sessions as of early 2003. In addition, he holds BS and MS degrees in computer science from the University of Wisconsin, and over the last two decades has worked on compilers, programming tools, scripting applications, and assorted client/server systems. Whenever Mark gets a break from spreading the Python word, he leads an ordinary, average life with his kids in Colorado. Mark can be reached by email at , or on the web at http://www.rmi.net/~lutz.

David Ascher is the lead for Python projects at ActiveState, including Komodo, ActiveState's integrated development environment written mostly in Python. David has taught courses about Python to corporations, in universities, and at conferences. He also organized the Python track at the 1999 and 2000 O'Reilly Open Source Conventions, and was the program chair for the 10th International Python Conference. In addition, he co-wrote Learning Python (both editions) and serves as a director of the Python Software Foundation. David holds a B.S. in physics and a Ph.D. in cognitive science, both from Brown University.

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Read an Excerpt


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.

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Table of Contents

  • Preface
  • The Core Language
    • Chapter 1: Getting Started
    • Chapter 2: Types and Operators
    • Chapter 3: Basic Statements
    • Chapter 4: Functions
    • Chapter 5: Modules
    • Chapter 6: Classes
    • Chapter 7: Exceptions


  • The Outer Layers
    • Chapter 8: Built-in Tools
    • Chapter 9: Common Tasks in Python
    • Chapter 10: Frameworks and Applications


  • Appendixes
    • Python Resources
    • Platform-Specific Topics
    • Solutions to Exercises


  • Colophon

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