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CHAPTER 21 ■ ■ ■ Project 2: Painting a Pretty Picture In this project, you learn how you can create graphics in Python. More specifically, you create a PDF file with graphics helping you visualize data that you read from a text file. While you could get such functionality from a regular spreadsheet, Python gives you much more power, as you’ll see when you get to the second implementation and automatically download your data from the Internet. ALPHABET SOUP REVISITED In the previous chapter, we looked at HTML and XML—and here is another acronym: PDF, short for Portable Document Format. PDF is a format created by Adobe that can represent any kind of document with graphics and text. The PDF file is not editable (as, say, a Microsoft Word file would be), but there is reader software freely available for most platforms, and the PDF file should look the same no matter which reader you use or which platform you are on (as opposed to HTML, with which the correct fonts may not be available, you’d have to ship pictures as separate files, and so on). If you don’t already have a PDF reader, Adobe’s own Acrobat Reader is freely available from the Adobe Web site (http://adobe.com/products/acrobat/readstep.html). What’s the Problem? Python is excellent for analyzing data. With its file handling and string processing facilities, it’s probably easier to create some form of report from a data file than to create something similar in your average spreadsheet, especially if what you want to do requires some complicated programming logic. You have seen (in Chapter 3) how you can use string formatting to get pretty output—for example, if you want to print numbers in columns. However, sometimes plain text just isn’t enough. (As they say, a picture is worth a thousand words.) In this project, you learn the basics of the ReportLab package, which enables you to create graphics and documents in the PDF format (and a few other formats) almost as easily as you created plain text earlier. As you play with the concepts in this project, I encourage you to find some application that is interesting to you. I have chosen to use data about sunspots (from the Space Environment 411
412 CHAPTER 21 ■ PROJECT 2: PAINTING A PRETTY PICTURE Center, a part of the U.S. National Oceanic and Atmospheric Administration) and to create a line diagram from this data. Specific Goals The program should be able to do the following: • Download a data file from the Internet. • Parse the data file and extract the interesting parts. • Create PDF graphics based on the data. As in the previous project, these goals might not be fully met by the first prototype. Useful Tools The crucial tool in this project is the graphics-generating package. There are quite a few such packages to choose from. If you visit the Vaults of Parnassus site (http://www.vex.net/parnassus), you will find a separate category for graphics. I have chosen to use ReportLab because it is easy to use and has extensive functionality for both graphics and document generation in PDF. If you want to go beyond the basics, you might also want to consider the P Y X graphics package (http://pyx.sf.net), which is really powerful, and has support for TEX -based typography. To get the ReportLab package, go to the official Web page at http://reportlab.org. There you will find the software, documentation, and samples. The software should be available at http://reportlab.org/downloads.html. Simply download the ReportLab toolkit, uncompress the archive (ReportLab_X.zip, where X is a version number), and put the resulting directory in your Python path. When you have done this, you should be able to import the reportlab module, as follows: >>> import reportlab >>> How Does It Work? Although I show you how some ReportLab features work in this project, much more functionality is available. To learn more, I suggest you obtain the user guide and the (separate) graphics guide, made available on the ReportLab Web site (on the documentation page). They are quite readable, and are much more comprehensive than this one chapter could possibly be. Preparations Before we start programming, we need some data with which to test our program. I have chosen (quite arbitrarily) to use data about sunspots, available from the Web site of the Space Environment Center (http://www.sec.noaa.gov). You can find the data I use in my examples at http:// www.sec.noaa.gov/ftpdir/weekly/Predict.txt. This data file is updated weekly and contains information about sunspots and radio flux. (Don’t ask me what that means.) Once you’ve got this file, you’re ready to start playing with the problem.
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Beginning Python From Novice to Pro
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About the Technical Reviewer ■JER
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Introduction A C program is like a
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256 CHAPTER 11 ■ FILES AND STUFF
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Index ■Symbols - operator 558 !=
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