| 18-1. | Processes versus Threads. What are the differences between processes and threads? |
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| 18-2. | Python Threads. Which type of multithreaded application will tend to fare better in Python, I/O-bound or CPU-bound? |
| 18-3. | Threads. Do you think anything significant happens if you have multiple threads on a multiple CPU system? How do you think multiple threads run on these systems? |
| 18-4. | Threads and Files. Update your solution to Exercise 9-19, which obtains a byte value and a file name, displaying the number of times that byte appears in the file. Let's suppose this is a really big file. Multiple readers in a file is acceptable, so create multiple threads that count in different parts of the file so that each thread is responsible for a certain part of the file. Collate the data from each thread and provide the summed-up result. Use your timeit() code to time both the single threaded version and your new multithreaded version and say something about the performance improvement. |
| 18-5. | Threads, Files, and Regular Expressions. You have a very large mailbox fileif you don't have one, put all of your e-mail messages together into a single text file. Your job is to take the regular expressions you designed in Chapter 15 that recognize e-mail addresses and Web site URLs, and use them to convert all e-mail addresses and URLs in this large file into live links so that when the new file is saved as an .html (or .htm) file, will show up in a Web browser as live and clickable. Use threads to segregate the conversion process across the large text file and collate the results into a single new .html file. Test the results on your Web browser to ensure the links are indeed working. |
| 18-6. | Threads and Networking. Your solution to the chat service application in the previous chapter (Exercises 16-7 to 16-10) may have required you to use heavyweight threads or processes as part of your solution. Convert that to be multithreaded code. |
| 18-7. | *Threads and Web Programming. The Crawler up ahead in Example 19.1 is a single-threaded application that downloads Web pages that would benefit from MT programming. Update crawl.py (you could call it mtcrawl.py) such that independent threads are used to download pages. Be sure to use some kind of locking mechanism to prevent conflicting access to the links queue. |
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| 18-8. | Thread Pools. Instead of a producer thread and a consumer thread, change the code in Example 18.9, prodcons.py, so that you have any number of consumer threads (a thread pool) which can process or consume more than one item from the Queue at any given moment. |
| 18-9. | Files. Create a set of threads to count how many lines there are in a set of (presumably large) text files. You may choose the number of threads to use. Compare the performance against a single-threaded version of this code. Hint: Review Chapter 9 (Files and I/O) exercises. |
| 18-10. | Take your solution to the previous exercise and adopt it to a task of your selection, i.e., processing a set of e-mail messages, downloading Web pages, processing RSS or Atom feeds, enhancing message processing as part of a chat server, solving a puzzle, etc. |
