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If you need to download and parse entire web sites, take a look at the Scrapy project, hosted at http://scrapy.org, which provides a framework for implementing your own web spiders. With the tools it provides, you can write programs that follow links to every page on a web site, tabulating the data you want extracted from each page. When web pages wind up being incomplete because they use dynamic JavaScript to load data that you need, you can use the QtWebKit module of the PyQt4 library to load a page, let the JavaScript run, and then save or parse the resulting complete HTML page. Finally, if you really need a browser to load the site, both the Selenium and Windmill test platforms provide a way to drive a standard web browser from inside a Python program. You can start the browser up, direct it to the page of interest, fill out and submit forms, do whatever else is necessary to bring up the data you need, and then pull the resulting information directly from the DOM elements that hold them.

These last two options both require third-party components or Python modules that are built against large libraries, and so we will not cover them here, in favor of techniques that require only pure Python. For our examples in this chapter, we will use the site of the United States National Weather Service, which lives here: www.weather.gov/. Among the better features of the United States government is its having long ago decreed that all publications produced by their agencies are public domain. This means, happily, that I can pull all sorts of data from their web site and not worry about the fact that copies of the data are working their way into this book. Of course, web sites change, so the source code package for this book available from the Apress web site will include the downloaded pages on which the scripts in this chapter are designed to work. That way, even if their site undergoes a major redesign, you will still be able to try out the code examples in the future. And, anyway as I recommended previously you should be kind to web sites by always developing your scraping code against a downloaded copy of a web page to help reduce their load.

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erhaps it is natural that a framework called Atlas has a built-in set of libraries for handling mapping functionality! In this chapter, you will look at this functionality and how you can use and leverage it in your own applications.

Next, a call is made to the function ReturnSingleStringSP, which uses the review ID to find the supervisor of the employee the review is for and get the e-mail address of that supervisor That e-mail address is stored in the local variable StrEmailAddress and will be used shortly Now it s time to begin creating the interface class that will be between the workflow and the ASPNET application This interface class will define the interface for the workflow and include the events that the ASPNET application can call and that the workflow will.

The task of grabbing information from a web site usually starts by reading it carefully with a web browser and finding a route to the information you need. Figure 10 1 shows the site of the National Weather Service; for our first example, we will write a program that takes a city and state as arguments and prints out the current conditions, temperature, and humidity. If you will explore the site a bit, you will find that city-specific forecasts can be visited by typing the city name into the small Local forecast form in the left margin.

In the foregoing section, we used routines in Python's subprocess module to directly invoke commands This was great, and let us pass characters that would have been special to a normal interactive shell If you have a big list of file names with spaces and other special characters in them, it can be wonderful to simply pass them into a subprocess call and have the command on the receiving end understand you perfectly But when you are using remote-shell protocols over the network (which, you will recall, is the subject of this chapter!), you are generally going to be talking to a shell like bash instead of getting to invoke commands directly like you do through the subprocess module.

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