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copied!<p>You just have a function which parses one file, and returns a list of dictionaries containing <code>{'name': 'Bob Simon', 'age': 29, ...}</code> etc. Then call this on each of your files, extending a master list. Then write this master list of dicts as a CSV file.</p> <p>More elaborately:</p> <p>First you need to parse the input files, you'd have a function which takes a file, and returns a list of "things".</p> <pre><code>def parse_txt(fname): f = open(fname) people = [] # Here, parse f. Maybe using a while loop, and calling # f.readline() until there is an empty line Construct a # dictionary from each person's block, and append it to allpeople return people </code></pre> <p>This returns something like:</p> <pre><code>people = [ {'name': 'Bob Simon', 'age': 29}, {'name': 'Susan Kim', 'age': 21}, ] </code></pre> <p>Then, loop over each of your input files (maybe by using <code>os.listdir</code>, or <a href="http://docs.python.org/library/optparse.html" rel="nofollow">optparse</a> to get a list of args):</p> <pre><code>allpeople = [] for curfile in args: people = parse_txt(fname = curfile) allpeople.extend(people) </code></pre> <p>So <code>allpeople</code> is a long list of all the people from all files.</p> <p>Finally you can write this to a CSV file using the <a href="http://docs.python.org/library/csv.html#csv.writer" rel="nofollow">csv module</a> (this bit usually involves another function to reorganise the data into a format more compatible with the writer module)</p>

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