The Content Wrangler, The 2016 Technical Communication Benchmarking Survey Desktop Publishingĭesktop publishing tools are standalone systems that live on your machine and allow you to author and publish from the same system. Adoption of advanced information development management technologies like component content management systems (CCMS), XML authoring tools, and machine translation are planned innovations for firms hoping to lower costs and connect content to customers. New content types-like video documentation-are being produced more often by more companies. Also not listed are ancillary tools like screen and video capture and editing, learning and training tools like Camtasia, Learning Management Systems (LMSs), presentation software, and website creation tools. Purposefully left off are standalone Content Management Systems (CMSs) and Component Content Management Systems (CCMSs), as they are not authoring tools. Many of the tools listed in these surveys can be broken down into five types. For example, from year-to-year we see that extensible markup language (XML)-based tools gain ground, but the “staples” remain Microsoft Word, Adobe FrameMaker, and Acrobat. These surveys are enlightening in the trends they uncover. So if you’re new to the field or looking to change the authoring tools you use at work, read further for an overview of the different types, what they do, and examples to investigate.Įvery few years, technical communicators are asked to fill out a survey indicating their current authoring and publishing tools. Authoring tools can quickly become a hot topic when you put technical communicators in a room together, as we all have our preferences. You could read the file and do the same again but reverse the logc in the remove loop.One of the hardest things about entering the technical communication field is learning what authoring tools are being used and how to get trained on them. > print(ET.tostring(root, xml_declaration=True, encoding='utf-8').decode()) Remove the ones that have a red: > for veg in root.findall('.//Color/./.'): To test if they have a red > for veg in root.findall('.//Color/./.'): > root = ET.parse('vegetables.xml').getroot() The vegetable tags are 2 levels up from - you can isolate them using: > import as ET Well there's, lxml, and BeautifulSoup can be used too.įor this particular task - I would just read the file twice. Let's say I had this xml file and people need me to split the data so I have two proper xml files, one containing the red vegetables and one containing the ones that can't be red (cucumber in this case) Īs it is now I usually do string.find for different tags and split the data and so on, but I feel really bad about working that way. Could you give me some advice on a good library/framework for this? I usually don't know all about each line in the files but rather need to take chunks and convert. I know it is blasphemy and I would like to take the step in working with them properly but the examples I find are often just to extract some part of the information. Hi, I manipulate quite a lot of different text files with python scripts, once in a while I encounter an xml file to work with and I am stuck in handling them as text files.
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