fixed-width

I'm writing a batch script to convert a fixed-width text file to .csv format. Here's what I've written so far: @echo off setlocal enabledelayedexpansion for /F "tokens=*" %%A in (HRV*.txt) do ( set var=%%A set mer=!var:~6,11! set cr=!var:~18,19! set dt=!var:~42,30! set aa=!var:~72,30! set ab=!var:~102,30! set ac=!var:~132,15! set ad=!var:~147,30! set ae=!var:~177,30! set af=!var:~283,36! set ag=!var:~318,3! set ah=!var:~329,7! set ai=!var:~337,17! set aj=!var:~442,2! set ak=!var:~460,15! set al=!var:~475,2! set am=!var:~482,15! set y=!mer!.!cr!,"!dt!","!aa!","!ab!","!ac!","!ad!","!ae!",="!af!"

How can I achieve the following effect without the use of a table? Example: http://enstar.nl/example.php (The example may not be visible at the moment, the nameservers should have been changed, but my hosting isn't that fast in updating them. Should be working later today. I apologize for the inconvenience) All methods require a header and/or a footer. I don't want that. What I want is the following: Pure CSS, no tables 2 columns, fixed fluid (in that order) if the content hasn't reach the bottom of the viewport, than extend the columns to it. Else extent to the content (so like a sticky

Are there built-in libraries to multiply a vector of points by an SVGMatrix? I have an SVG drawing that has been scaled, and I want to annotate that drawing in its original coordinate system with a line that has a fixed width in screen space. (I.e. the line should not change width when zooming in or out, but lines in the image do, of course.) So, my approach is to transform the image inside a , and then take my array of points and apply the same transformation, then create a new path object at the root level using these transformed points. I'm looking for the cleanest way to do this. The svg

For an android project, I need to show a view (WebView), that dynamically loads content. Content items will be <div class="content-item"> tags that are added by JavaScript to <div class="content-holder"> after page has loaded. The design is such that: List item Content items will be layed out in fixed-width columns. Content items do not necessarily have same height. Height of any column must not exceed screen height. If a column is full, additional content will be put in next column(create column if necessary). There will be no empty columns. Column must not break inside a content item. Page

I would like to write a fixed width, space delimited and minimally quoted CSV file using Python's csv writer. An example of the output: item1 item2 "next item1" "next item2" anotheritem1 anotheritem2 If I use writer.writerow( ("{0:15s}".format(item1), "{0:15s}".format(item2)) ) ... then, with the space delimiter, the formatting is broken as either quotes or escapes (depending on the csv.QUOTE_* constant) are added due to the trailing spaces of the items formatting: "item1 " "item2 " "next item1 " "next item2 " "anotheritem1 " "anotheritem2 " Of course, I could format everything myself: writer

I need help formatting this xml to a fixed width text file using a xsl style sheet. I know very little about xsl and have found very little information online on how this can be done. Basically I need this xml <?xml version="1.0" encoding="UTF-8"?> <Report> <table1> <Detail_Collection> <Detail> <SSN>*********</SSN> <DOB>1980/11/11</DOB> <LastName>user</LastName> <FirstName>test</FirstName> <Date>2013/02/26</Date> <Time>14233325</Time> <CurrentStreetAddress1>53 MAIN STREET</CurrentStreetAddress1> <CurrentCity>san diego</CurrentCity> <CurrentState>CA</CurrentState> </Detail_Collection> </table1>

Trying to parse a fixed width text file. my text file looks like the following and I need a row id, date, a string, and an integer: 00101292017you1234 00201302017 me5678 I can read the text file to an RDD using sc.textFile(path). I can createDataFrame with a parsed RDD and a schema. It's the parsing in between those two steps. Spark's substr function can handle fixed-width columns, for example: df = spark.read.text("/tmp/sample.txt") df.select( df.value.substr(1,3).alias('id'), df.value.substr(4,8).alias('date'), df.value.substr(12,3).alias('string'), df.value.substr(15,4).cast('integer')