diff -r b9bd0f06b4a1 -r 7029e6c47700 relpipe-data/examples-grep-cut-fstab.xml
--- a/relpipe-data/examples-grep-cut-fstab.xml Sat Jun 06 13:22:57 2020 +0200
+++ b/relpipe-data/examples-grep-cut-fstab.xml Mon Jun 08 12:34:16 2020 +0200
@@ -165,6 +165,59 @@
The letters
relation stays rock steady and relpipe-tr-cut 'numbers'
does not affect it in any way.
+ There are various input filters (relpipe-in-*
), one of them is relpipe-in-csv
+ which converts CSV files to relational format.
+ Thus we can process standard CSV files in our relational pipelines
+ and e.g. filter records that have certain value in certain column (relpipe-tr-grep
)
+ or keep only certain columns (relpipe-tr-cut
).
+
+ We may have a tasks.csv
file containing TODOs and FIXMEs:
+
+ And we can process it using this pipeline: +
+ +and get result like this:
+ + + + ++ We work with attribute (column) names, so there is no need to remember column numbers. + And thanks to regular expressions we can write elegant and powerful filters. +
+ + +