You don't even need awk for that one:
grep ^class `find . -mtime -1 | grep py$`
read -c foo.csv | sort (*x: int(x[3]) + int(x[6]))
Partly, I was also scratching an itch: I prefer using Python to exploring the sublanguages of various shell commands. Much cleaner, in my opinion.
Yes, that's a much better example. Here the "obvious" shell solution involves using awk to compute the sum of the two columns and putting it as the first field, sorting by the first field, and then removing that field. I guess a "rosetta stone" of such examples (e.g. on the frontpage of the site) would make a strong case for the interest of marcel.
awk -F, -v OFS=, {print $2+$3, $1, $2, $3}' foo.csv | sort -n | cut -d, -f2- awk -F, -v OFS=, '{print $4+$7, $0}' foo.csv | sort -n -k1 -t, | cut -f2- -d,
awk -F, -v OFS=, sets the input and output column separator to comma, '{print $4+$7, $0}' outputs the sum of column 4 and 7 before the rest of the line.
sort -n -k1 -t, sorts the file numerically on column 1, with comma separator.
cut -f2- -d, removes column 1, with comma separator.
This is of course not robust for general CSV files, but I don't think OPs marcel is either. A robust solution requires a proper CSV parser.
The biggest warts I see in the classic unix solution is that all the tools use different flags for the field separator.
edit: if you know that the csv doesn't contain tabs, you can omit some flags for a more concise
awk -F, -v OFS='\t' '{print $4+$7,$0}' foo.csv | sort -n -k1 | cut -f2-
I haven't tested corner cases, but marcel relies on the python csv module, which is probably better than any initial attempt at a parser that I could write in an hour.
This is what I meant about sublanguages. Many people, (myself included), would need to go to the man pages to find the necessary arguments to awk, sort, and cut. I find it much easier to just write a little Python, even if the end result involves more typing.
<foo.tsv awk '{print $4+$7,$0}' | sort -n -k1 | cut -f2- from marcel.api import *
for path, line in (ls(file=True, recursive=True) |
select(lambda f: f.suffix == '.py' and
now() - f.mtime < days(1)) |
read(label=True) |
select(lambda path, line: line.startswith('class '))):
print(f'({path}: {line})
read(label=True)
For example, find all the .py files under the current directory, find the ones that have changed in the last day, and then print the lines (with their filenames) that define classes:
read -l reads and labels a file, i.e., filename -> stream of (filename, line in file)(Yes, this is doable with find and awk, but this is just an accessible example that gets across the idea of Python functions on the command line.)