HNHiringTrends[1] is my goto site when I try to explain the current hiring sentiment of software.<p>[1] <a href="https://hnhiringtrends.com" rel="nofollow">https://hnhiringtrends.com</a>
my quick and dirty version of this from march was <a href="http://canonical.org/~kragen/sw/dev3/hiring.png" rel="nofollow">http://canonical.org/~kragen/sw/dev3/hiring.png</a>. i only bothered to gather 7 years of data though<p>csv generation script at <a href="http://canonical.org/~kragen/sw/dev3/whoishiring.py" rel="nofollow">http://canonical.org/~kragen/sw/dev3/whoishiring.py</a> (taking as input <a href="http://canonical.org/~kragen/sw/dev3/whoishiring.txt" rel="nofollow">http://canonical.org/~kragen/sw/dev3/whoishiring.txt</a>, copied and pasted from firefox), png generation script at <a href="http://canonical.org/~kragen/sw/dev3/plothiring.py" rel="nofollow">http://canonical.org/~kragen/sw/dev3/plothiring.py</a><p>it, uh, probably took me more than the 5 minutes it reportedly took chatgpt. more like two and a half hours, judging from time.ctime(os.stat('whoishiring.txt.~1~').st_mtime), although i think i ate dinner in the middle. clearly i should lean more on chatgpt<p><a href="https://github.com/saulpw/visidata">https://github.com/saulpw/visidata</a> looks pretty cool!