For calculations? Sure; but that's not really what bash is for.
Shells are excellent at invoking and managing subprocesses and piping. Python (not sure about Perl, I've not really used it) is terrible at those things.
Take a simple, very common piece of bash code like `foo | bar`. How might we do this in Python? Maybe we reach for the builtin `subprocess` module:
import subprocess
foo_output = subprocess.check_call(['foo'])
bar = subprocess.Popen(['bar'], stdin=subprocess.PIPE)
bar.communicate(foo_output)
Except that this isn't a pipe: it will run `foo` to completion, storing all of the output in memory, then call `bar` on this data, e.g. `foo_output=$(foo); echo "$foo_output" | bar`. This is unsuitable for long-lived processes (e.g. if `foo` is long lived and `bar` is meant to be logging its output), or if there is a lot of data (e.g. `foo` is generating GBs of text and `bar` is summarising it, like `wc -l`).OK, maybe instead of `check_call` (which is blocking) we make `foo` asynchronous. Note that we can't use `foo.communicate` to get its output, since that would also block. What if we just shuttle data between the two manually, line by line (urgh)?
import subprocess
foo = subprocess.Popen(['foo'], stdout=subprocess.PIPE)
bar = subprocess.Popen(['bar'], stdin=subprocess.PIPE)
while foo.poll() is None:
bar.stdin.write(foo.stdout.readline())
bar.stdin.close()
bar.wait()
This appears to work, especially when testing with small amounts of data. Yet it's actually a timebomb, since it will deadlock when the subprocesses' pipe buffers fill up (this is why the documentation tells us to use `communicate`, except that we can't since that's blocking https://docs.python.org/3.7/library/subprocess.html ).It's at this point that we move the data shuttling into a separate thread:
import subprocess
import threading
foo = subprocess.Popen(['foo'], stdout=subprocess.PIPE)
bar = subprocess.Popen(['bar'], stdin=subprocess.PIPE)
def shuttle():
while foo.poll() is not None:
bar.stdin.write(foo.stdout.readline())
foo.stdout.close()
bar.stdin.close()
thread = threading.Thread(target=shuttle)
thread.daemon = True
thread.start()
thread.join()
bar.wait()
Now we've got a pile of code mixing multiprocessing with multithreading, in a domain known to have deadlocks, with hand-written hard-coded line buffering.At this point, I'd say just freakin learn bash!