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March 4, 2019 05:22
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Calculate statistics around the line length of a set of matching files
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#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
""" | |
Usage: | |
$ find . | grep py$ | python line_counts.py | |
""" | |
from __future__ import unicode_literals | |
import subprocess | |
import numpy | |
def parse(line): | |
if not line: | |
return | |
count, filename = line.split() | |
if filename == 'total': | |
return | |
return (int(count), filename) | |
res = subprocess.check_output(['xargs', 'wc', '-l']) | |
counts_by_file = filter(None, map(parse, res.split('\n'))) | |
print "Biggest 5 files:" | |
biggest = sorted(counts_by_file)[-5:] | |
for count, filename in biggest: | |
print " ", count, filename | |
line_counts = [count for count, _ in counts_by_file] | |
median = int(numpy.median(line_counts)) | |
std = int(numpy.round(numpy.std(line_counts))) | |
print "matching files:", len(line_counts) | |
print "total lines:", numpy.sum(line_counts) | |
print "min:", numpy.min(line_counts) | |
print "median:", median | |
print "+1σ:", median + std | |
print "max:", numpy.max(line_counts) | |
# I like weighted average best - you're more likely to be working in a file | |
# with longer lines, so that gives you the best idea how long files will be in your day-to-day | |
print "weighted avg:", int(numpy.round(numpy.average(line_counts, weights=line_counts))) |
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