Peterbe.com

A blog and website by Peter Bengtsson

Filtered home page!
Currently only showing blog entries under thecategory: Linux. Clear filter

How to count the most common lines in a file

Bash, MacOSX, Linux

tl;dr sort myfile.log | uniq -c | sort -n -r

I wanted to count recurring lines in a log file and started writing a complicated Python script but then wondered if I can just do it with bash basics.
And after some poking and experimenting I found a really simple one-liner that I'm going to try to remember for next time:

You can't argue with the nice results :)

▶ cat myfile.log
one
two
three
one
two
one
once
one

▶ sort myfile.log | uniq -c | sort -n -r
   4 one
   2 two
   1 three
   1 once

Please post a comment if you have thoughts or questions.

Find the largest node_modules directories with bash

Bash, MacOSX, Linux

tl;dr; fd -I -t d node_modules | rg -v 'node_modules/(\w|@)' | xargs du -sh | sort -hr

It's very possible that there's a tool that does this, but if so please enlighten me.
The objective is to find which of all your various projects' node_modules directory is eating up the most disk space.
The challenge is that often you have nested node_modules within and they shouldn't be included.

The command uses fd which comes from brew install fd and it's a fast alternative to the built-in find. Definitely worth investing in if you like to live fast on the command line.
The other important command here is rg which comes from brew install ripgrep and is a fast alternative to built-in grep. Sure, I think one can use find and grep but that can be left as an exercise to the reader.

▶ fd -I -t d node_modules | rg -v 'node_modules/(\w|@)' | xargs du -sh | sort -hr
1.1G    ./GROCER/groce/node_modules/
1.0G    ./SHOULDWATCH/youshouldwatch/node_modules/
826M    ./PETERBECOM/django-peterbecom/adminui/node_modules/
679M    ./JAVASCRIPT/wmr/node_modules/
546M    ./WORKON/workon-fire/node_modules/
539M    ./PETERBECOM/chiveproxy/node_modules/
506M    ./JAVASCRIPT/minimalcss-website/node_modules/
491M    ./WORKON/workon/node_modules/
457M    ./JAVASCRIPT/battleshits/node_modules/
445M    ./GITHUB/DOCS/docs-internal/node_modules/
431M    ./GITHUB/DOCS/docs/node_modules/
418M    ./PETERBECOM/preact-cli-peterbecom/node_modules/
418M    ./PETERBECOM/django-peterbecom/adminui0/node_modules/
399M    ./GITHUB/THEHUB/thehub/node_modules/
...

How it works:

  • fd -I -t d node_modules: Find all directories called node_modules but ignore any .gitignore directives in their parent directories.
  • rg -v 'node_modules/(\w|@)': Exclude all finds where the word node_modules/ is followed by a @ or a [a-z0-9] character.
  • xargs du -sh: For each line, run du -sh on it. That's like doing cd some/directory && du -sh, where du means "disk usage" and -s means total and -h means human-readable.
  • sort -hr: Sort by the first column as a "human numeric sort" meaning it understands that "1M" is more than "20K"

Now, if I want to free up some disk space, I can look through the list and if I recognize a project I almost never work on any more, I just send it to rm -fr.

Please post a comment if you have thoughts or questions.

Create a large empty file for testing

Linux

Because I always end up Googling this and struggling to find it easily, I'm going to jot it down here so it's more present on the web for others (and myself!) to quickly find.

Suppose you want to test something like a benchmark; for example, a unit test that has to process a largish file. You can use the dd command which is available on macOS and most Linuxes.

▶ dd if=/dev/zero of=big.file count=1024 bs=1024

▶ ls -lh big.file
-rw-r--r--  1 peterbe  staff   1.0M Sep  8 15:54 big.file

So the count=1024 creates a 1MB file. To create a 500KB one you simply use...

▶ dd if=/dev/zero of=big.file count=500 bs=1024

▶ ls -lh big.file
-rw-r--r--  1 peterbe  staff   500K Sep  8 15:55 big.file

It creates a binary file so you can't cat view it. But if you try to use less, for example, you'll see this:

▶ less big.file
"big.file" may be a binary file.  See it anyway? [Enter]

^@^@^@...snip...^@^@^@
big.file (END)

Please post a comment if you have thoughts or questions.

Comparing compression commands with hyperfine

Bash, MacOSX, Linux

Today I stumbled across a neat CLI for benchmark comparing CLIs for speed: hyperfine. By David @sharkdp Peter.
It's a great tool in your arsenal for quick benchmarks in the terminal.

It's written in Rust and is easily installed with brew install hyperfine. For example, let's compare a couple of different commands for compressing a file into a new compressed file. I know it's comparing apples and oranges but it's just an example:

hyperfine usage example
(click to see full picture)

It basically executes the following commands over and over and then compares how long each one took on average:

  • apack log.log.apack.gz log.log
  • gzip -k log.log
  • zstd log.log
  • brotli -3 log.log

If you're curious about the ~results~ apples vs oranges, the final result is:

▶ ls -lSh log.log*
-rw-r--r--  1 peterbe  staff    25M Jul  3 10:39 log.log
-rw-r--r--  1 peterbe  staff   2.4M Jul  5 22:00 log.log.apack.gz
-rw-r--r--  1 peterbe  staff   2.4M Jul  3 10:39 log.log.gz
-rw-r--r--  1 peterbe  staff   2.2M Jul  3 10:39 log.log.zst
-rw-r--r--  1 peterbe  staff   2.1M Jul  3 10:39 log.log.br

The point is that you type hyperfine followed by each command in quotation marks. The --prepare is run for each command and you can also use --cleanup="{cleanup command here}.

It's versatile so it doesn't have to be different commands but it can be: hyperfine "python optimization1.py" "python optimization2.py" to compare to Python scripts.

🎵 You can also export the output to a Markdown file. Here, I used:

▶ hyperfine "apack log.log.apack.gz log.log" "gzip -k log.log" "zstd log.log" "brotli -3 log.log" --prepare="rm -fr log.log.*" --export-markdown log.compress.md
▶ cat log.compress.md | pbcopy

and it becomes this:

Command Mean [ms] Min [ms] Max [ms] Relative
apack log.log.apack.gz log.log 291.9 ± 7.2 283.8 304.1 4.90 ± 0.19
gzip -k log.log 240.4 ± 7.3 232.2 256.5 4.03 ± 0.18
zstd log.log 59.6 ± 1.8 55.8 65.5 1.00
brotli -3 log.log 122.8 ± 4.1 117.3 132.4 2.06 ± 0.09

Please post a comment if you have thoughts or questions.

./bin/huey-isnt-running.sh - A bash script to prevent lurking ghosts

Python, Linux, Bash

tl;dr; Here's a useful bash script to avoid starting something when its already running as a ghost process.

Huey is a great little Python library for doing background tasks. It's like Celery but much lighter, faster, and easier to understand.

What cost me almost an hour of hair-tearing debugging today was that I didn't realize that a huey daemon process had gotten stuck in the background with code that wasn't updating as I made changes to the tasks.py file in my project. I just couldn't understand what was going on.

The way I start my project is with honcho which is a Python Foreman clone. The Procfile looks something like this:

elasticsearch: cd /Users/peterbe/dev/PETERBECOM/elasticsearch-7.7.0 && ./bin/elasticsearch -q
web: ./bin/run.sh web
minimalcss: cd minimalcss && PORT=5000 yarn run start
huey: ./manage.py run_huey --flush-locks --huey-verbose
adminui: cd adminui && yarn start
pulse: cd pulse && yarn run dev

And you start that with simply typing:

honcho start

When you Ctrl-C, it kills all those processes but somehow somewhere it doesn't always kill everything. Restarting the computer isn't a fun alternative.

So, to prevent my sanity from draining I wrote this script:

#!/usr/bin/env bash
set -eo pipefail

# This is used to make sure that before you start huey, 
# there isn't already one running the background.
# It has happened that huey gets lingering stuck as a 
# ghost and it's hard to notice it sitting there 
# lurking and being weird.

bad() {
    echo "Huey is already running!"
    exit 1
}

good() {
    echo "Huey is NOT already running"
    exit 0
}

ps aux | rg huey | rg -v 'rg huey' | rg -v 'huey-isnt-running.sh' && bad || good

(If you're wondering what rg is; it's short for ripgrep)

And I change my Procfile accordingly:

-huey: ./manage.py run_huey --flush-locks --huey-verbose
+huey: ./bin/huey-isnt-running.sh && ./manage.py run_huey --flush-locks --huey-verbose

There really isn't much rocket science or brain surgery about this blog post but I hope it inspires someone who's been in similar trenches that a simple bash script can make all the difference.

Please post a comment if you have thoughts or questions.

How I added brotli_static to nginx 1.17 in Ubuntu (Eoan Ermine) 19.10

Nginx, Linux

I knew I didn't want to download the sources to nginx to install it on my new Ubuntu 19.10 server because I'll never have the discipline to remember to keep it upgraded. No, I'd rather just run apt update && apt upgrade every now and then.

Why is this so hard?! All I need is the ability to set brotli_static on; in my Nginx config so it'll automatically pick the .br file if it exists on disk.

These instructions totally helped but here they are specifically for my version (all run as root):

git clone --recursive https://github.com/google/ngx_brotli.git

apt install brotli
apt-get build-dep nginx

# Note the version of which nginx you have installed
nginx -v
# ...which informs which URL to wget
wget https://nginx.org/download/nginx-1.17.9.tar.gz
aunpack nginx-1.17.9.tar.gz
nginx -V 2>&1 >/dev/null | grep -o " --.*" | grep -oP .+?(?=--add-dynamic-module)| head -1 > nginx-1.17.9/build_args.txt
cd nginx-1.17.9/
./configure --with-compat $(cat build_args.txt) --add-dynamic-module=../ngx_brotli
make install

cp objs/ngx_http_brotli_filter_module.so  /usr/lib/nginx/modules/
chmod 644 /usr/lib/nginx/modules/ngx_http_brotli_filter_module.so
cp objs/ngx_http_brotli_static_module.so /usr/lib/nginx/modules/
chmod 644 /usr/lib/nginx/modules/ngx_http_brotli_static_module.so

ls -l /etc/nginx/modules

Now I can edit my /etc/nginx/nginx.conf (somewhere near the top) to:

load_module /usr/lib/nginx/modules/ngx_http_brotli_filter_module.so;
load_module /usr/lib/nginx/modules/ngx_http_brotli_static_module.so;

And test that it works:

nginx -t

Please post a comment if you have thoughts or questions.