Author Archives: hydralien

[tech] Leadership Growth

A great article on what to focus (and avoid focusing) on when pursuing your career growth as a tech lead – or any leadership role, really: https://staffeng.com/guides/work-on-what-matters

I guess it could be put simpler into something like “find the spot where you could help the most, and do it” – but there are several additional (and quite important) points there, like avoiding chasing simple tasks, don’t try to just look good, adjust your perspective to new challenges, plan ahead etc. Well worth reading!

Workout sketches for fun!

I won’t add much text here, as these are mostly for my own reference and describing each would take quite some time, while hopefully images are explanatory enough.

I’d just say these exercises were collected from the additional materials for the “Training For The New Alpinism” book, some other training materials and personal experiments.

Radial Charts

Why

I wanted to plot the data that is tightly connected to a time of a day as a circular chart, resembling the clock face – for no particular reason other than checking out how it looks.

Another thing I wanted to do was to play with some relatively modern JS framework.

And then I also got a bit a of a spare time on my hands.

What

So as a result, here’s a code that fetches CSV data from Graphite metrics (or any other CSV file) and displays it on a radial chart (aka Radar chart). It’s crude and unoptimised and inefficient, but it serves the goal of visual representation (see examples section below): https://github.com/hydralien/Radial-Charts

It’s mostly an amCharts showcase – amCharts are amazing, I love them dearly. Check them out if you’re not familiar, there’s seemingly nothing you can’t do with them: https://www.amcharts.com/demos/

Additionally, it also uses Github Actions (https://help.github.com/en/actions) as a CI mechanism – so on every push a build is pushed to a branch and then deployed as Github pages using https://github.com/marketplace/actions/github-pages-action#%EF%B8%8F-publish_branch (there’s many action plugins, this one was just the first one that worked).

Examples

Surprisingly, there’s npt that many public datasets with high-granularity daily data available on the Internet, but here’s at least one:
Bike rentals in NYC, January 1st 2020 vs July 1st 2019 (from https://s3.amazonaws.com/tripdata/index.html):

Bike rentals

Shortcomings

  • it’s not a working tool or a developing project – it’s a fun thing built for no reason
  • it loads a ton of unnecessary libraries, becasue how amCharts library for Vue.js is structured, and also because it’s not optimised for anything
  • <many other things>

Mandelbrot set

I was always fascinated by the Mandelbrot set pictures and always wanted to create a representation myself, but never really got to do it – till a few days ago when I stumbled over an article boiling the code down to a very simple sequence (https://slicker.me/fractals/excel.htm) – so I just took it and made parameters adjustable. Also used it as an exercise in Vue.js, as it was another thing I wanted to try but never did.

It’s a very-very crude solution, but it was a good exercise: https://www.hydralien.net/mandelbrood.html?pixelSize=4&divisor=50&cxStart=-2&cyStart=-2&boundary=200&precision=0.4&pixelIterations=30

Also the code is here (well, it’s also in the html file, but FTR): https://github.com/hydralien/mandelbrood

Permanently adding SSH private key to OSX keychain

It’s been bugging me for quite a while, but never enough to go and find a solution – until now.

Shamelessly re-posting a perfect guidance from https://apple.stackexchange.com/questions/48502/how-can-i-permanently-add-my-ssh-private-key-to-keychain-so-it-is-automatically:

On OSX, the native ssh-add client has a special argument to save the private key’s passphrase in the OSX keychain, which means that your normal login will unlock it for use with ssh. On OSX Sierra and later, you also need to configure SSH to always use the keychain (see Step 2 below).

Alternatively you can use a key without a passphrase, but if you prefer the security that’s certainly acceptable with this workflow.

Step 1 – Store the key in the keychain

Just do this once:

ssh-add -K ~/.ssh/[your-private-key]

Enter your key passphrase, and you won’t be asked for it again.

(If you’re on a pre-Sierra version of OSX, you’re done, Step 2 is not required.)

Step 2 – Configure SSH to always use the keychain

It seems that OSX Sierra removed the convenient behavior of persisting your keys between logins, and the update to ssh no longer uses the keychain by default. Because of this, you will get prompted to enter the passphrase for a key after you upgrade, and again after each restart.

The solution is fairly simple, and is outlined in this github thread comment. Here’s how you set it up:

  1. Ensure you’ve completed Step 1 above to store the key in the keychain.
  2. If you haven’t already, create an ~/.ssh/config file. In other words, in the .ssh directory in your home dir, make a file called config.
  3. In that .ssh/config file, add the following lines:Host * UseKeychain yes AddKeysToAgent yes IdentityFile ~/.ssh/id_rsa Change ~/.ssh/id_rsa to the actual filename of your private key. If you have other private keys in your ~.ssh directory, also add an IdentityFile line for each of them. For example, I have one additional line that reads IdentityFile ~/.ssh/id_ed25519 for a 2nd private key.The UseKeychain yes is the key part, which tells SSH to look in your OSX keychain for the key passphrase.
  4. That’s it! Next time you load any ssh connection, it will try the private keys you’ve specified, and it will look for their passphrase in the OSX keychain. No passphrase typing required.

Web server in OSX (Apache2, dammit!)

There’s an Apache2 in OSX!!!

Apache2! It’s been awhile since I touched httpd.conf… so many memories… ūüėČ

It’s all described in this tutorial:¬†http://osxdaily.com/2012/09/02/start-apache-web-server-mac-os-x/

It’s dead simple – see/edit¬†/etc/apache2/httpd.conf to find or set DirectoryRoot (mind directory access rights) and run “sudo apachectl start” (stop, restart).

To enable user websites, add following to etc/apache2/users/USERNAME.conf :

<Directory "/Users/USERNAME/Sites/">
Options Indexes Multiviews
AllowOverride AuthConfig Limit
Order allow,deny
Allow from all
</Directory>

and then it’d be served as¬†http://127.0.0.1/~USERNAME/

Also, generating self-signed certificates: https://devcenter.heroku.com/articles/ssl-certificate-self

And adding them to OSX keychain: https://tosbourn.com/getting-os-x-to-trust-self-signed-ssl-certificates/

And you’d need to put them into¬†/private/etc/apache2/ssl/ and (potentially) edit¬†/private/etc/apache2/extra/httpd-ssl.conf and enable (uncomment)

Include /private/etc/apache2/extra/httpd-ssl.conf

and

LoadModule ssl_module libexec/apache2/mod_ssl.so

in /etc/apache2/httpd.conf

and run “apachectl restart” as root.

Champagne for all!

  _
 {_}
 |(|
 |=|
/   \
|.--|
||  |
||  |    .    ' .
|'--|  '     \~~~/
'-=-' \~~~/   \_/
       \_/     Y
        Y     _|_
       _|_

Turning Reddit RSS into a usable thing, or replacing reddit links with article links

Reddit is a great place to follow various news and updates – I’m using it to keep up to date with programming-related stuff,¬†https://www.reddit.com/r/programming/

Although it could be read directly on the website (I guess), I prefer to do it via RSS aggregator (I use Feedly) Рit makes it so much easier to track updates. So adding .rss to the Reddit URL, I get all I need in the aggregator (e.g. https://www.reddit.com/r/programming/.rss)

Well, more than I need, actually – it points me to the Reddit page with comments about the article, and those comments are the very last thing I want to see (if you tried to read them at least once, you’d understand; if not – just try; or trust me).

So doing extra navigation by clicking each article’s subject one more time after Reddit page loads, it finally got me – and I wrote a little proxy page that would replace Reddit comment page link with actual article link in the RSS feed XML.

It’s all here: https://github.com/hydralien/tools/tree/master/reddit-streamline

There’s a bunch of debug stuff there, and Godaddy-caused library loading nonsense, but the gist is simple – could also be tested at¬†https://www.hydralien.net/py/direddit/r/programming/.rss

Math is beautiful – it’s a sheer magic to me, but now and then some good people publish approachable articles that allow me get a tiny dash of understanding of how things work.

There’s one such article today –¬†https://innovation.vivint.com/introduction-to-reed-solomon-bc264d0794f8 (and complimentary¬†https://medium.com/@jtolds/joseph-louis-lagrange-and-the-polynomials-499cf0742b39) that I could highly recommend. It’s a fairly simplified overview that provides just a basic idea of a particular error correction technique, but it’s simple yet comprehensive.

In fact it was so fascinating I couldn’t stop myself from giving it a (very short and simple) try. I won’t repeat the articles in any way, just post a code with some comments.

Let’s say we have this code in Python (minor comments inline):

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xs = [ 1.0, # float format to make suure calculation precision is not impacted - it fails badly otherwise
       2.0,
       3.0,
       4.0,
]
 
ys = [ 10, # the values here are random - like in "I made them up". But this is about "any numbers", right?
       42,
       74,
       111,
]
 
# it's a direct representation of what's described in the https://medium.com/@jtolds/joseph-louis-lagrange-and-the-polynomials-499cf0742b39 article
def l0(x):
    return ( (x-xs[1]) * (x-xs[2]) * (x-xs[3]) ) / ( (xs[0] - xs[1]) * (xs[0] - xs[2]) * (xs[0] - xs[3]) )
def l1(x):
    return ( (x-xs[0]) * (x-xs[2]) * (x-xs[3]) ) / ( (xs[1] - xs[0]) * (xs[1] - xs[2]) * (xs[1] - xs[3]) )
def l2(x):
    return ( (x-xs[0]) * (x-xs[1]) * (x-xs[3]) ) / ( (xs[2] - xs[0]) * (xs[2] - xs[1]) * (xs[2] - xs[3]) )
def l3(x):
    return ( (x-xs[0]) * (x-xs[1]) * (x-xs[2]) ) / ( (xs[3] - xs[0]) * (xs[3] - xs[1]) * (xs[3] - xs[2]) )
 
# as well as this
def f(num):
    return ys[0] * l0(num) + ys[1] * l1(num) + ys[2] * l2(num) + ys[3] * l3(num)
 
for x in range(0, 10):
    fx = f(x)
    print "{}: {}".format(x, fx)

And we run it and we get this:

0: -27.0
1: 10.0
2: 42.0
3: 74.0
4: 111.0
5: 158.0
6: 220.0
7: 302.0
8: 409.0
9: 546.0

(you can add more point; you could also use matplotlib to plot them)

So as you can see it reflected the pre-defined 4 points (10, 42, 74 and 111), but also calculated other points on a curve. So let’s say we sent 6 point, but client received only points 1,2,5 and 6 (10, 42, 158, 220).

If we adjust the input values to look like this:

xs = [ 1.0,
       2.0,
       5.0,
       6.0,
]
 
ys = [ 10,
       42,
       158,
       220,
]

and run it again, we’d still get all the values, because 4 values are enough to define the cubic function curve, and these were taken from that very curve:

0: -27.0
1: 10.0
2: 42.0
3: 74.0
4: 111.0
5: 158.0
6: 220.0
7: 302.0
8: 409.0
9: 546.0

Magic, right?

Some extra calculations around it are also available at http://mathonline.wikidot.com/linear-lagrange-interpolating-polynomials