Technology Tales

Adventures & experiences in contemporary technology

Using associative arrays in scripting for BASH version 4 and above

29th April 2023

Associated arrays get called different names in different computing languages: dictionaries, hash tables and so on. What is held in common is that they essentially are lists of key value pairs. In the case of BASH, you need at least version 4 to make use of this facility. In Linux Mint, I get 5.1.16, but macOS users apparently are still on BASH 3, so this post may not help them.

To declare an associative array in a later version of BASH, the following command gets issued:

declare -A hashtable

The code to add a key value pair then takes the following form:

hashtable[key1]=value1

Several values can be added to an empty array like this:

hashtable=( ["key1"]="value1" ["key2"]="value2" )

Declaration and instantiation of an associative can be done in the same line as follows:

declare -A hashtable=( ["key1"]="value1 ["key2"]="value2")

Handily, it is possible to loop through the entries in an associative array. It is possible to do this for keys and for values, once you expand out the appropriate list. The following expands a list of values:

"${hashtable[@]}"

Expanding a list of values needs something like this:

"${!hashtable[@]}"

Looping through a list of values needs something like the following:

for val in "${hashtable[@]}"; do echo "$val"; done;

The above has been placed on a single line with semicolon delimiters for brevity, but this can be put on several lines with no semicolons for added clarity as long as correct indentation is followed. It is also possible to similarly loop through a list of keys:

for key in "${!hashtable[@]}"; do echo "key: $key, value ${hashtable[$key]}"; done;

For the example associative array declared earlier, the last line produces this output, resolving the value using the supplied key:

key: key2, value value2
key: key1, value value1

All of this found a use in a script that I created for adding new Markdown files to a Hugo instance because there was more than one shortcode that I wished to apply due to my having more than one content directory in use.

String replacement in BASH scripting

28th April 2023

During creation of new posts for a Hugo deployed website, I found myself using the same directories again and again. Since I invariably ended up making typing mistakes when I did so, I fancied the idea of using shortcodes instead.

Because I wanted to turn the shortcode into the actual directory name, I chose the use of text replacement in BASH scripting. Thankfully, this is simple and avoids the use of regular expressions, which can bring their own problems. The essential syntax is as follows:

variable="${variable/search text/replacement}"

For the variable, the search text is substituted with the replacement very easily. It is even possible to include the search and replacement text in variables. In the example below, this is achieved using variables called original and replacement.

variable="${variable/$original/$replacement}"

Doing this got me my translatable shortcodes and converted them into actual directory names for the hugo command to process. There may be other uses yet.

Rendering Markdown into HTML using PHP

3rd December 2022

One of the good things about using virtual private servers for hosting websites in preference to shared hosting or using a web application service like WordPress.com or Tumblr is that you get added control and flexibility. There was a time when HTML, CSS and client-side scripting were all that was available from the shared hosting providers that I was using. Then, static websites were my lot until it became possible to use Perl server side scripting. PHP predominates now, but Python or Ruby cannot be discounted either.

Being able to install whatever you want is a bonus as well, though it means that you also are responsible for the security of the containers that you use. There will be infrastructure security, but that of your own machine will be your own concern. Added power always means added responsibility, as many might say.

The reason that these thought emerge here is that getting PHP to render Markdown as HTML needs the installation of Composer. Without that, you cannot use the CommonMark package to do the required back-work. All the command that you see here will work on Ubuntu 22.04. First, you need to download Composer and executing the following command will accomplish this:

curl https://getcomposer.org/installer -o /tmp/composer-setup.php

Before the installation, it does no harm to ensure that all is well with the script before proceeding. That means that capturing the signature for the script using the following command is wise:

HASH=`curl https://composer.github.io/installer.sig`

Once you have the script signature, then you can check its integrity using this command:

php -r "if (hash_file('SHA384', '/tmp/composer-setup.php') === '$HASH') { echo 'Installer verified'; } else { echo 'Installer corrupt'; unlink('composer-setup.php'); } echo PHP_EOL;"

The result that you want is “Installer verified”. If not, you have some investigating to do. Otherwise, just execute the installation command:

sudo php /tmp/composer-setup.php --install-dir=/usr/local/bin --filename=composer

With Composer installed, the next step is to run the following command in the area where your web server expects files to be stored. That is important when calling the package in a PHP script.

composer require league/commonmark

Then, you can use it in a PHP script like so:

define("ROOT_LOC",$_SERVER['DOCUMENT_ROOT']);
include ROOT_LOC . '/vendor/autoload.php';
use League\CommonMark\CommonMarkConverter;
$converter = new CommonMarkConverter();
echo $converter->convertToHtml(file_get_contents(ROOT_LOC . '<location of markdown file>));

The first line finds the absolute location of your web server file directory before using it when defining the locations of the autoload script and the required markdown file. The third line then calls in the CommonMark package, while the fourth sets up a new object for the desired transformation. The last line converts the input to HTML and outputs the result.

If you need to render the output of more than one Markdown file, then repeating the last line from the preceding block with a different file location is all you need to do. The CommonMark object persists and can be used like a variable without needing the reinitialisation to be repeated every time.

The idea of building a website using PHP to render Markdown has come to mind, but I will leave it at custom web pages for now. If an opportunity comes, then I can examine the idea again. Before, I had to edit HTML, but Markdown is friendlier to edit, so that is a small advance for now.

Moves to Hugo

30th November 2022

What amazes me is how things can become more complicated over time. As long as you knew HTML, CSS and JavaScript, building a website was not as onerous as long as web browsers played ball with it. Since then, things have got easier to use but more complex at the same time. One example is WordPress: in the early days, themes were much simpler than they are now. The web also has got more insecure over time, and that adds to complexity as well. It sometimes feels as if there is a choice to make between ease of use and simplicity.

It is against that background that I reassessed the technology that I was using on my public transport and Irish history websites. The former used WordPress, while the latter used Drupal. The irony was that the simpler website was using the more complex platform, so the act of going simpler probably was not before time. Alternatives to WordPress were being surveyed for the first of the pair, but none had quite the flexibility, pervasiveness and ease of use that WordPress offers.

There is another approach that has been gaining notice recently. One part of this is the use of Markdown for web publishing. This is a simple and distraction-free plain text format that can be transformed into something more readable. It sees usage in blogs hosted on GitHub, but also facilitates the generation of static websites. The clutter is absent for those who have no need of the Gutenberg Editor on WordPress.

With the content written in Markdown, it can be fed to a static website generator like Hugo. Using defined templates and fixed assets like CSS together with images and other static files, it can slot the content into HTML files very speedily since it is written in the Go programming language. Once you get acclimatised, there are no folder structures that cannot be used, so you get full flexibility in how you build out your website. Sitemaps and RSS feeds can be built at the same time, both using the same input as the HTML files.

In a nutshell, it automates what once needed manual effort used a code editor or a visual web page editor. The use of HTML snippets and layouts means that there is no necessity for hand-coding content, like there was at the start of the web. It also helps that Bootstrap can be built in using Node, so that gives a basis for any styling. Then, SCSS can take care of things, giving even more automation.

Given that there is no database involved in any of this, the required information has to be stored somewhere, and neither the Markdown content nor the layout files contain all that is needed. The main site configuration is defined in a single TOML file, and you can have a single one of these for every publishing destination; I have development and production servers, which makes this a very handy feature. Otherwise, every Markdown file needs a YAML header where titles, template references, publishing status and other similar information gets defined. The layouts then are linked to their components, and control logic and other advanced functionality can be added too.

Because static files are being created, it does mean that site searching and commenting or contact pages cannot work they would on a dynamic web platform. Often, external services are plugged in using JavaScript. One that I use for contact forms is Getform.io. Then, Zapier has had its uses in using the RSS feed to tweet site updates on Twitter when new content gets added. Though I made different choices, Disqus can be used for comments and Algolia for site searching. Generally, though, you can find yourself needing to pay, particularly if you need to remove advertising or gain advanced features.

Some comments service providers offer open source self-hosted options, but I found these difficult to set up and ended up not offering commenting at all. That was after I tried out Cactus Comments only to find that it was not discriminating between pages, so it showed the same comments everywhere. There are numerous alternatives like Remark42, Hyvor Talk, Commento, FastComments, Utterances, Isso, Mouthful, Muut and HyperComments but trying them all out was too time-consuming for what commenting was worth to me. It also explains why some static websites even send readers to Twitter if they have something to say, though I have not followed this way of working.

For searching, I added a JavaScript/JSON self-hosted component to the transport website, and it works well. However, it adds to the size of what a browser needs to download. That is not a major issue for desktop browsers, but the situation with mobile browsers is such that it has a sizeable effect. Testing with PageSpeed and Lighthouse highlighted this, even if I left things as they are. The solution works well in any case.

One thing that I have yet to work out is how to edit or add content while away from home. Editing files using an SSH connection is as much a possibility as setting up a Hugo publishing setup on a laptop. After that, there is the question of using a tablet or phone, since content management systems make everything web based. These are points that I have yet to explore.

As is natural with a code-based solution, there is a learning curve with Hugo. Reading a book provided some orientation, and looking on the web resolved many conundrums. There is good documentation on the project website, while forum discussions turn up on many a web search. Following any research, there was next to nothing that could not be done in some way.

Migration of content takes some forethought and took quite a bit of time, though there was an opportunity to carry some housekeeping as well. The history website was small, so copying and pasting sufficed. For the transport website, I used Python to convert what was on the database into Markdown files before refining the result. That provided some automation, but left a lot of work to be done afterwards.

The results were satisfactory, and I like the associated simplicity and efficiency. That Hugo works so fast means that it can handle large websites, so it is scalable. The new Markdown method for content production is not problematical so far apart from the need to make it more portable, and it helps that I found a setup that works for me. This also avoids any potential dealbreakers that continued development of publishing platforms like WordPress or Drupal could bring. For the former, I hope to remain with the Classic Editor indefinitely, but now have another option in case things go too far.

A look at the Julia programming language

19th November 2022

Several open-source computing languages get mentioned when talking about working with data. Among these are R and Python, but there are others; Julia is another one of these. It took a while before I got to check out Julia because I felt the need to get acquainted with R and Python beforehand. There are others like Lua to investigate too, but that can wait for now.

With the way that R is making an incursion into clinical data reporting analysis following the passage of decades when SAS was predominant, my explorations of Julia are inspired by a certain contrariness on my part. Alongside some small personal projects, there has been some reading in (digital) book form and online. Concerning the latter of these, there are useful tutorials like Introduction to Data Science: Learn Julia Programming, Maths & Data Science from Scratch or Julia Programming: a Hands-on Tutorial. Like what happens with R, there are online versions of published books available free of charge, and they include Julia Data Science and Interactive Visualization and Plotting with Julia. Video learning can help too and Jane Herriman has recorded and shared useful beginner’s guides on YouTube that start with the basics before heading onto more advanced subjects like multiple dispatch, broadcasting and metaprogramming.

This piece of learning has been made of simple self-inspired puzzles before moving on to anything more complex. That differs from my dalliance with R and Python, where I ventured into complexity first, not least because of testing them out with public COVID data. Eventually, I got around to doing that with Julia too though my interest was beginning to wane by then, and Julia’s abilities for creating multipage PDF files were such that PDF Toolkit was needed to help with this. Along the way, I have made use of such packages as CSV.jl, DataFrames.jl, DataFramesMeta, Plots, Gadfly.jl, XLSX.jl and JSON3.jl, among others. After that, there is PrettyTables.jl to try out, and anyone can look at the Beautiful Makie website to see what Makie can do. There are plenty of other packages creating graphs such as SpatialGraphs.jl, PGFPlotsX and GRUtils.jl. For formatting numbers, options include Format.jl and Humanize.jl.

So far, my primary usage has been with personal financial data together with automated processing and backup of photo files. The photo file processing has taken advantage of the ability to compile Julia scripts for added speed because just-in-time compilation always means there is a lag before the real work begins.

VS Code is my chosen editor for working with Julia scripts, since it has a plugin for the language. That adds the REPL, syntax highlighting, execution and data frame viewing capabilities that once were added to the now defunct Atom editor by its own plugin. While it would be nice to have a keyboard shortcut for script execution, the whole thing works well and is regularly updated.

Naturally, there have been a load of queries as I have gone along and the Julia Documentation has been consulted as well as Julia Discourse and Stack Overflow. The latter pair have become regular landing spots on many a Google search. One example followed a glitch that I encountered after a Julia upgrade when I asked a question about this and was directed to the XLSX.jl Migration Guides where I got the information that I needed to fix my code for it to run properly.

There is more learning to do as I continue to use Julia for various things. Once compiled, it does run fast like it has been promised. The syntax paradigm is akin to R and Python, but there are Julia-specific features too. If you have used the others, the learning curve is lessened but not eliminated completely. This is not an object-oriented language as such, but its functional nature makes it familiar enough for getting going with it. In short, the project has come a long way since it started more than ten years ago. There is much for the scientific programmer, but only time will tell if it usurped its older competitors. For now, I will remain interested in it.

Redirecting a WordPress site to its home page when its loop finds no posts

5th November 2022

Since I created a bespoke theme for this site, I have been tweaking things as I go. The basis came from the WordPress Theme Developer Handbook, which gave me a simpler starting point shorn of all sorts of complexity that is encountered with other themes. Naturally, this means that there are little rough edges that need tidying over time.

One of these is dealing with errors on the site like when content is not found. This could be a wrong address or a search query that finds no matching posts. When that happens, there is a redirection to the home page using some simple JavaScript within the loop fallback code enclosed within script start and end tags (including the whole code triggers the action from this post so it cannot be shown here):

location.href="[blog home page ]";

The bloginfo function can be used with the url keyword to find the home page so this does not get hard coded. For now, this works so long as JavaScript is enabled but a more robust approach may come in time. It is not possible to do a PHP redirect because of the nature of HTTP: when headers have been sent, it is not possible to do server redirects. At this stage, things become client side so using JavaScript is one way to go instead.

Removing a Julia package

5th October 2022

While I have been programming with SAS for a few decades and it remains a lynchpin in the world of clinical development in the pharmaceutical industry, other technologies like R and Python are gaining a foothold. Two years ago, I started to look at those languages with personal projects being a great way of facilitating this. In addition, I got to hear of Julia and got to try that too. That journey continues since I have put it into use for importing and backing up photos, and there are other possible uses too.

Recently, I updated Julia to version 1.8.2 but ran into a problem with the DataArrays package that I had installed so I decided to remove it since it was added during experimentation. The Pkg package that is used for package management is documented but I had not gotten to that so some web searching ensued. It turns out that there are two ways of doing this. One uses the REPL: after pressing the ] key, the following command gets issued:

rm DataArrays

When all is done, pressing the delete or backspace keys returns things to normal. This also can be done in a script as well as the REPL and the following line works in both instances:

using Pkg; Pkg.rm("DataArrays")

The semicolon is used to separate two commands issued in the same line but they can be on different lines or issued separately just as well. Naturally, DataArrays is just an example here so you just replace that with the name of whatever other package you need to remove. Since we can get carried away when downloading packages, there are times when a clean-up is needed to remove redundant packages so knowing how to remove any clutter is invaluable.

Accessing Julia REPL command history

4th October 2022

In the BASH shell used on Linux and UNIX, the history command calls up a list of recent commands used and has many uses. There is a .bash_history file in the root of the user folder that logs and provides all this information so there are times when you need to exclude some commands from there but that is another story.

The Julia REPL environment works similarly to many operating system command line interfaces, so I wondered if there was a way to recall or refer to the history of commands issued. So far, I have not come across an equivalent to the BASH history command for the REPL itself but there the command history is retained in a file like .bash_history. The location varies on different operating systems though. On Linux, it is ~/.julia/logs/repl_history.jl while it is %USERPROFILE%\.julia\logs\repl_history.jl on Windows. While I tend to use scripts that I have written in VSCode rather than entering pieces of code in the REPL, the history retains its uses and I am sharing it here for others. In the past, the location changed but these are the ones with Julia 1.8.2, the version that I have at the time of writing.

Changing the Ansible Vault editor from Vi to Nano

15th August 2022

Recently, I got to experimenting with Ansible after reading about the orchestration tool in a copy of Admin magazine. It came in handy for updating a few web servers that I have as well as updating my main Linux workstation. For the former, automated entry of SSH passwords sufficed but the same did not apply for sudo usage on my local machine. This meant that I needed to use Ansible Vault to store the administrator password and doing so opened up a file in the Vi editor. since I am not familiar with Vi and wanted to get things sorted quickly, I fancied using something more user-friendly like Nano.

Doing this meant adding the following line to .bashrc:

export EDITOR=nano

Saving and closing the file followed by reloading the session set me up for what was needed.

Getting custom Python imports to work in Visual Studio Code

18th February 2022

While I continue to use Spyder as my preferred Python code editor, I also tried out Visual Studio Code. Handily, this Integrated Development Environment also has facilities for working with R and Julia code as well as MarkDown text editing and adding the required extensions is enough for these applications; it helps that there is an unofficial Grammarly extension for content creation.

My Python code development makes use of the Pylance extension and it works a little differently from Spyder when it comes to including files using import statements. Spyder will look into the folder where the base script is located but the default behaviour of Pylance is that it looks in the root path of your workspace. This meant that any code that ran successfully in Spyder failed in Visual Studio Code.

The way around this was to add the required location using the python.analysis.extraPaths setting for the workspace. That meant opening Settings by navigating to File > Preferences > Settings in the menu system and entering python.analysis.extraPaths into the search box. That took me to the section that I needed and I then clicked on Add Item before entering the required path and clicking on the OK button. That was enough to fix the problem and all worked as it should after that.

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