TOPIC: LIGHTWEIGHT MARKUP LANGUAGES
Altering table and hyperlink tags for single Grav articles using HTML post-processing
1st April 2026
This year, there have been a few entries on here regarding Grav because of my moving parts of my website estate to that content management system, first from Textpattern and latterly from WordPress. Once the second activity was completed, I then added an article on German public holidays elsewhere. That brought me to the topic of this piece: ensuring that some Markdown was rendered as required.
There were two parts to this: the styling of tables and the actions of hyperlinks. Each needs to be performed in a page template when all HTML has been initially rendered. Further processing then makes the required changes. Since this is a page template and not a partial template and not a partial template, you need to import a master template like this:
{% extends 'partials/base.html.twig' %}
Then, you go to the next stage, defining the content block within {% block content %}...{% endblock %} Twig tags:
{% set content = page.content
|replace({'<table>': '<table class="table mt-5 mb-5">'})
|replace({'<a href="http': '<a target="_blank" rel="noopener noreferrer" href="http'})
%}
The above reads in the page content (page.content) and does some text replacement operations. The first of these changes <table> to <table class="table mt-5 mb-5">, while the second replaces <a href="http with <a target="_blank" rel="noopener noreferrer" href="http. While my content was a mix of Markdown and HTML, depending on the article, the latter operation appeared to standardise every link.
Once the text replacement has been completed, the next step is to output the processed HTML like this:
{{ content|raw }}
This last line sits outside the {% block content %}...{% endblock %} block; coming after it, in fact. To send the processed output to the generated web page, you need to ensure that you are referring to the right variable, the local one called content and not page.content. The raw filter also is essential here to ensure that nothing is rendered into HTML when the raw HTML itself is what is needed.
All of this effort ensures that straightforward Markdown can be used in content, while Grav does some extra work in the background to ensure that all is rendered without extra intervention. While there may need to be a certain level of standardisation to make this all work well, I find that it does what is needed, albeit in a different manner from shortcode approach that you find in Hugo.
Some R packages to explore as you find your feet with the language
24th March 2026
Here are some commonly used R packages and other tools that are pervasive, along with others that I have encountered while getting started with the language, itself becoming pervasive in my line of business. The collection grew organically as my explorations proceeded, and reflects what I was trying out during my acclimatisation.
General
Here are two general packages to get things started, with one of them being unavoidable in the R world. The other is more advanced, possibly offering more to package developers.
You cannot use R without knowing about this collection of packages. In many ways, they form a mini-language of their own, drawing some criticism from those who reckon that base R functionality covers a sufficient gamut anyway. Nevertheless, there is so much here that will get you going with data wrangling and visualisation that it is worth knowing what is possible. The complaints may come from your not needing to use anything else for these purposes.
This R package enables developers to convert existing R functions into web API endpoints by adding roxygen2-like comment annotations to their code. Once annotated, functions can handle HTTP GET and POST requests, accept query string or JSON parameters and return outputs such as plain values or rendered plots. The package is available on CRAN as a stable release, with a development version hosted on GitHub. For deployment, it integrates with DigitalOcean through a companion package called {plumberDeploy}, and also supports Posit Connect, PM2 and Docker as hosting options. Related projects in the same space include OpenCPU, which is designed for hosting R APIs in scientific research contexts, and the now-discontinued jug package, which took a more programmatic approach to API construction.
Data Preparation
You simply cannot avoid working with data during any analysis or reporting work. While there is a learning curve if you are used to other languages, there is little doubt that R is well-endowed when it comes to performing these tasks. Here are some packages that extend base R capabilities and might even add some extra user-friendliness along the way.
The {forcats} package in R provides functions to manage categorical variables by reordering factor levels, collapsing infrequent values and adjusting their sequence based on frequency or other variables. It includes tools such as reordering by another variable, grouping rare categories into 'other' and modifying level order manually, which are useful for data analysis and visualisation workflows. Designed as part of the tidyverse, it integrates with other packages to streamline tasks like counting and plotting categorical data, enhancing clarity and efficiency in handling factors within R.
Around this time last year, I remember completing a LinkedIn course on a set of good practices known as tidy data, where each variable occupies a column, each observation a row and each value a single cell. This package is designed to help users restructure data so it follows those rules. It provides tools for reshaping data between long and wide formats, handling nested lists, splitting or combining columns, managing missing values and layering or flattening grouped data.
Installation options include the {tidyverse} collection, standalone installation, or the development version from GitHub. The package succeeds earlier reshaping tools like {reshape2} and {reshape}, offering a focused approach to tidying data rather than general reshaping or aggregation.
Having a long track record of working with SAS, {haven} with its abilities to read and write data files from statistical software such as SAS, SPSS and Stata, leveraging the ReadStat library, arouses my interest. Handily, it supports a range of file formats, including SAS transport and data files, SPSS system and older portable files and Stata data files up to version 15, converting these into tibbles with enhanced printing capabilities. Value labels are preserved as a labelled class, allowing conversion to factors, while dates and times are transformed into standard R classes.
While there are other approaches to working with databases using R, {RMariaDB} provides a database interface and driver for MariaDB, designed to fully comply with the DBI specification and serve as a replacement for the older {RMySQL} package. It supports connecting to databases using configuration files, executing queries, reading and writing data tables and managing results in chunks. Installation options include binary packages from CRAN or development versions from GitHub, with additional dependencies such as MariaDB Connector/C or libmysqlclient required for Linux and macOS systems. Configuration is typically handled through a MariaDB-specific file, and the package includes acknowledgments for contributions from various developers and organisations.
For many people, the pandemic may be a fading memory, yet it offered its chances for learning R, not least because there was a use case with more than a hint of personal interest about it. Here is a library making it easier to get hold of the data, with some added pre-processing too. Memories of how I needed to wrangle what was published by various sources make me appreciate just how vital it is to have harmonised data for analysis work.
Table Production
While many appear to graphical presentation of results to their tabular display, R does have its options here too. In recent times, the options have improved, particularly of the pharmaverse initiative. Here is a selection of what I found during my explorations.
Part of the {officeverse} along with {officedown}, {Flextable}, {Rvg} and {mschart}, the {officer} R package enables users to create and modify Word and PowerPoint documents directly from R, allowing the insertion of images, tables and formatted content, as well as the import of document content into data frames. It supports the generation of RTF files and integrates with other packages for advanced features such as vector graphics and native office charts. Installation options include CRAN and GitHub, with community resources available for assistance and contributions. The package facilitates the manipulation of document elements like paragraphs, tables and section breaks and provides tools for exporting and importing content between R and office formats, alongside functions for managing slide layouts and embedded objects in presentations.
If you work in clinical research like I do, the need to produce data tabulations is a non-negotiable requirement. That is how this package came to be developed and the pharmaverse of which it is part has numerous other options, should you need to look at using one of those. The flavour of RTF produced here is the Microsoft Word variety, which did not look as well in LibreOffice Writer when I last looked at the results with that open-source alternative. Otherwise, the results look well to many eyes.
Here is a package that enhances data presentation by applying customisable formatting to vectors and data frames, supporting formats such as percentages, currency and accounting. Available on GitHub and CRAN, it integrates with dynamic document tools like {knitr} and {rmarkdown} to produce visually distinct tables, with features including gradient colour scales, conditional styling and icon-based representations. It automatically converts to {htmlwidgets} in interactive environments and is licensed under MIT, enabling flexible use in both static and interactive data displays.
The {reactable} package for R provides interactive data tables built on the React Table library, offering features such as sorting, filtering, pagination, grouping with aggregation, virtual scrolling for large datasets and support for custom rendering through R or JavaScript. It integrates seamlessly into R Markdown documents and Shiny applications, enabling the use of HTML widgets and conditional styling. Installation options include CRAN and GitHub, with examples demonstrating its application across various datasets and scenarios. The package supports major web browsers and is licensed under MIT, designed for developers seeking dynamic data presentation tools within the R ecosystem.
Particularly useful in dynamic web applications like Shiny, the {DT} package in R provides a means of rendering interactive HTML tables by building on the DataTables JavaScript library. It supports features including sorting, searching, pagination and advanced filtering, with numeric, date and time columns using range-based sliders whilst factor and character columns rely on search boxes or dropdowns. Filtering operates on the client side by default, though server-side processing is also available. JavaScript callbacks can be injected after initialisation to manipulate table behaviour, such as enabling automatic page navigation or adding child rows to display additional detail. HTML content is escaped by default as a safeguard against cross-site scripting attacks, with the option to adjust this on a per-column basis. Whilst the package integrates with Shiny applications, attention is needed around scrolling and slider positioning to prevent layout problems. Overall, the package is well suited to exploratory data analysis and the building of interactive dashboards.
The {gt} package in R enables users to create well-structured tables with a variety of formatting options, starting from data frames or tibbles and incorporating elements such as headers, footers and customised column labels. It supports output in HTML, LaTeX and RTF formats and includes example datasets for experimentation. The package prioritises simplicity for common tasks while offering advanced functions for detailed customisation, with installation available via CRAN or GitHub. Users can access resources like documentation, community forums and example projects to explore its capabilities, and it is supported by a range of related packages that extend its functionality.
Enabling users to produce publication-ready outputs with minimal code, the {gtsummary} package offers a streamlined approach to generating analytical and summary tables in R. It automates the summarisation of data frames, regression models and other datasets, identifying variable types and calculating relevant statistics, including measures of data incompleteness. Customisation options allow for formatting, merging and styling tables to suit specific needs, while integration with packages such as {broom} and {gt} facilitates seamless incorporation into R Markdown workflows. The package supports the creation of side-by-side regression tables and provides tools for exporting results as images, HTML, Word, or LaTeX files, enhancing flexibility for reporting and sharing findings.
Here is an R package designed to generate LaTeX and HTML tables with a modern, user-friendly interface, offering extensive control over styling, formatting, alignment and layout. It supports features such as custom borders, padding, background colours and cell spanning across rows or columns, with tables modifiable using standard R subsetting or dplyr functions. Examples demonstrate its use for creating simple tables, applying conditional formatting and producing regression output with statistical details. The package also facilitates quick export to formats like PDF, DOCX, HTML and XLSX. Installation options include CRAN, R-Universe and GitHub, while the name reflects its origins as an enhanced version of the {xtable} package. The logo was generated using the package itself, and the background design draws inspiration from Piet Mondrian’s artwork.
Figure Generation
R has such a reputation for graphical presentations that it is cited as a strong reason to explore what the ecosystem has to offer. While base R itself is not shabby when it comes to creating graphs and charts, these packages will extend things by quite a way. In fact, the first on this list is near enough pervasive.
Though its default formatting does not appeal to me, the myriad of options makes this a very flexible tool, albeit at the expense of some code verbosity. Multi-panel plots are not among its strengths, which may send you elsewhere for that need.
Focusing on features not included in the core library, the {ggforce} package extends {ggplot2} by offering additional tools to enhance data visualisation. Designed to complement the primary role of {ggplot2} in exploratory data analysis, it provides a range of geoms, stats and other components that are well-documented and implemented, aiming to support more complex and custom plot compositions. Available for installation via CRAN or GitHub, the package includes a variety of functionalities described in detail on its associated website, though specific examples are not included here.
Developed by Claus O. Wilke for internal use in his lab, {cowplot} is an R package designed to help with the creation of publication-quality figures built on top of {ggplot2}. It provides a set of themes, tools for aligning and arranging plots into compound figures and functions for annotating plots or combining them with images. The package can be installed directly from CRAN or as a development version via GitHub, and it has seen widespread use in the book Fundamentals of Data Visualisation.
The {sjPlot} package provides a range of tools for visualising data and statistical results commonly used in social science research, including frequency tables, histograms, box plots, regression models, mixed effects models, PCA, correlation matrices and cluster analyses. It supports installation via CRAN for stable releases or through GitHub for development versions, with documentation and examples available online. The package is licensed under GPL-3 and developed by Daniel Lüdecke, offering functions to create visualisations such as scatter plots, Likert scales and interaction effect plots, along with tools for constructing index variables and presenting statistical outputs in tabular formats.
By offering a centralised approach to theming and enabling automatic adaptation of plot styles within Shiny applications, the {thematic} package simplifies the styling of R graphics, including {ggplot2}, {lattice} and base R plots, R Markdown documents and RStudio. It allows users to apply consistent visual themes across different plotting systems, with auto-theming in Shiny and R Markdown relying on CSS and {bslib} themes, respectively. Installation requires specific versions of dependent packages such as {shiny} and {rmarkdown}, while custom fonts benefit from {showtext} or {ragg}. Users can set global defaults for background, foreground and accent colours, as well as fonts, which can be overridden with plot-specific theme adjustments. The package also defines default colour scales for qualitative and sequential data and integrates with tools like bslib to import Google Fonts, enhancing visual consistency across different environments and user interfaces.
Publishing Tools
The R ecosystem goes beyond mere graphical and tabular display production to offer means for taking things much further, often offering platforms for publishing your work. These can be used locally too, so there is no need to entrust everything to a third-party provider. The uses are endless for what is available, and it appears that Posit has used this to help with building documentation and training too.
What you have here is one of those distinguishing facilities of the R ecosystem, particularly for those wanting to share their analysis work with more than a hint of reproducibility. The tool combines narrative text and code to generate various outputs, supporting multiple programming languages and formats such as HTML, PDF and dashboards. It enables users to produce reports, presentations and interactive applications, with options for publishing and scheduling through platforms like RStudio Connect, facilitating collaboration and distribution of results in professional settings.
Distill for R Markdown is a tool designed to streamline the creation of technical documents, offering features such as code folding, syntax highlighting and theming. It builds on existing frameworks like Pandoc, MathJax and D3, enabling the production of dynamic, interactive content. Users can customise the appearance with CSS and incorporate appendices for supplementary information. The tool acknowledges the contributions of developers who created foundational libraries, ensuring accessibility and functionality for a wide audience. Its design prioritises clarity, allowing authors to focus on presenting results rather than underlying code, while maintaining flexibility for those who wish to include detailed explanations.
For a while, this was one of R's unique selling points, and remains as compelling a reason to use the language even when Python has got its own version of the package. Enabling the creation of interactive web applications for data analysis without requiring web development expertise allows users to build interfaces that let others explore data through dynamic visualisations and filters. Here is a simple example: an app that generates scatter plots with adjustable variables, species filters and marginal plots, hosted either on personal servers or through a dedicated hosting service.
The {bslib} R package offers a modern user interface toolkit for Shiny and R Markdown applications, leveraging Bootstrap to enable the creation of customisable dashboards and interactive theming. It supports the use of updated Bootstrap and Bootswatch versions while maintaining compatibility with existing defaults, and provides tools for real-time visual adjustments. Installation is available through CRAN, with example previews demonstrating its capabilities.
Enabling users to manipulate and validate data within a spreadsheet-like interface, the {rhandsontable} package introduces an interactive data grid for R. It supports features such as custom cell rendering, validation rules and integration with Shiny applications. When used in Shiny, the widget requires explicit conversion of data using the hot_to_r function, as updates may not be immediately reflected in reactive contexts. Examples demonstrate its application in various scenarios, including date editing, financial calculations and dynamic visualisations linked to charts. The package also accommodates bookmarks in Shiny apps with specific handling. Users are encouraged to report issues or contribute improvements, with guidance provided for those seeking to expand its functionality. The development team welcomes feedback to refine the tool further, ensuring it aligns with evolving user needs.
{xaringanExtra} offers a range of enhancements and extensions for creating and presenting slides with xaringan, enabling features such as adding an overview tile view, making slides editable, broadcasting in real time, incorporating animations, embedding live video feeds and applying custom styles. It allows users to selectively activate individual tools or load multiple features simultaneously through a single function call, supporting tasks like adding banners, enabling code copying, fitting slides to screen dimensions and integrating utility toolkits. The package is available for installation via CRAN or GitHub, providing flexibility for developers and presenters seeking to expand the functionality of their slides.
Online R programming books that are worth bookmarking
23rd March 2026
As part of making content more useful following its reorganisation, numerous articles on the R statistical computing language have appeared on here. All of those have taken a more narrative form. With this collation of online books on the R language, I take a different approach. What you find below is a collection of links with associated descriptions. While narrative accounts can be very useful, there is something handy about running one's eye down a compilation as well. Many entries have a corresponding print edition, some of which are not cheap to buy, which makes me wonder about the economics of posting the content online as well, though it can help with getting feedback during book preparation.
We start with this comprehensive collection of over 400 free and affordable resources related to the R programming language, organised into categories such as data science, statistics, machine learning and specific fields like economics and life sciences. In many ways, it is a superset of what you find below and complements this collection with many other finds. The fact that it is a living collection makes it even more useful.
R Programming for Data Science
Here is an introduction to the R programming language, focusing on its application in data science. It covers foundational topics such as installation, data manipulation, function writing, debugging and code optimisation, alongside advanced concepts like parallel computation and data analysis case studies. The text includes practical guidance on handling data structures, using packages such as {dplyr} and {readr} as well as working with dates, times and regular expressions. Additional sections address control structures, scoping rules and profiling techniques, while the author also discusses resources for staying updated through a podcast and accessing e-book versions for ongoing revisions.
Designed for individuals with no prior coding experience, the book provides an introduction to programming in R while using practical examples to teach fundamental concepts such as data manipulation, function creation and the use of R's environment system. It is structured around hands-on projects, including simulations of weighted dice, playing cards and a slot machine, alongside explanations of core programming principles like objects, notation, loops and performance optimisation. Additional sections cover installation, package management, data handling and debugging techniques. While the book is written using RMarkdown and published under a Creative Commons licence, a physical edition is available through O’Reilly.
What you have here is one of several books written by Hadley Wickham. This one is published in its second edition as part of Chapman and Hall's R Series and is aimed primarily at R users who want to deepen their programming skills and understanding of the language, though it is also useful for programmers migrating from other languages. The book covers a broad range of topics organised into sections on foundations, functional programming, object-oriented programming, metaprogramming and techniques, with the latter including debugging, performance measurement and rewriting R code in C++.
Unlike Paul Teetor's separately published R Cookbook, the Cookbook for R was created by Winston Chang. It offers solutions to common tasks and problems in data analysis, covering topics such as basic operations, numbers, strings, formulas, data input and output, data manipulation, statistical analysis, graphs, scripts and functions, and tools for experiments.
The second edition of R for Data Science by Hadley Wickham, Mine Çetinkaya-Rundel and Garrett Grolemund offers a structured approach to learning data science with R, covering essential skills such as data visualisation, transformation, import, programming and communication. Organised into chapters that explore workflows, data manipulation techniques and tools like Quarto for reproducible research, the book emphasises practical applications and best practices for handling data effectively.
The R Graphics Cookbook, 2nd edition, offers a comprehensive guide to creating visualisations in R, structured into chapters that cover foundational skills such as installing and using packages, loading data from various formats and exploring datasets through basic plots. It progresses to detailed techniques for constructing bar graphs, line graphs, scatter plots and histograms, alongside methods for customising axes, annotations, themes and legends.
The book also addresses advanced topics like colour application, faceting data into subplots, generating specialised graphs such as network diagrams and heat maps and preparing data for visualisation through reshaping and summarising. Additional sections focus on refining graphical outputs for presentation, including exporting to different file formats and adjusting visual elements for clarity and aesthetics, while an appendix provides an overview of the {ggplot2} system.
R Markdown: The Definitive Guide
Published by Chapman & Hall/CRC, R Markdown: The Definitive Guide by Yihui Xie, J.J. Allaire and Garrett Grolemund covers the R Markdown document format, which has been in use since 2012 and is built on the knitr and Pandoc tools. The format allows users to embed code within Markdown documents and compile the results into a range of output formats including PDF, HTML and Word. The guide covers a broad scope of practical applications, from creating presentations, dashboards, journal articles and books to building interactive applications and generating blogs, reflecting how the ecosystem has matured since the {rmarkdown} package was first released in 2014.
A key principle running throughout is that Markdown's deliberately limited feature set is a strength rather than a drawback, encouraging authors to focus on content rather than complex typesetting. Despite this simplicity, the format remains highly customisable through tools such as Pandoc templates, LaTeX and CSS. Documents produced in R Markdown are also notably portable, as their straightforward syntax makes conversion between output formats more reliable, and because results are generated dynamically from code rather than entered manually, they are far more reproducible than those produced through conventional copy-and-paste methods.
The R Markdown Cookbook is a practical guide designed to help users enhance their ability to create dynamic documents by combining analysis and reporting. It covers essential topics such as installation, document structure, formatting options and output formats like LaTeX, HTML and Word, while also addressing advanced features such as customisations, chunk options and integration with other programming languages. The book provides step-by-step solutions to common tasks, drawing on examples from online resources and community discussions to offer clear, actionable advice for both new and experienced users seeking to improve their workflow and explore the full potential of R Markdown.
This book provides a practical guide to using R Markdown for scientists, developed from a three-hour workshop and designed to evolve as a living resource. It covers essential topics such as setting up R Markdown documents, integrating with RStudio for efficient workflows, exporting outputs to formats like PDF, HTML and Word, managing figures and tables with dynamic references and captions, incorporating mathematical equations, handling bibliographies with citations and style adjustments, troubleshooting common issues and exploring advanced R Markdown extensions.
bookdown: Authoring Books and Technical Documents with R Markdown
Here is a guide to using the {bookdown} package, which extends R Markdown to facilitate the creation of books and technical documents. It covers Markdown syntax, integration of R code, formatting options for HTML, LaTeX and e-book outputs and features such as cross-referencing, custom blocks and theming. The package supports both multipage and single-document outputs, and its applications extend beyond traditional books to include course materials, manuals and other structured content. The work includes practical examples, publishing workflows and details on customisation, alongside information about licensing and the availability of a printed version.
[blogdown]: Creating Websites with R Markdown
Though the authors note that some information may be outdated due to recent updates to Hugo and the {blogdown} package, and they direct readers to additional resources for the latest features and changes, this book still provides a guide to building static websites using R Markdown and the Hugo static site generator, emphasising the advantages of this approach for creating reproducible, portable content. It covers installation, configuration, deployment options such as Netlify and GitHub Pages, migration from platforms like WordPress and advanced topics including custom layouts and version control as well as practical examples, workflow recommendations and discussions on themes, content management and technical aspects of website development.
[pagedown]: Create Paged HTML Documents for Printing from R Markdown
The R package {pagedown} enables users to create paged HTML documents suitable for printing to PDF, using R Markdown combined with a JavaScript library called paged.js, that later of which implements W3C specifications for paged media. While tools like LaTeX and Microsoft Word have traditionally dominated PDF production, pagedown offers an alternative approach through HTML and CSS, supporting a range of document types including resumes, posters, business cards, letters, theses and journal articles.
Documents can be converted to PDF via Google Chrome, Microsoft Edge or Chromium, either manually or through the chrome_print() function, with additional support for server-based, CI/CD pipeline and Docker-based workflows. The package provides customisable CSS stylesheets, a CSS overriding mechanism for adjusting fonts and page properties, and various formatting features such as lists of tables and figures, abbreviations, footnotes, line numbering, page references, cover images, running headers, chapter prefixes and page breaks. Previewing paged documents requires a local or remote web server, and the layout is sensitive to browser zoom levels, with 100% zoom recommended for the most accurate output.
Dynamic Documents with R and knitr
Developed by Yihui Xie and inspired by the earlier {Sweave} package, {knitr} is an R package designed for dynamic report generation that consolidates the functionality of numerous other add-on packages into a single, cohesive tool. It supports multiple input languages, including R, Python and shell scripts, as well as multiple output markup languages such as LaTeX, HTML, Markdown, AsciiDoc and reStructuredText. The package operates on a principle of transparency, giving users full control over how input and output are handled, and runs R code in a manner consistent with how it would behave in a standard R terminal.
Among its notable features are built-in caching, automatic code formatting via the {formatR} package, support for more than 20 graphics devices and flexible options for managing plots within documents. It also allows advanced users to define custom hooks and regular expressions to extend and tailor its behaviour further. The package is affiliated with the Foundation for Open Access Statistics, a nonprofit organisation promoting free software, open access publishing and reproducible research in statistics.
Mastering Shiny is a comprehensive guide to developing web applications using R, focusing on the Shiny framework designed for data scientists. It introduces core concepts such as user interface design, reactive programming and dynamic content generation, while also exploring advanced topics like performance optimisation, security and modular app development. The book covers practical applications across industries, from academic teaching tools to real-time analytics dashboards, and aims to equip readers with the skills to build scalable, maintainable applications. It includes detailed chapters on workflow, layout, visualisation and user interaction, alongside case studies and technical best practices.
Engineering Production-Grade Shiny Apps
This is aimed at developers and team managers who already possess a working knowledge of the Shiny framework for R and wish to advance beyond the basics toward building robust, production-ready applications. Rather than covering introductory Shiny concepts or post-deployment concerns, the book focuses on the intermediate ground between those two stages, addressing project management, workflow, code structure and optimisation.
It introduces the {golem} package as a central framework and guides readers through a five-step workflow covering design, prototyping, building, strengthening and deployment, with additional chapters on optimisation techniques including R code performance, JavaScript integration and CSS. The book is structured to serve both those with project management responsibilities and those focused on technical development, acknowledging that in many small teams these roles are carried out by the same individual.
Outstanding User Interfaces with Shiny
Written by David Granjon and published in 2022, Outstanding User Interfaces with Shiny is a book aimed at filling the gap between beginner and advanced Shiny developers, covering how to deeply customise and enhance Shiny applications to the point where they become indistinguishable from classic web applications. The book spans a wide range of topics, including working with HTML and CSS, integrating JavaScript, building Bootstrap dashboard templates, mobile development and the use of React, providing a comprehensive resource that consolidates knowledge and experience previously scattered across the Shiny developer community.
Now in its second edition, R Packages by Hadley Wickham and Jennifer Bryan is a freely available online guide that teaches readers how to develop packages in R. A package is the core unit of shareable and reproducible R code, typically comprising reusable functions, documentation explaining how to use them and sample data. The book guides readers through the entire process of package development, covering areas such as package structure, metadata, dependencies, testing, documentation and distribution, including how to release a package to CRAN. The authors encourage a gradual approach, noting that an imperfect first version is perfectly acceptable provided each subsequent version improves on the last.
Written by Javier Luraschi, Kevin Kuo and Edgar Ruiz, Mastering Spark with R is a comprehensive guide designed to take readers from little or no familiarity with Apache Spark or R through to proficiency in large-scale data science. The book covers a broad range of topics, including data analysis, modelling, pipelines, cluster management, connections, data handling, performance tuning, extensions, distributed computing, streaming and contributing to the Spark ecosystem.
Happy Git and GitHub for the useR
Here is a practical guide written by Jenny Bryan and contributors, aimed primarily at R users involved in data analysis or package development. It covers the installation and configuration of Git alongside GitHub, the development of key workflows for common tasks and the integration of these tools into day-to-day work with R and R Markdown. The guide is structured to take readers from initial setup through to more advanced daily workflows, with particular attention paid to how Git and GitHub serve the needs of data science rather than pure software development.
Written by John Coene and intended for release as part of the CRC Press R series, JavaScript for R explore how the R programming language and JavaScript can be used together to enhance data science workflows. Rather than teaching JavaScript as a standalone language, the book demonstrates how a limited working knowledge of it can meaningfully extend what R developers can achieve, particularly through the integration of external JavaScript libraries.
The book covers a broad range of topics, progressing from foundational concepts through to data visualisation using the {htmlwidgets} package, bidirectional communication with Shiny, JavaScript-powered computations via the V8 engine and Node.js and the use of modern JavaScript tools such as Vue, React and webpack alongside R. Practical examples are woven throughout, including the building of interactive visualisations, custom Shiny inputs and outputs, image classification and machine learning operations, with all accompanying code made publicly available on GitHub.
This guide addresses challenges faced by developers of R packages that interact with web resources, offering strategies to create reliable unit tests despite dependencies on internet connectivity, authentication and external service availability. It explores tools such as {vcr}, {webmockr}, {httptest} and {webfakes}, which enable mocking and recording HTTP requests to ensure consistent testing environments, reduce reliance on live data and improve test reliability. The text also covers advanced topics like handling errors, securing tests and ensuring compatibility with CRAN and Bioconductor, while emphasising best practices for maintaining test robustness and contributor-friendly workflows. Funded by rOpenSci and the R Consortium, the resource aims to support developers in building more resilient and maintainable R packages through structured testing approaches.
The Shiny AWS Book is an online resource designed to teach data scientists how to deploy, host and maintain Shiny web applications using cloud infrastructure. Addressing a common gap in data science education, it guides readers through a range of DevOps technologies including AWS, Docker, Git, NGINX and open-source Shiny Server, covering everything from server setup and cost management to networking, security and custom configuration.
{ggplot2}: Elegant Graphics for Data Analysis
The third edition of {ggplot2}: Elegant Graphics for Data Analysis provides an in-depth exploration of the Grammar of Graphics framework, focusing on the theoretical foundations and detailed implementation of the ggplot2 package rather than offering step-by-step instructions for specific visualisations. Written by Hadley Wickham, Danielle Navarro and Thomas Lin Pedersen, the book is presented as an online work-in-progress, with content structured across sections such as layers, scales, coordinate systems and advanced programming topics. It aims to equip readers with the knowledge to customise plots according to their needs, rather than serving as a direct guide for creating predefined graphics.
YaRrr! The Pirate’s Guide to R
Written by Nathaniel D. Phillips, this is a beginner-oriented guide to learning the R programming language from the ground up, covering everything from installation and basic navigation of the RStudio environment through to more advanced topics such as data manipulation, statistical analysis and custom function writing. The guide progresses logically through foundational concepts including scalars, vectors, matrices and dataframes before moving into practical areas such as hypothesis testing, regression, ANOVA and Bayesian statistics. Visualisation is given considerable attention across dedicated chapters on plotting, while later sections address loops, debugging and managing data from a variety of file formats. Each chapter includes practical exercises to reinforce learning, and the book concludes with a solutions section for reference.
Data Visualisation: A Practical Introduction
Data Visualisation: A Practical Introduction is a forthcoming second edition from Princeton University Press, written by Kieran Healy and due for release in March 2026, which teaches readers how to explore, understand and present data using the R programming language and the {ggplot2} library. The book aims to bridge the gap between works that discuss visualisation principles without teaching the underlying tools and those that provide code recipes without explaining the reasoning behind them, instead combining both practical instruction and conceptual grounding.
Revised and updated throughout to reflect developments in R and {ggplot2}, the second edition places greater emphasis on data wrangling, introduces updated and new datasets, and substantially rewrites several chapters, particularly those covering statistical models and map-drawing. Readers are guided through building plots progressively, from basic scatter plots to complex layered graphics, with the expectation that by the end they will be able to reproduce nearly every figure in the book and understand the principles that inform each choice.
The book also addresses the growing role of large language models in coding workflows, arguing that genuine understanding of what one is doing remains essential regardless of the tools available. It is suitable for complete beginners, those with some prior R experience, and instructors looking for a course companion, and requires the installation of R, RStudio and a number of supporting packages before work can begin.
Building a modular Hugo website home page using block-driven front matter
22nd February 2026
Inspired by building a modular landing page on a Grav-powered subsite, I wondered about doing the same for a Hugo-powered public transport website that I have. It was part of an overall that I was giving it, with AI consultation running shotgun with the whole effort. The home page design was changed from a two-column design much like what was once typical of a blog, to a single column layout with two-column sections.
The now vertical structure consisted of numerous layers. First, there is an introduction with a hero image, which is followed by blocks briefly explaining what the individual sections are about. Below them, two further panels describe motivations and scope expansions. After those, there are two blocks displaying pithy details of recent public transport service developments before two final panels provide links to latest articles and links to other utility pages, respectively.
This was a conscious mix of different content types, with some nesting in the structure. Much of the content was described in page front matter, instead of where it usually goes. Without that flexibility, such a layout would not have been possible. All in all, this illustrates just how powerful Hugo is when it comes to constructing website layouts. The limits essentially are those of user experience and your imagination, and necessarily in that order.
On Hugo Home Pages
Building a home page in Hugo starts with understanding what content/_index.md actually represents. Unlike a regular article file, _index.md denotes a list page, which at the root of the content directory becomes the site's home page. This special role means Hugo treats it differently from a standard single page because the home is always a list page even when the design feels like a one-off.
Front matter in content/_index.md can steer how the page is rendered, though it remains entirely optional. If no front matter is present at all, Hugo still creates the home page at .Site.Home, draws the title from the site configuration, leaves the description empty unless it has been set globally, and renders any Markdown below the front matter via .Content. That minimal behaviour suits sites where the home layout is driven entirely by templates, and it is a common starting point for new projects.
How the Underlying Markdown File Looks
While this piece opens with a description of what was required and built, it is better to look at the real _index.md file. Illustrating the block-driven pattern in practical use, here is a portion of the file:
---
title: "Maximising the Possibilities of Public Transport"
layout: "home"
blocks:
- type: callout
text1: "Here, you will find practical, thoughtful insight..."
text2: "You can explore detailed route listings..."
image: "images/sam-Up56AzRX3uM-unsplash.jpg"
image_alt: "Transpennine Express train leaving Manchester Piccadilly train station"
- type: cards
heading: "Explore"
cols_lg: 6
items:
- title: "News & Musings"
text: "Read the latest articles on rail networks..."
url: "https://ontrainsandbuses.com/news-and-musings/"
- title: "News Snippets"
...
- type: callout
heading: "Motivation"
text2: "Since 2010, British public transport has endured severe challenges..."
image: "images/joseph-mama-aaQ_tJNBK4c-unsplash.jpg"
image_alt: "Buses in Leeds, England, U.K."
- type: callout
heading: "An Expanding Scope"
text2: "You will find content here drawn from Ireland..."
image: "images/snap-wander-RlQ0MK2InMw-unsplash.jpg"
image_alt: "TGV speeding through French countryside"
---There are several things that are worth noting here. The title and layout: "home" fields appear at the top, with all structural content expressed as a blocks list beneath them. There is no Markdown body because the blocks supply all the visible content, and the file contains no layout logic of its own, only a description of what should appear and in what order. However, the lack of a Markdown body does pose a challenge for spelling and grammar checking using the LanguageTool extension in VSCode, which means that you need to ensure that proofreading needs to happen in a different way, such as using the editor that comes with the LanguageTool browser extension.
Template Selection and Lookup Order
Template selection is where Hugo's home page diverges most noticeably from regular sections. In Hugo v0.146.0, the template system was completely overhauled, and the lookup order for the home page kind now follows a straightforward sequence: layouts/home.html, then layouts/list.html, then layouts/all.html. Before that release, the conventional path was layouts/index.html first, falling back to layouts/_default/list.html, and the older form remains supported through backward-compatibility mapping. In every case, baseof.html is a wrapper rather than a page template in its own right, so it surrounds whichever content template is selected without substituting for one.
The choice of template can be guided further through front matter. Setting layout: "home" in content/_index.md, as in the example above, encourages Hugo to pick a template named home.html, while setting type: "home" enables more specific template resolution by namespace. These are useful options when the home page deserves its own template path without disturbing other list pages.
The Home Template in Practice
With the front matter established, the template that renders it is worth examining in its own right. It happens that the home.html for this site reads as follows:
<!DOCTYPE html>
{{- partial "head.html" . -}}
<body>
{{- partial "header.html" . -}}
<div class="container main" id="content">
<div class="row">
<h2 class="centre">{{ .Title }}</h2>
{{- partial "blocks/render.html" . -}}
</div>
{{- partial "recent-snippets-cards.html" . -}}
{{- partial "home-teasers.html" . -}}
{{ .Content }}
</div>
{{- partial "footer.html" . -}}
{{- partial "cc.html" . -}}
{{- partial "matomo.html" . -}}
</body>
</html>This template is self-contained rather than wrapping a base template. It opens the full HTML document directly, calls head.html for everything inside the <head> element and header.html for site navigation, then establishes the main content container. Inside that container, .Title is output as an h2 heading, drawing from the title field in content/_index.md. The block dispatcher partial, blocks/render.html, immediately follows and is responsible for looping through .Params.blocks and rendering each entry in sequence, handling all the callout and cards blocks described in the front matter.
Below the blocks, two further partials render dynamic content independently of the front matter. recent-snippets-cards.html displays the two most recent news snippets as full-content cards, while home-teasers.html presents a compact linked list of recent musings alongside a weighted list of utility pages. After those, {{ .Content }} outputs any Markdown written below the front matter in content/_index.md, though in this case, the file has no body content, so nothing is rendered at that point. The template closes with footer.html, a cookie notice via cc.html and a Matomo analytics snippet.
Notice that this template does not use {{ define "main" }} and therefore does not rely on baseof.html at all. It owns the full document structure itself, which is a legitimate approach when the home page has a sufficiently distinct shape that sharing a base template would add complexity rather than reduce it.
The Block Dispatcher
The blocks/render.html partial is the engine that connects the front matter to the individual block templates. Its full content is brief but does considerable work:
{{ with .Params.blocks }}
{{ range . }}
{{ $type := .type | default "text" }}
{{ partial (printf "blocks/%s.html" $type) (dict "page" $ "block" .) }}
{{ end }}
{{ end }}The with .Params.blocks guard means the entire loop is skipped cleanly if no blocks key is present in the front matter, so pages that do not use the system are unaffected. For each block in the list, the type field is read and passed through printf to build the partial path, so type: callout resolves to blocks/callout.html and type: cards resolves to blocks/cards.html. If a block has no type, the fallback is text, so a blocks/text.html partial would handle it. The dict call constructs a fresh context map passing both the current page (as page) and the raw block data (as block) into the partial, keeping the two concerns cleanly separated.
The Callout Blocks
The callout.html partial renders bordered, padded sections that can carry a heading, an image and up to five paragraphs of text. Used for the website introduction, motivation and expanded scope sections, its template is as follows:
{{ $b := .block }}
<section class="mt-4">
<div class="p-4 border rounded">
{{ with $b.heading }}<h3>{{ . }}</h3>{{ end }}
{{ with $b.image }}
<img
src="{{ . }}"
class="img-fluid w-100 rounded"
alt="{{ $b.image_alt | default "" }}">
{{ end }}
<div class="text-columns mt-4">
{{ with $b.text1 }}<p>{{ . }}</p>{{ end }}
{{ with $b.text2 }}<p>{{ . }}</p>{{ end }}
{{ with $b.text3 }}<p>{{ . }}</p>{{ end }}
{{ with $b.text4 }}<p>{{ . }}</p>{{ end }}
{{ with $b.text5 }}<p>{{ . }}</p>{{ end }}
</div>
</div>
</section>The pattern here is consistent and deliberate. Every field is wrapped in a {{ with }} block, so fields absent from the front matter produce no output and no empty elements. The heading renders as an h3, sitting one level below the page's h2 title and maintaining a coherent document outline. The image uses img-fluid and w-100 alongside rounded, making it fully responsive and visually consistent with the bordered container. According to the Bootstrap documentation, img-fluid applies max-width: 100% and height: auto so the image scales with its parent, while w-100 ensures it fills the container width regardless of its intrinsic size. The image_alt field falls back to an empty string via | default "" rather than omitting the attribute entirely, which keeps the rendered HTML valid.
Text content sits inside a text-columns wrapper, which allows a stylesheet to apply a CSS multi-column layout to longer passages without altering the template. The numbered paragraph fields text1 through text5 reflect the varying depth of the callout blocks in the front matter: the introductory callout uses two paragraphs, while the Motivation callout uses four. Adding another paragraph field to a block requires only a new {{ with $b.text6 }} line in the partial and a matching text6 key in the front matter entry.
The Section Introduction Blocks
The cards.html partial renders a headed grid of linked blocks, with the column width at large viewports driven by a front matter parameter. This is used for the website section introductions and its template is as follows:
{{ $b := .block }}
{{ $colsLg := $b.cols_lg | default 4 }}
<section class="mt-4">
{{ with $b.heading }}<h3 class="h4 mb-3">{{ . }}</h3>{{ end }}
<div class="row">
{{ range $b.items }}
<div class="col-12 col-md-6 col-lg-{{ $colsLg }} mb-3">
<div class="card h-100 ps-2 pe-2 pt-2 pb-2">
<div class="card-body">
<h4 class="h5 card-title mt-1 mb-2">
<a href="{{ .url }}">{{ .title }}</a>
</h4>
{{ with .text }}<p class="card-text mb-0">{{ . }}</p>{{ end }}
</div>
</div>
</div>
{{ end }}
</div>
</section>The cols_lg value defaults to 4 if not specified, which produces a three-column grid at large viewports using Bootstrap's twelve-column grid. The transport site's cards block sets cols_lg: 6, giving two columns at large viewports and making better use of the wider reading space for six substantial card descriptions. At medium viewports, the col-md-6 class produces two columns regardless of cols_lg, and col-12 ensures single-column stacking on small screens.
The heading uses the h4 utility class on an h3 element, pulling the visual size down one step while keeping the document outline correct, since the page already has an h2 title and h3 headings in the callout blocks. Each card title then uses h5 on an h4 for the same reason. The h-100 class on the card sets its height to one hundred percent of the column, so all cards in a row grow to match the tallest one and baselines align even when descriptions vary in length. The padding classes ps-2 pe-2 pt-2 pb-2 add a small inset without relying on custom CSS.
Brief Snippets of Recent Public Transport Developments
The recent-snippets-cards.html partial sits outside the blocks system and renders the most recent pair of short transport news posts as full-content cards. Here is its template:
<h3 class="h4 mt-4 mb-3">Recent Snippets</h3>
<div class="row">
{{ range ( first 2 ( where .Site.Pages "Type" "news-snippets" ) ) }}
<div class="col-12 col-md-6 mb-3">
<div class="card h-100">
<div class="card-body">
<h4 class="h6 card-title mt-1 mb-2">
{{ .Date.Format "15:04, January 2" }}<sup>{{ if eq (.Date.Format "2") "2" }}nd{{ else if eq (.Date.Format "2") "22" }}nd{{ else if eq (.Date.Format "2") "1" }}st{{ else if eq (.Date.Format "2") "21" }}st{{ else if eq (.Date.Format "2") "3" }}rd{{ else if eq (.Date.Format "2") "23" }}rd{{ else }}th{{ end }}</sup>, {{ .Date.Format "2006" }}
</h4>
<div class="snippet-content">
{{ .Content }}
</div>
</div>
</div>
</div>
{{ end }}
</div>The where function filters .Site.Pages to the news-snippets content type, and first 2 takes only the two most recently created entries. Notably, this collection does not call .ByDate.Reverse before first, which means it relies on Hugo's default page ordering. Where precise newest-first ordering matters, chaining ByDate.Reverse before first makes the intent explicit and avoids surprises if the default ordering changes.
The date heading warrants attention. It formats the time as 15:04 for a 24-hour clock display, followed by the month name and day number, then appends an ordinal suffix using a chain of if and else if comparisons against the raw day string. The logic handles the four irregular cases (1st, 21st, 2nd, 22nd, 3rd and 23rd) before falling back to th for all other days. The suffix is wrapped in a <sup> element so it renders as a superscript. The year follows as a separate .Date.Format "2006" call, separated from the day by a comma. Each card renders the full .Content of the snippet rather than a summary, which suits short-form posts where the entire entry is worth showing on the home page.
Latest Musings and Utility Pages Blocks
The home-teasers.html partial renders a two-column row of linked lists, one for recent long-form articles and one for utility pages. Its template is as follows:
<div class="row mt-4">
<div class="col-12 col-md-6 mb-3">
<div class="card h-100">
<div class="card-body">
<h3 class="h5 card-title mb-3">Recent Musings</h3>
{{ range first 5 ((where .Site.RegularPages "Type" "news-and-musings").ByDate.Reverse) }}
<p class="mb-2">
<a href="{{ .Permalink }}">{{ .Title }}</a>
</p>
{{ end }}
</div>
</div>
</div>
<div class="col-12 col-md-6 mb-3">
<div class="card h-100">
<div class="card-body">
<h3 class="h5 card-title mb-3">Extras & Utilities</h3>
{{ $extras := where .Site.RegularPages "Type" "extras" }}
{{ $extras = where $extras "Title" "ne" "Thank You for Your Message!" }}
{{ $extras = where $extras "Title" "ne" "Whoops!" }}
{{ range $extras.ByWeight }}
<p class="mb-2">
<a href="{{ .Permalink }}">{{ .Title }}</a>
</p>
{{ end }}
</div>
</div>
</div>
</div>The left column uses .Site.RegularPages rather than .Site.Pages to exclude list pages, taxonomy pages and other non-content pages from the results. The news-and-musings type is filtered, sorted with .ByDate.Reverse and then limited to five entries with first 5, producing a compact, current list of article titles. The heading uses h5 on an h3 for the same visual-scale reason seen in the cards blocks, and h-100 on each card ensures the two columns match in height at medium viewports and above.
The right column builds the extras list through three chained where calls. The first narrows to the extras content type, and the subsequent two filter out utility pages that should never appear in public navigation, specifically the form confirmation and error pages. The remaining pages are then sorted by ByWeight, which respects the weight value set in each page's front matter. Pages without a weight default to zero, so assigning small positive integers to the pages that should appear first gives stable, editorially controlled ordering without touching the template.
Diagnosing Template Choices
Diagnosing which template Hugo has chosen is more reliable with tooling than with guesswork. Running the development server with debug output reveals the selected templates in the terminal logs. Another quick technique is to place a visible marker in a candidate file and inspect the page source.
HTML comments are often stripped during minified builds, and Go template comments never reach the output, so an innocuous meta tag makes a better marker because a minifier will not remove it. If the marker does not appear after a rebuild, either the template being edited is not in use because another file higher in the lookup order is taking precedence, or a theme is providing a matching file without it being obvious.
Front Matter Beyond Layout
Front matter on the home page earns its place when it supplies values that make their way into head tags and structured sections, rather than when it tries to replicate layout logic. A brief description is valuable for metadata and social previews because many base templates output it as a meta description tag. Where a site uses social cards, parameters for images and titles can be added and consumed consistently.
Menu participation also remains available to the home page, with entries in front matter allowing the home to appear in navigation with a given weight. Less common but still useful fields include outputs, which can disable or configure output formats, and cascade, which can provide defaults to child pages when site-wide consistency matters. Build controls can influence whether a page is rendered or indexed, though these are rarely changed on a home page once the structure has settled.
Template Hygiene
Template hygiene pays off throughout this process. Whether the home page uses a self-contained template or wraps baseof.html, the principle is the same: each file should own a clearly bounded responsibility. The home template in the example above does this well, with head.html, header.html and footer.html each handling their own concerns, and the main content area occupied by the blocks dispatcher and the two dynamic partials. Column wrappers are easiest to manage when each partial opens and closes its own structure, rather than relying on a sibling to provide closures elsewhere.
That self-containment prevents subtle layout breakage and means that adding a new block type requires only a small partial in layouts/partials/blocks/ and a new entry in the front matter blocks list, with no changes to any existing template. Once the home page adopts this pattern, the need for CSS overrides recedes because the HTML shape finally expresses intent instead of fighting it.
Bootstrap Utility Classes in Summary
Understanding Bootstrap's utility classes rounds off the technique because these classes anchor the modular blocks without the need for custom CSS. h-100 sets height to one hundred percent and works well on cards inside a flex row so that their bottoms align across a grid, as seen in both the cards block and the home teasers. The h4, h5 and h6 utilities apply a different typographic scale to any element without changing the document outline, which is useful for keeping headings visually restrained while preserving accessibility. img-fluid provides responsive behaviour by constraining an image to its container width and maintaining aspect ratio, and w-100 makes an image or any element fill the container width even if its intrinsic size would let it stop short. Together, these classes produce predictable and adaptable blocks that feel consistent across all viewports.
Closing Remarks
The result of combining Hugo's list-page model for the home, a block-driven front matter design and Bootstrap's light-touch utilities is a home page that reads cleanly and remains easy to extend. New block types become a matter of adding a small partial and a new blocks entry, with the dispatcher handling the rest automatically. Dynamic sections such as recent snippets sit in dedicated partials called directly from the template, updating without any intervention in content/_index.md. Existing sections can be reordered without editing templates, shared structure remains in one place, and the need for brittle CSS customisation fades because the templates do the heavy lifting.
A final point returns to content/_index.md. Keeping front matter purposeful makes it valuable. A title, a layout directive and a blocks list that models the editorially controlled page structure are often enough, as we have seen in this example from my public transport website. More seldom-used fields such as outputs, cascade and build remain available should a site require them, but their restraint reflects the wider approach: let content describe structure, let templates handle layout and avoid unnecessary complexity.
Lessons learned during migrations to Grav CMS from Textpattern
21st February 2026
After the most of four years since the arrival of Textpattern 4.8.8, Textpattern 4.9.0 was released. Since, I was running two subsites using the software, I tried one of them out with the new version. That broke an elderly navigation plugin that no longer appears in any repository, prompting a rollback, which was successful. Even so, it stirred some curiosity about alternatives to this veteran of the content management system world, which is pushing on for twenty-two years of age. That might have been just as well, given the subsequent release of Textpattern 4.9.1 because of two reported security issues, one of which affecting all preceding versions of the software.
Well before that came to light, there had been a chat session in a Gemini app on a mobile which travelling on a bus. This started with a simple question about alternatives to Textpattern. The ensuing interaction led me to choose Grav CMS after one other option turned out to involve a subscription charge; A personal website side hustle generating no revenue was not going to become a more expensive sideline than it already was, the same reasoning that stops me paying for WordPress plugins.
Exploring Known Options
Without any recourse to AI capability, I already had options. While WordPress was one of those that was well known to me, the organisation of the website was such that it would be challenging to get everything placed under one instance and I never got around to exploring the multisite capability in much depth. Either way, it would prove to involve quite an amount of restructuring, Even having multiple instances would mean an added amount of maintenance, though I do automate things heavily. The number of attack surfaces because of database dependence is another matter.
In the past, I have been a user of Drupal, though its complexity and the steepness of the associated learning curve meant that I never exploited it fully. Since those were pre-AI days, I wonder how things would differ now. Nevertheless, the need to make parts of a website fit in with each other was another challenge that I failed to overcome in those days. Thus, this content framework approach was not one that I wished to use again. In short, this is an enterprise-grade tool that may be above the level of personal web tinkering, and I never did use its capabilities to their full extent.
The move away from Drupal brought me to Hugo around four years ago. That too presents a learning curve, though its inherent flexibility meant that I could do anything that I want with it once I navigated its documentation and ironed out oversights using web engine searches. This static website generator is what rebuilds a public transport website, a history website comprised of writings by my late father together with a website for my freelancing company. There is no database involved, and you can avoid having any dynamic content creation machinery on the web servers too. Using Git, it is possible to facilitate content publishing from anywhere as well.
Why Grav?
Of the lot, Hugo had a lot going for it. The inherent flexibility would not obstruct getting things to fit with a website wide consistency of appearance, and there is nothing to stop one structuring things how they wanted. However, Grav has one key selling point in comparison: straightforward remote production of content without recourse to local builds being uploaded to a web server. That decouples things from needing one to propagate the build machinery across different locations.
Like Hugo, Grav had an active project behind it and a decent supply of plugins and an architecture that bested Textpattern and its usual languid release cycle. The similarity also extended as far as not having to buy into someone else's theme: any theming can be done from scratch for consistency of appearance across different parts of a website. In Grav's case, that means using the Twig PHP templating engine, another thing to learn and reminiscent of Textpattern's Textile as much as what Hugo itself has.
The centricity of Markdown files was another area of commonality, albeit with remote editing. If you are conversant with page files having a combination of YAML front matter and subsequent page content from Hugo, Grav will not seem so alien to you, even if it has a web interface for editing that front matter. This could help if you need to edit the files directly for any reason.
That is never to say that there were no things to learn, for there was plenty of that. For example, it has its own way of setting up modular pages, an idea that I was to retrofit back into a Hugo website afterwards. This means care with module naming as well as caching, editor choice and content collections, each with their own uniqueness that rewards some prior reading. A learning journey was in the offing, a not attractive part of the experience in any event.
Considerations
There have been a number of other articles published here regarding the major lessons learned during the transitions from Textpattern to Grav. Unlike previous experiences with Hugo, another part of this learning was the use of AI as part of any debugging. At times, there was a need to take things step by step, interacting with the AI instead of trying out a script that it had put my way. There are times when one's own context window gets overwhelmed by the flow of text, meaning that such behaviour needs to be taken in hand.
Another thing to watch is that human consultation of the official documentation is not neglected in a quest for speed that lets the AI do that for you; after all, this machinery is fallible; nothing we ever bring into being is without its flaws. Grav itself also comes from a human enterprise that usefully includes its own Discord community. The GitHub repository was not something to which I had recourse, even if the Admin plugin interface has prompts for reporting issues on there. Here, I provide a synopsis of the points to watch that may add to the help provided elsewhere.
Choosing an Editor
By default, Grav Admin uses CodeMirror as its content editor. While CodeMirror is well-suited to editing code, offering syntax highlighting, bracket matching and multiple cursors, it renders its editing surface in a way that standard browser extension APIs cannot reach. Grammar checkers and spell-check extensions such as LanguageTool rely on native editable elements to detect text, and CodeMirror does not use these. The result is that browser-based writing tools produce no output in Grav Admin at all, which is a confirmed architectural incompatibility rather than a configuration issue documented in the LanguageTool issue tracker.
This can be addressed by replacing CodeMirror using the TinyMCE Editor Integration plugin, installable directly from the Admin plugin interface, which brings a familiar style of editor that browser extensions can access normally. Thus, LanguageTool functionality is restored, the writing workflow stays inside Grav Admin and the change requires only a small amount of configuration to prevent TinyMCE from interfering with Markdown files in undesirable ways. Before coming across the TinyMCE Editor plugin, I was seriously toying with the local editing option centred around a Git-based workflow. Here, using VS Code with the LanguageTool extension like I do for Hugo websites remained a strong possibility. The plugin means that the need to do this is not as pressing as it otherwise might be.
None of this appears to edit Twig templates and other configuration files unless one makes use of the Editor plugin. My brief dalliance with this revealed a clunky interface and interference with the appearance of the website, something that I never appreciated when I saw it with Drupal. Thus, the plugin was quickly removed, and I do not miss it. As it happened, editing and creating files over an SSH connection with a lightweight terminal editor worked well enough for me during the setup phase anyway. If I wanted a nicer editing experience, then a Git-based approach would allow local editing in VSCode before pushing the files back onto the server.
Grav Caching
Unlike WordPress, which requires plugins to do so, Grav maintains its own internal cache for compiled pages and assets. Learning to work with it is part of understanding the platform: changes to CSS, JavaScript and other static assets are served from this cache until it is refreshed. That can be accomplished using the admin panel or by removing the contents of the cache directory directly. Once this becomes second nature, it adds very little overhead to the development process.
Modular Pages
On one of the Textpattern subsites, I had set up the landing page in a modular fashion. This carried over to Grav, which has its own way of handling modular pages. There, the modular page system assembles a single page from the files found within a collection of child folders, each presenting a self-contained content block with its own folder, Markdown file and template.
All modules render together under a single URL; they are non-routable, meaning visitors cannot access them directly. When the parent folder contains a modular.md file, the name tells Grav to use the modular.html.twig template and whose front matter defines which modules to include and in what order.
Module folders are identified by an underscore at the start of their name, and numeric prefixes control the display sequence. The prefix must come before the underscore: _01.main is the correct form. For a home page with many sections this structure scales naturally, with folder names such as 01._title, 04._ireland or 13._practicalities-inspiration making the page architecture immediately readable from the file system alone.
Each module's Markdown filename determines which template renders it: a file named text.md looks for text.html.twig in the theme's modular templates folder. The parent modular.md assembles the modules using @self.modular to collect them, with a custom order list giving precise control over sequence. Once the folder naming convention and the template matching relationship are clear, the system is very workable.
Building Navigation
Given that the original impetus for leaving Textpattern was a broken navigation plugin, ensuring that Grav could replicate the required menu behaviour was a matter of some importance. Grav takes a different approach to navigation from database-driven systems, deriving its menu structure directly from the content directory tree using folder naming conventions and front matter flags rather than a dedicated menu editor.
Top-level navigation is driven by numerically prefixed subfolders within the content directory (pages), so a structure such as 01.home, 02.about and 03.blog yields an ordered working menu automatically. Visibility can be fine-tuned without renaming folders by setting visible: true or visible: false in a page's YAML front matter, and menu labels can be shortened for navigation purposes using the menu: field while retaining a fuller title for the page itself.
The primary navigation loop iterates over the visible children of the pages tree and uses the active and activeChild flags on each page object to highlight the current location, whether the visitor is on a given top-level page directly or somewhere within its subtree. A secondary menu for the current section is assembled by first identifying the active top-level page and then rendering its visible children as a list. Testing for activeChild as well as active in the secondary menu is important, as omitting it means that visitors to grandchild pages see no item highlighted at all. The approach differs from what was possible with Textpattern, where a single composite menu could drill down through the full hierarchy, but displaying one menu for pages within a given section alongside another showing the other sections proves to be a workable and context-sensitive alternative.
Setting Up RSS Feeds
Because Grav does not support the generation of RSS feeds out of the box, it needs a plugin and some extra configuration. The latter means that you need to get your head around the Grav concept of a collection because without it, you will not see anything in your feed. In contrast, database-driven platforms like WordPress or Drupal push out the content by default, which may mean that you are surprised when you first come across how Grav needs you to specify the collections explicitly.
There are two details that make performing configuration of a feed straightforward once understood. The first is that Grav routes do not match physical folder paths: a folder named 03.deliberations on disk is referenced in configuration as /deliberations, since the numeric prefix controls navigation ordering but does not appear in the route, that is the actual web page address. The second is the choice between @page.children, which collects only the immediate children of a folder, and @page.descendants, which collects recursively through all subdirectories. The collection definition belongs in the feed page's front matter, specifying where the content lives, how it should be ordered and in which direction.
Where All This Led
Once I got everything set in place, the end results were pleasing, with much learned along the way. Web page responsiveness was excellent, an experience enhanced by the caching of files. In the above discussion, I hardly mentioned the transition of existing content. For one subsite, this was manual because the scale was smaller, and the Admin plugin's interface made everything straightforward such that all was in place after a few hours of work. In the case of the other, the task was bigger, so I fell on an option used for a WordPress to Hugo migration: Python scripting. That greatly reduced the required effort, allowing me to focus on other things like setting up a modular landing page. The whole migration took around two weeks, all during time outside my client work. There are other places where I can use Grav, which surely will add to what I already have learned. My dalliance with Textpattern is feeling a little like history now.
Rendering Markdown in WordPress without plugins by using Parsedown
4th November 2025
Much of what is generated using GenAI as articles is output as Markdown, meaning that you need to convert the content when using it in a WordPress website. Naturally, this kind of thing should be done with care to ensure that you are the creator and that it is not all the work of a machine; orchestration is fine, regurgitation does that add that much. Naturally, fact checking is another need as well.
Writing plain Markdown has secured its own following as well, with WordPress plugins switching over the editor to facilitate such a mode of editing. When I tried Markup Markdown, I found it restrictive when it came to working with images within the text, and it needed a workaround for getting links to open in new browser tabs as well. Thus, I got rid of it to realise that it had not converted any Markdown as I expected, only to provide rendering at post or page display time. Rather than attempting to update the affected text, I decided to see if another solution could be found.
This took me to Parsedown, which proved to be handy for accomplishing what I needed once I had everything set in place. First, that meant cloning its GitHub repo onto the web server. Next, I created a directory called includes under that of my theme. Into there, I copied Parsedown.php to that location. When all was done, I ensured that file and directory ownership were assigned to www-data to avoid execution issues.
Then, I could set to updating the functions.php file. The first line to get added there included the parser file:
require_once get_template_directory() . '/includes/Parsedown.php';
After that, I found that I needed to disable the WordPress rendering machinery because that got in the way of Markdown rendering:
remove_filter('the_content', 'wpautop');
remove_filter('the_content', 'wptexturize');
The last step was to add a filter that parsed the Markdown and passed its output to WordPress rendering to do the rest as usual. This was a simple affair until I needed to deal with code snippets in pre and code tags. Hopefully, the included comments tell you much of what is happening. A possible exception is $matches[0]which itself is an array of entire <pre>...</pre> blocks including the containing tags, with $i => $block doing a $key (not the same variable as in the code, by the way) => $value lookup of the values in the array nesting.
add_filter('the_content', function($content) {
// Prepare a store for placeholders
$placeholders = [];
// 1. Extract pre blocks (including nested code) and replace with safe placeholders
preg_match_all('//si', $content, $pre_matches);
foreach ($pre_matches[0] as $i => $block) {
$key = "§PREBLOCK{$i}§";
$placeholders[$key] = $block;
$content = str_replace($block, $key, $content);
}
// 2. Extract standalone code blocks (not inside pre)
preg_match_all('/).*?<\/code>/si', $content, $code_matches);
foreach ($code_matches[0] as $i => $block) {
$key = "§CODEBLOCK{$i}§";
$placeholders[$key] = $block;
$content = str_replace($block, $key, $content);
}
// 3. Run Parsedown on the remaining content
$Parsedown = new Parsedown();
$content = $Parsedown->text($content);
// 4. Restore both pre and code placeholders
foreach ($placeholders as $key => $block) {
$content = str_replace($key, $block, $content);
}
// 5. Apply paragraph formatting
return wpautop($content);
}, 12); All of this avoided dealing with extra plugins to produce the required result. Handily, I still use the Classic Editor, which makes this work a lot more easily. There still is a Markdown import plugin that I am tempted to remove as well to streamline things. That can wait, though. It best not add any more of them any way, not least avoid clashes between them and what is now in the theme.
Displaying superscripted text in Hugo website content
6th January 2025
In a previous post, there was a discussion about displaying ordinal publishing dates with superscripted suffixes in Hugo and WordPress. Here, I go further with inserting superscripted text into Markdown content. Because of the default set up for the Goldmark Markdown renderer, it is not as simple as adding <sup>...</sup> constructs to your Markdown source file. That will generate a warning like this:
WARN Raw HTML omitted while rendering "[initial location of Markdown file]"; see https://gohugo.io/getting-started/configuration-markup/#rendererunsafe
You can suppress this warning by adding the following to your site configuration:
ignoreLogs = ['warning-goldmark-raw-html']
Because JavaScript can be added using HTML tags, there is an added security hazard that could be overlooked if you switch off the warning as suggested. Also, Goldmark does not interpret Markdown specifications of superscripting without an extension whose incorporation needs some familiarity with Go development.
That leaves using a Shortcode. These go into layouts/shortcodes under your theme area; the file containing mine got called super.html. The content is the following one-liner:
<sup>{{ .Get 0 | markdownify }}/sup>
This then is what is added to the Markdown content:
{{< super "th" >}}
What happens here is that the Shortcode picks up the content within the content within the quotes and encapsulates it with the HTML superscript tags to give the required result. This approach can be extended for subscripts and other similar ways of rendering text, too. All that is required is a use case, and the rest can be put in place.
Rendering Markdown into HTML using PHP
3rd December 2022
One of the good things about using virtual private servers for hosting websites instead of 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 back then. 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.