Introducing gpt-realtime and Realtime API updates
We’re releasing a more advanced speech-to-speech model and new API capabilities including MCP server support, image input, and SIP phone calling support.
“Manga Masterpieces: A Showcase of 600+ Drawings by Influential Artists”
The Power of Manga: A Journey Through Time and Culture
From the vivid landscapes of Tezuka’s Astro Boy to the gripping narratives of Miyazaki’s Spirited Away, manga has captivated audiences around the world with its diverse storytelling and intricate artwork. This exhibition will shine a spotlight on the rich history and cultural impact of manga, featuring over 600 drawings by influential artists who have shaped the medium into what it is today.
A Historical Perspective
Manga has a long and colorful history, dating back to the 12th century when the first Japanese scrolls depicted humorous animal caricatures. Over the centuries, manga evolved and flourished, with artists like Hokusai and Tezuka pioneering new styles and genres that captured the imagination of readers across Japan.
- In the 20th century, manga became a staple of Japanese popular culture, with iconic series like Osamu Tezuka’s Astro Boy and Princess Knight setting the standard for future generations of artists.
- Today, manga continues to thrive as a global phenomenon, with millions of fans around the world eagerly awaiting the latest releases from their favorite artists and series.
Exploring Themes and Influences
Through the artwork on display, visitors will be able to explore the diverse themes and influences that have shaped manga over the years. From the supernatural adventures of Naruto to the poignant reflections on war in Barefoot Gen, manga offers a reflection of both the dreams and struggles of Japanese society.
“Manga is not just entertainment—it is a powerful medium for expressing ideas and emotions that resonate with people of all ages and backgrounds,” says curator Yoko Takahashi.
Join us on this journey through time and culture as we celebrate the enduring legacy of manga and the artists who continue to push the boundaries of creativity and storytelling.
The exhibition will spotlight manga, through more than 600 drawings by influential manga artists
Step-by-Step Guide: Scraping Empleos Publicos with R and Selenium
[This article was first published on pacha.dev/blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
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Because of delays with my scholarship payment, if this post is useful to you I kindly ask a minimal donation on Buy Me a Coffee. It shall be used to continue my Open Source efforts. The full explanation is here: A Personal Message from an Open Source Contributor.
Motivation
My friend Nicolas Didier asked me about reading Empleos Publicos with R or Python. Here is a short example for him and anybody who may benefit from reading this.
The following steps were adapted from a tutorial I taught at the University of Michigan (GO BLUE!) in 2023.
Required R packages
- RSelenium: R-Selenium integration
- rvest: HTML processing
- dplyr: to load the pipe operator (can be used later for data cleaning)
- purrr: iteration (i.e., repeated operations)
I installed RSelenium from the R console:
if (!require(RSelenium)) install.packages("RSelenium")
# or
remotes::install_github("ropensci/RSelenium")
For the rest of the packages:
if (!require(rvest)) install.packages("rvest")
if (!require(dplyr)) install.packages("dplyr")
if (!require(purrr)) install.packages("purrr")
Installing Selenium and Chrome/Chromium
Note for Ubuntu/Debian users: We need to check that chrome or chromium is installed in our system. One of the many options is to use the bash console.
sudo add-apt-repository ppa:savoury1/chromium sudo apt update sudo apt install chromium-browser sudo apt install chromium-chromedriver
Not using the PPA will install the snap version of Chromium, which is not compatible with Selenium.
I tried to start Selenium as it is mentioned in the official guide and it did not work.
I had to install Chromium. I am on Manjaro and I ran sudo pacman -S chromium. Windows/Mac users can use Google Chrome.
An extra requirement was to download Selenium Server. Based on this, I started by creating a directory to store the data for this post by typing this in VS Code terminal:
mkdir -p /tmp/didier-example cd /tmp/didier-example
Then I opened R witn R and downloaded the JAR file:
url_jar <- "https://github.com/SeleniumHQ/selenium/releases/download/selenium-3.9.1/selenium-server-standalone-3.9.1.jar"
sel_jar <- "selenium-server-standalone-3.9.1.jar"
if (!file.exists(sel_jar)) {
download.file(url_jar, sel_jar)
}
I had to run Selenium from a new terminal:
cd /tmp/didier-example java -jar selenium-server-standalone-3.9.1.jar
Back to the R terminal, I was finally in condition to control the browser from R:
library(RSelenium) library(rvest) library(dplyr) library(purrr) rmDr <- remoteDriver(port = 4444L, browserName = "chrome") rmDr$open(silent = TRUE) url <- "https://www.empleospublicos.cl" rmDr$navigate(url)
This should display a new Chrome/Chromium window that says “Chrome is being controlled by automated test software”.
Scraping the data
Using the browser’s inspector (ctrl + shift + i), I explored the page to see that the search bar corresponds to:
<input class="buscador-principal search form-control buscador-movil" name="q" type="search" autocomplete="off" placeholder="Ingresa el cargo, comuna o institución" id="buscadorprincipal">
For example, I can search for “Ministerio de Salud” because there were many posts by that organization on the landing page:
search_box <- rmDr$findElement(using = "id", value = "buscadorprincipal")
search_box$sendKeysToElement(list("Ministerio de Salud", key = "enter"))
That typed “Ministerio de Salud” and clicked search on my behalf. Inspecting the results I see that each job offer starts with
<div class="items col-md-4 col-lg-4 postulacion ...
The first offer listed is this:
<div class="items col-md-4 col-lg-4 postulacion otro otro eepp region7renta3calidad2 busqueda "><div class="item"><div class="top"><div class="label label-estado"><i class="fa fa-circle circulo-status1" aria-hidden="true"></i> Postulación hasta 30/09/2025 23:59:00</div><h3><a target="_blank" href="https://www.empleospublicos.cl/pub/convocatorias/convpostularavisoTrabajo.aspx?i=130648&c=0&j=0&tipo=convpostularavisoTrabajo" onclick="ga('send', 'event', 'convocatorias', 'Medico (a) especialista en Anestesiología 44 horas | Servicio de Salud Maule / Hospital de Constitución', 'eepp');">Medico (a) especialista en Anestesiología 44 horas</a></h3><p>Servicio de Salud Maule / Hospital de Constitución</p></div><hr><div class="cnt"><p>Ministerio de Salud</p><p>Constitución</p><br><div class="alert alert-primer"><i class="fa fa-address-card" aria-hidden="true"></i> No pide experiencia</div><div class="row card-footer"><div class="col-xs-9 col-md-8 text-left"><a class="cronograma btn " url="https://www.empleospublicos.cl/pub/convocatorias/convpostularavisoTrabajo.aspx?i=130648&c=0&j=0&tipo=convpostularavisoTrabajo" onclick="return false;" href="#" title="Ver Cronograma de la Convocatoria"><i class="fa fa-calendar-days"></i> Calendarización</a>
<div class="compartir-social">
<div class="row">
<div class="col-xs-3 col-md-4">
<a class="btn" onclick="enviarRS('t', 'https://www.empleospublicos.cl/pub/convocatorias/convpostularavisoTrabajo.aspx?i=130648&c=0&j=0&tipo=convpostularavisoTrabajo', 'Medico (a) especialista en Anestesiología 44 horas Servicio de Salud Maule / Hospital de Constitución'); return false;" href="#" target="_blank" title="Compartir en Twitter"><i class="fa-brands fa-square-x-twitter fa-xl" aria-hidden="true"></i></a>
</div>
<div class="col-xs-3 col-md-4">
<a class="btn" onclick="enviarRS('f', 'https://www.empleospublicos.cl/pub/convocatorias/convpostularavisoTrabajo.aspx?i=130648&c=0&j=0&tipo=convpostularavisoTrabajo', 'Medico (a) especialista en Anestesiología 44 horas Servicio de Salud Maule / Hospital de Constitución'); return false;" href="#" target="_blank" title="Compartir en Facebook"><i class="fa-brands fa-square-facebook fa-xl" aria-hidden="true"></i></a>
</div>
<div class="col-xs-3 col-md-4">
<a class="btn" onclick="enviarRS('l', 'https://www.empleospublicos.cl/pub/convocatorias/convpostularavisoTrabajo.aspx?i=130648&c=0&j=0&tipo=convpostularavisoTrabajo', 'Medico (a) especialista en Anestesiología 44 horas Servicio de Salud Maule / Hospital de Constitución'); return false;" href="#" target="_blank" title="Compartir en Linkedin"><i class="fa-brands fa-linkedin fa-xl" aria-hidden="true"></i></a>
</div>
<div class="col-xs-3 col-md-4">
<a class="btn whatsapp-link visible-xs visible-sm" title="Compartir en Whatsapp" onclick="enviarRS('w', 'https://www.empleospublicos.cl/pub/convocatorias/convpostularavisoTrabajo.aspx?i=130648&c=0&j=0&tipo=convpostularavisoTrabajo', 'Medico (a) especialista en Anestesiología 44 horas Servicio de Salud Maule / Hospital de Constitución'); return false;" href="#" data-action="share/whatsapp/share"><i class="fa-brands fa-square-whatsapp fa-xl" aria-hidden="true"></i></a>
</div>
</div>
</div>
<div class="row"><div class="col-md-12 card-footer-contenido "></div></div></div></div></div></div></div>
html <- read_html(rmDr$getPageSource()[[1]])
offers <- html %>%
html_nodes("div.items")
offers_tbl <- map_df(offers, function(offer) {
# Extract position (job title)
position <- offer %>%
html_node("h3 a") %>%
html_text(trim = TRUE)
# Extract organization (usually the first <p> inside .top)
organization <- offer %>%
html_node(".top p") %>%
html_text(trim = TRUE)
# Extract city (the second <p> inside .cnt)
city <- offer %>%
html_nodes(".cnt p") %>%
.[2] %>%
html_text(trim = TRUE)
tibble(
position = position,
organization = organization,
city = city
)
})
The result has the following structure:
offers_tbl # A tibble: 552 × 3 position organization city <chr> <chr> <chr> 1 Medico (a) especialista en Anestesiología 44 horas Servicio de… Cons… 2 Titulares de la Planta Profesional Ley 18.834 Servicio de… Valp… 3 ENFERMERA-O, JORNADA DIURNA, GRADO 12, PARA SERVICIO CLÍN… Servicio de… Reco… 4 Psiquiatra infanto-juvenil sistema de atención intersecto… Servicio de… La P… 5 Neurólogo(a) adulto GES Alzheimer y otras demencias Servicio de… Puen… 6 Médico(a) especialista en Neurología Infantil Hospital de… Servicio de… Cast… 7 Arquitecto de Software Central de … Ñuñoa 8 TENS OPERADOR DE EQUIPOS DE ESTERILIZACIÓN Servicio de… Peña… 9 (850-2892) Médico Especialista Broncopulmonar o Internist… Servicio de… Talc… 10 Enfermero(a) Clínico(a) Atención Abierta y Cerrada Servicio de… Huas… glimpse(offers_tbl) > glimpse(offers_tbl) Rows: 552 Columns: 3 $ position <chr> "Medico (a) especialista en Anestesiología 44 horas", "Ti… $ organization <chr> "Servicio de Salud Maule / Hospital de Constitución", "Se… $ city <chr> "Constitución", "Valparaíso", "Recoleta", "La Pintana", "…
I know this is a simple example but should allow different kinds of exploration and data extraction. I hope it helps.
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Continue reading: Step-by-Step Guide to Use R and Selenium to Scrape Empleos Publicos
Key points of the article
The article demonstrates the process of using the R language integrated with Selenium, explaining how to scrape data from public job catalogs, specifically from the website Empleos Publicos. The author lists out required R packages and provides steps to install them. The author also describes the process of installing Selenium and a compatible browser (in this case Chromium) and how to use them in tandem. The final part of the author’s tutorial teaches users how to scrape data and reads it into a table format for easy visualization.
Long-term implications and possible future developments
The demonstration provided in the article indicates there is potential for further simplification and automation in the process of extracting, processing, and visualizing data from various web sources. This application of R and Selenium opens possibilities to build more comprehensive and automated data scraping workflows in the future. Further developments could include the creation of functions or packages that allow for easy implementation of similar scraping tasks on other platforms, or even general-purpose utilities that simplify many common scraping tasks.
Actionable advice
Although the article provided an excellent step-by-step guide on using Selenium and R to scrape a specific website, generalizing this methodology could be useful in many other contexts. Consequently, readers and aspiring data analysts or data scientists could widen their skillsets by applying the provided code and understanding to other websites and use-cases. However, it’s necessary to understand and respect the terms of service of each website before initiating web scraping activities since not all websites permit this.
Regarding possible improvements, learning how to handle possible errors (e.g., the website undergoing changes, causing the scraper to break) and creating more dynamic, reusable code might be beneficial. Also, considering privacy and ethical issues while scraping personal data is crucial.
Finally, exploring technologies similar to R and Selenium, understanding their strengths and weaknesses, could be valuable since it may offer more efficient or easier ways to achieve the same results.
“10 Practical One-Liners for Streamlining Machine Learning Workflows with Scikit-learn and Pand
This tutorial will focus on ten practical one-liners that leverage the power of libraries like Scikit-learn and Pandas to help streamline your machine learning workflows.
The Future of Machine Learning Workflow
The integration of libraries such as Scikit-learn and Pandas into machine learning workflows, as highlighted in the tutorial, will have numerous long-term implications. As machine learning continues to evolve, the use of these powerful libraries could redefine the field.
Implications and Future Developments
Scikit-learn and Pandas offer a selection of high-level data structures and data manipulation tools that are perfect for data analysis. These libraries provide the opportunity to make data exploration, cleaning, and preprocessing more efficient, thereby affecting the future of machine learning significantly. These could result in changes in the following areas:
- Data analysis and preprocessing: With more advanced tools at their disposal, data professionals can easily manipulate massive data sets and transform them into a more manageable format.
- Algorithms and models: Scikit-learn offers a range of machine learning algorithms. As the library grows, it may expand to include even more complex models. This could change the dynamics of machine learning workflows dramatically.
- Automation: The expansion of these libraries could lead to increased automation in processes, reducing the need for manual intervention substantially.
Actionable Advice
Preparing for developments in the future implicates embracing these libraries and honing your skills around them. Here is some advice based on these insights:
- Improve your proficiency: To take advantage of the benefits of libraries such as Scikit-learn and Pandas, delve into a more exploratory learning phase. Make use of tutorials and guides to hone your skills.
- Staying Updated: Machine learning and its associated libraries are consistently updated and advanced. It is beneficial to follow industry discussions and keep an eye on the latest research.
- Automation: Take steps towards automating your machine learning workflows and regularly review these processes to include enhancements.
- Join and contribute to Community: Being part of the community of each library, you can learn from real cases, offer your contribution, and follow experts with similar needs.
The future of machine learning workflows is set to evolve along with advancements in libraries like Scikit-learn and Pandas. As these tools develop, the field is expected to refine and become even more efficient and powerful.
Learn how agentic AI is reshaping software development, enabling autonomous coding, smarter DevOps, faster testing, and continuous innovation at scale.
The Rise of Agentic AI in Software Development
Advancements in artificial intelligence are opening up new avenues in a plethora of industries, and software development is no exception, specifically agentic AI. This technology is shifting the paradigm in various software development zones, including autonomous coding, smarter DevOps, rapid testing, and innovation at a large scale. The impact of this shift will have far reaching implications, and recognizing these will enable developers and organizations to prepare and take full advantage of the opportunities that arise.
How Agentic AI is Changing the Software Development Industry
AI has long been recognized as a game-changing technology, and its agentic variant is living up to this expectation in software development. Agentic AI is enabling autonomous coding, which relieves developers from many repetitive and time-consuming tasks, leaving them with more time for more complex challenges. The result is faster, more efficient, and error-free coding.
Agentic AI is also propelling the smarter DevOps. With automated and intelligent processes, tasks in the DevOps pipeline are carried out quickly, efficiently, and with fewer mistakes. This results in higher quality outputs and improved project timelines.
Testing, a critical and often time-consuming part of the software development process, is also becoming faster with agentic AI. Thanks to its capability to automate and speed up testing processes, developers can detect and correct bugs more quickly, ensuring the delivery of high-quality software.
Lastly, continuous innovation at scale is being made possible with agentic AI. It facilitates more rapid development cycles, allowing for more frequent release of updates and improvements. This translates to better software that meets user needs more effectively.
Long-Term Implications and Predicted Future Developments
In the longer term, agentic AI is set to revolutionize software development. One can envisage an industry that’s significantly automated, with humans focusing on the creative and complex aspects. Additionally, projects are likely to be executed more swiftly and with fewer errors, leading to a higher-quality output.
In terms of future developments, advancements in AI and machine learning technologies are likely to trigger further improvements in autonomous coding, smarter DevOps, and faster testing processes. Agentic AI could even lead to the evolution of completely autonomous software development cycles, where AI systems design, develop, and test software products with minimal human intervention.
Actionable Advice for Harnessing Agentic AI
Companies and developers that wish to stay on the cutting edge of the evolution within the software development industry need to take proactive steps. Here are some actionable insights:
- Invest in AI Research and Training: Developers should continually improve their AI knowledge and skills, and companies ought to facilitate this by providing necessary training and resources.
- Embrace Agile Development: With AI enabling faster development cycles, companies must streamline their processes to accommodate the quicker pace.
- Incorporate AI in Testing and Quality Assurance: Embrace autonomous testing and continuous innovation to create high-quality, user-centric software.
- Prepare for Change: As agentic AI streamlines and automates many tasks, roles may change within the software development cycle. It’s essential to prepare for this eventuality by broadening skills and being ready to transition into new roles.
The rise of agentic AI within the software development industry opens up a myriad of opportunities for both developers and companies. Those who adapt and embrace this evolution are set to reap the benefits of enhanced efficiency, reduced errors, and increased development speed, ultimately leading to high-quality, user-centric software products.