Son Irremplazables('They are Irreplaceable' in Spanish) is a grassroots initiative committed to raising awareness about the issue of missing individuals in the Dominican Republic. In this presentation, we will delve into the development of a missing persons database, leveraging the power of Django as the backend framework and React as the frontend library. Join us as we explore this application's technical intricacies designed to assist in the search and recovery efforts for missing individuals. By highlighting the disappearances and their impact, the website aims to bring attention to this pressing social concern, advocate for solutions, and support affected family members while they search for their loved ones.
I'll be going over new features and changes in Pydantic V2. Pydantic is a very popular schema definition and data validation library for Python.
Demonstration of using Python as the core of a multi-language workflow to mine through terabytes of genomic data.
A lightning talk to discuss Globus Labs's ongoing work developing tools to support Findable, Accessible, Interoperable, and Reusable (FAIR) applied AI research in the natural sciences. Including Foundry, a platform for sharing and accessing AI-ready data for training scientific models. And Garden, a platform for making model discovery and hosted inference easier for scientific workflows.
We made a job scheduler and reporting tool for ourselves. And then it turned out to be too good to keep internal. So here it is. Named rpeat, because jobs repeat but it also repeats important details about your job's to you wherever you are. It is dead simple but feature rich, intuitive but powerful.
Software has become a major driver for research with over 90% of researchers answering surveys that they use software for their research and over 65% expressing that they even could not do their research without software. Science gateways are defined as collaborative environments that allow science and engineering communities to access shared data, software, computing services, instruments, educational materials, and other resources specific to their disciplines. Their goal is to remove the barriers to online content, computing and data infrastructures. SGX3 is the newly funded NSF Center of Excellence for Science Gateways serving the science gateway community from users to providers to developers. Mature science gateway frameworks enable developers to re-use building blocks for typical tasks such as invoking simulations or sharing data. This way, a ramp up of a science gateway can be more efficient and developers can focus on the unique aspects of a science gateway that is tailored to a specific community. Many frameworks such as Hubzero and Tapis are open source and can be further developed by the community. SGX3 offers services to the community from UX design to technical gap analysis to internship opportunities. The talk will go into detail for SGX3 and its services and examples for science gateways openly available.
Over several decades, (Quasi-)Monte Carlo ((Q)MC) methods have become indispensable in computational sciences. However, the field still lacks comprehensive, user-friendly software that fully harnesses the power of (Q)MC algorithms in research, development, and production environments. In response to this gap, we introduce QMCPy, an open-source software framework designed to bring together global (Q)MC researchers and practitioners. Through this presentation, we will unpack the unique features that make QMCPy a critical tool in advancing computational sciences, including its extensibility, robustness, and integration with existing (Q)MC libraries. By illustrating the criteria and practices taken in the development of QMCPy, we aim to not only showcase our work but also to invite you to contribute to and co-create in this open-source software and accelerate scientific discovery through improved (Q)MC algorithms.
What is a JWT and why would I want to use one?
This talk will cover common use cases.
This talk is for those who want to pierce the veil of abstraction and learn how their Python code is actually executed on a computer. First we will start with a guided overview of the Python Run Time envioronment in the CPython interpreter. Next will be an overview of the builtin inspect package and how it allows for direct access to the python runtime in your own Python code. After which I will show how you leverage this knowledge in PDB.
How does the elipses work? Let's find out.