Merge pull request #1288 from ELC/jupytercon-2023

Add JupyterCon 2023

Author: jonafato

jupytercon-2023/category.json

@@ -0,0 +1,3 @@
+{
+  "title": "JupyterCon 2023"
+}

jupytercon-2023/videos/afshin-darian-martha-cryan-whats-new-in-jupyterlab-4-0-jupytercon-2023.json

@@ -0,0 +1,25 @@
+{
+  "description": "There are some exciting new features and enhancements shipping with JupyterLab 4. JupyterLab is a web-based user interface for scientists and developers for data exploration, analysis, and visualization. JupyterLab provides a Jupyter notebook editor, code editor, code console, terminal, debugger, and more as core extensions. In the talk we will highlight some of the recent new features such as the settings editor, real time collaboration and the reworked extension manager.",
+  "duration": 1925,
+  "language": "eng",
+  "recorded": "2023-05-10",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://web.archive.org/web/20230531110007/https://www.jupytercon.com/"
+    }
+  ],
+  "speakers": [
+    "Afshin Darian",
+    "Martha Cryan"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/RtYDdziRqAI/maxresdefault.jpg",
+  "title": "What’s New in JupyterLab 4.0",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=RtYDdziRqAI"
+    }
+  ]
+}

jupytercon-2023/videos/alejandro-coca-castro-anne-fouilloux-environmental-data-science-book-a-computational-notebook-co.json

@@ -0,0 +1,89 @@
+{
+  "description": "Environmental Data Science Book (or EDS Book) is a pan-european community-driven resource hosted on GitHub and powered by Jupyter Book. The resource leverages executable notebooks, regional cloud resources and technical implementations of the FAIR principles to support the publication of datasets, innovative research and open-source tools in environmental science. EDS book provides practical guidelines and templates that maximise open infrastructure services to translate research outputs into curated, interactive, shareable and reproducible executable notebooks which benefit from a collaborative and transparent reviewing process. Each notebook and its dependencies (input/output data, documentation, computational environments, etc.) are bundled into a Research Object (RO) and deposited to RoHub (a RO management platform) that provides the technical basis for implementing FAIR (Findable, Accessible, Interoperable and Reusable) executable notebooks.\n\nTo date, the community has successfully published multiple python-based notebooks covering a wide range of topics in environmental data science. The notebooks consume open-source python libraries e.g., Pangeo stack (intake, iris, xarray) and Holoviz (hvplot, panel) for fetching, processing and interactively visualizing environmental research.\n\nIn future work, we expect to increase contributions showcasing scalable and interoperable open-source developments in other programming languages e.g Julia and R, and engage with computational notebooks communities and research networks interested in improving scientific software practices in environmental science.\n\nWhat is the EDS book?\n\nA book: https://edsbook.org\nAn open source project: https://github.com/alan-turing-institute/environmental-ds-book\nA community: EDS book is also an open-source collaborative project that involves and supports its members of diverse skills and backgrounds to ensure that data science is accessible and useful for everyone interested in Environmental sciences.\nImpact and outreach over last 12 months\n\n10 executable notebooks (see the gallery in https://edsbook.org/notebooks/gallery.html)\n24 contributors in the GitHub Host Repository\n240 Twitter followers | 23 Mastodon followers\nHighlighted in the Supporting Pangeo: the community-driven platform for Big Data geoscience project page, https://www.turing.ac.uk/research/research-projects/supporting-pangeo-community-driven-platform-big-data-geoscience\nHighlighted in a FOSS4G 2022 workshop aiming to teach the basics of Pangeo, an open-source stack suited for big geoscience data https://pangeo-data.github.io/foss4g-2022/afterword/envds-book.html\nOutreach\n\nWorkshops/Hackathons\n- Climate Informatics 2023 Reproducibility Challenge. Co-hosted by EDS book, Climate Informatics and Cambridge University Press & Assessment with support from Cambridge University, The Alan Turing Institute and Simula Research Laboratory, https://eds-book.github.io/reproducibility-challenge-2023/\n\nPresentations\n- European Geophysical Union 2023 (EGU23), https://meetingorganizer.copernicus.org/EGU23/EGU23-13768.html\n- Pangeo Community Showcase, https://www.youtube.com/watch?v=9lhbU0vbhw0\n- European Geophysical Union 2022 (EGU22), https://meetingorganizer.copernicus.org/EGU22/EGU22-3739.html\n- UK Conference on Environmental Data Science, https://wp.lancs.ac.uk/ceds/abstracts/abstracts-6th-july-22/#castro\n- The Turing Way Fireside chat, https://www.youtube.com/watch?v=EeeRZZ3-Stc\n- AGU22, Open Science Practices and Success Stories Across the Earth, Space and Environmental Sciences session, https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1072564\n\nSee also:\nhttps://edsbook.org/welcome.html\nhttps://fosstodon.org/@EDSbook\nhttps://github.com/alan-turing-institute/environmental-ds-book\nhttps://twitter.com/eds_book\nhttps://www.youtube.com/channel/UC148zpdIEfRun-cUJbgbIyg",
+  "duration": 1783,
+  "language": "eng",
+  "recorded": "2023-05-10",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://web.archive.org/web/20230531110007/https://www.jupytercon.com/"
+    },
+    {
+      "label": "https://meetingorganizer.copernicus.org/EGU22/EGU22-3739.html",
+      "url": "https://meetingorganizer.copernicus.org/EGU22/EGU22-3739.html"
+    },
+    {
+      "label": "https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1072564",
+      "url": "https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1072564"
+    },
+    {
+      "label": "https://edsbook.org/notebooks/gallery.html",
+      "url": "https://edsbook.org/notebooks/gallery.html"
+    },
+    {
+      "label": "https://meetingorganizer.copernicus.org/EGU23/EGU23-13768.html",
+      "url": "https://meetingorganizer.copernicus.org/EGU23/EGU23-13768.html"
+    },
+    {
+      "label": "https://pangeo-data.github.io/foss4g-2022/afterword/envds-book.html",
+      "url": "https://pangeo-data.github.io/foss4g-2022/afterword/envds-book.html"
+    },
+    {
+      "label": "https://www.youtube.com/watch?v=EeeRZZ3-Stc",
+      "url": "https://www.youtube.com/watch?v=EeeRZZ3-Stc"
+    },
+    {
+      "label": "https://eds-book.github.io/reproducibility-challenge-2023/",
+      "url": "https://eds-book.github.io/reproducibility-challenge-2023/"
+    },
+    {
+      "label": "https://www.turing.ac.uk/research/research-projects/supporting-pangeo-community-driven-platform-big-data-geoscience",
+      "url": "https://www.turing.ac.uk/research/research-projects/supporting-pangeo-community-driven-platform-big-data-geoscience"
+    },
+    {
+      "label": "https://www.youtube.com/watch?v=9lhbU0vbhw0",
+      "url": "https://www.youtube.com/watch?v=9lhbU0vbhw0"
+    },
+    {
+      "label": "https://wp.lancs.ac.uk/ceds/abstracts/abstracts-6th-july-22/#castro",
+      "url": "https://wp.lancs.ac.uk/ceds/abstracts/abstracts-6th-july-22/#castro"
+    },
+    {
+      "label": "https://fosstodon.org/@EDSbook",
+      "url": "https://fosstodon.org/@EDSbook"
+    },
+    {
+      "label": "https://edsbook.org/welcome.html",
+      "url": "https://edsbook.org/welcome.html"
+    },
+    {
+      "label": "https://edsbook.org",
+      "url": "https://edsbook.org"
+    },
+    {
+      "label": "https://github.com/alan-turing-institute/environmental-ds-book",
+      "url": "https://github.com/alan-turing-institute/environmental-ds-book"
+    },
+    {
+      "label": "https://www.youtube.com/channel/UC148zpdIEfRun-cUJbgbIyg",
+      "url": "https://www.youtube.com/channel/UC148zpdIEfRun-cUJbgbIyg"
+    },
+    {
+      "label": "https://twitter.com/eds_book",
+      "url": "https://twitter.com/eds_book"
+    }
+  ],
+  "speakers": [
+    "Alejandro Coca Castro",
+    "Anne Fouilloux"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/1pJA65lrKZw/maxresdefault.jpg",
+  "title": "Environmental Data Science Book: A computational notebook community for open environmental science",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=1pJA65lrKZw"
+    }
+  ]
+}

jupytercon-2023/videos/alyssa-goodman-a-goodman-alyssa-goodman-keynote-jupytercon-2023.json

@@ -0,0 +1,26 @@
+{
+  "description": "Alyssa Goodman will present our second day keynote.",
+  "duration": 3375,
+  "language": "eng",
+  "recorded": "2023-05-10",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://web.archive.org/web/20230531110007/https://www.jupytercon.com/"
+    }
+  ],
+  "speakers": [
+    "Alyssa Goodman"
+  ],
+  "tags": [
+    "Keynote"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/HvLCmzoz5Hw/maxresdefault.jpg",
+  "title": "Seeing the universe, more clearly, with glue",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=HvLCmzoz5Hw"
+    }
+  ]
+}

jupytercon-2023/videos/amit-rathi-building-github-code-review-experience-for-jupyter-notebooks-jupytercon-2023.json

@@ -0,0 +1,24 @@
+{
+  "description": "Key Takeaways\nWhat is notebook code review & why should Jupyter users care\nHow to build rich diffs & commenting for notebooks\nHow to integrate notebook diff & commenting with version control platforms like GitHub & Bitbucket\nSummary\nFor the past 4+ years, I\u2019ve built a notebook code review experience (ReviewNB) for GitHub as a solo bootstrapped developer. Thousands of organizations now use the service, including Apple, Airbnb, Lyft, Deloitte, Affirm, AWS, Meta Reality Labs, and NASA JPL.\n\nThis talk focuses on behind-the-scenes technical details such as,\n\nChallenges of building rich notebook diffs on top of GitHub / Bitbucket\nhandling JSON diffs\nhandling images, plots & other rich outputs\nChallenges of building discussion / commenting functionality for notebooks\nwhere & how to store notebook comments\nhow to handle comments when underlying notebook changes",
+  "duration": 1513,
+  "language": "eng",
+  "recorded": "2023-05-10",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://web.archive.org/web/20230531110007/https://www.jupytercon.com/"
+    }
+  ],
+  "speakers": [
+    "Amit Rathi"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/Huf3muGynwM/maxresdefault.jpg",
+  "title": "Building GitHub Code Review Experience for Jupyter Notebooks",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=Huf3muGynwM"
+    }
+  ]
+}

jupytercon-2023/videos/amit-rathi-vinay-kakade-simplify-devops-with-executable-notebooks-jupytercon-2023.json

@@ -0,0 +1,29 @@
+{
+  "description": "Today, Jupyter Notebooks are mostly confined to science, research & education. But notebooks can provide organizations with a powerful general-purpose \u201cexecutable documentation\u201d platform. A solid use case for this is DevOps & more specifically, IT incident response.\n\nTechnology teams usually have an on-call rotation with static wiki-style documentation to guide the on-call engineer. Jupyter Notebooks can replace static documentation with executable notebooks. E.g. \u201cfetch service logs\u201d and \u201crollback last deployment\u201d can simply mean executing a code cell that\u2019s available alongside the markdown instructions.\n\nWhat are the benefits of executable vs. static documentation for DevOps -\n\nQuick e.g. \u201ccheck DB latency\u201d is 1-click notebook code cell execution to plot latency graph vs. going to a third-party UI in the middle of an incidence\nPrecise e.g. \u201cpromote read replica to master\u201d can mean a series of steps & possibility of human error; codifying the steps in advance removes ambiguity & results in precise action.\n\u201cExecutable documentation\u201d is a simple yet powerful concept that can extend to other use cases such as - API documentation, developer onboarding, data visualization & reporting, scheduling routine tasks & so on. Think of it as executable GoogleDocs powered by Jupyter!\n\nIn this talk, we\u2019d like to,\n- Introduce the concept of Jupyter powered \u201cexecutable documentation\u201d platform, particularly for DevOps and Incident Response,\n- Show a demo of how it\u2019d work - (https://www.youtube.com/watch?v=vvLXSAHCGF8)\n- Talk about important challenges, and propose a way forward to make this a mainstream application of Jupyter notebooks.",
+  "duration": 1665,
+  "language": "eng",
+  "recorded": "2023-05-10",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://web.archive.org/web/20230531110007/https://www.jupytercon.com/"
+    },
+    {
+      "label": "https://www.youtube.com/watch?v=vvLXSAHCGF8",
+      "url": "https://www.youtube.com/watch?v=vvLXSAHCGF8"
+    }
+  ],
+  "speakers": [
+    "Amit Rathi",
+    "Vinay Kakade"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/TUYY2kHrTzs/maxresdefault.jpg",
+  "title": "Simplify DevOps with Executable Notebooks",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=TUYY2kHrTzs"
+    }
+  ]
+}

jupytercon-2023/videos/ana-ruvalcaba-afshin-darian-jason-grout-fernando-perez-state-of-the-union-jupyter-community.json

@@ -0,0 +1,27 @@
+{
+  "description": "Come learn how the Jupyter community and leadership is organized today. We'll talk about new strategic initiatives impacting the global Jupyter community.",
+  "duration": 1750,
+  "language": "eng",
+  "recorded": "2023-05-10",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://web.archive.org/web/20230531110007/https://www.jupytercon.com/"
+    }
+  ],
+  "speakers": [
+    "Ana Ruvalcaba",
+    "Afshin Darian",
+    "Jason Grout",
+    "Fernando Pérez"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/GlCAHwmoh_w/maxresdefault.jpg",
+  "title": "State of the Union: Jupyter Community",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=GlCAHwmoh_w"
+    }
+  ]
+}

jupytercon-2023/videos/carlos-cordoba-the-spyder-debugger-an-interactive-debugger-based-on-jupyter-technologies.json

@@ -0,0 +1,24 @@
+{
+  "description": "One of the main features of scientific programming is its exploratory nature: starting from some input data, the goal is to analyze it in order to understand what it can tell us about the phenomena that generated it. However, the means to do this are often unclear, and the results unforeseen. That is why this type of programming requires tools for rapid, interactive prototyping that allow users to seamlessly switch solutions to tackle the problem at hand. Unfortunately, it is not possible to follow the same approach while debugging, because traditional debuggers are mostly focused on letting users explore the call stack and state of variables, and have limited capabilities to run code.\n\nSpyder, a community developed, open source IDE written in and for Python, aims to bridge the gap in that area. It blends the debugger with the interpreter to allow data exploration at any point during code execution, not just at the end. For that, Spyder's debugger attempts to offer the same functionality as a full IPython interpreter, so that its users can debug their code in the same way they are used to doing the rest of their scientific programming.\n\nIn this talk, I will cover the debugger features available in Spyder 5, as well as those planned for future versions. Specifically, I will present a live demo to showcase the following features (described in depth in this blog post and the Spyder documentation):\n\nHow to start the debugger and set breakpoints.\nHow to better understand the code at a certain frame by writing code snippets in the debugger itself, facilitated by syntax highlighting, code completion, multi-line editing and command history.\nHow to move up and down in the call stack to explore other frames in the same way.\nHow to use Spyder's Variable Explorer to browse the contents of objects.\nHow to generate Matplotlib plots while in the debugger.\nHow to use IPython magics while debugging to profile code using %timeit, explore the filesystem with %cd and %ls, and open files with %edit.\nThanks to these improvements, Spyder transforms debugging from a task that feels foreign to scientific programming, to be almost second nature. By adding breakpoint calls or setting breakpoints in the debugger, users can easily prototype different solutions for their problems at any point during code execution, and not just at end. This also increases programming speed by allowing to constantly check the correctness of code during development.\n\nAt the end of this talk, I hope attendees will learn that they don't need resort to print() or other workarounds to debug their code. Instead, they can rely on the robust debugging methods used by professional developers, supported by the interactivity and workflow they're familiar with in IPython/Jupyter.",
+  "duration": 1857,
+  "language": "eng",
+  "recorded": "2023-05-10",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://web.archive.org/web/20230531110007/https://www.jupytercon.com/"
+    }
+  ],
+  "speakers": [
+    "Carlos Cordoba"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi_webp/93aabAQtdQM/maxresdefault.webp",
+  "title": "The Spyder debugger: An interactive debugger based on Jupyter technologies",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=93aabAQtdQM"
+    }
+  ]
+}

jupytercon-2023/videos/carlos-herrero-trung-le-david-brochart-real-time-collaboration-in-jupyter-jupytercon-2023.json

@@ -0,0 +1,26 @@
+{
+  "description": "In the past years, real-time collaboration has become a must for any editor, a feature that users expect as core functionality in their daily editor. Sharing and collaborating on the same document with your colleagues or teachers increases productivity by improving the teamwork experience.\n\nThe adoption of real-time collaboration in JupyterLab has been a challenge for many developers over the years. From the very beginning, RTC was in JupyterLab's roadmap. Still, it was only in v3.x that it became a reality, and in v4.0, that it shows its real power. We want to describe the feature in detail with everyone to give extension developers the knowledge to leverage it into their plugins.\n\nThis talk will go through the RTC implementation and describe the role of the packages used.. The various entry points to use and extend real-time collaboration on documents will be highlighted. And it will show the corner cases and the restrictions it enforces.\n\nFinally, we will offer a glimpse into how real-time collaboration works in JupyterCAD and JupyterLite. JupyterCAD is a JupyterLab extension using a non-default document type for 3D geometry modeling that supports the FreeCAD format. JupyterLite is a lightweight serverless version of JupyterLab, which changes the paradigm of collaboration. It adds a new challenge by removing the central authority that's the server, requiring the use of peer-to-peer communication to synchronize clients. The document is leveraging the real-time collaboration API to allow collaborative editing.",
+  "duration": 1588,
+  "language": "eng",
+  "recorded": "2023-05-10",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://web.archive.org/web/20230531110007/https://www.jupytercon.com/"
+    }
+  ],
+  "speakers": [
+    "Carlos Herrero",
+    "Trung Le",
+    "David Brochart"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/CoZ3Sg--JLk/maxresdefault.jpg",
+  "title": "Real Time Collaboration in Jupyter",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=CoZ3Sg--JLk"
+    }
+  ]
+}

jupytercon-2023/videos/cheuk-ting-ho-driving-down-the-memray-lane-profiling-your-data-science-work-jupytercon-2023.json

@@ -0,0 +1,24 @@
+{
+  "description": "When handling a large amount of data, memory profiling the data science workflow becomes more important. It gives you insight into which process consumes lots of memory. In this talk, we will introduce Mamray, a Python memory profiling tool and its new Jupyter plugin.",
+  "duration": 1964,
+  "language": "eng",
+  "recorded": "2023-05-10",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://web.archive.org/web/20230531110007/https://www.jupytercon.com/"
+    }
+  ],
+  "speakers": [
+    "Cheuk Ting Ho"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/56smzzDadwQ/maxresdefault.jpg",
+  "title": "Driving down the Memray lane Profiling your data science work",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=56smzzDadwQ"
+    }
+  ]
+}