Merge pull request #1182 from amyreese/pycascades2024

Talks for PyCascades 2024

pycascades-2024/category.json

@@ -0,0 +1,3 @@
+{
+  "title": "PyCascades 2024"
+}

pycascades-2024/videos/building-graphql-microservices-using-fastapi.json

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+{
+  "copyright_text": "",
+  "description": "FastAPI is a Python web framework built on top of the ASGI standard. The fusion of GraphQL and FastAPI emerges as a pivotal approach for constructing agile and scalable microservices. This talk delves into the symbiotic relationship between GraphQL's query flexibility and FastAPI's high-performance capabilities. Attendees will gain insights into seamless integration techniques, leveraging FastAPI's asynchronous framework, dependency injection, and GraphQL's expressive querying.",
+  "duration": 1422,
+  "language": "eng",
+  "recorded": "2024-04-07",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Aby M Joseph",
+    "Thameem Karakkoth"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/keiaOBCfWNE/maxresdefault.jpg",
+  "title": "Building GraphQL microservices using FastAPI",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=keiaOBCfWNE"
+    }
+  ]
+}

pycascades-2024/videos/containerizing-python-crafting-better-and-efficient-containers.json

@@ -0,0 +1,29 @@
+{
+  "copyright_text": "",
+  "description": "Containerization, particularly with tools like Docker, has become a cornerstone in deploying applications efficiently. Building a Docker image for Python applications is generally uncomplicated, yet optimizing these images requires extra work. Notably, many of these optimizations are uniquely tailored to Python.\n\nThis talk focuses on techniques and best practices to build more efficient Docker images for Python in order to generate reproducible and quicker builds while reducing the image sizes at the same time.",
+  "duration": 1652,
+  "language": "eng",
+  "recorded": "2024-04-07",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Avik Basu"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/MMUjFzcyIWs/maxresdefault.jpg",
+  "title": "Containerizing Python: Crafting Better and Efficient Containers",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=MMUjFzcyIWs"
+    }
+  ]
+}

pycascades-2024/videos/cutting-the-usb-cord-wirelessly-programming-circuitpython.json

@@ -0,0 +1,29 @@
+{
+  "copyright_text": "",
+  "description": "Come learn how to program CircuitPython wirelessly over Bluetooth and WiFi. CircuitPython is a version of Python designed for small computers used in electronics projects called microcontrollers. Bluetooth is great for connecting devices to a phone or tablet on the go. At home, WiFi simplifies connecting to a multitude of devices without needing to plug into them directly. Both are also great for devices that are hard to access.",
+  "duration": 1278,
+  "language": "eng",
+  "recorded": "2024-04-07",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Scott Shawcroft"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/eiQ9RIt-cNM/maxresdefault.jpg",
+  "title": "Cutting the USB cord: wirelessly programming CircuitPython",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=eiQ9RIt-cNM"
+    }
+  ]
+}

pycascades-2024/videos/designing-a-human-friendly-cli-for-api-driven-infrastructure.json

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+{
+  "copyright_text": "",
+  "description": "As Bloomberg\u2019s infrastructure grows and evolves, the tools we use to manage it are becoming increasingly important. To streamline infrastructure management, our team set out to design a REST API and constituent CLI (Command Line Interface) that would comprise a single interface for both programmatic and human interaction with our infrastructure. Traditionally, building a CLI that is tightly coupled to an API requires maintaining a separate codebase, which is tedious and error-prone. Instead, we designed a CLI that dynamically generates commands based on the OpenAPI JSON documentation. However, since APIs are designed for computer interaction, we designed our API to include the information needed to implement a human-friendly CLI. Leveraging Python, FastAPI, and numerous other open source projects, we built a stable, extensible tool that greatly improves how we interact with our infrastructure.",
+  "duration": 1392,
+  "language": "eng",
+  "recorded": "2024-04-07",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Oliver Rew"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/LZQCLsqxVKI/sddefault.jpg",
+  "title": "Designing a Human-Friendly CLI for API-Driven Infrastructure",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=LZQCLsqxVKI"
+    }
+  ]
+}

pycascades-2024/videos/embracing-mlops-bridging-the-gap-between-machine-learning-and-devops.json

@@ -0,0 +1,29 @@
+{
+  "copyright_text": "",
+  "description": "In the dynamic field of machine learning, MLOps (Machine Learning Operations) has emerged as a crucial discipline combining aspects of machine learning, data science and operations. This talk aims to demystify MLOps differentiating it from traditional DevOps practices and highlighting its growing importance.",
+  "duration": 1398,
+  "language": "eng",
+  "recorded": "2024-04-06",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Mayank Jindal"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/wRnKcWIZEvk/maxresdefault.jpg",
+  "title": "Embracing MLOps: Bridging the Gap Between Machine Learning and DevOps",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=wRnKcWIZEvk"
+    }
+  ]
+}

pycascades-2024/videos/i-declare-an-environment-reproducibility-with-and-without-docker.json

@@ -0,0 +1,29 @@
+{
+  "copyright_text": "",
+  "description": "A software project being called \"reproducible\" can mean a lot of things, but usually includes a description of how and where the code in your project can be run. Often this means including Python virtual environment, a Conda environment, or even a Docker container to help others replicate your work. In this talk I will introduce some of the most common ways the scientific Python community approaches reproducibility, and what are the advantages and disadvantages of the approaches. I will also share a new way that you can make not only your Python code but your development machine reproducible without Docker containers with a tool called Nix. I will also show an example of using a Nix defined operating system (NixOS) with Docker containers to run my home lab.",
+  "duration": 1591,
+  "language": "eng",
+  "recorded": "2024-04-06",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Sarah Kaiser"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/acGazOBPpeo/maxresdefault.jpg",
+  "title": "I declare an environment! - Reproducibility with and without Docker",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=acGazOBPpeo"
+    }
+  ]
+}

pycascades-2024/videos/intro-to-introspection.json

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+{
+  "copyright_text": "",
+  "description": "Python holds no secrets about your code; except perhaps how to access that information. in this talk you'll find out how to discover almost any information about running python code.",
+  "duration": 1307,
+  "language": "eng",
+  "recorded": "2024-04-06",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Jeremiah Paige"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/bCIDqS1sY5c/sddefault.jpg",
+  "title": "Intro to Introspection",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=bCIDqS1sY5c"
+    }
+  ]
+}

pycascades-2024/videos/kandinsky-using-kmeans-and-friends-to-play-with-the-colors.json

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+{
+  "copyright_text": "",
+  "description": "Clustering is tricky yet absolutely essential for many a Machine Learning initiative. The what, the how and the why confound each time we look at the data, whether it is customer segmentation (or cohort) analysis or it is finding centers of influence or breaking down a population into groups to build different models for each.\n\nStudying clustering algorithms like KMeans using toy datasets is insufficient (and often tedious) because it does not let you experience real-world problems. For e.g. the problem when the centroids don't settle, or situations where we have too many or too few clusters. Which distance measure to use and when? How to prepare (normalize? standardize?) the dataset for clustering?\n\nAlso, not too many real-world scenarios are \"visual\", unless we plot a graph or two, and that fails when we deal with higher dimensions.\n\nWhat if we could use a non-trivial but visual data source? Like the colors and pixels of a photograph, where we could see the data that went in and the resultant output clusters?\n\nThe obvious **takeaways of this talk**, in my experience, are that *Data Science and Data Engineering practitioners* gain a deeper understanding of what's going on in the clustering algorithms in a fun, very \"visual\" and engaging manner; and also build a better intuition about the best approach to take for solving a problem.",
+  "duration": 1513,
+  "language": "eng",
+  "recorded": "2024-04-06",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Shaurya Agarwal"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/3v876L6_ay4/maxresdefault.jpg",
+  "title": "Kandinsky: Using KMeans (and friends) to play with the colors of photograph(s)",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=3v876L6_ay4"
+    }
+  ]
+}

pycascades-2024/videos/lightning-talks.json

@@ -0,0 +1,27 @@
+{
+  "copyright_text": "",
+  "description": "",
+  "duration": 2042,
+  "language": "eng",
+  "recorded": "2024-04-07",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/mtfu_D3pAlo/sddefault.jpg",
+  "title": "Lightning Talks",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=mtfu_D3pAlo"
+    }
+  ]
+}

pycascades-2024/videos/next-level-python-applications-with-pyscript.json

@@ -0,0 +1,29 @@
+{
+  "copyright_text": "",
+  "description": "Zero Installation, massive scalability, mobile support and more. This talk is going to cover the super powers of running Python in the Browser and how to best use PyScript.",
+  "duration": 1522,
+  "language": "eng",
+  "recorded": "2024-04-06",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Fabio Pliger"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/btEFmI633Pg/maxresdefault.jpg",
+  "title": "Next Level Python Applications with PyScript",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=btEFmI633Pg"
+    }
+  ]
+}

pycascades-2024/videos/notably-inaccessible-data-driven-understanding-of-jupyter-notebook-inaccessibility.json

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+{
+  "copyright_text": "",
+  "description": "Speaker: Venkatesh Potluri\n\nJupyter notebooks are versatile tools that open up rich storytelling possibilities by providing the means to interleave code, data and text together. Notebooks are widely adopted in a variety of expert domains such as data science, machine learning, and astronomy making the ability to create and consume them a critical requirement to participate in these professional domains. Notebooks and notebook software (tools and infrastructure to create and share notebooks) however are inaccessible resulting in barriers preventing blind or visually impaired (BVI) experts from participating in these professions.\n\nIn this talk, I will draw from our systematic large scale analysis on 100000 Jupyter notebooks and provide a broad understanding of why these notebooks are inaccessible, and exactly how inaccessible these notebooks really are. I will close with recommendations to infrastructures that drive the notebook pipeline and authoring practices to create and share truly accessible notebooks. It is imperative that we contribute to accessible notebook artifacts and software to make high-skilled work accessible!",
+  "duration": 1023,
+  "language": "eng",
+  "recorded": "2024-04-07",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Venkatesh P"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/vQS8bKCt6Hw/maxresdefault.jpg",
+  "title": "Notably Inaccessible -- Data Driven Understanding of Jupyter Notebook Inaccessibility",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=vQS8bKCt6Hw"
+    }
+  ]
+}

pycascades-2024/videos/oh-the-methods-you-can-make-by-dunder-seuss.json

@@ -0,0 +1,29 @@
+{
+  "copyright_text": "",
+  "description": "You can make many methods\n\nOver 100 to be exact\n\nThat start with two underscores\n\nWhat do you think of that?\n\nThe runtime, it calls these\n\nAt points A or B\n\nTo do special magic\n\nAt runtime, you see.\n\nYou may have seen `__getattr__` or `__init__`\n\nBut `__rfloordiv__`? What\u2019s the point of it?",
+  "duration": 1205,
+  "language": "eng",
+  "recorded": "2024-04-06",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Joshua Cannon"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/JiWhOHzho8o/maxresdefault.jpg",
+  "title": "Oh the (Methods) You Can (Make): By Dunder Seuss",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=JiWhOHzho8o"
+    }
+  ]
+}

pycascades-2024/videos/pyladies-panel-talking-about-experiences-and-roles-within-the-python.json

@@ -0,0 +1,32 @@
+{
+  "copyright_text": "",
+  "description": "Panelists: Christy Heaton, Mariatta, Lynn Root, Luciana Abud",
+  "duration": 2621,
+  "language": "eng",
+  "recorded": "2024-04-07",
+  "related_urls": [
+    {
+      "label": "Conference schedule",
+      "url": "https://2024.pycascades.com/program/schedule/"
+    },
+    {
+      "label": "Full playlist",
+      "url": "https://www.youtube.com/playlist?list=PLcNrB7gPa-Ne6QknxKayJaEBsKfkmA72l"
+    }
+  ],
+  "speakers": [
+    "Lynn Root",
+    "Mariatta",
+    "Christy Heaton",
+    "Luciana Abud"
+  ],
+  "tags": [],
+  "thumbnail_url": "https://i.ytimg.com/vi/whXlOKFk4Js/sddefault.jpg",
+  "title": "PyLadies Panel: Talking about experiences and roles within the Python community",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=whXlOKFk4Js"
+    }
+  ]
+}