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Talks for PyBay 2024
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{ | ||
"title": "PyBay 2024" | ||
} |
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pybay-2024/videos/13-fun-facts-about-python-s-return-statement-for-savvy.json
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{ | ||
"copyright_text": "", | ||
"description": "Python\u2019s return statement is one of the first keywords introduced to new learners of the language. We\u2019re taught that it \u201ctells Python the function is done\u201d and often not much else about it! What happens if you forget to include a return at the end of a function? What if you try to use one outside of a function? Can a function return another function? Come learn about all of the cool things you can achieve in your programs through a better understanding of return statements!", | ||
"duration": 1149, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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"url": "https://2024.pybay.org/attending/schedule/" | ||
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"url": "https://www.youtube.com/playlist?list=PL85KuAjbN_gvx5b_BgLVcKfccnlZAVPMk" | ||
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], | ||
"speakers": [ | ||
"Erin 'August' Allard" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/O6vdUANk_rI/maxresdefault.jpg", | ||
"title": "13 fun facts about Python's return statement for savvy programmers", | ||
"videos": [ | ||
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"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=O6vdUANk_rI" | ||
} | ||
] | ||
} |
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pybay-2024/videos/a-101-in-time-series-analytics-with-apache-arrow-pandas.json
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"copyright_text": "", | ||
"description": "Columnar databases are on the rise! They provide an efficient and scalable data warehouse for many use cases including time series data. The problem? many conventional database drivers and querying methods become the bottleneck for data processing and analytics within our client-side applications. Learn how to leverage open-source projects like Apache Arrow Flight and Apache Parquet alongside industry-standard analytics libraries to build the foundations of a performant analytics application for time series data.", | ||
"duration": 1957, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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], | ||
"speakers": [ | ||
"Zoe Steinkamp" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/CZztanBkVfI/maxresdefault.jpg", | ||
"title": "A 101 in time series analytics with Apache Arrow, Pandas and Parquet", | ||
"videos": [ | ||
{ | ||
"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=CZztanBkVfI" | ||
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pybay-2024/videos/accelerating-ml-prototyping-the-pythonic-way.json
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"description": "Effective machine learning (ML) prototyping is critical for developing successful models and applications. Python, with its robust ecosystem of tools, plays a significant role in this process.\n\nThis talk will bring a fresh perspective on how we, at Meta, provide tools for efficient ML prototyping for our researchers and ML engineers. We will first go through a comprehensive overview of the ML lifecycle and then deep dive into the ML prototyping phase, emphasizing on its significance. We will focus on conda for environment management and jupyter notebooks for interactive development \u2014 two powerful tools that streamline development and experimentation at Meta and in the industry, in general. In the last part of the talk, I will highlight interesting examples of improvements made to these tools at Meta for efficient prototyping, accelerating the developer productivity in the AI space.", | ||
"duration": 554, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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"speakers": [ | ||
"Parul Gupta" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/RgFe5tc-3TQ/maxresdefault.jpg", | ||
"title": "Accelerating ML Prototyping: The Pythonic Way", | ||
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"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=RgFe5tc-3TQ" | ||
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pybay-2024/videos/architecting-native-python-extension-modules.json
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"copyright_text": "", | ||
"description": "Over 20% of the most downloaded Python modules rely on native extension modules written in compiled languages like C, C++, and Rust. These extension modules, with their low-level control and high performance, enable Python to be used in new domains, from numerical computing to interfacing with hardware. However, they also present a new set of architecture-level questions, as well as trade-offs between performance, Python API ergonomics, and extension module maintainability. This talk will answer those questions and provide a set of best practices for creating fast, useful, and maintainable extension modules.", | ||
"duration": 623, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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"url": "https://2024.pybay.org/attending/schedule/" | ||
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} | ||
], | ||
"speakers": [ | ||
"Alexander Steele" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/dwQAbWCcQHY/maxresdefault.jpg", | ||
"title": "Architecting Native Python Extension Modules", | ||
"videos": [ | ||
{ | ||
"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=dwQAbWCcQHY" | ||
} | ||
] | ||
} |
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pybay-2024/videos/automate-your-city-data-with-python.json
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"copyright_text": "", | ||
"description": "Every week, in every city, hundreds if not thousands of decisions, big and small, are being made about the places where we all live. Most of the time, these decisions are hidden behind old systems, arcane websites, or poorly formatted PDFs. With the power of Datasette, Python data tooling, and Github actions, you can quickly set up a low-or-no-cost city data pipeline, and help us all better understand the decisions being made where we live.", | ||
"duration": 1691, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
"related_urls": [ | ||
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"url": "https://2024.pybay.org/attending/schedule/" | ||
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"url": "https://www.youtube.com/playlist?list=PL85KuAjbN_gvx5b_BgLVcKfccnlZAVPMk" | ||
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], | ||
"speakers": [ | ||
"Philip James" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/aabAskJgDII/maxresdefault.jpg", | ||
"title": "Automate Your City Data With Python", | ||
"videos": [ | ||
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"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=aabAskJgDII" | ||
} | ||
] | ||
} |
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{ | ||
"copyright_text": "", | ||
"description": "A branch deploy system\u2014where developers deploy a branch to production before merging\u2014 enables everyone to deploy faster, unblocks developer productivity, and dramatically reduces the need for reverts. Companies at large scale do it, but anyone can! We'll go through the benefits, logistics, and how you use Python to build one.", | ||
"duration": 614, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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"url": "https://www.youtube.com/playlist?list=PL85KuAjbN_gvx5b_BgLVcKfccnlZAVPMk" | ||
} | ||
], | ||
"speakers": [ | ||
"Ted Nyman" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/rsSDK8mIWns/maxresdefault.jpg", | ||
"title": "Branch deploys at any scale", | ||
"videos": [ | ||
{ | ||
"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=rsSDK8mIWns" | ||
} | ||
] | ||
} |
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pybay-2024/videos/deploy-python-apps-on-kubernetes-and-prepare-for-scale.json
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"copyright_text": "", | ||
"description": "Python Applications aren't stand alone, they need to work along with other applications, talk to databases; and be prepared for scale. Kubernetes is the de-facto standard for achieving scalability. \n\nIn this talk, we will see how Developers can be design their workflow ad architecture, the take the python app, interacting with database and an AI Model (not api) and deploy the application to Kubernetes, and prepare for scale.", | ||
"duration": 1543, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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"url": "https://2024.pybay.org/attending/schedule/" | ||
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"url": "https://www.youtube.com/playlist?list=PL85KuAjbN_gvx5b_BgLVcKfccnlZAVPMk" | ||
} | ||
], | ||
"speakers": [ | ||
"Senthil Kumaran" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/QCeEv0pIHhg/maxresdefault.jpg", | ||
"title": "Deploy Python Apps on Kubernetes and Prepare for Scale", | ||
"videos": [ | ||
{ | ||
"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=QCeEv0pIHhg" | ||
} | ||
] | ||
} |
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pybay-2024/videos/edges-of-python-three-radical-python-hacks-for-fun-and.json
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"copyright_text": "", | ||
"description": "Building complex software projects is hard, but the fun part of doing it is that it often pushes you to find non-obvious solutions to problems which seem radical at first, yet almost obvious in hindsight. In this talk you learn some of the unusual Python tricks that we use at EdgeDB to write more efficient Python with fewer bugs, and which you can apply in your project next time you need to scratch a similar itch.", | ||
"duration": 1292, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
"related_urls": [ | ||
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"url": "https://2024.pybay.org/attending/schedule/" | ||
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"url": "https://www.youtube.com/playlist?list=PL85KuAjbN_gvx5b_BgLVcKfccnlZAVPMk" | ||
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], | ||
"speakers": [ | ||
"Elvis Pranskevichus" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/dehXne5KItI/maxresdefault.jpg", | ||
"title": "Edges of Python: Three Radical Python Hacks for Fun and Profit", | ||
"videos": [ | ||
{ | ||
"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=dehXne5KItI" | ||
} | ||
] | ||
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{ | ||
"copyright_text": "", | ||
"description": "By now we hope you've been using f-strings, but do you know that there's more to it than sticking variables into curly braces?\n\nIn this talk, we'll go through the useful features of f-strings, from formatting to debugging. We'll also share how f-strings have been improved since Python 3.12. Watch this talk so you don't miss out!", | ||
"duration": 1436, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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], | ||
"speakers": [ | ||
"Mariatta" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/8r5rB8x4uFI/maxresdefault.jpg", | ||
"title": "F-Strings!", | ||
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{ | ||
"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=8r5rB8x4uFI" | ||
} | ||
] | ||
} |
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pybay-2024/videos/from-pandas-to-polars-upgrading-your-data-workflow.json
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{ | ||
"copyright_text": "", | ||
"description": "Thinking about making the switch from Pandas to Polars? This talk is for you. Matt Harrison, author of both Effective Pandas and Effective Polars, will compare the two libraries, highlighting Polars' unique advantages and how it addresses some of Pandas' limitations. You\u2019ll learn how to translate your existing Pandas knowledge into Polars, taking full advantage of its speed and efficiency for more effective data processing", | ||
"duration": 3477, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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"speakers": [ | ||
"Matt Harrison" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/s5DxsBHDi1o/maxresdefault.jpg", | ||
"title": "From Pandas to Polars: Upgrading Your Data Workflow", | ||
"videos": [ | ||
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"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=s5DxsBHDi1o" | ||
} | ||
] | ||
} |
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pybay-2024/videos/how-to-build-a-cross-platform-gui-with-python.json
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"copyright_text": "", | ||
"description": "If you need to build a user interface for your Python code, many guides will tell you that your only options are to use the command line, or wrap your code in a web interface. However, there is another option - building a GUI interface. In fact, in some cases, a GUI app may be your *only* option. In this talk, you'll learn how to build a cross-platform GUI application to wrap your Python code, and how to use that GUI application to access device features that may not be accessible from a command line or web interface.", | ||
"duration": 2846, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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"url": "https://2024.pybay.org/attending/schedule/" | ||
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"url": "https://www.youtube.com/playlist?list=PL85KuAjbN_gvx5b_BgLVcKfccnlZAVPMk" | ||
} | ||
], | ||
"speakers": [ | ||
"Russell Keith-Magee" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/tuSnatBqItE/maxresdefault.jpg", | ||
"title": "How to build a cross-platform GUI with Python", | ||
"videos": [ | ||
{ | ||
"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=tuSnatBqItE" | ||
} | ||
] | ||
} |
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pybay-2024/videos/impress-your-enterprise-customers-with-openid-connect-login.json
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{ | ||
"copyright_text": "", | ||
"description": "When you sell a Python SaaS app, customers' first question will be, \"How do I log in?\". Are you committing the security faux pas of rolling your own authentication? Does your app only support password login? If you've integrated identity standards, do you understand how they work and how you can benefit from their full set of features? In this talk, you'll learn the principles of how to use OpenID Connect (OIDC) to secure a Django app for the first time or refresh your knowledge. OIDC allows enterprise customers' users to sign in with their corporate identity providers and facilitates social login with Google or Twitter. Show your customers how you're prioritizing their authentication needs by following secure open standards.", | ||
"duration": 1166, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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], | ||
"speakers": [ | ||
"Semona Igama" | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/u4fVsTMjyPE/maxresdefault.jpg", | ||
"title": "Impress your enterprise customers with OpenID Connect login", | ||
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{ | ||
"type": "youtube", | ||
"url": "https://www.youtube.com/watch?v=u4fVsTMjyPE" | ||
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pybay-2024/videos/make-a-working-implementation-of-async-functions-in-python-2.json
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{ | ||
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"description": "FULL TITLE: \"Let's make a working implementation of async functions in Python 1.6; or, why to use newer Pythons\" \u2014 Christopher Neugebauer (PyBay 2024)\"\n\nOften I hear people lamenting that Python has too many features and that older versions of Python were better for that exact reason.\n\nTo make those people happy, we're going to pick apart the features of Python that enable the `async`/`await` syntax, layer by layer, until we happen upon a working implementation of coroutines that will function in Python 2.1.\n\nSomewhere in this talk will be some useful discussions about why recent syntactic developments in Python are a good thing actually, but let's not lie, you're reading this abstract for the stunt content. You'll get what you came for.", | ||
"duration": 1742, | ||
"language": "eng", | ||
"recorded": "2024-09-21", | ||
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], | ||
"speakers": [ | ||
"Christopher Neugebauer " | ||
], | ||
"tags": [], | ||
"thumbnail_url": "https://i.ytimg.com/vi/iU6QK54Exik/maxresdefault.jpg", | ||
"title": "Make a working implementation of async functions in Python 1.6!", | ||
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"url": "https://www.youtube.com/watch?v=iU6QK54Exik" | ||
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