SF Python<br>
PyBay 2023<br>
 1. Pants: Cargo for Python (Benjy Weinberger) https://youtu.be/0-qKNTouuOY 42 min.<br>
 2. Programming Your Computer With Python (Glyph Lefkowitz) https://youtu.be/LceLUPdIzRs 36 min.<br>
 3. Ranking and Retrieval Techniques for Retrieval Augmented Generation with Haystack (Tuana Celik) https://youtu.be/6u7osMnIQHg 30 min.<br>
 4. Data Science beasts (failures) and where to find them (Grishma Jena) https://youtu.be/pHlptwP20MY 10 min.<br>
 5. Type safe data validation using Pydantic v2 (Adrian Garcia Badaracco) https://youtu.be/h9uCUVjKeas 20 min.<br>
 6. Craft Complex Mock Data (Jason Koo) https://youtu.be/N5Anbq8vYNk 21 min.<br>
 7. Embeddings: What they are and why they matter (Simon Willison) https://youtu.be/snKTqb10vWQ 38 min.<br>
 8. Python deployment with Docker and Poetry (Cristian Heredia) https://youtu.be/hXYFS2pOEH8 12 min.<br>
 9. Let&#x27;s talk about JWT (Jessica Temporal) https://youtu.be/0vxVUjUL_Nw 17 min.<br>
 10. Infrastructure as a Product: Lessons in Platform Engineering (Nick DiRienzo) https://youtu.be/5hbxUX4dwyk 29 min.<br>
 11. FORKS? POOLS? ASYNC? Solving Wordle with Python’s concurrency tools (Christopher Neugebauer) https://youtu.be/ViUEGvNDwrQ 31 min.<br>
 12. Using pandas and pyspark to address challenges in processing and storing time series instrument data (Aaron Wiegel) https://youtu.be/yCp6b_rHrLQ 28 min.<br>
 13. Elevating Python Development with Nix Package Manager (Salar Rahmanian) https://youtu.be/AJs_izrEBOA 28 min.<br>
 14. Python in Hardware &amp; Embedded Systems: A Deep Dive (Sriram Vamsi Ilapakurthy) https://youtu.be/r6wabaVH7CE 29 min.<br>
 15. Contain Yourself (Moshe Zadka) https://youtu.be/tI2y7pG6v84 24 min.<br>
 16. No More Nitpicks: effortless cleanup with fixers, formatters, and codemods (Zac Hatfield-Dodds) https://youtu.be/vqlHqqhTwzA 14 min.<br>
 17. Better Together: Unleashing the Synergy of Pandas, Polars, and Apache Arrow (Chris Brousseau) https://youtu.be/IVgizc711OA 15 min.<br>
 18. Python, Planets, and Portals: Designing Web Apps for Modern Astronomers (Dan Burger) https://youtu.be/oZMe1EgNvZg 29 min.<br>
 19. Scale Data Science by Pandas API on Spark (Xinrong Meng) https://youtu.be/uQRmZbIyuzg 26 min.<br>
 20. Beyond Conventional: Embracing Python &amp; LLMs for Quality Assurance (Paul Pereyda Karayan) https://youtu.be/TSI4rYKpwws 26 min.<br>
 21. Testing Strategies for Python (Liz Acosta) https://youtu.be/HHR2YnWD0rw 14 min.<br>
 22. Understanding LangChain Agents and Tools with Twilio (or with SMS) (Lizzie Siegle) https://youtu.be/0d-v9yeTIeY 25 min.<br>
 23. Shiny: Data-centric web applications in Python (Joe Cheng) https://youtu.be/o8vxlj8Vcqo 25 min.<br>
 24. Unleashing Python&#x27;s Power: Serverless Innovations with AWS Lambda (Mayank Jindal) https://youtu.be/yaXfmdasT9E 11 min.<br>
 25. Python&#x27;s Types: 5 Amazing Ways Python Type Hints Will Supercharge Your Code (Michael Kennedy) https://youtu.be/aKcolk8lGGk 43 min.<br>
 26. Design Patterns for Data Pipelines (Lisa Dusseault) https://youtu.be/opR44Tu9p1I 41 min.<br>

<hr>
  1. https://youtu.be/0-qKNTouuOY 42 min.<br>
  2. https://youtu.be/LceLUPdIzRs 36 min.<br>
  3. https://youtu.be/6u7osMnIQHg 30 min.<br>
  4. https://youtu.be/pHlptwP20MY 10 min.<br>
  5. https://youtu.be/h9uCUVjKeas 20 min.<br>
  6. https://youtu.be/N5Anbq8vYNk 21 min.<br>
  7. https://youtu.be/snKTqb10vWQ 38 min.<br>
  8. https://youtu.be/hXYFS2pOEH8 12 min.<br>
  9. https://youtu.be/0vxVUjUL_Nw 17 min.<br>
  10. https://youtu.be/5hbxUX4dwyk 29 min.<br>
  11. https://youtu.be/ViUEGvNDwrQ 31 min.<br>
  12. https://youtu.be/yCp6b_rHrLQ 28 min.<br>
  13. https://youtu.be/AJs_izrEBOA 28 min.<br>
  14. https://youtu.be/r6wabaVH7CE 29 min.<br>
  15. https://youtu.be/tI2y7pG6v84 24 min.<br>
  16. https://youtu.be/vqlHqqhTwzA 14 min.<br>
  17. https://youtu.be/IVgizc711OA 15 min.<br>
  18. https://youtu.be/oZMe1EgNvZg 29 min.<br>
  19. https://youtu.be/uQRmZbIyuzg 26 min.<br>
  20. https://youtu.be/TSI4rYKpwws 26 min.<br>
  21. https://youtu.be/HHR2YnWD0rw 14 min.<br>
  22. https://youtu.be/0d-v9yeTIeY 25 min.<br>
  23. https://youtu.be/o8vxlj8Vcqo 25 min.<br>
  24. https://youtu.be/yaXfmdasT9E 11 min.<br>
  25. https://youtu.be/aKcolk8lGGk 43 min.<br>
  26. https://youtu.be/opR44Tu9p1I 41 min.<br>




<hr>
 1, Pants: Cargo for Python, Pants_Cargo_for_Python.mp4, 42<br>
 2, Programming Your Computer With Python, Programming_Your_Computer_With_Python.mp4, 36<br>
 3, Ranking and Retrieval Techniques for Retrieval Augmented Generation with Haystack, Ranking_and_Retrieval_Techniques_for_Retrieval_Augmented_Generation_with_Haystack.mp4, 30<br>
 4, Data Science beasts (failures) and where to find them, Data_Science_beasts_failures_and_where_to_find_them.mp4, 10<br>
 5, Type safe data validation using Pydantic v2, Type_safe_data_validation_using_Pydantic_v2.mp4, 20<br>
 6, Craft Complex Mock Data, Craft_Complex_Mock_Data.mp4, 21<br>
 7, Embeddings: What they are and why they matter, Embeddings_What_they_are_and_why_they_matter.mp4, 38<br>
 8, Python deployment with Docker and Poetry, Python_deployment_with_Docker_and_Poetry.mp4, 12<br>
 9, Let&#x27;s talk about JWT, Lets_talk_about_JWT.mp4, 17<br>
 10, Infrastructure as a Product: Lessons in Platform Engineering, Infrastructure_as_a_Product_Lessons_in_Platform_Engineering.mp4, 29<br>
 11, FORKS? POOLS? ASYNC? Solving Wordle with Python’s concurrency tools, FORKS_POOLS_ASYNC_Solving_Wordle_with_Pythons_concurrency_tools.mp4, 31<br>
 12, Using pandas and pyspark to address challenges in processing and storing time series instrument data, Using_pandas_and_pyspark_to_address_challenges_in_processing_and_storing_time_series_instrument_data.mp4, 28<br>
 13, Elevating Python Development with Nix Package Manager, Elevating_Python_Development_with_Nix_Package_Manager.mp4, 28<br>
 14, Python in Hardware &amp; Embedded Systems: A Deep Dive, Python_in_Hardware_Embedded_Systems_A_Deep_Dive.mp4, 29<br>
 15, Contain Yourself, Contain_Yourself.mp4, 24<br>
 16, No More Nitpicks: effortless cleanup with fixers, formatters, and codemods, No_More_Nitpicks_effortless_cleanup_with_fixers_formatters_and_codemods.mp4, 14<br>
 17, Better Together: Unleashing the Synergy of Pandas, Polars, and Apache Arrow, Better_Together_Unleashing_the_Synergy_of_Pandas_Polars_and_Apache_Arrow.mp4, 15<br>
 18, Python, Planets, and Portals: Designing Web Apps for Modern Astronomers, Python_Planets_and_Portals_Designing_Web_Apps_for_Modern_Astronomers.mp4, 29<br>
 19, Scale Data Science by Pandas API on Spark, Scale_Data_Science_by_Pandas_API_on_Spark.mp4, 26<br>
 20, Beyond Conventional: Embracing Python &amp; LLMs for Quality Assurance, Beyond_Conventional_Embracing_Python_LLMs_for_Quality_Assurance.mp4, 26<br>
 21, Testing Strategies for Python, Testing_Strategies_for_Python.mp4, 14<br>
 22, Understanding LangChain Agents and Tools with Twilio (or with SMS), Understanding_LangChain_Agents_and_Tools_with_Twilio_or_with_SMS.mp4, 25<br>
 23, Shiny: Data-centric web applications in Python, Shiny_Datacentric_web_applications_in_Python.mp4, 25<br>
 24, Unleashing Python&#x27;s Power: Serverless Innovations with AWS Lambda, Unleashing_Pythons_Power_Serverless_Innovations_with_AWS_Lambda.mp4, 11<br>
 25, Python&#x27;s Types: 5 Amazing Ways Python Type Hints Will Supercharge Your Code, Pythons_Types_5_Amazing_Ways_Python_Type_Hints_Will_Supercharge_Your_Code.mp4, 43<br>
 26, Design Patterns for Data Pipelines, Design_Patterns_for_Data_Pipelines.mp4, 41<br>