List of videos

Read the abstract ➤ https://www.conf42.com/Python_2024_Ivan_Popov_speed_accuracy_model_development Other sessions at this event ➤ https://www.conf42.com/python2024 Join Discord ➤ https://discord.gg/DnyHgrC7jC Support our mission ➤ https://www.conf42.com/support Chapters 0:00 intro 0:20 preamble 0:29 data scientist at about & render, london, uk 0:57 today's talk 1:20 the essence of balance: speed vs accuracy 1:33 factors impacting accuracy and speed 2:20 the business impact of speed and accuracy 3:11 real-world examples 4:24 balancing act: speed, accuracy, and cost 6:12 strategic importance of the balance 6:37 how to understand business objectives 7:20 scenarios for ml-models 8:30 optimisation strategies 8:40 training data quality and quantity 9:04 what is a good dataset? 9:18 what is a bad dataset? 9:50 data pre-processing 10:40 how to find inefficiencies in data pre-processing? 11:19 yappi 14:07 most common inefficiencies 16:23 feature selection 17:18 shap values for feature selection 20:03 model selection 21:05 xgboost 22:13 lightgbm 23:02 how to choose the best option 23:19 a quick recap 24:45 thank you for your time!

Read the abstract ➤ https://www.conf42.com/Python_2024_Ukanah_Dean_python_security_best_practices_protecting_common_vulnerabilities Other sessions at this event ➤ https://www.conf42.com/python2024 Join Discord ➤ https://discord.gg/DnyHgrC7jC Support our mission ➤ https://www.conf42.com/support Chapters 0:00 intro 0:20 preamble 0:27 about ukanah 0:40 peek into this talk 1:04 section 1: introduction to python security 4:33 section 2: common security threats in python 10:16 section 3: secure coding practices in python 19:24 section 3: authentication and authorization 24:38 section 4: encryption and hashing in python - demo 38:58 section 5: python security tools and libraries 42:34 section 6: emerging threats and future considerations 50:52 section 7: conclusion 51:23 peek into this talk 53:39 thanks!

Read the abstract ➤ https://www.conf42.com/Python_2024_Zhiya_Zang_sandbox_dynamic_rule_execution Other sessions at this event ➤ https://www.conf42.com/python2024 Join Discord ➤ https://discord.gg/DnyHgrC7jC Support our mission ➤ https://www.conf42.com/support Chapters 0:00 intro 0:20 preamble 0:53 agenda 1:50 what is it 3:04 why and why not 6:50 practices 14:40 thanks

Read the abstract ➤ https://www.conf42.com/Python_2024_Marco_Verleun_prove_safety_software Other sessions at this event ➤ https://www.conf42.com/python2024 Join Discord ➤ https://discord.gg/DnyHgrC7jC Support our mission ➤ https://www.conf42.com/support Chapters 0:00 intro 0:20 preamble 0:47 short agenda 1:57 for future use... 2:09 from code to production 2:52 a (random) app step by step: worker.py 3:36 how is this done in the food industry? 3:50 food safety 4:33 it probably depends 5:02 it is nice to know what's inside 5:42 why not do the same with our 6:20 ...boms are there to help 7:18 why use sboms? 7:39 did you see this? 8:05 was your app affected? 8:45 like food labels sboms tell you what's inside 8:50 example sbom snippet 10:21 more and more you can download them upfront 11:39 and analyze them before you install something 12:33 back to our app: worker.py 12:47 step 1: the code 13:10 shipping the app 13:53 building the container images 14:24 build result 15:21 sbom creation 16:13 source code analysis 16:33 our first image based on python:latest 17:29 can we do better: python:3.9.18-slim 18:01 let's try one more image: python:alpine 18:35 summary 18:48 storing sbom files 20:31 distributing sbom files 21:40 final words 22:54 interesting links

Read the abstract ➤ https://www.conf42.com/Python_2024_Karin_Wolok_Tim_Spann_nifi__kafka_risingwave_iceberg_llm Other sessions at this event ➤ https://www.conf42.com/python2024 Join Discord ➤ https://discord.gg/DnyHgrC7jC Support our mission ➤ https://www.conf42.com/support Chapters 0:00 intro 0:20 preamble 0:04 about karin 0:54 what is stream processing? 3:47 understanding stream processes 6:15 what is risingwave 8:40 data stream processes in risingwave risingwave use cases: 10:02 - streaming etl 10:27 - real-time analytics 12:55 - event-driven applications 13:21 - the architecture 14:12 using apache nifi, apache kafka, risingwave, and apache iceberg with stock data and llm 27:24 thank you

Read the abstract ➤ https://www.conf42.com/Python_2024_Dan_DAvella_writing_python_codemods_fun_profit Other sessions at this event ➤ https://www.conf42.com/python2024 Join Discord ➤ https://discord.gg/DnyHgrC7jC Support our mission ➤ https://www.conf42.com/support Chapters 0:00 intro 0:20 preamble 1:24 https://github.com/pixee/codemodder-python 1:55 there is a problem 3:42 security tools 6:03 we need to fix and harden codes 7:57 code + modification 10:19 codemodder philosophy 12:01 leverage open-source tools 12:52 process results from other tools 13:43 invoke open-source tools 14:54 codemods tell a story 15:53 how can i use it? 16:44 what does it do? 18:04 what can we fix? 18:32 replace unsafe pyyaml loader 19:29 use defusedxml for parsing xml 21:06 automatically close resources 22:05 parametrize sql queries 22:57 use generator expressions 24:09 codemodder architecture 26:27 codemod metadata 28:07 dependency management 30:11 let's write a codemod 30:57 codemod plugin template 38:41 make the easy things easy 39:59 make the hard things possible 41:47 looking ahead 44:16 we want your feedback! 44:50 pixeebot app 46:06 about pixee

Read the abstract ➤ https://www.conf42.com/Python_2024_Salman_Saeed_Khan_probabilistic_programming Other sessions at this event ➤ https://www.conf42.com/python2024 Join Discord ➤ https://discord.gg/DnyHgrC7jC Support our mission ➤ https://www.conf42.com/support Chapters 0:00 intro 0:20 preamble 0:49 motivation 2:45 bayesian vs. frequentist statistics 3:57 bayes theorem 4:46 bayesian vs non-bayesian inference 6:24 bayesian inference 7:19 markov chain monte carlo (mcmc) 8:01 probabilistic modelling 8:47 workflow of probabilistic programming 9:43 demo

Read the abstract ➤ https://www.conf42.com/Python_2025_Aby_M_Joseph_Jayalekshmi_K_S_graphql_microservices_fastapi Other sessions at this event ➤ https://www.conf42.com/python2025 Join Circle ➤ https://conf42.circle.so/checkout/subscribe Chapters 00:00 Introduction and Welcome 00:08 Overview of GraphQL and FastAPI 01:33 Understanding GraphQL 02:27 Challenges with REST APIs 04:56 How GraphQL Solves REST API Issues 07:12 GraphQL Operations: Queries, Mutations, and Subscriptions 10:06 GraphQL Schema Explained 12:03 GraphQL vs REST API: A Burger Analogy 13:51 GraphQL Python Ecosystem 15:08 Introduction to FastAPI 16:14 Core Components of FastAPI 17:40 Features of FastAPI 19:47 Integrating FastAPI with GraphQL 23:52 GraphQL Federation 25:59 Conclusion and Wrap-Up

Read the abstract ➤ https://www.conf42.com/Python_2025_Eti_Ijeoma_python_dunder_methods Other sessions at this event ➤ https://www.conf42.com/python2025 Join Circle ➤ https://conf42.circle.so/checkout/subscribe Chapters 00:00 Introduction to Python's Dunder Methods 00:25 Understanding Dunder Methods 01:15 Practical Examples of Dunder Methods 03:46 Implementing Custom Dunder Methods 05:26 Advanced Dunder Methods 14:40 Best Practices for Using Dunder Methods 17:45 Conclusion and Final Thoughts