Conf42 Python 2024

Support our mission ➤ https://www.conf42.com/support Schedule, Lineup & RSVP ➤ https://www.conf42.com/python2024 Join Discord ➤ https://discord.gg/DnyHgrC7jC Upcoming CFPs ➤ https://www.papercall.io/events?cfps-scope=&keywords=conf42 0:00 intro ai 0:39 Sharon Yelenik - https://www.conf42.com/Python_2024_Sharon_Yelenik_personalizing_images_aipowered_features 1:25 Joshua Arvin Lat & Sophie Soliven - https://www.conf42.com/Python_2024_Joshua_Arvin_Lat_Sophie_Soliven_power_augmented_generation_ai 2:20 Deepak Karunanidhi - https://www.conf42.com/Python_2024_Deepak_Karunanidhi_neural_language_processingi_healthcare 3:00 Duncan Blythe - https://www.conf42.com/Python_2024_Duncan_Blythe_superduperdb_database 3:48 Jayram Palamadai - https://www.conf42.com/Python_2024_Jayram_Palamadai_visual_generative_AI apache 4:18 Anais Dotis-Georgiou - https://www.conf42.com/Python_2024_Anais_DotisGeorgiou_apache_flight_influxdb 5:12 Tim Spann - https://www.conf42.com/Python_2024_Tim_Spann_apache_nifi_2_processors cloud 6:03 Gustavo Amigo - https://www.conf42.com/Python_2024_Gustavo_Amigo_cloud_infrastructure_optimization 6:45 Ivan Chiou - https://www.conf42.com/Python_2024_Ivan_Chiou_virtualphysical_ros_python_threejs 7:27 Sohan Maheshwar - https://www.conf42.com/Python_2024_Sohan_Maheshwar_serverless_webassembly_app_spin 8:03 Tomas Neubauer - https://www.conf42.com/Python_2024_Tomas_Neubauer_dataframes_process_streaming_data data 9:01 Tun Shwe - https://www.conf42.com/Python_2024_Tun_Shwe_sketching_algorithms_big_data 9:35 Santosh Nikhil Kumar - https://www.conf42.com/Python_2024_Santosh_Nikhil_Kumar_api_design_scalable_distributed_systems 10:17 Tom Levy - https://www.conf42.com/Python_2024_Tom_Levy_data_refinement_sql_csv deep dive 10:44 Hazel Andrea Saenz Giron - https://www.conf42.com/Python_2024_Hazel_Andrea_Saenz_Giron_resilient_applications_serverless 11:06 Chaur Wu - https://www.conf42.com/Python_2024_Chaur_Wu_functor_zoo 11:26 Dmitrii Ivashchenko - https://www.conf42.com/Python_2024_Dmitrii_Ivashchenko_latest_features_python_312 11:47 Alex Sharypov - https://www.conf42.com/Python_2024_Alex_Sharypov_improve_application_code_quality 12:23 Andre Santos - https://www.conf42.com/Python_2024_Andre_Santos_work_smarter_python_repetitive_tasks 12:49 Petr Emelianov - https://www.conf42.com/Python_2024_Petr_Emelianov_nextgeneration_multiparty_computation lessons learned 13:22 Tamara Janina Fingerlin - https://www.conf42.com/Python_2024_Tamara_Janina_Fingerlin_frameworks_apache_airflow_pipelines 14:10 Adam Furmanek - https://www.conf42.com/Python_2024_Adam_Furmanek_lessons_learned_maintaining_sdk_in_python 14:50 Pawel Zajaczkowski - https://www.conf42.com/Python_2024_Pawel_Zajaczkowski_s_bb_x_y_z_a_generations_tech models 15:16 Darya Petrashka - https://www.conf42.com/Python_2024_Darya_Petrashka_unlock_power_llm_build_huggingface_agent 15:55 Boluwatife Ben-Adeola - https://www.conf42.com/Python_2024_Boluwatife_BenAdeola_python_cutting_edge_language_model_research 16:15 Ivan Popov - https://www.conf42.com/Python_2024_Ivan_Popov_speed_accuracy_model_development security 16:49 Ukanah Dean - https://www.conf42.com/Python_2024_Ukanah_Dean_python_security_best_practices_protecting_common_vulnerabilities 17:38 Zhiya Zang - https://www.conf42.com/Python_2024_Zhiya_Zang_sandbox_dynamic_rule_execution 18:12 Marco Verleun - https://www.conf42.com/Python_2024_Marco_Verleun_prove_safety_software tools 18:47 Karin Wolok & Tim Spann - https://www.conf42.com/Python_2024_Karin_Wolok_Tim_Spann_nifi__kafka_risingwave_iceberg_llm 19:17 Dan D'Avella - https://www.conf42.com/Python_2024_Dan_DAvella_writing_python_codemods_fun_profit 20:08 Salman Saeed Khan - https://www.conf42.com/Python_2024_Salman_Saeed_Khan_probabilistic_programming 20:44 thanks!

Read the abstract ➤ https://www.conf42.com/Python_2024_Sharon_Yelenik_personalizing_images_aipowered_features 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 0:30 how do you handle your images? 1:06 what if you have too many images to handle manually? 1:57 ai can help you manage your images 5:31 demo 23:32 get the code on github, learn more, be in touch

Read the abstract ➤ https://www.conf42.com/Python_2024_Joshua_Arvin_Lat_Sophie_Soliven_power_augmented_generation_ai 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 0:31 about speakers 1:21 can we build a generative ai-powered application in 24 hours?

Read the abstract ➤ https://www.conf42.com/Python_2024_Deepak_Karunanidhi_neural_language_processingi_healthcare 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 1:05 anomaly detection 2:27 the challenges we set out to solve 4:51 anomaly detection at a glance 5:47 ml algorithm development process 7:20 why data annotation? 8:24 data annotation... 10:04 a comprehensive ai impl journey 12:19 anomaly identification framework 14:29 machine learning model framework - continuous training for optimized performance 16:33 llm + guardrails 17:18 challenges in bert models 19:35 generative ai and prompt engineering 19:35 gen ai - llm's approach 19:35 thank you

Read the abstract ➤ https://www.conf42.com/Python_2024_Duncan_Blythe_superduperdb_database 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 0:57 data and ai live in separate silos 1:24 bringing machine learning to production is very complicated 1:59 ai needs and vector search need to be integrated directly with the data source to remove overhead 2:30 superduperdb brings ai to the database 2:51 building, deploying and managing ai applications without moving data 3:17 superduperdb: the centerpiece of the modern data-centric ai stack 4:13 all-in-one platform for all data-centric enterprise ai use-cases 4:43 python-first: build for developers with the ecosystem in mind 5:05 open-source: free apache 2.0 software 5:24 how superduperdb works code to: 8:23 - connect 8:43 - code to query 9:25 - code to create custom datatype 10:09 - code to create inline model 10:09 - code to map model to superduperdb 11:52 - create custom superduperdb model 12:36 - apply model 13:04 - apply model to data updates in real time 13:43 - create vector-index 14:07 - create superduperdb stack 14:28 - parametrize superduperdb stack 15:09 - share superduperdb app 15:25 setup even the most complex ai workflows effortlessly 21:56 learn more

Read the abstract ➤ https://www.conf42.com/Python_2024_Jayram_Palamadai_visual_generative_AI 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 0:26 table of contents 0:52 introduction 1:47 diffusion models 5:05 current research 9:59 future implications 13:06 current limitations 18:06 navigating ai growth 24:28 summary 25:03 thanks!

Read the abstract ➤ https://www.conf42.com/Python_2024_Anais_DotisGeorgiou_apache_flight_influxdb 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 0:35 about anais 1:26 agenda 2:04 introduction to influxdb and time series data 6:17 influxdb 3.0 6:47 some of our customers 7:50 ingest benchmark 8:35 commitment to open data architecture with the fdap stack 9:06 data storage 11:34 advantages of columnar data storage (sidebar) 13:58 leveraging the arrow flight client influxdb v3 python client library 15:23 arrow flight sql client 16:35 influxdb v3 python client library 17:36 projects that leverage the arrow flight 17:51 grafana flow 18:24 try it yourself - grafana quick starts 19:33 mage & influxdb - anomaly detection 20:07 quix + influxdb 22:10 solution architecture 23:20 join the influxdb community

Read the abstract ➤ https://www.conf42.com/Python_2024_Tim_Spann_apache_nifi_2_processors 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 0:34 about tim 0:52 flank stack weekly by tim spann 1:04 future of data - nyc + nj + philly + virtual 1:26 generative ai 3:05 rapid innovation in the llm space 3:58 cloudera generative ai stack 5:39 apache nifi and real-time genai 7:18 readyflow gallery 7:41 cloudera + llms 8:28 nifi 2.0.0 features 9:04 python processors 12:00 extract company names 13:47 get compound gtfs data 14:50 extract text from web vtt 15:37 watsonx sdk to foundation 16:11 system / process monitoring 16:58 generate synthetic records w/ faker 17:41 download a wiki page as html or wikiformat (text) 18:30 get gtfs data 19:09 other python processors 21:29 demo 28:35 thank you

Read the abstract ➤ https://www.conf42.com/Python_2024_Gustavo_Amigo_cloud_infrastructure_optimization 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 0:37 intro 1:09 agenda 1:53 scaling is hard 3:24 problem 7:04 context 9:31 approach 10:34 load test one host 11:05 retrieve data from aws to pandas 12:59 analyse one host performance 13:14 we can do better 14:28 another thing - latency 17:03 approaches 18:45 create a scaling simulator 20:12 create a traffic shape generator 20:52 and run a first local experiment 22:40 what does it mean? 22:59 first attempt 24:13 find the best parameters 25:08 and the winner is 26:29 which actually looks better 26:53 testing new parameters in production 28:42 simulation versus real life 31:19 conclusion 31:41 code 33:22 about gustavo

Read the abstract ➤ https://www.conf42.com/Python_2024_Ivan_Chiou_virtualphysical_ros_python_threejs 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 1:02 today's agenda 2:36 speaker introduction 3:43 tools & skills 5:40 architecture 6:29 demo 8:08 what is ros and three.js 11:43 figma 16:13 three.js 27:16 webrtc 32:42 ros bridge 35:13 backend - python 37:51 backend - c# 38:27 devops 39:28 conclusion

Read the abstract ➤ https://www.conf42.com/Python_2024_Sohan_Maheshwar_serverless_webassembly_app_spin 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 0:50 the next wave of cloud compute will be powered by webassembly 1:37 what is webassembly? 2:07 a few things to know about webassembly 2:32 wasm is another bytecode format 3:49 a few things to know about webassembly 5:55 compile and run 6:43 wasi: a new kind of system interface 7:46 compilation and language support 8:27 rust has a great wasm support 8:52 interpreted languages are a little more tricky 9:11 you need to compile the interpreter to wasm 10:24 getting started with wasm 10:32 introducing spin 11:51 demo 1 17:15 4 things making webassembly great 19:19 how this will change cloud computing 20:46 no more clunky containers 22:30 fix serverless 24:32 demo 2 27:43 component model 28:33 wasm module 29:06 composing applications 29:35 componentize-py 30:27 thank you!

Read the abstract ➤ https://www.conf42.com/Python_2024_Tomas_Neubauer_dataframes_process_streaming_data 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 0:30 hello, nice to meet you! 0:41 racing background 2:08 agenda 2:31 why strean processing? 4:19 stream processing architecture 5:12 kafka producer and consumer apis 6:07 stream processing frameworks 9:15 stream processing library example 9:35 debugging 9:54 jar files... 10:11 udfs are nasty 10:26 our approach to stream processing 11:10 goals 11:33 is there a third way? 12:08 quix streams - sdf 12:45 goal 13:16 demo 20:09 try quix

Read the abstract ➤ https://www.conf42.com/Python_2024_Tun_Shwe_sketching_algorithms_big_data 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 0:30 hello 1:12 quix 1:52 quix streams 2:06 quix cloud 2:44 what is a sketch? 3:20 approximate answers 3:42 sketch characteristics 4:24 sketch components 5:37 why exact == slow 5:40 distributed processing 6:17 unique word count 7:19 massively parallel processing (mpp) 7:31 shuffling is slow 8:00 latency numbers every programmer should know 8:28 why sketches == fast 9:08 sketch design 9:51 sublinear data structure growth 10:21 mergability 10:30 non-additive challenges are everywhere 11:03 unique counts are non-additive 11:29 non-additive challenges solved 12:40 types of sketches 13:57 count min sketch 19:10 open source sketches 19:24 apache datasketches (java, c++, python) 22:26 datasketch extensions 23:14 thank you

Read the abstract ➤ https://www.conf42.com/Python_2024_Santosh_Nikhil_Kumar_api_design_scalable_distributed_systems 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 2:20 rest for http and thrift for rpc 15:24 design asynchronous api calls with callback 27:34 design rate limiting your apis 31:32 design idempotency for apis

Read the abstract ➤ [abstract link] Other sessions at this event ➤ https://www.conf42.com/python2024 Join Discord ➤ https://discord.gg/DnyHgrC7jC Support our mission ➤ https://www.conf42.com/support Reach out to Tom ➤ tomlevy02@gmail.com Chapters 0:00 intro 0:20 preamble 0:32 agenda 0:54 why polars? 3:09 introduction to sql content 5:05 utilize lazyframes for big datasets 10:16 common table expressions (ctes) 13:47 thank you!

Read the abstract ➤ https://www.conf42.com/Python_2024_Hazel_Andrea_Saenz_Giron_resilient_applications_serverless 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 0:45 this is the story about how i learned to design resilient applications as a rock star 3:44 hexagonal architecture 5:59 serverless architecture 11:42 the perfect mix 14:52 with great power comes great responsibility 17:19 resilient architecture 19:41 dive into the code - demo 25:02 do it yourself 26:06 thank you!

Read the abstract ➤ https://www.conf42.com/Python_2024_Chaur_Wu_functor_zoo 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 0:31 about this talk 1:06 about me 1:21 agenda 1:32 a function 1:58 another function 2:16 category of types (t) 3:01 list of numbers 3:27 clist of numbers 4:01 clist is a functor 4:49 io side effects 6:06 io functor 6:58 partial function 7:37 not very composable 8:15 option for better composability 9:01 option is a functor 9:18 composing functors 10:26 category od small categories 10:44 example of clist . option 11:31 covariant functor in general 12:07 contravariant functor 12:43 predicate is a contravariant functor 13:24 closed category 15:58 applicative functor is lax closed functor 16:22 example of applicative functor 17:29 bifunctor 18:47 example of bifunctor 19:38 profunctor 21:05 forget 21:16 star and costar 21:44 example of star profunctor 22:57 summary

Read the abstract ➤ https://www.conf42.com/Python_2024_Dmitrii_Ivashchenko_latest_features_python_312 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 the latest features of python 3.12 0:39 typing improvements 1:21 generics with new syntax 1:52 typedict 2:37 override decorator 3:10 advanced type parameters 3:58 type aliases 4:28 lazy evaluation 5:03 syntax improvements 5:45 reusing quotes within f-strings 6:14 arbitraty nesting of f-strings 6:33 multi-line expressions and comments 7:02 backlashes and unicode characters 7:21 improved error messaging for f-strings 7:48 itertools.batched 8:13 performance 8:42 asyncio performance enhancements 9:16 boost in inspect and typing modules 9:52 unique per interpreter gil 10:26 comprehension inlining 11:12 immortal objects 11:50 buffer protocol 12:26 other enhancements 12:50 debugging 13:17 improved nameerror suggestions 13:42 syntax and importerror enhancements 14:07 low impact monitoring 14:48 resources & links

Read the abstract ➤ https://www.conf42.com/Python_2024_Alex_Sharypov_improve_application_code_quality 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 lightning talk

Read the abstract ➤ https://www.conf42.com/Python_2024_Andre_Santos_work_smarter_python_repetitive_tasks 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 2:28 why python is a popular choice for rpa? 2:49 benefits of using rpa in daily work 3:58 how rpa automates repetitive tasks 4:28 example of rpa application in various industries 7:18 libraries for rpa development in python 7:49 demo 12:37 conclusion and future trends in rpa with python

Read the abstract ➤ https://www.conf42.com/Python_2024_Petr_Emelianov_nextgeneration_multiparty_computation 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 security and privacy 1:52 examples 5:42 mpc in a nutshell 6:38 secret sharing 7:45 addition/substraction 9:58 multiplication 14:24 linear regression 15:02 real (almost) case 16:34 drawbacks 18:12 closing thoughts 18:22 security considerations 20:21 crypten 20:51 conclusions 21:35 thank you!

Read the abstract ➤ https://www.conf42.com/Python_2024_Tamara_Janina_Fingerlin_frameworks_apache_airflow_pipelines 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 0:31 agenda 1:07 what is airflow? who is astronomer? 9:33 why test data pipelines? 10:53 local development and testing 13:33 astro cli and airflow cli testing features 16:23 dag.test() 17:45 ci/cd and testing 18:08 from dev to staging 19:16 dag validation testing 21:26 unit tests with airflow 22:44 integration tests with airflow 24:06 the cf in ci/cd - our code on the way to the cloud 25:38 code getting promoted to prod 26:26 demo 45:49 take home message

Read the abstract ➤ https://www.conf42.com/Python_2024_Adam_Furmanek_lessons_learned_maintaining_sdk_in_python 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 what do we do? 9:35 how it works 13:48 three different approaches 15:08 sdk per tech stack 17:13 first approach 22:09 reading from the database 24:39 second approach 29:00 moving the ownership 33:40 third approach 37:33 what we learned 38:01 uniform functionality 43:10 json vs grpc 45:03 proprietary vs well-known protocol 46:40 versions management 48:16 rigorous testing 50:51 diversity 53:07 q&a

Read the abstract ➤ https://www.conf42.com/Python_2024_Pawel_Zajaczkowski_s_bb_x_y_z_a_generations_tech 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 0:43 agenda 1:30 about pawel 1:46 act 1: generations, myths, diffs, theories 2:02 generations / cohorts 5:26 general population 6:19 tech examples 7:41 myths or facts? 8:21 generation gap 8:49 conflict 9:12 generation narcissism 9:39 the sliding 2+2 10:39 cohort vs aging 12:32 differences strenght 12:32 act 2: s, bb, x, y, z, a 14:12 silent generation 16:05 baby boomers 18:59 generation x 23:25 millenials 28:33 generation z 35:11 generation alpha 38:14 what do we want 39:59 questions?

Read the abstract ➤ https://www.conf42.com/Python_2024_Darya_Petrashka_unlock_power_llm_build_huggingface_agent Other sessions at this event ➤ https://www.conf42.com/python2024 Join Discord ➤ https://discord.gg/DnyHgrC7jC Support our mission ➤ https://www.conf42.com/support Code and links ➤ https://github.com/dashapetr/hf_agents Chapters 0:00 intro 0:20 preamble 1:01 agenda 1:35 what are agents 3:35 what are tools 4:46 agents and tools 6:17 why should we care 7:31 hands-on: setup and initialize the agent 14:57 what other predefined tools exist 19:20 custom tool creation 25:25 conclusion 26:48 further ideas 27:41 code and links

Read the abstract ➤ https://www.conf42.com/Python_2024_Boluwatife_BenAdeola_python_cutting_edge_language_model_research 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 0:40 intro to mechanistic interpretability 2:06 mech interp 2:57 mech interp toolkit: causal interventions 5:10 example mech interp research 16:59 interpretability libraries and packages 17:44 nnsight architecture 20:42 example intervention 23:30 anatomy of an intervention 27:43 model internal i/o are nodes on the intervention graph 28:33 information flow 29:11 average-out information vectors 31:06 getting the average activation vector 34:45 adding the average to one-shot activation vector 39:15 resources

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