Fix conflicting characters

Author: ELC

europython-2023/videos/fish-and-chips-and-apache-kafka-r-tibs.json

@@ -1,5 +1,5 @@
 {
-  "description": "[EuroPython 2023 \u2014 Terrace 2A on 2023-07-21]\n\rhttps://ep2023.europython.eu/session/fish-and-chips-and-apache-kafka\n\nApache Kafka\u00ae is the de facto standard in the data streaming world for sending messages from multiple producers to multiple consumers, in a fast, reliable and scalable manner. Come and learn the basic concepts and how to use it, by modelling a traditional British fish and chips shop!\n_________________________\n[ *CORRECTIONS FROM THE SPEAKER* ]: \nWhen talking about two of the slides in the video, I say *\"topic\"* when I should have said *\"partition\".* Below is the text as it should be - the highlighted words are what I should have said.\n\ud83d\udd37 At 7:14 -  slide  *Multiple partitions, consumer groups:* \n\ud83d\udd39Sometimes that's not what you want. Sometimes you want your consumers to share the reading, so here we've got two *partitions,*  one with 1, 2, 3 and one with b, c, d in it.\n\ud83d\udd39The producers [...] can choose which partition by hand, say I want *partition* one, two, three, or you can say here is a key, choose by the key which *partition* to go to.\n\ud83d\udd39The consumers at the top right are in the same consumer group, they said \"we want to share consuming the *topic\".* \n\ud83d\udd39Each consumer will get one or more *partitions,*  but they won't both see the same *partitions.*  So one of them is seeing 1, 2, 3 and the other is seeing b, c, d. The bottom consumer is not in a consumer group, it's entirely independent, and like the previous consumers it's just getting all the messages in order.\n\n\ud83d\udd37 At 14:43  -  slide *Three tills:* \n\ud83d\udd39So now we're going to add three producers and we'll add three *partitions,*  because then we can say each till will send to a separate *partition.*  The food preparer is still reading from all of them so it will get things interleaved nicely.\n_________________________\nThis work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/",
+  "description": "[EuroPython 2023 \u2014 Terrace 2A on 2023-07-21]\nhttps://ep2023.europython.eu/session/fish-and-chips-and-apache-kafka\n\nApache Kafka\u00ae is the de facto standard in the data streaming world for sending messages from multiple producers to multiple consumers, in a fast, reliable and scalable manner. Come and learn the basic concepts and how to use it, by modelling a traditional British fish and chips shop!\n_________________________\n[ *CORRECTIONS FROM THE SPEAKER* ]: \nWhen talking about two of the slides in the video, I say *\"topic\"* when I should have said *\"partition\".* Below is the text as it should be - the highlighted words are what I should have said.\n\ud83d\udd37 At 7:14 -  slide  *Multiple partitions, consumer groups:* \n\ud83d\udd39Sometimes that's not what you want. Sometimes you want your consumers to share the reading, so here we've got two *partitions,*  one with 1, 2, 3 and one with b, c, d in it.\n\ud83d\udd39The producers [...] can choose which partition by hand, say I want *partition* one, two, three, or you can say here is a key, choose by the key which *partition* to go to.\n\ud83d\udd39The consumers at the top right are in the same consumer group, they said \"we want to share consuming the *topic\".* \n\ud83d\udd39Each consumer will get one or more *partitions,*  but they won't both see the same *partitions.*  So one of them is seeing 1, 2, 3 and the other is seeing b, c, d. The bottom consumer is not in a consumer group, it's entirely independent, and like the previous consumers it's just getting all the messages in order.\n\n\ud83d\udd37 At 14:43  -  slide *Three tills:* \n\ud83d\udd39So now we're going to add three producers and we'll add three *partitions,*  because then we can say each till will send to a separate *partition.*  The food preparer is still reading from all of them so it will get things interleaved nicely.\n_________________________\nThis work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/",
   "duration": 1768,
   "language": "eng",
   "recorded": "2023-07-17",

europython-2023/videos/from-jupyter-notebooks-to-a-python-package-the-best-of-both-worlds-sin-seok-seo.json

@@ -1,5 +1,5 @@
 {
-  "description": "[EuroPython 2023 \u2014 Terrace 2A on 2023-07-19]\n\rhttps://ep2023.europython.eu/session/from-jupyter-notebooks-to-a-python-package-the-best-of-both-worlds\n\nA Jupyter notebook is quite handy for rapid REPL (Read-Eval-Print-Loop) style tasks such as exploratory data analysis and data science. However, we would feel \rdeficiencies in proper SW engineering supports at some point as the notebook grows to have larger and more complicated code. It is because the Jupyter notebook lacks several important features including code sharing, refactoring support, \rversion control and advanced editing. Fortunately, traditional full-fledged IDEs,\r such as _VS Code_ or _PyCharm,_ are available at hand and they support \rthese lacking features very well. \rThen, why don\u2019t we take advantage of the best of both worlds?\n\n\rIn this beginner-level hands-on talk, I will demonstrate how to \rtransform Jupyter notebook workflows to a proper Python package using _VS Code._ \rI will also introduce several basic but essential refactoring recommendations. By doing so, you can use the package for several notebooks \rand even share with your colleagues and friends.\n\nThis work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/",
+  "description": "[EuroPython 2023 \u2014 Terrace 2A on 2023-07-19]\nhttps://ep2023.europython.eu/session/from-jupyter-notebooks-to-a-python-package-the-best-of-both-worlds\n\nA Jupyter notebook is quite handy for rapid REPL (Read-Eval-Print-Loop) style tasks such as exploratory data analysis and data science. However, we would feel deficiencies in proper SW engineering supports at some point as the notebook grows to have larger and more complicated code. It is because the Jupyter notebook lacks several important features including code sharing, refactoring support, version control and advanced editing. Fortunately, traditional full-fledged IDEs, such as _VS Code_ or _PyCharm,_ are available at hand and they support these lacking features very well. Then, why don\u2019t we take advantage of the best of both worlds?\n\nIn this beginner-level hands-on talk, I will demonstrate how to transform Jupyter notebook workflows to a proper Python package using _VS Code._ I will also introduce several basic but essential refactoring recommendations. By doing so, you can use the package for several notebooks and even share with your colleagues and friends.\n\nThis work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License http://creativecommons.org/licenses/by-nc-sa/4.0/",
   "duration": 2334,
   "language": "eng",
   "recorded": "2023-07-17",