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| 1 | +events = [ |
| 2 | + { |
| 3 | + "day": 7, |
| 4 | + "start_time": "09:00", |
| 5 | + "duration": 30, |
| 6 | + "title": "Welcoming Session", |
| 7 | + "room": "Auditorium", |
| 8 | + "speaker": "", |
| 9 | + "description": "Welcoming Session", |
| 10 | + }, |
| 11 | + { |
| 12 | + "day": 7, |
| 13 | + "start_time": "09:15", |
| 14 | + "duration": 60, |
| 15 | + "title": "Optimising for joy", |
| 16 | + "room": "Auditorium", |
| 17 | + "speaker": "Tom Forbes", |
| 18 | + "description": "The good feeling new developers get when they begin to program for the first time fades as we get more experience and learn more. Is it possible to recapture that feeling?", # noqa |
| 19 | + }, |
| 20 | + { |
| 21 | + "day": 7, |
| 22 | + "start_time": "10:15", |
| 23 | + "duration": 35, |
| 24 | + "title": "Amazon CodeWhisperer, ChatGPT, and GitHub Copilot: Choosing the Best Python AI Code Assistant ", |
| 25 | + "room": "Auditorium", |
| 26 | + "speaker": "Darya Petrashka", |
| 27 | + "description": "Discover the right helper for your Python coding needs. Explore security, code readability, cut-off limitations, creativity, ability to generate tests, and troubleshooting capabilities. Find survey results for programmers.", # noqa |
| 28 | + }, |
| 29 | + { |
| 30 | + "day": 7, |
| 31 | + "start_time": "11:20", |
| 32 | + "duration": 35, |
| 33 | + "title": "A simples serverless data pipeline", |
| 34 | + "room": "Auditorium", |
| 35 | + "speaker": "Riccardo Magliocchetti", |
| 36 | + "description": "Building and maintaining data pipelines when it’s not your full time job is a pain! So better keep things simple without the need to manage the system yourself. In this talk I’ll show a data pipeline architecture built leveraging some cloud offerings by AWS and Preset.", # noqa |
| 37 | + }, |
| 38 | + { |
| 39 | + "day": 7, |
| 40 | + "start_time": "11:55", |
| 41 | + "duration": 35, |
| 42 | + "title": "Building Dainty Dashboards in Plotly Dash for health data science.", |
| 43 | + "room": "Auditorium", |
| 44 | + "speaker": "Avneet Kaur", |
| 45 | + "description": "Data science projects are often characterized by visualizations which enhances the creative storytelling process and allow us to derive actionable insights from data. ", # noqa |
| 46 | + }, |
| 47 | + { |
| 48 | + "day": 7, |
| 49 | + "start_time": "12:30", |
| 50 | + "duration": 35, |
| 51 | + "title": "Tools to setup great python projects", |
| 52 | + "room": "Auditorium", |
| 53 | + "speaker": "Duarte Pompeu", |
| 54 | + "description": "In a professional python project, there are many steps one can take to improve its quality. In this talk, I will review some tools that have been useful to me:", # noqa |
| 55 | + }, |
| 56 | + { |
| 57 | + "day": 7, |
| 58 | + "start_time": "13:05", |
| 59 | + "duration": 25, |
| 60 | + "title": "Lunch break", |
| 61 | + "room": "Auditorium", |
| 62 | + "speaker": "", |
| 63 | + "description": "", |
| 64 | + }, |
| 65 | + { |
| 66 | + "day": 7, |
| 67 | + "start_time": "13:30", |
| 68 | + "duration": 35, |
| 69 | + "title": "Tools to setup great python projects", |
| 70 | + "room": "Auditorium", |
| 71 | + "speaker": "Duarte Pompeu", |
| 72 | + "description": "In a professional python project, there are many steps one can take to improve its quality. In this talk, I will review some tools that have been useful to me:", # noqa |
| 73 | + }, |
| 74 | + { |
| 75 | + "day": 9, |
| 76 | + "start_time": "09:00", |
| 77 | + "duration": 120, |
| 78 | + "title": "Beyond the basics", |
| 79 | + "room": "1", |
| 80 | + "speaker": "Stefanie Molin", |
| 81 | + "description": "In a professional python project, there are many steps one can take to improve its quality. In this talk, I will review some tools that have been useful to me", # noqa |
| 82 | + }, |
| 83 | + { |
| 84 | + "day": 9, |
| 85 | + "start_time": "09:00", |
| 86 | + "duration": 120, |
| 87 | + "title": "Django and ReportLab: Create PDF", |
| 88 | + "room": "2", |
| 89 | + "speaker": "Maxin Danilov", |
| 90 | + "description": "In a professional python project, there are many steps one can take to improve its quality. In this talk, I will review some tools that have been useful to me", # noqa |
| 91 | + }, |
| 92 | + { |
| 93 | + "day": 9, |
| 94 | + "start_time": "11:30", |
| 95 | + "duration": 120, |
| 96 | + "title": "MicroPython and the time series", |
| 97 | + "room": "1", |
| 98 | + "speaker": "Olaniyan Adeweale, Sulaiman Adisa", |
| 99 | + "description": "In a professional python project, there are many steps one can take to improve its quality. In this talk, I will review some tools that have been useful to me", # noqa |
| 100 | + }, |
| 101 | + { |
| 102 | + "day": 9, |
| 103 | + "start_time": "11:30", |
| 104 | + "duration": 120, |
| 105 | + "title": "Django and ReportLab: Create PDF", |
| 106 | + "room": "2", |
| 107 | + "speaker": "Maxin Danilov", |
| 108 | + "description": "In a professional python project, there are many steps one can take to improve its quality. In this talk, I will review some tools that have been useful to me", # noqa |
| 109 | + }, |
| 110 | + { |
| 111 | + "day": 9, |
| 112 | + "start_time": "14:30", |
| 113 | + "duration": 120, |
| 114 | + "title": "MicroPython and the time series", |
| 115 | + "room": "1", |
| 116 | + "speaker": "Olaniyan Adeweale, Sulaiman Adisa", |
| 117 | + "description": "In a professional python project, there are many steps one can take to improve its quality. In this talk, I will review some tools that have been useful to me", # noqa |
| 118 | + }, |
| 119 | + { |
| 120 | + "day": 9, |
| 121 | + "start_time": "14:30", |
| 122 | + "duration": 120, |
| 123 | + "title": "Django and ReportLab: Create PDF", |
| 124 | + "room": "2", |
| 125 | + "speaker": "Maxin Danilov", |
| 126 | + "description": "In a professional python project, there are many steps one can take to improve its quality. In this talk, I will review some tools that have been useful to me", # noqa |
| 127 | + }, |
| 128 | +] |
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