{"id":69949,"date":"2026-09-17T13:59:33","date_gmt":"2026-09-17T11:59:33","guid":{"rendered":"https:\/\/www.inovex.de\/?post_type=events&#038;p=69949"},"modified":"2026-09-18T11:08:18","modified_gmt":"2026-09-18T09:08:18","slug":"swiss-python-summit-2026","status":"publish","type":"events","link":"https:\/\/www.inovex.de\/de\/news-events\/events\/swiss-python-summit-2026\/","title":{"rendered":"Swiss Python Summit 2026"},"content":{"rendered":"<p>Der Swiss Python Summit ist eine zweit\u00e4gige Konferenz rund um die Programmiersprache Python. Neben einem allgemeinen Python-Tag zur Vielfalt der Anwendungsm\u00f6glichkeiten bietet das Programm einen eigenen Data Science Day. Das Event l\u00e4dt zum Vernetzen mit der Community, zum Erfahrungsaustausch und zum Entdecken aktueller Trends ein.<\/p>\n<p>Wir freuen uns sehr, dass unsere Kollegen <span class=\"text-neutral-500\">Dominik Traxl mit seinem Vortrag <\/span><a href=\"https:\/\/www.python-summit.ch\/program\/\"><strong>No more model training? TabPFN v3 vs. tuned trees<\/strong><\/a>, <span class=\"text-neutral-500\">Jonas B\u00f6er mit seinem Vortrag <strong><a href=\"https:\/\/www.python-summit.ch\/program\/\">Pulumi: Making Infrastructure as Code fun again with Python<\/a>\u00a0<\/strong>und Florian Wilhelm mit seinem Vortrag\u00a0<\/span><strong><a href=\"https:\/\/www.python-summit.ch\/program\/\">Sentinel Values in Python: Why None Is Not Enough<\/a>\u00a0<\/strong>vertreten sein werden.<\/p>\n<p><strong>Abstract<\/strong> von <span class=\"text-neutral-500\">Dominik Traxls Vortrag <\/span><strong>No more model training? TabPFN v3 vs. tuned trees<\/strong>:<\/p>\n<p>What if you never had to train or tune a model again? That is the pitch behind<br \/>\ntabular foundation models: state-of-the-art predictions with no training, no<br \/>\nhyperparameter search, no feature engineering. Just call .fit() and .predict().<br \/>\nThe headliner, TabPFN, whose earlier version was published in Nature, now adds<br \/>\nclaims aimed straight at the gradient-boosted trees most of us reach for by<br \/>\ndefault. TabPFN v3 promises to ingest raw text natively, scale toward a million<br \/>\nrows, support multi-class classification natively and offer a<br \/>\n&#8222;thinking mode&#8220; for extra quality. Too good to be true? I put it on trial.<\/p>\n<p>This talk walks through a systematic, reproducible Python benchmark that puts<br \/>\nTabPFN, exactly as it ships, up against a best-effort, Optuna-tuned pipeline of<br \/>\nXGBoost, LightGBM, and CatBoost on the messy public Steam Dataset 2025:<br \/>\nnumerics, booleans, categoricals, date-times, free-text, embeddings, skewed<br \/>\ndistributions, NaNs. The case spans three tasks: binary sentiment classification,<br \/>\nmulti-class publisher prediction, and Metacritic-score regression.<\/p>\n<p>We stress-test each vendor claim one at a time: raw text versus sentence<br \/>\nembeddings versus no text, out-of-the-box versus cleaned data, default versus<br \/>\nthinking mode, small samples up to large, few to many classes.<\/p>\n<p>But the real takeaway is the method: how to benchmark a hyped claim fairly, why<br \/>\nthe metric you pick can quietly decide the winner, and the data-leakage traps you<br \/>\nmust defuse before you trust a single result.<\/p>\n<p>The honest answer to &#8222;Too good to be true?&#8220; is: &#8222;it depends&#8220;. And knowing what<br \/>\nit depends on is the point. You&#8217;ll leave with a feel for when a tabular<br \/>\nfoundation model earns its keep, when a tuned tree still wins, and how to put<br \/>\nthe next &#8222;no training required&#8220; promise on trial yourself.<\/p>\n<p><strong>Abstract<\/strong> von J<span class=\"text-neutral-500\">onas B\u00f6ers Vortrag <strong>Pulumi: Making Infrastructure as Code fun again with Python<\/strong>:<\/span><\/p>\n<p>We don&#8217;t need to use Python only for developing applications and pipelines, we can also use it to maintain our infrastructure. Pulumi allows us to describe our infrastructure as a Python program. As this gives us access to Python&#8217;s flexibility, readability, power, and joy, it has quickly become my favourite way to manage infrastructure, no matter if for a small team&#8217;s ML application or for a multinational company&#8217;s analytics platform. Let me share this joy with you!<\/p>\n<p>In this talk I will show you how Pulumi works and what it does better than other IaC tools: Among others, I will talk about custom resources and resource grouping, state versioning and understanding your infrastructure deployment as a program to be run.<\/p>\n<p>Caution: This talk may lead to strong feelings of &#8222;why haven&#8217;t we always done it like this?&#8220;<\/p>\n<p><strong>Abstract<\/strong> <span class=\"text-neutral-500\">Florian Wilhelms Vortrag <\/span><strong>Sentinel Values in Python: Why None Is Not Enough<\/strong>:<\/p>\n<p>Every Python developer has used <code>None<\/code> as a default but what happens when <code>None<\/code> is also a valid value? This talk explores sentinel values as a first-class concept in Python. We&#8217;ll uncover why <code>None<\/code> is semantically overloaded, how built-in sentinels like <code>NotImplemented<\/code> and <code>...<\/code> (Ellipsis) quietly power Python&#8217;s object model, and what happens when you try to create your own. The central challenge: Python&#8217;s type system has no good answer for sentinel values. We&#8217;ll walk through why <code>Optional<\/code>, <code>Literal<\/code>, and custom classes all fall short, look at real-world workarounds including Pydantic&#8217;s experimental MISSING, and discuss what PEP 661&#8217;s deferral means for your code today. You&#8217;ll leave with a clear mental model and practical guidance for handling absence in typed Python.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Wir freuen uns sehr, dass unsere Kollegen Dominik Traxl mit seinem Vortrag \u201eNo more model training? TabPFN v3 vs. tuned trees\u201c, Jonas B\u00f6er mit seinem Vortrag \u201ePulumi: Making Infrastructure as Code fun again with Python\u201c\u00a0und Florian Wilhelm mit seinem Vortrag\u00a0\u201eSentinel Values in Python: Why None Is Not Enough\u201c\u00a0vertreten sein werden.<\/p>\n","protected":false},"featured_media":69956,"parent":0,"template":"","events_types":[85],"service":[431],"class_list":["post-69949","events","type-events","status-publish","has-post-thumbnail","hentry","events_types-konferenz","service-data-science"],"acf":{"start_date":"20261022","finish_date":"20261023","time":null,"finish_time":null,"location":"Rapperswil, Schweiz","organizer":"Swiss Python Summit Association","file":null,"hubspot_signups":false,"hubspot_signups_text":"","add_speakers":false,"speakers_headline":"Speaker:innen","speakers":null,"contact":null,"contact_heading":"","contact_text":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Swiss Python Summit 2026 - 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