Name: PyData Helsinki Picnic
Start: 2025-06-25T14:00:00.000Z
Location: Kaivopuisto

FastAPI in 2025: Building Lightning-Fast Python APIs with Automatic Documentation and Type Safety

Abstract: FastAPI has emerged as the go-to framework for high-performance Python API development, processing over 3,000 requests per second while maintaining developer productivity. This talk explores FastAPI's game-changing features including automatic OpenAPI documentation generation, built-in data validation through Pydantic, and native async/await support that rivals Node.js and Go performance.
Key topics include FastAPI's modern Python type hint integration, automatic interactive documentation (Swagger UI/ReDoc), advanced security features, and testing strategies.

PyData T&T

T. Dyer

kris manohar

Zachary Subran

37th Meet up: FastAPI in 2025 Building Lightning-Fast Python APIs

Online event

Welcome to the PyData Berlin June meetup!

We would like to welcome you all starting from 18:00. There will be food and drinks. The talks begin around 18.30 and the doors will close at 18:45. **Make sure to arrive on time!**

Please provide your first and last name for the registration because this is required for the venue's entry policy. If you cannot attend, please cancel your spot so others are able to join as the space is limited.

**Host**:
**GetYourGuide** is excited to welcome you to this month's version of PyData.
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The Lineup for the evening

**Talk 1: AI-Powered Carbon Emission Analytics from Public Transit Data - BVG Case Study**
**Abstract**: Imagine planning your route on Google Maps and alongside travel time, walking distance, and number of transfers, you also see the carbon footprint of each route. This project brings that idea to life by integrating real-time BVG transit data with an AI-powered emissions engine. Using segment-level routing information from Berlin’s public transport API, the system estimates CO₂ emissions for each journey based on the transport mode and distance.
The dashboard calculates, visualizes, and even forecasts emissions over time using machine learning techniques like Prophet, while also detecting emission spikes and anomalies. It goes a step further by integrating a language model that explains emissions in plain language and recommends greener alternatives. The goal: to make sustainable commuting as easy and intuitive as choosing the fastest or cheapest route.

**Speaker: Sirisha Padmasekhar**
**Bio**: Sirisha is a data scientist on the growth team at a queer social app, where she dives into data to uncover patterns in user behavior, retention, and content impact. She's especially drawn to data passion projects, anything that helps people see things a little more clearly through numbers and storytelling. Outside of work, she hosts a podcast where she interviews people from different walks of life, creating space for warm, honest conversations. For Sirisha, data and stories go hand in hand, both start with curiosity.

**Talk 2:** **Lessons in Data Visualization from My Academic Journey**
**Abstract**: In this short talk, I’ll share practical opinions and approaches to data visualisation developed over years of storytelling to biologists in academia. Expect simple tweaks and tips to make your visuals more impactful and clear—without extra overhead—along with best practices from scientific publishing that I believe can benefit industry. These are personal takeaways that I hope will be useful in your day-to-day as well.

**Speaker: Saulius Lukauskas**
**Bio**: Saulius Lukauskas is a data scientist with a Ph.D. in machine learning and an academic background in computational biology. He is currently a Data Science Manager at GetYourGuide, where he develops AI solutions to help suppliers deliver outstanding travel experiences.

**Lightning talks**
There will be slots for 2-3 Lightning Talks (3-5 Minutes for each) between the two main talks.
Kindly let us know if you would like to present something :)

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PyData Berlin

Carolina Shimabukuro

Daniel Ringler

Francesco Bruzzesi

Theodore Meynard

Prajwal Shastrimath

Dimm Kiselov

Juan Pizarro

poojachoudhary2404

Maria

Foan

Hiroki

Bojarovski Stefan

Rudolf Schreiner

Samantha Lisik

Yuka

Partha Mandal

Bhavya

sirisha padmasekhar

Shreyas Wade

An Bo

PyData Berlin 2025 June Meetup

Ampere Garden

Ве покануваме на летниот PyData собир во среда на **18.6.2025 година** во [Base42](https://42.mk/) во 18 часот. Предавање на тема **„Quantum Realtime Algorithm**
**for Wildfire Containment“** ќе одржи тимот кој освои **второ место** на овогодинешниот **Blaise Pascal Quantum Challenge 2025** - **Петар Крстевски**, **Никола Гилев** и **Алек Пачемски**.

На овој настан ќе имате можност да се запознаете со револуционерни пристапи за справување со шумски пожари – една од најголемите глобални еколошки закани. Ќе се започне со вовед во предизвиците од шумските пожари и нивното влијание врз екосистемите и човечките животи, а потоа ќе се продолжи со квантни алгоритми и вештачка интелигенција преку платформата **Quantum Realtime Algorithm for Wildfire Containment (QuRAWC)**. Ќе се покаже како комбинацијата од квантни пресметки и AI овозможува реално-временско донесување одлуки за спречување и контрола на пожарите. Ќе се разгледаат примери за предвидување на однесувањето на пожарите и оптимизација на стратегиите за нивно ограничување. На крајот, ќе се отвори дискусија за иднината на ваквите технологии и нивниот потенцијал за спасување животи и заштита на природата.

**Петар Крстевски AI Engineer @Talnets** \- Дипломиран инженер по електротехника и информациски технологии во насоката компјутерско инженерство\. Моментално е дел од startup чиј фокус е football scouting и пронаоѓање на млади неоткриени таленти\. Работи на развој на модели од вештачка интелигенција со аудио/видео податоци за примена на фудбалски натпревари\.

**Никола Гилев Machine Learning Engineer @CodeChem** со искуство во развој на full-stack апликации и страст кон вештачката интелигенција. Во последно време, неговиот фокус е насочен кон LLMs и Retrieval-Augmented Generation (RAG) системи, каде што активно истражува и имплементира решенија базирани на напредни јазични модели. Во моментов работи на проект од областа на машински вид, кој користи слики од Google Maps за извлекување на корисни информации.

**Алек Пачемски Front-End Engineer @ Marek Engineering** Toj активно придонесува во развојот на модерни web-first ERP системи. Претходно има работено со ML модели и стриминг ML predictive pipelines, а денес во неговото слободно време развива алатки за ML преку knowledge graphs и SQL бази, трансформирани во граф-структури, со цел поставување прашања врз основа на бази на податоци, овозможувајќи понапредна интеракција со податоците. Има силна техничка основа и пасија за решавање на комплексни предизвици.

PyData Skopje

Pavlina Buchevska

Velimir Graorkoski

Dushan Merdjanovski 

Stefani Kulebanova

Marija

Tomislav Ignjatov

Filip Stefanovski

Aleksandar Radulovski

Aleksandar K

Dushko Klincharov

Anastasija

ljupco.semov

Filip Angelov

Jovan Krajevski

Viktor Domazetoski

IvicaArsov

Haris

Maria Cieva

Frosina Cvetkovska

Georgi Kamchevski

Quantum Realtime Algorithm for Wildfire Containment

Base42

We are pleased to invite you to our upcoming meetup, co-organized with Adyen, on Thursday, **June 19**, at the **Adyen Amsterdam office**. Get ready for two in-depth talks: one on real-world machine learning for payment routing optimization, and another on an innovative interactive next-gen notebooks data tool. We look forward to seeing you there! Food and drinks will be provided! 🚀💡

**Note: To ensure a smooth check-in process, please register using your full name.**

**SCHEDULE**
17.30 - 18.25: Welcome with drinks 🍕 / 🍻
18:25 - 18.30: Intro / About Adyen
18:30 - 19.15: **Multi-Objective Optimization in Payment Routing** \- Yuan Yue & Simon van der Zon
19.15 - 19.45: Break
19:45 - 20.30: **Let’s completely rethink the notebook** \- Vincent Warmerdam
20.30 - 21.00: Networking, food, drinks ! 🍻

**TALKS**
**\[Talk 1\]: “Multi\-Objective Optimization in Payment Routing”** by [Yuan Yue](https://www.linkedin.com/in/yy2022/) and [Simon van der Zon](https://www.linkedin.com/in/simonzon/?originalSubdomain=nl)

Machine learning (ML) models in production often start with a single objective, such as maximizing conversion rate in the payment industry. However, real-world business contexts are often more nuanced where other aspects relevant to a transaction, such as transaction cost or fraud risk, come into play. These objectives can be inherently conflicting: while optimizing for authorization may drive more revenue, it could also lead to higher costs or increased risk exposure.

Addressing such trade-offs necessitates the consideration of multi-objective optimization (MOO), while key information in the payment context plays a role in determining which objective should get more weight when considering the trade-off. In this talk we will share how we (Optimize ML team at Adyen) use the contextualized scalarization approach to improve our Intelligent Payment Routing product with a focus on conversion rate and transaction cost optimization.

**\[Talk 2\]: “Let’s completely rethink the notebook”** by [Vincent Warmerdam](https://www.linkedin.com/in/vincentwarmerdam/?originalSubdomain=nl)

Jupyter notebooks have been around for a while now and are an approachable starting point for anyone interested to explore data and programming. It's done a lot of good, but it was never really designed to be "the" Python notebook. It's always wanted to support multiple languages and this is reflected in many of the design decisions. And that makes you wonder, what could one do if we really did do just that? What if we ignored other languages and really only cared about Python and data tools? Would the notebook be different?

The goal of this talk is to demonstrate this idea by talking about widgets, reactive Python, modern data tooling and also about the freedom to rethink your tools. There will also be demos. Lots. Of. Demos.

**DIRECTIONS**
Address:
Simon Carmiggeltstraat 6-50,
1011 DJ Amsterdam

The event will be held at the Adyen SC office event space, which is just a seven-minute walk from Amsterdam Central Station. Please enter through the main entrance (the revolving doors) and collect your visitor badge at the reception desk.

**Note: To ensure a smooth check-in process, please register using your full name.**

PyData Amsterdam

Akhila Vangara

Jaap Stefels

Kally Chung

Atul Chhotray

Shunyao Yu

Arjan M

Sattar Stamkul

Simin Sh

Mark Stupin

Marcel Boersma

Qiulin Zhu

kiran Nreddy

Mihály Lőrinc

Karin

Suraj GHIMIRE

Rob Romijnders

Saeed Choobani

Abel Soares Siqueira

Stefan Bloemheuvel

Joy Machado

Payment Routing Optimization & Next-Gen Data Notebooks

Adyen

**PyData Helsinki is Back**! 🚀🐍

After a quiet period following five awesome online events in 2020–2021, we're rebooting PyData Helsinki!

With the recent sold-out, standing-room-only Helsinki Python events proving there's plenty of enthusiasm in our community, now is a great opportunity to meet and reconnect in person.

**First Meetup:**

* 🗓 **Wednesday, June 25th**
* ⏰ **17:00**
* 📍 **Kaivopuisto**

Come along, bring snacks and possibly beer, and let's enjoy a relaxed evening of networking and discussions. Meet old friends, make new connections, and let's talk about what we want PyData Helsinki to become!

Please register for the event so we know how many are coming. In case of bad weather, we'll pick some pub in the vicinity. Closer to the event (when we have a better idea about the weather) we'll send a message with the more precise location through Meetup.com and on the [Helsinki Python Discord](https://helsinki-python.github.io/discord).

― ― ― ― ― ―

And we've already found a great host for August: Wonna is a hands-on software consulting company that is committed to working with the developer community. We're privileged to be able to have our **next meetup** there. Save the date:

* 🗓 **Tuesday, August 26th**
* **⏰ 18:00**
* **📍 Wonna**, Elimäenkatu 17-19

We need some talks for this event. If you would like to **give a talk**, please reach out. We welcome talks of all levels from beginner to advanced. Also ⚡️ lightning talks of 5–10 minutes! Suitable subjects include the tools of the data trade, including but not limited to Python, and experiences using them. Think more "this is why Parquet is a great file format" or "I hated Cursor until I implemented these .cursorrules" than "AGI is coming, buy my product or be left behind" or "quantum-proof your digitalisation strategies with AI-driven design sprints".

Meetups always need venues—please ask your employer to **host an event**!

― ― ― ― ― ―

Looking forward to seeing everyone again, or in many cases for the first time,

**The PyData Helsinki Team**

PyData Helsinki

Jouni Seppänen

Cal Paterson

Hugo van Kemenade

Niko Föhr

Matti Ryttyläinen

PranavChendur

Patrick Da Silva

Yue Zhang

Chandreyee 

Nicolas Tomatis

Hadi Zare

Roman

David Ramos

Zoltán Buka

Vladimir Uspenskii

Stanislava Golubchenko

Fahid Hasan

Dollwin Matharu

PyData Helsinki Picnic

Kaivopuisto

PyData

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