Events: PyDay BCN (2020)

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Ready, Set, Go with Numba

Ankit Mahato

YouTube track1
Language: English
Topic: Data Science, ML, DL
Python level: Beginner
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The prominent reasons for the wide adoption of Python is the ease of learning, usability and readability coupled with the powerful ecosystem of Python packages. This often makes Python an attractive language for researchers & scholars to undertake computational projects and thesis. The ease of prototyping and tinkering allows for higher number of iterations and customization, leading to an increase in research output. But, a major pain point of using Python is its speed when compared to languages like C++ or FORTRAN which are still widely used in research.

Developers, when hit by the performance bottleneck of python code, often come across some methods to increase their code performance like using PyMPI, Numpy or CPython. But, the learning curve is steep and APIs get less familiar.

If learning Python is so easy, why should increasing the performance of Python code be so difficult?

This talk will address this question and get us up and running with Numba, an open source JIT compiler that translates Python and NumPy code into fast machine code. We will delve into real world exercises which will demonstrate the core concepts, ease and effectiveness of using Numba and how it can be useful in lowering the barrier to achieve code performance in Python.

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Working with Text Data in Pandas

Daniel Mesejo León

YouTube track1
Language: Spanish
Topic: Data Science, ML, DL
Python level: Intermediate
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I’ll will present some tips, tricks and libraries to speed up text processing with pandas.

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Lifebox: a virtual ecosystem

Ferran Fàbregas

YouTube track1
Language: Catalan
Topic: Data Science, ML, DL
Python level: Intermediate
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Lifebox is a project about a virtual ecosystem created using Python. Inside the Lifebox you can find two different kind of species, the ‘species’ and the ‘mana’. Each of the ‘species’ have a set of parameters that defines how they evolve inside the virtual ecosystem, and you can change all the parameter of species in real-time. The goal of the project is to offer the possibility to learn the basic concepts of biology through the experimentation, viewing the consequences of your actions and trying to find the way to balance the ecosystem through changing the Lifebox parameters.

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Transformers: the all-in-one tool for NLP

Julio Martínez

YouTube track1
Language: English
Topic: Data Science, ML, DL
Python level: Intermediate
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NLP has been evolving from classic bag of words to embedding methods. But in 2017 finally a new model that can be used for all kind of NLP tasks emerged: transformers. Let’s review its general ideas, and a practical example of its use.

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A Day Has Only 24±1 Hours

Miroslav Šedivý

YouTube track1
Language: English
Topic: Python programming
Python level: Intermediate
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On the last Sunday of October you may get “one more hour of sleep” but as well may spend much more time debugging code dealing with the time zones, daylight saving time shifts and datetime stuff in general. Two centuries of short-sighted propaganda and long-term chaos in ten minutes. Maybe that will make you want to avoid time zones in your code altogether!

El último domingo de octubre puedes obtener “una hora más de sueño”, pero también puedes pasar mucho más tiempo debugando el código tratando con las zonas horarias, los cambios de horario de verano y las cosas de fecha y hora en general. Dos siglos de propaganda miope y caos a largo plazo en diez minutos. ¡Quizás eso te haga querer evitar las zonas horarias en tu código por completo!

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Ho sento, no ets el meu tipus

Carles Barrobés

YouTube track1
Language: Catalan
Topic: Python programming
Python level: Intermediate
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Type Hints were introduced in Python 3 but you may have never used them, known that they exist, or seen code that uses them. Or you may have seen code with type hints and cringed because it didn’t look like the Python you know. In this talk we will demistify type hints and show how they can actually help you find potential bugs.

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Alexa, te elijo a ti

Elisabeth Ortega Carrasco

YouTube track2
Language: Spanish
Topic: IOT
Python level: Beginner
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Algunos de nosotros tenemos un aparatito en casa escuchándonos 24/7 que usamos para escuchar música, preguntarle la hora y pedirle un temporizador o un chiste malo. En esta charla os voy a enseñar como programar a Alexa usando Python para que os ayude en vuestras tareas usando dos ejemplos: una skill que nos calculará equivalencias para ayudarnos en las recetas de cocina (entre otras cosas) y otra que nos aconsejará sobre qué tipo de Pokémon elegir para enfrentarnos a un oponente.

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Network automation using Python

Christian Adell

YouTube track2
Language: English
Topic: Network automation
Python level: Intermediate
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I will share the status of network automation using Python, presenting and demoing some popular libraries such as Netmiko, Napalm and Nornir.

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Retrying, a better way

Christian Adell

YouTube track2
Language: English
Topic: Python programming
Python level: Beginner
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Python have a lot of libraries, for multiple purposes, and among them there are a lot of hidden gems, such as the Backoff library (https://github.com/litl/backoff) which will make retrying operations based on exceptions or predicates an easy game.
Handling retries have never been so simple.

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Antifragile Software: Code that gains from disorder

Álvaro Durán Barata

YouTube track2
Language: English
Topic: Python programming
Python level: Beginner
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Joel Spolsky famously said that you should never rewrite your code from scratch. Still, many organizations see no other way out of their codebases. Why? In this talk we explore the concept of antifragility, and how it can be applied to software engineer to keep your codebase from getting “rusty”.

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Performing Sentiment Analysis on Video with Serverless Architectures

Eduard Céspedes Borràs

YouTube track1
Language: English
Topic: Data Science, ML, DL
Python level: Intermediate
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In this talk we will explain how to create video processing pipelines using an event-driven and fully Serverless Architecture in AWS. We will use AWS Chalice, a Python framework from AWS, for managing the serverless Lambda Functions and a range variety of AWS services for the video manipulation like AWS Elastic Transcoder, Amazon Transcribe, Amazon Comprehend. And of course the more common architectural and traditional services like S3, DynamoDB, Gateway, SQS, SNS and SES.

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Counting votes: analyzing a large dataset with Dask

Alberto Cámara

YouTube track1
Language: English
Topic: Data Science, ML, DL
Python level: Intermediate
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We will explain how to switch from Pandas to Dask in order to analyze a large dataset that does not fit into single-machine memory.

Repository: https://github.com/ber2/pyday2020-counting-votes-with-dask

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Kornia: differentiable Computer Vision with Pytorch

Edgar Riba

YouTube track1
Language: English
Topic: Data Science, ML, DL
Python level: Intermediate
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The talk is an introduction to Kornia which is a library that implements classical Computer Vision algorithms in PyTorch that got a lot of attention within the open source community during the last year. The core of the library is written from scratch using pure PyTorch operators and uses the auto-reverse differentiable engine to allow to the user to plug any function within neural networks with a transparent API for high performance devices such as GPUs and TPUs. During the talk I’ll go through the different principle designs and the functionalities found in each of the modules, practical examples, basic usage of the library and more. Information about the project in the website: www.kornia.org

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JINA AI: An Open Source Neural Search Framework

Joan Fontanals Martínez

YouTube track1
Language: English
Topic: Data Science, ML, DL
Python level: Beginner
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What is neural or semantic search? How is it different from traditional symbolic search? Jina AI is an open source framework for AI-powered search.

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Building My First Python IoT Device with Containers (in 20 minutes)

Marc Pous

YouTube track2
Language: English
Topic: IOT
Python level: Beginner
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This workshop is designed for developers who are coming from Web development and other technologies into the Internet of Things. This session will guide assistants how to connect an Arm-powered device such as a Raspberry Pi to the Internet with balena and open source tools.

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Documentation-driven development for Python web APIs

Jose Haro Peralta

YouTube track2
Language: English
Topic: Web
Python level: Beginner
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In this presentation, I want to show how developers can minimise the risk of API integration failures by using documentation-driven development. Documentation-driven development is an approach where we first write the API documentation, and then we validate the API implementation against the specification. This approach helps us create a more robust software delivery process for our APIs. I’ll show useful tools and frameworks, such as Dredd, that can help us automatically generate tests that validate our APIs.

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Alice in Pythonland: Object oriented programming in Lewis Carroll games

Maria Teresa Grifa

YouTube track2
Language: English
Topic: Python programming
Python level: Beginner
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Tutorial regarding object oriented programming in Python. The applications that will be presented are some of the maths games hidden in the book Alice in Wonderland of Lewis Carroll. These games are algorimths pubblished by Lewis Carroll on scientific journals. My contribution would be to explain oop techniques (inheritance,decorators,dataclass, nametuple,…) for developing maths games and use some NLP techniques (i.e., finding the dialogs between charcaters in the books) for presenting the interactions between the playes involved in the game.
I have been inspired by a repository from Anna-Lena Popkes
(please see https://github.com/zotroneneis/magical_universe) on working on one programming topic per day. In this way, I have improved my coding skills day by day and I have created the a Wonderland Universe. The idea of coding the games created by Lewis Carroll is related to my maths background and has the intent of explain some joyful algorithms. My goal is to encourage other people to use the same learning technique and challege theiself with custom examples and applications.

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Investigating Digital Crimes using Python

Gajendra Deshpande

YouTube track2
Language: English
Topic: Security
Python level: Beginner
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A recent study by CheckPoint Research has recorded over 1,50,000 cyber-attacks every week during the COVID-19 pandemic. There has been an increase of 30% in cyber-attacks compared to previous weeks. The pandemic has been the main reason for job loss and pay cuts of people and has led to an increase in cybercrimes. Examples of cyber-attacks include phishing, ransomware, fake news, fake medicine, extortion, and insider frauds. Cyber forensics is a field that deals with the investigation of digital crimes by analyzing, examining, identifying, and recovering digital evidence from electronic devices and producing them in the court of law. Python has a great collection of built-in modules for digital forensics tasks. The talk begins with an introduction to digital crimes, digital forensics, the process of investigation, and the collection of evidence. Next, I will discuss report creation using CSV and Excel reports, investigation of acquisition media using the pyscreenshot module. Finally, I will conclude the talk with the investigation of embedded metadata, emails, and log files. In this talk, I will cover mutagen, mailbox, tqdm, argparser, yara python modules, and utilities which are used for the above-mentioned tasks.

In this talk, the audience will learn the procedure to be followed while investigating digital crimes and most importantly how to develop their own digital forensic tools using Python. I believe that the attendees will learn about the new exciting field where there are lots of opportunities with respect to their careers. Basic understanding of Python language or any other scripting language will be helpful in understanding the concepts.

Outline 1. Introduction to digital crimes, digital forensics, the process of investigation, and collection of evidence. [05 Minutes] 2. Report creation using CSV and Excel reports [04 Minutes] 3. Investigation of acquisition media using the pyscreenshot module [03 Minutes] 4. Investigation of embedded metadata [05 Minutes] 5. Investigation of emails [05 Minutes] 6. Investigation of log files [05 Minutes] 7. Conclusion and Questions [03 Minutes]

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