PyCon Sri Lanka 2022 will be held on February 22nd, online for free.
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Python is everywhere. It's running some of your favorite apps, it's used in companies worldwide, it even runs governments. Python has a massive impact, not only in the computing world, but the entire world. It has proved itself, whether you are an amateur programmer working on a hobby project, or a professional bootstrapping a startup.
PyCon Sri Lanka is the largest online conference for the Python community to meet and learn from each other. PyCon Sri Lanka is for Python enthusiasts of all experience levels, from new users to professionals.
PyCon Sri Lanka will feature speakers from multiple countries and diverse disciplines and will serve as the hotspot for Python enthusiasts to connect with other Python communities overseas.
With the goal of strengthening the Python community in Sri Lanka and promoting Python, we are making the conference accessible to all free of charge.
Date: February 22, 2022
Time: 9.00 AM onwards
Duration: 1 day
Hosting the first-ever large scale PyCon conference in Sri Lanka, we bring together several prominent speakers with vast experience in Python. The speakers are both international and local with specialized knowledge on Python and its applications. They will guide you on three Python tracks: Python in General, Python for Web, and Python in Data.
David Beazley is an independent author, educator, and researcher primarily known for his ongoing work in the Python community, and also he has a Ph.D. in computer science and a M.S. in mathematics.
In 1999, he authored the Python Essential Reference, the first reference book published on Python, and also in 2013, he authored a new edition of the Python Cookbook, modernized to Python 3. David continues to actively develop software and is a well-respected conference speaker.
Dr Russell Keith-Magee is the founder of the BeeWare project, developing GUI tools and libraries to support the development of Python software on desktop and mobile platforms. He is also a 13 year veteran of the Django core team, and for 5 years, was President of the Django Software Foundation. In his day job, he wrangles data pipelines for Upwave.
He is a frequent speaker at Python and Django conferences around the globe, sharing his experiences as an Open Source developer, community maintainer, and (unsuccessful) startup founder. He lives in Whadjuk Noongar country - otherwise known as Perth, Western Australia.
Bargava Subramanian is a Data Scientist turned Entrepreneur. His expertise is in building AI-first data products. He mentors students, individuals and teams in their data science journey. He holds a Masters degree in Statistics from University of Maryland, College Park.
Chamindu has 20 years experience in the software industry as an engineer and a software architect, designing numerous enterprise, mobile, machine learning and IoT applications. He is currently the CTO of Azend Technologies.
Kracekumar is a software engineer based out of Bangalore and interested in building reliable systems. He has interests in software engineering, data-engineering, and FOSS. He has given talks in several Python conferences like PyCon India, PyGotham, Euro Python, etc ...".
Manas is a tech geek and python enthusiast who is passionate about solving everyday problems using the latest technologies! He is a Member of British Computer Society and is working as the Head of Systems Development at a Fintech startup. Prior to that he was building and implementing software for the operations and management of smart cities and smart buildings.
Mirantha is currently a PhD candidate in Computer Science at the University of Manchester, UK. In academic research, he has contributed towards improving deep learning-based computer vision algorithms using ontology-based background knowledge. His industry involvement has ranged from building AI-centered software with natural language processing to Python-based data analytics. Having started his career in the field of Robotics he has shifted his focus fully towards Machine Learning applications over the past years.
I’m Paolo Melchiorre, a longtime Python backend developer who contributes to the Django project and gives talks at tech conferences. I’ve been a GNU/Linux user for over 20 years and I use and promote Free Software.
I graduated in Software Engineering and I’m an alumnus of the University of Bologna, Italy.
I’ve been working in the web for 15 years and now I’m the CTO of 20tab, a pythonic software company, for which I work remotely.
Reuven is a full-time Python trainer. In a given year, he teaches courses at companies in the United States, Europe, Israel, India, and China — as well as to people around the world, via his online courses.
Reuven created one of the first 100 Web sites in the world just after graduating from MIT’s computer science department. He opened Lerner Consulting in 1995, and has been offering training services since 1996.
In 2020, Reuven published “Python Workout,” a collection of Python exercises with extensive explanations, published by Manning. He’s currently working on “Pandas Workout,” a similar collection of exercises using the “pandas” library for data analysis.
Reuven lives in Modi'in, Israel with his wife and three children."
Rodrigo has always been fascinated by problem solving and that is why he picked up programming – so that he could solve more problems. He also loves sharing knowledge, and that is why he spends so much time writing articles in his blog mathspp.com/blog, writing on Twitter @mathsppblog, and giving workshops and courses. His main areas of scientific interest are mathematics (numerical analysis in particular) and programming in general (with a preference for the Python and APL languages), but Rodrigo also enjoys reading fantasy books, watching silly comedy movies and eating chocolate.
Sahan is affiliated to the UCL Centre for Artificial Intelligence currently contributing to the X5GON and HumaneAI projects. His research interests lie on the theme: “Improving Recommendations of Educational Contents to Lifelong Learners”. Before joining UCL, he has worked in several research and advanced development roles both in the Silicon Valley and in London in a range of domains from cybersecurity to personalised advertising where his expertise in user state modelling, big data and machine learning were used for data product development. At UCL, he is continues research into the role of AI in Education while leading the development of the intelligent learning platform www.x5learn.org.
Sebastiaan is a Software Engineer for the Ordina Pythoneers and a Fellow of the Python Software Foundation. As a Python enthusiast, he loves discussing the inner workings of the language and coaching others to become better developers. In 2021, Sebastiaan gave talks at various conferences, including PyCon, EuroPython, FOSDEM, PyCon Indonesia, Pyjamas, and PyGrunn. He is also active in the Python community, as an owner of Python Discord, an open-source contributor, and as a Python educator.
Tonya is a former Professional Basketball player turned Python enthusiast. She is currently a Python Developer Advocate for Deepgram, a speech-to-text company that has revolutionized the market. Her path to Python is unconventional. Her career started in athletics then transitioned to pharmaceutical sales. She finally landed in her destination spot, the tech industry. Driven by her passion for teaching, she takes pride in helping others and loves connecting with her fellow Pythonistas! Outside of coding, Tonya enjoys all things sports. She is also an avid reader who loves writing and spending time with her nieces and nephews.
Yasiru Ratnayake is VP for Product Development at Trabeya, building data-intensive, intelligent systems. His work involves building prototypes composing applied research models and leading agile teams taking them to production, all the while closely aligning with diverse domain and product considerations.
He has previously developed solutions for biological supply chains and online retail. Having worked in non-life actuarial and having an MSc in Financial Mathematics, he is passionate about machine learning applications in these domains. He also follows Effective Altruism and work in AI safety.
The sessions will be held on three parallel tracks: General, Python for Web and Python in Data.
Python has always been a good language for problem solving. In this talk, I'll talk about the problems with that.
Sorting is one of those things that we take for granted in Python. The built-in "sorted" unction knows how to sort any iterable of objects that are themselves sortable.
But hiding behind that simple description is a great deal of depth. In this talk, I'll go deep into what it means to sort, and how we can sort any collection of Python data. We'll see how you can use custom functions to sort built-in data structures in new and interesting ways. And we'll see how you can design your own custom classes such that they will sort in just the way you want.
After watching this talk, you'll have a better understanding of sorting, built-in data structures, function objects, and how "magic methods" affect the our Python classes. Moreover, you'll be able to write clearer, shorter, and more easily understood code.
A ton of automation can be done by knowing a little bit of python. Some of the everyday tasks you can start with are working on files (read/write), sending emails, reading from your favourite APIs or scraping websites. This talk will give you the "know-how" to start your own journey in Python Automation.
“All the cool kids are using FastAPI for web development.” Imagine hearing this just as you start getting more comfortable using other frameworks, like Django or Flask, to build your web app.
There's a new kid on the block. In this talk, let's walk through how to build a simple web application with FastAPI that transcribes sports audio in real-time.
What is Fast API?
Fast API (aka the new kid) is a modern Python framework that takes all your favorite features from other tools and combines them into one. It's built for speed, rapid development, and enhanced developer experience.
By the end, you'll have a much better understanding of how to use FastAPI in your next project.
This talk is for developers of all levels, including beginners.
Python introduced gradual typing with the mypy tool in 3.5. It has received mixed opinions in the community. As the code base grows over time, typing becomes an important tool to maintain code-quality and improve developer productivity.
The talk will introduce the audience to gradual typing in Python and focus on adding type-hints to Django using Django stubs, a third party plugin.
Machine learning techniques such as deep neural networks have gained massive popularity in the area of artificial intelligence in the recent past due to their high accuracy in narrowed-down visual and language tasks. But the latest research findings demand the need to address their limitations such as low explainability and high data dependency, especially when it comes to high impact applications. When the evolution of the study of artificial intelligence is considered, we find that techniques such as deep neural networks fall under an area named sub-symbolic or data-driven machine learning. There exists another realm of techniques that use logic rules and explicit, highly interpretable representations named symbolic or knowledge-driven artificial intelligence. This talk introduces a family of techniques named hybrid machine learning that combines these two areas. The aim of these hybrid approaches is to reap the benefits of symbolic approaches to overcome the limitations of state-of-the-art data-driven machine learning.
Cricket is a religion for more than 1 Billion people in the world. But as fans, the kind of analytics that’s available and the tools to do further analysis on his/her own has been quite limited so far.
In this talk, the speaker talks about how he and his team created a data product to analyze Indian Premier League (a Twenty20 league based in India). The resulting app, iplnani.com was entirely built just using Python.
He covers how the data was sourced and how a web product was built using streamlit, a simple yet potent library to quickly build web applications. The analysis was done using pandas, the most popular data analysis library. The visualizations were built using altair and folium.
The attendees can learn how to quickly build a web app and/or an internal tool for their own use case, be it as a student or for their industry, just using Python.
If you ever had a test that one day just started to fail unprovoked, or a test that fails once in a while for no apparent reason, it's possible your code is relying on something that is not deterministic. Dependency injection is a way to tame nondeterminism in code, and take back control over your code! As a bonus, it will also make writing tests much easier! In this talk I'll demonstrate how to implement dependency injection in Python and how it can simplify your tests.
In this talk I show what idiomatic Python code looks like and illustrate how the subjective notion of “beautiful”, or “elegant” code, can make your code objectively better, regardless of your Python skill level.
We do that by visiting several vanilla Python features that people sometimes forget to learn, as they rush to importing all the shiny modules and frameworks they really want to use. In order to achieve this, we go through the learning journey of a hypothetical Pythonista that wanted to implement `enumerate` from scratch. We will start with a first version written by them and then refactor it incrementally through the use of Pythonic idioms and patterns.
The talk will build around a series of articles available online (at https://mathspp.com/blog/pydonts), where I explore all the vanilla Python features that make Python one of the most interesting programming languages to learn. There are no prerequisites for this talk, and both advanced users and beginners alike can benefit from it.
After the talk, you will have a better understanding of several concepts such as iterables and (infinite!) lazy generators, and you will know how to use them effectively to get the job done.
An introduction to how to write clean code (type hinting, docstrings, inline comments et cetera) and supporting the clean code with maintainable project structure and unit tests.
Goals - with comparisons/examples:
Django is a powerful framework that supports clean, rapid development of web applications. If you built your web application in Django and need to provide an API, Django REST framework is your best choice. This session will be an introduction on how to use the Django REST Framework.
Driven by the immense popularity of asynchronous frameworks, such as FastAPI, asynchronous database support became a hot topic in the Python community. As talking to your database often forms a significant portion of the input and output of your application, it's important to do that asynchronously as well. With the release of version 1.4, SQLAlchemy added support for Asynchronous I/O for both its core and ORM features. This means that you can now use the popular SQL toolkit for Python in your asynchronous applications.
In my talk, I will introduce you to the newly added support for asyncio in SQLAlchemy. I will go over how easy it is to set up the new AsyncEngine, point you to some of the differences with synchronous SQLAlchemy, and show you some of the pitfalls to avoid. In addition, I will also show you how you can run your existing synchronous SQLAlchemy code asynchronously to help you transition to a fully asynchronous application. By the end of my talk, you should know enough to start your own asynchronous SQLAlchemy adventure.
Every time we’re going to create a new project with Django we make assessments on its requirements to choose the best architecture, of which, the database is usually the core.
Django is a database-agnostic web framework but natively supports only4 Open Source databases: PostgreSQL, SQLite, MariaDB and MySQL. PostgreSQL has the richest feature set of any supported database and some of these features are natively supported directly in Django via its contrib module.
In this talk we’ll see how to use to our advantage the features of PostgreSQL as a database in Django, its exclusive features present in its contrib module and also other superpowers that can be exploited through the use of third-party packages.
Differentiable programming is a new software paradigm wherein computer programs can be parametrized and optimised to allow them to learn dynamically from examples. The workhorse behind this is automatic differentiation, whereby gradient-based optimization can be brought to bear for such programs efficiently.
In this talk, I will motivate differentiable programming and illustrate how automatic differentiation works by translating between the mathematical framework and Python. While many mature options exist in Python for automatic differentiation, spurred by active work in deep neural networks, Jax is a package of particular interest bringing together a familiar NumPy-like API with flexible, performance-geared compilation.
Throughout, we will survey how functional programming is a natural fit for this new kind of computation as its ideas appear in our own implementations and in Jax. Coming in with familiarity with NumPy, by the end of the talk you should have a basic grasp of automatic differentiation and of Jax to begin exploring its growing ecosystem.
Natural language is about texts, alphabets, words, sentences, numbers, special characters, emoticons - in a nutshell, every way we express our thoughts. But machine learning is about only and only numbers. This use-case walk-through focuses on an advanced technique that helps us represent natural language as numbers, called word vectors or embeddings, to apply machine learning and build text classification models.
While the world is transitioning from the industrial revolution to the new data revolution, data science and machine learning practices have matured over the last few years leading to more understood and robust realisations of data science lifecycles. The former part of this talk will introduce the ideas relating to how one can improve data drive in a business and outlines briefly where python can be utilised in the data science lifecycle in a business taking the directors' perspective.
However, building Machine Learning (ML) models entail more uncertainty as the outcomes are not deterministic. This encourages the developer/ data scientist to thread in this path in a much more systematic way, to avoid setbacks. The latter part of the talk will take the engineers' perspective and outlines agile data science practices that will help manage developing ML artefacts. This part will also argue and convince the audience how Python presents one of the most stable and widest ecosystems for data science. A variety of Pythonic tools that can future proof your data science career available to carry out critical processes such as processing data, testing ML models, versioning ML models and monitoring ML models will be presented to the audience with example use cases.
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All attendees, speakers, Partners and volunteers at our conference are kindly asked to adopt the following code of conduct, and are required to agree to the Anti-Harassment Policy. We are expecting cooperation from all participants to help ensure a safe and comfortable environment for everybody.
Be friendly, patient, welcoming and considerate; be respectful, use appropriate language, and avoid discriminatory behavior or expressions. In particular, harassment is unacceptable; our conference is dedicated to providing a harassment free conference experience for everyone, and participants violating the Anti-Harassment Policy may be sanctioned or even expelled from the conference, at the discretion of the conference organisers.
Be friendly and welcoming. We strive to be a community that welcomes and supports people of all backgrounds and identities.
Be patient and considerate. We all want to have fun teaching and learning, and a cooperative atmosphere will make us more productive.
Be respectful. Not all of us will agree all the time, but disagreement is no excuse for poor behavior and poor manners. Refrain from personal attacks, and be respectful when dealing with other members of the Python community as well as with people outside it.
Use appropriate language, and avoid discriminatory behavior. Everybody is welcome to this conference, regardless of gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, or religion (or lack thereof).
We do not tolerate harassment of conference participants in any form. Organisers will enforce the Anti-Harassment Policy throughout the event.
Harassment includes offensive comments related to gender, gender identity and expression, age, sexual orientation, disability, physical appearance, body size, race, ethnicity, or religion (or lack thereof); deliberate intimidation, stalking, following, harassing photography or recording, sustained disruption of talks or other events, inappropriate physical contact, and unwelcome sexual attention. Sexual language and imagery is not appropriate for any conference venue, including talks, workshops, parties and online media.
Participants asked to stop any harassing behavior are expected to comply immediately.
Partners are also subject to the Anti-Harassment Policy. In particular, Partners should not use sexualised images, activities, or other material.
If a participant engages in harassing behavior, the conference organisers may take any action they deem appropriate, including warning the offender or even expulsion from the conference.
If you are being harassed, notice that someone else is being harassed, or have any other concerns, please contact a member of conference staff immediately.
We expect participants to follow these rules at conference and workshop venues and conference related social events.
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