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?
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.
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.
Data science projects are often characterized by visualizations which
enhances the creative storytelling process and allow us to derive actionable
insights from data. This is enabled through the use of good visualization tools/libraries which enable us to present data in a manner that is interactive and is easily understandable. Often, the action in itself tends to be more significantly remembered by the audience in comparison to static insights. This inturn
calls for the need for using interactive dashboards as a way to present the data.
Currently, the plethora of tools available for this purpose often makes it a tedious task to decide which is the best fit. Often the choice oscillates between learning to use explicit dashboarding tools or using existing python libraries which may allow visualizations but not necessarily dashboarding.
Apart from the cost associated with some of these explicit dashboarding tools, there might also be a learning curve associated with it.
Therefore, in this talk, I would like to take you through a simple pythonic approach of building dainty dashboards using Plotly Dash in python to ease the process of data exploration and allow for interactive visualizations that enable creative storytelling.
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:
- package managers
- code formatters
- code linters
- test runners
- python manager
I will also talk about centralizing the configuration so different tools can act consistently, eg CLI, IDE and CI/CD.
In my talk I will go over the story of how I set up the service that sends text message reminders to patients of the Portuguese primary care health system. I will explain the constraints of working with a distributed silo legacy application and other proprietary projects in a large company, and the impact of that and short deadlines on application design. Python shines through the project for its vast amazing libraries, ease of design and speed of iteration.
New technology now allows machine learning models to be uploaded to the blockchain, enhancing decentralized applications' (dapps) functionality and competitiveness against centralized apps. In this talk, we will discuss how anyone can easily deploy a simple machine learning model to the blockchain.
In Artificial Intelligence systems, a renaissance has unfolded in recent years, captivating the imagination of many! However, a startling statistic emerges amidst the enthusiasm: merely 13% of machine learning models are deployed into production!
Indeed, the artistry of building and deploying these systems supersedes mere scientific methodology as these models dwell within the realm of complexity and are characterized by an inherent reliance on data distribution. Have you ever wondered if these models are trained upon biased data they are destined to produce haywire decisions?
In this talk, let us delve into the realm of ethicality, fairness, and unbiasedness, culminating in the seamless integration of machine learning models that embrace ethical considerations in their journey towards production using Python!
Python usually works the way we expect to, but sometimes it doesn't. This talk is about when to expect the unexpected.
Tavern is an open source pytest plugin aimed to write automated integration tests for HTTP and MQTT APIs. Currently, there isn’t any UI support for it. This talk presents a Visual Studio Code extension that enables easy and fast writing of Tavern tests .
"Unveiling Perspectives: The Art of Data Insight Communication in the Data-Driven Projects" is an engaging presentation that emphasizes the criticality of effectively communicating findings and insights in the field of Data Science. Often overlooked, the final stage of a data-driven project involves presenting results to stakeholders. This talk sheds light on the importance of this stage and explores the art of presenting findings, storytelling, and employing interactive methods to convey complex information in an intuitive manner. By leveraging powerful Python tools such as PyShiny, FastAPI, Streamlit, Flask, and ReactPy, participants will gain insights into how to effectively utilize these tools to enhance their data analysis and ensure understandability and memorability. In addition, the session will touch upon color science principles and other intriguing elements. The speaker will showcase a real-life data-driven project and demonstrate their innovative solution for result communication, providing practical examples and valuable takeaways.
The newest Python versions are including many changes that improve the performance and functionality, but what's going on under the hood? In this talk, you will learn the necessary topics to start discovering how CPython internals work, and how to create a new module based in C or C++.
In this keynote we are going to talk about how unconscious bias can impact on business and real world IT products and learn the importance of understanding the inclusion of diverse teams.
From the team behind AWS Lambda Powertools for Python, we will explore trade-offs in API design and UX when your project is used by thousands of customers in production.
Race conditions? No problem! Dive into the world of database locks with Django and gain hands-on knowledge on how to eliminate race conditions, maintain order, and boost your application's performance.
Python's presence in Qiskit environments for quantum computing is vital for several reasons. Its simplicity, extensive libraries, and integration with scientific computing tools make it an ideal language for expressing quantum algorithms and designing quantum circuits. Python's versatility allows researchers to combine quantum computing with machine learning techniques, opening new possibilities for advancements in the field. Furthermore, Python's emphasis on readability and the support of a vibrant community fosters collaboration and knowledge-sharing, propelling the growth and adoption of quantum computing.
We all know it by now: Polars is blazingly fast™️. Yet my pipelines are all written in pandas, and it will just take too much time to rewrite them in Polars... won't it? Turns out, it takes less than thirty minutes to tame this new arctic beast!
Python's flexible and intuitive syntax enables developers to quickly build applications. But on the other hand, it may be slow during runtime. Luckily, there are different ways we can speed up a Python program. In this talk, we'll explore different alternatives to make Python programs faster.
Discover the immense potential of Python's list comprehensions, dictionary comprehensions, set comprehensions, and generator expressions, as we present them as an idiom that focuses on data transformations.
Using real-world examples, we'll demonstrate how these tools can streamline data manipulation and transformation tasks while enhancing code readability. We'll also provide insights on best practices and use cases to maximize their effectiveness.
By the end of this talk, you will be equipped to confidently harness the full potential of comprehensions and generator expressions, empowering you to create more expressive and elegant Python code. Join us on this exciting journey and level up your Python programming!
Let's make sense of modern Python packaging tooling.
Python in the context of data for python developers, non python engineers and businesses using Esmerald and Saffier with the power of async python.
The human brain excels at finding patterns in visual representations, which is why data visualizations are essential to any analysis. Done right, they bridge the gap between those analyzing the data and those consuming the analysis. However, learning to create impactful, aesthetically-pleasing visualizations can often be challenging. This session will equip you with the skills to make customized visualizations using Python.
PDF document guarantees 100% delivery of content to the customers as planned.
The workshop shows how to use the REPORTLab library to create PDF generator, based on Django Models and Templates to allow complex document layout for auto-generated catalogs or reports in PDF format.
Level up your Flask skills in this workshop! Learn Flask the hard way by diving into architectural patterns. Discover how to build scalable and maintainable applications using Repository, Unit of Work, and Use Cases. Don't miss this opportunity to become a Flask pro!
The workshop on "MicroPython and time series analysis: Forecasting and trend analysis" is designed to help attendees learn how to perform time series analysis, forecasting, and trend analysis using MicroPython. This workshop is ideal for anyone interested in learning how to analyze data collected over time, and how to use MicroPython to implement these analyses on microcontrollers.
In this captivating workshop, participants will embark on an exciting journey to explore the art of data storytelling with the power of Python. Led by Jayesh Kothari, a Python enthusiast and data storytelling expert, this session promises to be both informative and engaging.
Learn how to develop multiparadigm web scrapers and crawlers leveraging an async model. Discover how to extract valuable information from websites using Python's environment and powerful tools. Master the art of collecting data at scale. Join this exhilarating journey of web exploration.
Have you introduced bugs to your project when refactoring or making a “small” change to your code? Do you want to make your code base bulletproof? Learn how and when to write property-based tests, with little effort but significant benefits.
Practice how to write elegant comprehensions to make your code more idiomatic and easier to follow. With dozens of exercises, this tutorial will be perfect for you to finally get to grips with:
• list comprehensions;
• dictionary comprehensions;
• set comprehensions; and
• generator expressions.
Among other things, you will learn to identify situations where you should be using these powerful and elegant Python constructs. You will also learn how to use them to level up your Python skills.
By the end of the tutorial, you will learn all of the ins and outs of comprehensions, their use cases, best practices and things to avoid, and some advanced usage patterns as well!