When your software is too slow in production, how can you figure out the source of the problem? One common starting point to improving production observability is logging, and ideally trace-based logging (tracing for short). For example, the OpenTelemetry standard and the libraries and backend services that work with it can help you collect metrics, logs, and traces. Tracing—both within and across processes—is the most general of these, immensely useful for identifying and debugging problems, including performance problems. But there’s […]

# samples.py dictionary_of_dictionaries = { 1: {“first_name”: “Dorthea”, “last_name”: “Emmanuele”, “age”: 29}, 2: {“first_name”: “Evelina”, “last_name”: “Ferras”, “age”: 91}, 3: {“first_name”: “Frederica”, “last_name”: “Livesay”, “age”: 99}, 4: {“first_name”: “Murray”, “last_name”: “Linning”, “age”: 36}, 5: {“first_name”: “Annette”, “last_name”: “Garioch”, “age”: 93},

In July 2022, Python reached for the stars, playing a key role in processing data from the James Webb Space Telescope. After two years of virtual conferences, EuroPython 2022 took place in Dublin, Ireland. Anaconda celebrated its tenth birthday, and Flask achieved a major milestone on GitHub. Two new pre-release versions of Python 3.11 were released, with 3.11.0b5 representing the final beta version. Meanwhile, the Python Package Index (PyPI) introduced a two-factor authentication requirement for maintainers of critical projects. Finally, […]

In programming, the term constant refers to names representing values that don’t change during a program’s execution. Constants are a fundamental concept in programming, and Python developers use them in many cases. However, Python doesn’t have a dedicated syntax for defining constants. In practice, Python constants are just variables that never change. To prevent programmers from reassigning a name that’s supposed to hold a constant, the Python community has adopted a naming convention: use uppercase letters. For every Pythonista, it’s […]

Your customers are complainin’, your monitors are alertin’, your thumbs are a-twiddlin’—whatever the symptom, the problem is that your application is too slow. And you want to find out why, so you can fix it. You could spin up your application on your laptop, do some benchmarking, and try to find the bottleneck. Sometimes, that’s all it takes, but quite often, local testing tells you nothing useful. For many performance bottlenecks, the only way to identify the problem is to […]

You’ve built a shiny Django app and want to release it to the public, but you’re worried about time-intensive tasks that are part of your app’s workflow. You don’t want your users to have a negative experience navigating your app. You can integrate Celery to help with that. Celery is a distributed task queue for UNIX systems. It allows you to offload work from your Python app. Once you integrate Celery into your app, you can send time-intensive tasks to […]

Vectorization in Python, as implemented by NumPy, can give you faster operations by using fast, low-level code to operate on bulk data. And Pandas builds on NumPy to provide similarly fast functionality. But vectorization isn’t a magic bullet that will solve all your problems: sometimes it will come at the cost of higher memory usage, sometimes the operation you need isn’t supported, and sometimes it’s just not relevant. For each problem, there are alternative solutions that can address the problem. […]

Templates are an essential ingredient in full-stack web development. With Jinja, you can build rich templates that power the front end of your Python web applications. But you don’t need to use a web framework to experience the capabilities of Jinja. When you want to create text files with programmatic content, Jinja can help you out. In this tutorial, you’ll learn how to: Install the Jinja template engine Create your first Jinja template Render a Jinja template in Flask Use […]