Python

lightstep

OpenTelemetry Python: All you need to know

Hi all, tedsuo back again, dropping a knowledge bomb and a bunch of stale-yet-crunchy pop culture references. Last week we covered Node; this week we are going to dive into Python. If you crack open OpenTelemetry, you’ll quickly discover that there’s a lot there. But, as a developer applying OpenTelemtry to your application, 99% of what’s in there doesn’t matter.

stackify

How to catch all exceptions in Python

One of the struggles developers face is how to catch all Python exceptions. Developers often categorize exceptions as coding mistakes that lead to errors when running the program. Some developers still fail to distinguish between errors and exceptions. In the case of Python application development, a python program terminates as soon as it encounters an unhandled error. So, to establish the difference between errors and exceptions, there are two types of errors.

Workshop: Getting Started with OpenTelemetry and Distributed Tracing in Python

OpenTelemetry is an open source framework that provides a single set of APIs, libraries and instrumentation resources to capture distributed traces and metrics from your applications. Join Ted Young, Director of Developer Education at Lightstep, to learn how to get started with distributed tracing in Python using OpenTelemetry.
stackify

Top 5 Python Memory Profilers

According to the Stackoverflow survey of 2019, Python programming language garnered 73.1% approval among developers. It ranks second to Rust and continues to dominate in Data Science and Machine Learning(ML). Python is a developers’ favorite. It is a high-level language known for its robustness and its core philosophy―simplicity over complexity. However, Python application’s performance is another story. Just like any other application, it has its share of performance issues.

iguazio

MLOps for Python: Real-Time Feature Analysis

Data scientists today have to choose between a massive toolbox where every item has its pros and cons. We love the simplicity of Python tools like pandas and Scikit-learn, the operation-readiness of Kubernetes, and the scalability of Spark and Hadoop, so we just use all of them. What happens? Data scientists explore data using pandas, then data engineers use Spark to recode the same logic to scale or with live streams or operational databases.

bearer

Sort, Filter, and Remap API Data in Python

Are you taking data from an API in the format the web services gives it to you? You should not dictate the structure of data inside your application based on how an API provider structures their data. Instead, you can take advantage of the power of Python's list manipulation techniques to sort, filter, and reorganize data in ways that best suit your needs.

rookout

Python Debugging: More Than Just A (Print) Statement

As most developers will agree, writing code is oftentimes, if not always, easier than debugging. As a simple definition, debugging is the process of understanding what is going on in your code. When speaking in terms of Python, it is a relatively simple process. Every developer has their own personal debugging method or tool they swear by. When it comes to Python, most developers use one (or more) of the following: print statements, traditional logging, a pdb debugger, or an IDE debugger.