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Python

Start with Python and InfluxDB

Although time series data can be stored in a MySQL or PostgreSQL database, that’s not particularly efficient. If you want to store data that changes every minute (that’s more than half a million data points a year!) from potentially thousands of different sensors, servers, containers, or devices, you’re inevitably going to run into scalability issues. Querying or performing aggregation on this data also leads to performance issues when using relational databases.

A Look at the 6 Best Python Error Monitoring Tools in 2022

Errors are the necessary evils of software development. They bring to your attention critical information about what’s wrong with your application and what needs fixing before your end-users suffer. Error monitoring tools offer significant help in this cause by aggregating all the errors and issues your applications (and their end users) are struggling with under one roof and providing valuable insights to resolve these and optimize performance.

Continuous Performance Improvement of HTTP API

The following guest post addresses how to improve your services’s performance with Sentry and other application profilers for Python. Visit Specto.dev to learn more about application profiling and Sentry’s upcoming mobile application profiling offering. We’re making intentional investments in performance monitoring to make sure we give you all the context to help you solve what’s urgent faster.

How we optimized Python API server code 100x

Python code optimization may seem easy or hard depending on the performance target. If the target is “best effort”, carefully choosing the algorithm and applying well-known common practices is usually enough. If the target is dictated by the UX, you have to go down a few abstraction layers and hack the system sometimes. Or rewrite the underlying libraries. Or change the language, really. This post is about our experience in Python code optimizations when whatever you do is not fast enough.

Why is Python so Popular?

Despite several widely acknowledged flaws, Python remains one of the most popular development languages worldwide. The sole fact that for years Python had two different and incompatible versions existing in parallel should have spelled the end for Python given the numerous alternatives available in the market. But Python overcame this conflict. Developers also criticized Python’s design and functionalities. Python is known to be slow and inadequate at dealing with memory-intensive operations.

JFrog Discloses 3 Remote Access Trojans in PyPI

The JFrog Security research team continuously monitors popular open source software (OSS) repositories with our automated tooling to detect and avert potential software supply chain security threats. After validating the findings, the team reports any security vulnerabilities or malicious packages discovered to repository maintainers and the wider community.

Getting Started with Google Cloud Logging Python v3.0.0

We’re excited to announce the release of a major update to the Google Cloud Python logging library. v3.0.0 makes it even easier for Python developers to send and read logs from Google Cloud, providing real-time insights into what is happening in your application. If you’re a Python developer working with Google Cloud, now is a great time to try out Cloud Logging! If you're unfamiliar with the `google-cloud-logging` library, getting started is simple.

REST API Observability for Python

In this blog post we’ll help answer the age old question, “What does this service talk to and what does it say?” We’ll see how to inspect inbound and outbound REST API calls to see what calls are being made and what incoming traffic causes a reaction. This can be pretty handy when you’re taking over maintenance of an existing service, or if your code just isn’t behaving the way you expect.

Object validation and conversion with Marshmallow in Python

Marshmallow is a Python library that converts complex data types to and from Python data types. It is a powerful tool for both validating and converting data. In this tutorial, I will be using Marshmallow to validate a simple bookmarks API where users can save their favorite URLs along with a short description of each site.