Top Python libraries of 2020

Welcome to the sixth yearly edition of our Top Python Libraries list! The rules are simple. We are looking for libraries that satisfy the following conditions: They were launched or popularized in 2020. They are well maintained and have been since their launch data. They are outright cool, and you should check them out. Disclaimer: this year, our picks are heavily influenced by machine learning / data science libraries, although some can indeed be very useful for non-data science people.

Top 10 Python libraries of 2019

Welcome back to the fifth yearly edition of our Top Python Libraries list. Here you will find some hidden gems of the open-source world to get you started on your new project or spice up your existing ones. You’ll find machine learning and non-machine learning libraries, so we got you all covered. We hope you enjoy it as much as we did creating it, so here we go! 1. HTTPX As a die-hard Python fan who usually interacts with APIs, you are probably familiar with the requests library.

Top 10 Python libraries of 2018

Update December 2019: The edition with the top Python libraries 2019 has been published here. Like in 2015, 2016 and 2017, we’re thrilled to share our hand-picked selection of the top Python libraries (according to our most humble opinion) with you. If you can think of a library that is not mentioned here but you believe deserves to be on the list, please let us know in the comments section at the end of the post.

Getting started with AWS: open source workshop

Introduction One of our strengths at Tryolabs is that we have people coming from diverse technological backgrounds. In order to make sure that everyone who joins the company, no matter their previous experience, can be up to speed with developing apps with the stack we usually use, we have an extensive onboarding process that involves the development of a real application (frontend, backend and some data science), with a coach, code reviews, and iterative improvements.

Top 10 Python libraries of 2017

Update December 2019: The edition with the top Python libraries 2019 has been published here. December is the time when you sit back and think about the accomplishments of the past year. For us programmers, this is often looking at the open source libraries that were either released this year (or close enough), or whose popularity has recently boomed because they are simply great tools to solve a particular problem.

Launching Requestium: An integration layer between Requests and Selenium for automation of web actions

From time to time at Tryolabs we have the need of simulating user interactions on websites. To tackle this problem, we usually use Requests, the beloved Python HTTP library, for simple sites; and Selenium, the popular browser automation tool, for sites that make heavy use of Javascript. Using Requests generally results in faster and more concise code, while using Selenium makes development faster on Javascript heavy sites. After writing several of these interactions we found ourselves with the need of writing code that made use of both these approaches at the same time.

Top 10 Python libraries of 2016

Update December 2019: The edition with the top Python libraries 2019 has been published here. Last year, we did a recap with what we thought were the best Python libraries of 2015, which was widely shared within the Python community (see post in r/Python). A year has gone by, and again it is time to give due credit for the awesome work that has been done by the open source community this year.

Scalable infrastructure in AWS (Part I)

Let’s imagine you have an API running on a single node and you need to implement a new feature that requires some heavy task processing. Obviously you can’t simultaneously process the HTTP request and the task without blocking the web server. Although in Python we have a few alternatives like Celery (check our post on this) or Asyncio (when the heavy task processing is IO bound, future post 😃) to handle this situation, this time we’ll explore a new approach: take advantage of Amazon Web Services (AWS).

Building our site: From Django & Wordpress to a static generator (Part I)

We recently announced the redesign of our website and blog. So far, it has been a great success. The site is a lot faster, SEO is better than ever (signaled by the growth of organic traffic), user bounce rates are down, the amount of visited pages went up as did the duration of the sessions. Hurray! :-) However, the change was much deeper than just a visual revamp. We decided to revise the tech stack that has been powering the site for more than 6 years.

Raspberry Pi + Slack: Our humble contribution to the office's laziness

If there is one issue that permeates every culture, is not wanting to answer the door. We used to have countless hours of discussion about who would do it and led to a myriad of problems: relationships were broken, projects were lost, accidents happened on the way to answer the door phone! (Well, not really. Nothing of this happened, but IT COULD HAVE). This clearly had to be fixed. Thinking a bit, we realized we could ease the annoyance of this task if we could avoid having to do the enormous, unbearable exercise of standing up and walking to the phone.

Like what you read?

Subscribe to our newsletter and get updates on Deep Learning, NLP, Computer Vision & Python.

No spam, ever. We'll never share your email address and you can opt out at any time.