Python tutorials

Best and the most useful tutorials for Python developers
18 July 2017   3489

Multi-paradigm programming language with easy-to-use syntax and many features.

Python programming language is a powerful tool for creating various programs for a wide variety of purposes, suitable even for beginners. With its help you can solve different problems. 

Main Python features:

  • xml / html files work support
  • http requests work support
  • GUI (graphical interface)
  • Creating Web Scripts
  • FTP support
  • images, audio and video files
  • Robotics
  • Programming of mathematical and scientific calculations

And many others. 

Thus, python is suitable for solving the lion's share of everyday tasks such as backup, read e-mail, or creating some kind of game. 

The Python programming language is practically unlimited, so it is widely used in large projects. For example, python is heavily used by IT-Giants, such as, for example, Google. In addition, simplicity and universality of Python make it one of the most popular programming languages.

Learning any programming language starts with tutorials. Let’s take a good look on best Python tutorials for beginners.

Official Python tutorial

Great place to start learning any technology is to check official website. Luckily, official Python website has a big free online tutorial.

Official Python tutorial
Official Python tutorial

Tutorial is divided into 16 topics, every topic has many lessons. Tons of code examples included. Convenient navigation makes this web tutorial very handle and easy-to-use.

Python Programming Tutorial

Website, which has Python related tutorials on such topics as:

  • Data Analysis
  • Robotics
  • We Developement
  • Game Developement
  • Python Fundamentals
  • GUI

Python Programming Tutorial
Python Programming Tutorial

All tutorials have related screencast. For example, below you can see the Python 3 Basic Tutorial series video.

Great approach! This is very helpful and it facilitates learning process greatly.

Online tutorial with in-browser coding feature.

Every topic has an interactive example code right in your browser. Simple navigation also included. 

Learn Python the Hard Way

Book, available both in digital and hard formats.

Learn Python the Hard Way
Learn Python the Hard Way

Brilliantly written by the Zed A. Shaw. Hands on. No jargon. Assumes you know nothing, which is extremely important if we are to learn something new.

Great resource for Russian-speaking Python fans.

Has a lot of helpful materials, such as bundlers review, books, guides, docs and many others. Irreplaceable resource for Russian-speaking Python beginner.

Python at Tutorials Point

Tutorials Point is ine of the biggest only tutorials resources. And, naturally, it has a Python Section. 

Python at Tutorials Point
Python at Tutorials Point

Has a "Basic" and "Advanced" levels of tutorials. Simple navigation and large amount of examples included. Also, a python tutorial pdf version available too. 

What Python tutorial is most helpful for you?

Python is one the most popular programming languages in the world. It is a powerful tool for creating various programs for a wide variety of purposes, suitable even for beginners. With its help you can solve different problems.  Please choose the tutorial, which was the most useful for your Python study process. 

Official Python tutorial
44% (4 votes)
22% (2 votes)
Python at Tutorials Point
11% (1 vote)
Learn Python the Hard Way
11% (1 vote)
Python Programming Tutorial
11% (1 vote)
0% (0 votes)
Total votes: 9

Nvidia to Open SPADE Source Code

SPADE machine learning system creates realistic landscapes based on rough human sketches
15 April 2019   674

NVIDIA has released the source code for the SPADE machine learning system (GauGAN), which allows for the synthesis of realistic landscapes based on rough sketches, as well as training models associated with the project. The system was demonstrated in March at the GTC 2019 conference, but the code was published only yesterday. The developments are open under the non-free license CC BY-NC-SA 4.0 (Creative Commons Attribution-NonCommercial-ShareAlike 4.0), allowing use only for non-commercial purposes. The code is written in Python using the PyTorch framework.

Sketches are drawn up in the form of a segmented map that determines the placement of exemplary objects on the scene. The nature of the generated objects is set using color labels. For example, a blue fill turns into sky, blue into water, dark green into trees, light green into grass, light brown into stones, dark brown into mountains, gray into snow, a brown line into a road, and a blue line into the river. Additionally, based on the choice of reference images, the overall style of the composition and the time of day are determined. The proposed tool for creating virtual worlds can be useful to a wide range of specialists, from architects and urban planners to game developers and landscape designers.

Objects are synthesized by a generative-adversarial neural network (GAN), which, based on a schematic segmented map, creates realistic images by borrowing parts from a model previously trained on several million photographs. In contrast to the previously developed systems of image synthesis, the proposed method is based on the use of adaptive spatial transformation followed by transformation based on machine learning. Processing a segmented map instead of semantic markup allows you to achieve an exact match of the result and control the style.

To achieve realism, two competing neural networks are used: the generator and the discriminator (Discriminator). The generator generates images based on mixing elements of real photos, and the discriminator identifies possible deviations from real images. As a result, a feedback is formed, on the basis of which the generator begins to assemble more and more qualitative samples, until the discriminator ceases to distinguish them from the real ones.