News : The new python version 3.10.0.

Almost six days ago, the new version of python was released, version 3.10.0, see this.

Its installation on windows operating systems is done in the same way as the old installations, with the same steps and the same settings.

After installation, I turned it on and tested some of the new features.

C:\Python310>python
Python 3.10.0 (tags/v3.10.0:b494f59, Oct  4 2021, 19:00:18) [MSC v.1929 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.

Python 3.10 comes with precise and constructive error messages like:

...
SyntaxError: '{' was never closed
...
>>> foo(a, b for b in range(5), c)
...
    foo(a, b for b in range(5), c)
           ^^^^^^^^^^^^^^^^^^^
SyntaxError: Generator expression must be parenthesized
...
>>> {a, b for (a, b) in zip("a", "b")}
...
    {a, b for (a, b) in zip("a", "b")}
     ^^^^
SyntaxError: did you forget parentheses around the comprehension target?
...
SyntaxError: expected ':'
...
SyntaxError: invalid syntax. Perhaps you forgot a comma?
...
SyntaxError: ':' expected after dictionary key
...
SyntaxError: expected 'except' or 'finally' block
...
SyntaxError: cannot assign to attribute here. Maybe you meant '==' instead of '='?
...
IndentationError: expected an indented block after 'if' statement in line ...
...
>>> import collections
>>> collections.namedtoplo
...
AttributeError: module 'collections' has no attribute 'namedtoplo'. Did you mean: 'namedtuple'?
...
>>> a = 0
>>> aa
...
NameError: name 'aa' is not defined. Did you mean: 'a'?

PEP 634: Structural Pattern Matching Structural 

... the pattern matching is a comprehensive addition to the Python language. 

They tell us: Pattern matching enables programs to extract information from complex data types, branch on the structure of data, and apply specific actions based on different forms of data.

PEP 604: New Type Union Operator as X|Y 

PEP 613: Explicit Type Aliases 

PEP 647: User-Defined Type Guards 

PEP 612: Parameter Specification Variables

You can see more on the official webpage.

Python Qt5 : The QSvgWidget for the SVG image format.

In this example tutorial, I will show you how can show an SVG image format with the PyQt5 and QSvgWidget.

I used Fedora 35 Beta with python pyqt5 package install with pip tool.

$ pip install pyqt5

The source code in the Python programming language is this:

The result image is this:

The Hitchhiker’s Guide to Python.

Greetings, Earthling! Welcome to The Hitchhiker’s Guide to Python.

This project comes with this license, is free, and help you to learn Python:

Creative Commons Legal Code

Attribution-NonCommercial-ShareAlike 3.0 Unported ...

This guide is currently under heavy development. This opinionated guide exists to provide both novice and expert Python developers a best practice handbook to the installation, configuration, and usage of Python on a daily basis.

You can contribute to this project on the GitHub project.

Python 3.7.11 : My colab tutorials - part 018.

In this colab tutorial, you can see how to use the webcam with python and javascript.

This colab notebook can be found on my colab project on the GitHub webpage.

• catafest_001.ipynb - first step, import TensorFlow;
• catafest_002.ipynb - testing the GPU , Linux commands and python modules torch and fastai;
• catafest_003.ipynb - testing the Altair;
• catafest_004.ipynb - testing the cirq python package for quantum computing;
• catafest_005.ipynb - using the estimator on tensoflow 2.0;
• python_imdb_001.ipynb - using the colab with python module imdbpy;
• catafest_006.ipynb - google authentification and google.colab drive and files
• catafest_007.ipynb - test with https://github.com/harrism/numba_examples/blob/master/mandelbrot_numba.ipynb
• catafest_008.ipynb - few simple examples with selenium and chromium-chromedriver;
• catafest_009.ipynb - show you how to use %% colab features;
• catafest_010.ipynb - example with Detectron2 is Facebook AI Research's with state-of-the-art object detection algorithms;
• catafest_011.ipynb - test a sound classification with YAMNet from a web example - not very happy with the result;
• catafest_012.ipynb - a simple tutorial about Colab tool and HTML and JavaScript with examples;
• catafest_013.ipynb - a simple tutorial with settings for TPU and IMDB dataset;
• catafest_014.ipynb - get IMDB review dataset and show it;
• catafest_015.ipynb - how to get, show and use it data and create a new train data set from IMDB dataset;
• catafest_016.ipynb - show the shape of the Fashion-MNIST dataset;
• catafest_017.ipynb - this example show you how to write another python script in colab and run it;
• catafest_018.ipynb - PIFuHD demo;
• catafest_019.ipynb - get title from tiles.virtualearth.net;
• catafest_020.ipynb - get video from youtube with pytube, converting to audio, show signal wave, energy and frequency;
• catafest_021.ipynb - BERT is a transformers model with example and sentiment-analysis;
• catafest_022.ipynb - webcam on colab with python and javascript;

Python 3.7.11 : My colab tutorials - part 017.

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, see this https://arxiv.org/abs/1810.04805.

I used transformers, see this video: https://www.youtube.com/watch?v=SZorAJ4I-sA and this: https://arxiv.org/pdf/2003.08271.pdf.

See this colab notebook with examples at my GitHub account.

Python 3.7.11 : My colab tutorials - part 016.

This new colab notebook comes with: get youtube videos with pytube, converting to audio, show signals, energy and frequency.

You can see this work on the GitHub account.