Python 3.9.1 : Testing the drawSvg python package.

The tutorial for today is about drawSvg python package.
This python package let you to create SVG images (vector drawings) and rendering them or displaying them in a Jupyter notebook.
Let's install it with pip3 tool:

[mythcat@desk ~]$ cd PythonProjects/
[mythcat@desk PythonProjects]$ pip3 install drawSvg
...
Successfully installed drawSvg-1.7.0 imageio-2.9.0

A simple source code test added to svg_001.py python script:

import drawSvg as draw

# Draw a frame of the animation
def draw_frame(t):
    #Create draw surface and add a geometric shapes ...
    out = draw.Drawing(1, 1, origin=(0,0))
    out.setRenderSize(h=460)
    out.append(draw.Rectangle(0, 0, 5, 5, fill='white'))
    y = t + 0.3
    out.append(draw.Circle(0.5, y, 0.5, fill='blue'))
    return out

with draw.animate_video('example.gif', draw_frame, duration=0.01) as anim:
    # Add each frame to the animation
    for i in range(20):
        anim.draw_frame(i/10)

You can change the source code and open the GIF animation file:

[mythcat@desk PythonProjects]$ vi svg_001.py
[mythcat@desk PythonProjects]$ python svg_001.py 
[mythcat@desk PythonProjects]$ google-chrome example.gif

The result of the source code is this:

Python 3.6.9 : Ursina python game engine - part 001 .

I wrote the tutorial a few days ago and today I completed it with a video clip ...
The official webpage comes with this intro:
Ursina makes it easier to develop games, visualizations and other kinds of software.
The concise API combined with the power of the Python programming language, makes life easier for the developer so they can focus on what they are making.
Ursina can be used on Windows and Linux
Today I tested on Fedora Linux and works great.
First, the install process is easy with pip3 tool.

[mythcat@desk ~]$ pip3 install ursina
Defaulting to user installation because normal site-packages is not writeable
Requirement already satisfied: ursina in ./.local/lib/python3.9/site-packages (3.2.2)
Requirement already satisfied: screeninfo in ./.local/lib/python3.9/site-packages (from ursina) (0.6.6)
Requirement already satisfied: numpy in /usr/lib64/python3.9/site-packages (from ursina) (1.19.4)
Requirement already satisfied: panda3d in ./.local/lib/python3.9/site-packages (from ursina) (1.10.7)
Requirement already satisfied: pyperclip in ./.local/lib/python3.9/site-packages (from ursina) (1.8.1)
Requirement already satisfied: pillow in /usr/lib64/python3.9/site-packages (from ursina) (7.2.0)

Let's create some examples and see how this python package works.
Create a python script file:

[mythcat@desk ~]$ cd PythonProjects/
[mythcat@desk PythonProjects]$ vi ursina_001.py

Add this simple example:

from ursina import *
# create the application
app = Ursina()
# set some data , like a cube
ground = Entity(
    model = 'cube',
    color = color.blue,
    z = -.1,
    y = -3,
    origin = (0, .5),
    scale = (50, 1, 10),
    collider = 'box'
    )
# run the application
app.run()

And the last pas, run it with python:

[mythcat@desk PythonProjects]$ python ursina_001.py 
ursina version: 3.2.2
package_folder: /home/mythcat/.local/lib/python3.9/site-packages/ursina
asset_folder: .
psd-tools not installed
which: no blender in (/usr/local/bin:/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/sbin:
/home/mythcat/.composer/vendor/bin:/home/mythcat/.dotnet/tools:/var/lib/snapd/snap/bin)
blender_paths:
{}
OS: posix
screen resolution: (1280, 1024)
Known pipe types:
  glxGraphicsPipe
(all display modules loaded.)
render mode: default
no settings.py file
no settings.py file
development mode: True
application successfully started

You can read on web!:

Python 3.6.9 : My colab tutorials - part 010.

In this tutorial created with Colab online tool I used HTML and JavaScript source code.
The tutorial is easy to understand and use it.
You can see all my examples of my GitHub repo.

Python 3.6.9 : My colab tutorials - part 009.

I update may colab work and I add new notebooks.
You can see all of these on my GitHub account.
These are examples:

• 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;