Python 3.13.0 : emoji symbols with PIL.

Today I want to use emoji symbols and I wrote this python script:

from PIL import Image, ImageDraw, ImageFont
import os

# Font size and image dimensions
font_size = 88
width = 640
height = 480

# Use Symbola.ttf from current directory
font_path = "Symbola.ttf"

# Create image
img = Image.new('RGB', (width, height), color='white')
draw = ImageDraw.Draw(img)

# Get font
font = ImageFont.truetype(font_path, font_size)

# Emoji matrix
emoji_matrix = [
    ['😀', '😁', '😂', '🤣', '😃'],
    ['😄', '😅', '😆', '😇', '😈'],
    ['😉', '😊', '😋', '😌', '😍'],
    ['😎', '😏', '😐', '😑', '😒']
]

# Calculate spacing
x_spacing = font_size + 10
y_spacing = font_size + 10

# Calculate starting position to center the grid
start_x = (width - (len(emoji_matrix[0]) * x_spacing)) // 2
start_y = (height - (len(emoji_matrix) * y_spacing)) // 2

# Draw emojis
for i, row in enumerate(emoji_matrix):
    for j, emoji in enumerate(row):
        x = start_x + (j * x_spacing)
        y = start_y + (i * y_spacing)
        draw.text((x, y), emoji, font=font, fill='black')

# Save the image
img.save('emoji_art.png')
print("Emoji art has been created successfully! Check emoji_art.png")

The result image named emoji_art.png is this:

Python 3.13.0 : generates multiple deformed polygonal shapes .

Today I created this source code in python that generates eight random convex polygons. The idea was to create sprites for a 2D game: snowballs, boulders, or similar objects... Obviously I also used Sonet 3.5 artificial intelligence. You can find the source code on the pagure account in fedora.

#!/usr/bin/env python3
"""
SVG Polygon Generator

This script generates multiple deformed polygonal shapes and saves them as separate SVG files.
Each polygon maintains convex properties while having controlled random deformations.

Features:
    - Generates 8 unique polygonal shapes
    - Controls deformation through radial and angular factors
    - Maintains convex properties
    - Exports each shape to a separate SVG file
    - Uses random colors for visual distinction

Usage:
    python generate_svgs.py

Output:
    Creates 8 SVG files named 'polygon_1.svg' through 'polygon_8.svg'
"""

from lxml import etree
import random
import math
from pathlib import Path


def create_svg_root():
    """Create and return a base SVG root element with standard attributes."""
    root = etree.Element("svg")
    root.set("width", "500")
    root.set("height", "500")
    root.set("xmlns", "http://www.w3.org/2000/svg")
    return root


def calculate_points(center_x: float, center_y: float, radius: float, 
                    num_sides: int, deform_factor: float) -> list:
    """
    Calculate polygon points with controlled deformation.

    Args:
        center_x: X coordinate of polygon center
        center_y: Y coordinate of polygon center
        radius: Base radius of the polygon
        num_sides: Number of polygon sides
        deform_factor: Maximum allowed deformation factor

    Returns:
        List of tuples containing (x, y) coordinates
    """
    points = []
    angle_step = 2 * math.pi / num_sides
    
    for i in range(num_sides):
        angle = i * angle_step
        radial_deform = random.uniform(-deform_factor, deform_factor)
        angular_deform = random.uniform(-deform_factor/2, deform_factor/2)
        
        modified_angle = angle + angular_deform
        modified_radius = radius * (1 + radial_deform)
        
        x = center_x + modified_radius * math.cos(modified_angle)
        y = center_y + modified_radius * math.sin(modified_angle)
        points.append((x, y))
    
    return points


def generate_deformed_shapes():
    """Generate multiple deformed polygons and save them to separate SVG files."""
    # Base parameters
    num_sides = 8
    center_x = 250
    center_y = 250
    base_radius = 150
    max_deformation = 0.15
    output_dir = Path("generated_polygons")
    
    # Create output directory if it doesn't exist
    output_dir.mkdir(exist_ok=True)

    for i in range(8):
        root = create_svg_root()
        points = calculate_points(center_x, center_y, base_radius, 
                                num_sides, max_deformation)
        
        path = etree.SubElement(root, "path")
        path_data = f"M {points[0][0]} {points[0][1]}"
        path_data += "".join(f" L {p[0]} {p[1]}" for p in points[1:])
        path_data += " Z"
        
        path.set("d", path_data)
        path.set("fill", "none")
        path.set("stroke", f"#{random.randint(0, 16777215):06X}")
        path.set("stroke-width", "2")
        path.set("opacity", "0.7")

        # Save individual SVG file
        output_file = output_dir / f"polygon_{i+1}.svg"
        tree = etree.ElementTree(root)
        tree.write(str(output_file), pretty_print=True, 
                  xml_declaration=True, encoding='utf-8')
    
    print(f"Generated {num_sides} polygons in {output_dir}")

if __name__ == "__main__":
    generate_deformed_shapes()

Python 3.13.0 : Tested TinyDB on Fedora 41.

Today I tested the TinyDB python package on Fedora 41 Linux distro:

TinyDB is a lightweight document oriented database optimized for your happiness :) It’s written in pure Python and has no external dependencies. The target are small apps that would be blown away by a SQL-DB or an external database server.

The documentation for this python package can be found on the official website.

The install on Fedora 14 distro can be done with pip tool:

pip install tinydb

This is the source code I tested:

from tinydb import TinyDB, Query
import datetime

# Create a TinyDB instance
db = TinyDB('my_database.json')

# Define a schema for our documents
UserSchema = {
    'name': str,
    'email': str,
    'age': int,
    'created_at': datetime.datetime
}# Insert some sample data
users = [
    {'name': 'John Doe', 'email': 'john@example.com', 'age': 30},
    {'name': 'Jane Smith', 'email': 'jane@example.com', 'age': 25},
    {'name': 'Bob Johnson', 'email': 'bob@example.com', 'age': 35}
]

for user in users:
    db.insert(user)

# Querying all users
print("\nQuerying all users:")
all_users = db.all()
for user in all_users:
    print(f"Name: {user['name']}, Email: {user['email']}, Age: {user['age']}")

# Filtering data
print("\nFidig users older than 28:")
older_than_28 = db.search(Query().age > 28)
for user in older_than_28:
    print(f"Name: {user['name']}, Email: {user['email']}, Age: {user['age']}")

# Updating data
print("\nUpdatig John Doe's age:")
db.update({'age': 31}, Query().name == 'John Doe')

# Deleting data
print("\nDeletig Jane Smith:")
doc_ids = [doc.doc_id for doc in db.search(Query().email == 'jane@example.com')]
if doc_ids:
    db.remove(doc_ids=doc_ids)
else:
    print("No document found with email 'jane@example.com'")

# Adding a new field
print("\nAddig a 'city' field to all users:")
for user in db.all():
    user['city'] = 'New York'
    db.update(user, doc_ids=[doc.doc_id for doc in db.search(Query().name == user['name'])])

# Sorting data
print("\nSorting users by age:")
sorted_users = sorted(db.all(), key=lambda x: x['age'])
for user in sorted_users:
    print(f"Name: {user['name']}, Email: {user['email']}, Age: {user['age']}")

# Getting document count
print("\nTotal number of users:", len(db.all()))

# Closing the database connection
db.close()

This is the result:

$ python test_001.py 

Querying all users:
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 30
Name: Jane Smith, Email: jane@example.com, Age: 25
Name: Bob Johnson, Email: bob@example.com, Age: 35

Fidig users older than 28:
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: John Doe, Email: john@example.com, Age: 30
Name: Bob Johnson, Email: bob@example.com, Age: 35

Updatig John Doe's age:

Deletig Jane Smith:

Addig a 'city' field to all users:

Sorting users by age:
Name: John Doe, Email: john@example.com, Age: 31
Name: John Doe, Email: john@example.com, Age: 31
Name: John Doe, Email: john@example.com, Age: 31
Name: John Doe, Email: john@example.com, Age: 31
Name: John Doe, Email: john@example.com, Age: 31
Name: John Doe, Email: john@example.com, Age: 31
Name: John Doe, Email: john@example.com, Age: 31
Name: John Doe, Email: john@example.com, Age: 31
Name: John Doe, Email: john@example.com, Age: 31
Name: John Doe, Email: john@example.com, Age: 31
Name: John Doe, Email: john@example.com, Age: 31
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: Bob Johnson, Email: bob@example.com, Age: 35
Name: Bob Johnson, Email: bob@example.com, Age: 35

Total number of users: 22

Python 3.13.0 : Test the gi python package on Fedora distro linux.

The gi (GObject Introspection) Python package is excellent! It provides Python bindings for GObject-based libraries like GTK, GLib, and Secret Service. It enables you to write native GNOME applications in Python and access system services seamlessly.

First, install these Fedora packages:

[mythcat@fedora ~]# dnf5 install python3-gobject libsecret-devel
...
Package "python3-gobject-3.48.2-3.fc41.x86_64" is already installed.
Package "libsecret-devel-0.21.4-3.fc41.x86_64" is already installed.
...
[mythcat@fedora ~]# dnf5 install gnome-shell gnome-keyring libsecret
...

I used this simple python source code to test the gi python package:

import gi

# Specify the version of Gio and Secret we want to use
gi.require_version('Gio', '2.0')
gi.require_version('Secret', '1')

from gi.repository import Gio, Secret, GLib

def check_schema(schema_name):
    try:
        Gio.Settings.new(schema_name)
        print(f"Schema '{schema_name}' is available")
        return True
    except GLib.GError as e:
        print(f"Schema '{schema_name}' is not installed: {str(e)}")
        return False

def store_secret():
    schema = Secret.Schema.new("org.example.Password",
        Secret.SchemaFlags.NONE,
        {
            "username": Secret.SchemaAttributeType.STRING,
        }
    )
    
    Secret.password_store_sync(schema, 
        {"username": "myuser"},
        Secret.COLLECTION_DEFAULT,
        "My secret item",
        "Hello, World!",
        None)
    
    print("Secret stored successfully")

def get_secret():
    schema = Secret.Schema.new("org.example.Password",
        Secret.SchemaFlags.NONE,
        {
            "username": Secret.SchemaAttributeType.STRING,
        }
    )
    
    password = Secret.password_lookup_sync(schema,
        {"username": "myuser"},
        None)
    
    if password is not None:
        print(f"Retrieved secret: {password}")
    else:
        print("No secret found")

if __name__ == "__main__":
    print("Starting secret operations...")
    store_secret()
    get_secret()
    print("Finished secret operations.")

The result is this:

$ python test_001.py 
Starting secret operations...
Secret stored successfully
Retrieved secret: Hello, World!
Finished secret operations.

Python 3.13.0 : know this -OOt ?

Today, I follow the actions from NEMO the basic explorer files from linux and I found this: -OOt

This first source code:

#!/usr/bin/python3 -OOt

... this is new, and refers to Python compiler optimizations.

The -OOt par in the shebang line #!/usr/bin/python3 -OOt refers to Python compiler optimizations:

1. -O: This flag enables basic optimizations. It tells the Python compiler to optimize constants and global variables.
2. -O2: This flag enables more aggressive optimizations. It applies additional compiler passes to further optimize the code .
3. -Ot: This flag optimizes for size. It reduces memory usage by eliminating unused variables and dead code.

So, -OOt combines three levels of optimization:

• Basic optimization (-O)
• More aggressive optimization (-O2)
• Optimization for size (-Ot)

Python 3.13.0 : Testing ntplib on Fedora 42.

Today I tested the ntplib python package on Fedora 42 with the python 3.13.0 version.

This is the source code:

from ntplib import NTPClient
import socket
import os
import datetime

def sync_ntp_server(server_address='pool.ntp.org'):
    try:
        client = NTPClient()
        response = client.request(server_address)
        
        # Get the offset in seconds
        offset = response.offset
        
        # Calculate the drift rate (seconds per day)
        drift_rate = offset * 86400 / response.tx_time
        
        print(f"NTP synchronization successful. Offset: {offset:.2f} seconds")
        print(f"Drift rate: {drift_rate:.2f} seconds per day")
        
        # Apply the offset to the system clock
        os.system(f"date -s '@{response.tx_time}'")
        
        # Optionally, you can also apply the drift rate to the system clock
        # However, this is generally not recommended as it can lead to further drift
        # os.system(f"ntpdate -d {server_address}")
        
    except Exception as e:
        print(f"Error synchronizing NTP: {e}")

# Disable SELinux temporarily
os.system("setenforce 0")

# Sync with NTP server
sync_ntp_server()

# Print current system time after sync
current_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
print(f"Current system time after sync: {current_time}")

The result is output is in the romanian language but this is not a problem for programmers:

[mythcat@fedora network_python_tools]$ pip install ntplib
Defaulting to user installation because normal site-packages is not writeable
Collecting ntplib
  Downloading ntplib-0.4.0-py2.py3-none-any.whl.metadata (1.6 kB)
Downloading ntplib-0.4.0-py2.py3-none-any.whl (6.8 kB)
Installing collected packages: ntplib
Successfully installed ntplib-0.4.0
[mythcat@fedora network_python_tools]$ python ntplib_test_001.py 
...
NTP synchronization successful. Offset: -5.25 seconds
Drift rate: -0.00 seconds per day
date: nu se poate stabili data: Operație nepermisă
vineri 25 octombrie 2024, 22:24:13 +0300
Current system time after sync: 2024-10-25 22:24:19

Python 3.13.0rc1 : ... pkg_resources is deprecated as an API .

I tried an old version of python script for upgrade all my ython packages on windows 10 with pkg_resources python package.

I got this error:

DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html

... and this python script will upgrade all python packages

import subprocess

try:
    # Obține lista pachetelor învechite
    outdated_packages = subprocess.check_output(["pip", "list", "--outdated", "--format=columns"]).decode("utf-8")
    packages = [line.split()[0] for line in outdated_packages.splitlines()[2:]]
    
    if not packages:
        print("Toate pachetele sunt deja actualizate.")
    else:
        print("Pachete Python învechite: ", packages)
        
        # Actualizează fiecare pachet
        for package in packages:
            print("Actualizează pachetul: ", package)
            subprocess.check_call(["pip", "install", "--upgrade", package])
except subprocess.CalledProcessError as e:
    print("A apărut o eroare la rularea comenzii pip:", e)
except Exception as e:
    print("A apărut o eroare neașteptată:", e)

Python 3.12.3 : 8in8 game project with pygame and agentpy - 001.

I started a game project with the python packages pygame and agentpy in the Fedora Linux distribution.

You can find it on my fedora pagure repo

Python 3.12.3 : PyGame, DuckDB and AgentPy on Fedora 42 linux distro.

Today I tested the installation of some python packages in the Fedora 42 Linux distribution. On the Windows 10 operating system I failed to install pygame because it was trying to build.

[mythcat@fedora ~]$ pip install duckdb --upgrade
Defaulting to user installation because normal site-packages is not writeable
Collecting duckdb
...
Installing collected packages: duckdb
Successfully installed duckdb-1.1.0
[mythcat@fedora ~]$ pip install pygame
Defaulting to user installation because normal site-packages is not writeable
Requirement already satisfied: pygame in ./.local/lib/python3.12/site-packages (2.5.2)
[mythcat@fedora ~]$ pip install agentpy
...
Installing collected packages: scipy, networkx, kiwisolver, joblib, fonttools, dill, cycler, contourpy, pandas, multiprocess, matplotlib, SALib, agentpy
Successfully installed SALib-1.5.1 agentpy-0.1.5 contourpy-1.3.0 cycler-0.12.1 dill-0.3.8 fonttools-4.53.1 joblib-1.4.2 kiwisolver-1.4.7 matplotlib-3.9.2 multiprocess-0.70.16 networkx-3.3 pandas-2.2.2 scipy-1.14.1

Python 3.13.0rc1 : AgentPy python module ...

AgentPy is an open-source library for the development and analysis of agent-based models in Python.

The project can be found on the GitHub repo.

This can be install with the pip tool:

pip install agentpy
Collecting agentpy
...
Successfully installed SALib-1.5.1 agentpy-0.1.5 contourpy-1.3.0 cycler-0.12.1 dill-0.3.8 fonttools-4.53.1 
joblib-1.4.2 kiwisolver-1.4.7 matplotlib-3.9.2 multiprocess-0.70.16 networkx-3.3 packaging-24.1 
pillow-10.4.0 pyparsing-3.1.4 scipy-1.14.1

This is the source code:

import agentpy as ap
import matplotlib.pyplot as plt

# define Agent class
class RandomWalker(ap.Agent):
    def setup(self):
        self.position = [0, 0]

    def step(self):
        self.position += self.model.random.choice([[1, 0], [-1, 0], [0, 1], [0, -1]])

# define Model class
class RandomWalkModel(ap.Model):
    def setup(self):
        self.agents = ap.AgentList(self, self.p.agents, RandomWalker)
        self.agents.setup()

    def step(self):
        self.agents.step()

    def update(self):
        self.record('Positions', [agent.position for agent in self.agents])

    def end(self):
        positions = self.log['Positions']
        plt.figure()
        for pos in positions:
            plt.plot(*zip(*pos))
        plt.show()

# configuration and running 
parameters = {'agents': 5, 'steps': 20}
model = RandomWalkModel(parameters)
results = model.run()

The result is a simple graph with these output:

python test001.py
Matplotlib is building the font cache; this may take a moment.
Completed: 20 steps
Run time: 0:00:50.823483
Simulation finished

Python Qt6 : Use regular expression with PyQt6.

Today I tested a python source code with PyQt6.

This source code let you to clean the text by HTML tags and regular expression in realtime.

If you want to parse in realtime then check the Realtime and add the regular expresion in editbox.

This is the result:

This is the source code I used to parse realtime regular expresion on editbox

from PyQt6.QtWidgets import QApplication, QMainWindow, QTextEdit, QVBoxLayout, QHBoxLayout, QWidget, QPushButton, QCheckBox, QLineEdit, QLabel
from PyQt6.QtGui import QTextDocument
from PyQt6.QtCore import Qt
import re

class MainWindow(QMainWindow):
    def __init__(self):
        super().__init__()

        self.setWindowTitle("HTML Cleaner")

        self.text_edit = QTextEdit()
        self.clean_button = QPushButton("Clean HTML")
        self.transform_div_checkbox = QCheckBox("Transform 
 tags")
        self.realtime_checkbox = QCheckBox("Realtime")
        self.regex_edit = QLineEdit()
        self.regex_edit.setPlaceholderText("Enter regex pattern")
        self.regex_edit.setEnabled(False)  # Dezactivăm inițial

        top_layout = QHBoxLayout()
        top_layout.addWidget(self.clean_button)
        top_layout.addWidget(self.transform_div_checkbox)
        top_layout.addWidget(QLabel("Regex:"))
        top_layout.addWidget(self.regex_edit)
        top_layout.addWidget(self.realtime_checkbox)

        main_layout = QVBoxLayout()
        main_layout.addLayout(top_layout)
        main_layout.addWidget(self.text_edit)

        container = QWidget()
        container.setLayout(main_layout)
        self.setCentralWidget(container)

        self.clean_button.clicked.connect(self.clean_html)
        self.realtime_checkbox.stateChanged.connect(self.toggle_realtime)
        self.regex_edit.textChanged.connect(self.realtime_update)

    def clean_html(self):
        html_text = self.text_edit.toPlainText()
        clean_text = self.remove_html_tags(html_text)
        self.text_edit.setPlainText(clean_text)

    def remove_html_tags(self, text):
        # Remove CSS
        text = re.sub(r'.*?', '', text, flags=re.DOTALL)
        # Remove JavaScript
        text = re.sub(r'.*?', '', text, flags=re.DOTALL)
        # Remove HTML comments
        text = re.sub(r'', '', text, flags=re.DOTALL)
        # Transform 
 tags if checkbox is checked
        if self.transform_div_checkbox.isChecked():
            text = re.sub(r']*>', '
', text)
        # Remove HTML tags but keep content
        clean = re.compile('<.*?>')
        text = re.sub(clean, '', text)
        # Remove empty lines
        text = re.sub(r'\n\s*\n', '\n', text)
        return text

    def toggle_realtime(self):
        if self.realtime_checkbox.isChecked():
            self.regex_edit.setEnabled(True)  # Activăm editbox-ul
            self.text_edit.textChanged.connect(self.realtime_update)
        else:
            self.regex_edit.setEnabled(False)  # Dezactivăm editbox-ul
            self.text_edit.textChanged.disconnect(self.realtime_update)

    def realtime_update(self):
        if self.realtime_checkbox.isChecked():
            html_text = self.text_edit.toPlainText()
            regex_pattern = self.regex_edit.text()
            if regex_pattern:
                try:
                    html_text = re.sub(regex_pattern, '', html_text)
                except re.error:
                    pass  # Ignore regex errors
            self.text_edit.blockSignals(True)
            self.text_edit.setPlainText(html_text)
            self.text_edit.blockSignals(False)

app = QApplication([])
window = MainWindow()
window.show()
app.exec()

Python 3.12.4 : DuckDB operate in in-memory mode.

DuckDB aims to automatically achieve high performance by using well-chosen default configurations and having a forgiving architecture. Of course, there are still opportunities for tuning the system for specific workloads. The Performance Guide's page contain guidelines and tips for achieving good performance when loading and processing data with DuckDB.

DuckDB can operate in in-memory mode. In most clients, this can be activated by passing the special value :memory: as the database file or omitting the database file argument.

You can use with python or another programming language.

I used Python 3.13.0rc1 version and pip tool ...

pip install duckdb --upgrade
Collecting duckdb
...
Installing collected packages: duckdb
Successfully installed duckdb-1.0.0

I created a python script :

python test_memory_duckdb_sqlite_db.py
[]
[('table', 'users', 'users', 0, 'CREATE TABLE users(id BIGINT PRIMARY KEY, first_name VARCHAR, last_name VARCHAR, occupation VARCHAR, hobby VARCHAR, year_of_birth BIGINT, age BIGINT);')]

This is the source code I used:

import duckdb

# Conectare la baza de date în memorie
con = duckdb.connect(database=':memory:')

# Instalează extensia sqlite
con.execute("INSTALL sqlite")

# Încarcă extensia sqlite
con.execute("LOAD sqlite")

# Verifică dacă extensia este încărcată
result = con.execute("SELECT * FROM sqlite_master").fetchall()
print(result)

# Conectare la baza de date pe disc
con_disk = duckdb.connect(database='sqlite_database.db', read_only=False)

# Instalează extensia sqlite pentru baza de date pe disc
con_disk.execute("INSTALL sqlite")

# Încarcă extensia sqlite pentru baza de date pe disc
con_disk.execute("LOAD sqlite")

# Verifică dacă extensia este încărcată pentru baza de date pe disc
result_disk = con_disk.execute("SELECT * FROM sqlite_master").fetchall()
print(result_disk)

Python 3.13.0rc1 : Use faker with build pandas and PyQt6.

In this tutorial I will show you how I build pandas and use faker and PyQt6.

The faker python module is a powerful library designed to generate fake data, which is particularly useful for testing, filling databases, and creating realistic-looking sample data.

I used python version 3.13.0rc1 and I install with pip tool faker and the pandas and PyQt6 is build with pip tool.

pip install faker
Collecting faker
...
Installing collected packages: six, python-dateutil, faker
Successfully installed faker-28.1.0 python-dateutil-2.9.0.post0 six-1.16.0

The pandas installation fail first time then today works, maybe comes with fixes ...

pip install pandas
...
Successfully built pandas
Installing collected packages: pytz, tzdata, pandas
Successfully installed pandas-2.2.2 pytz-2024.1 tzdata-2024.1

Let's try one example to see how this works, I used copilot from microsoft to generate this first source code:

import sys
from PyQt6.QtWidgets import QApplication, QMainWindow, QTableView
from PyQt6.QtCore import Qt, QAbstractTableModel
import pandas as pd
from faker import Faker

# Generăm date false folosind Faker
fake = Faker()
data = {
    'Name': [fake.name() for _ in range(100)],
    'Address': [fake.address() for _ in range(100)],
    'Email': [fake.email() for _ in range(100)],
    'IP Address': [fake.ipv4() for _ in range(100)]  # Adăugăm adresa IP
}

# Creăm un DataFrame Pandas
df = pd.DataFrame(data)

# Definim un model pentru QTableView
class PandasModel(QAbstractTableModel):
    def __init__(self, df):
        super().__init__()
        self._df = df

    def rowCount(self, parent=None):
        return len(self._df)

    def columnCount(self, parent=None):
        return self._df.shape[1]

    def data(self, index, role=Qt.ItemDataRole.DisplayRole):
        if index.isValid():
            if role == Qt.ItemDataRole.DisplayRole:
                return str(self._df.iloc[index.row(), index.column()])
        return None

    def headerData(self, section, orientation, role=Qt.ItemDataRole.DisplayRole):
        if role == Qt.ItemDataRole.DisplayRole:
            if orientation == Qt.Orientation.Horizontal:
                return self._df.columns[section]
            else:
                return str(section)
        return None

# Aplicatia PyQt6
app = QApplication(sys.argv)
window = QMainWindow()
view = QTableView()

# Setăm modelul pentru QTableView
model = PandasModel(df)
view.setModel(model)

# Configurăm fereastra principală
window.setCentralWidget(view)
window.resize(800, 600)
window.show()

# Rulăm aplicația
sys.exit(app.exec())

Python Qt6 : Two sliders

I used the Python 3.13.0rc1 version and PyQt6 6.7.1 version.

This is the source code:

import sys
from PyQt6.QtWidgets import QApplication, QWidget, QVBoxLayout, QSlider
from PyQt6.QtCore import Qt

class SliderWindow(QWidget):
    def __init__(self):
        super().__init__()

        self.setWindowTitle("Two Slideres")
        self.setGeometry(100, 100, 640, 200)

        layout = QVBoxLayout()

        self.slider_max = QSlider(Qt.Orientation.Horizontal)
        self.slider_max.setMinimum(0)
        self.slider_max.setMaximum(100)
        self.slider_max.setValue(100)
        self.slider_max.valueChanged.connect(self.update_min_slider)

        self.slider_min = QSlider(Qt.Orientation.Horizontal)
        self.slider_min.setMinimum(0)
        self.slider_min.setMaximum(100)
        self.slider_min.setValue(0)
        self.slider_min.valueChanged.connect(self.update_max_slider)

        layout.addWidget(self.slider_max)
        layout.addWidget(self.slider_min)

        self.setLayout(layout)

    def update_min_slider(self, value):
        self.slider_min.blockSignals(True)
        self.slider_min.setValue(100 - value)
        self.slider_min.blockSignals(False)

    def update_max_slider(self, value):
        self.slider_max.blockSignals(True)
        self.slider_max.setValue(100 - value)
        self.slider_max.blockSignals(False)

if __name__ == "__main__":
    app = QApplication(sys.argv)
    window = SliderWindow()
    window.show()
    sys.exit(app.exec())

Python 3.13.0rc1 : Test MSBuild with PyQt6.

The goal of this tutorial is to test the build process of the Python package.

Installing the PyQt6 python module may come with the build error.

In this case, MS Build is installed from the official website, and then other necessary Python modules can be installed depending on the files needed to build the PyQt6 package.

pip install --upgrade setuptools

pip install msvc-runtime
ERROR: Could not find a version that satisfies the requirement msvc-runtime (from versions: none)
ERROR: No matching distribution found for msvc-runtime

pip install pyqt6
Collecting pyqt6
  Using cached PyQt6-6.7.1-cp38-abi3-win_amd64.whl.metadata (2.1 kB)
...
Successfully built PyQt6-sip
Installing collected packages: PyQt6-Qt6, PyQt6-sip, pyqt6
Successfully installed PyQt6-Qt6-6.7.2 PyQt6-sip-13.8.0 pyqt6-6.7.1

This process uses a lot of files and MSBuild needs some Gb free on the hard disk.

Python 3.13.0rc1 : Using pydoc python module.

This is default python module.

You can find pydoc - documentation.

Simple use of this python module for example: sys python module to see the documentation.

PythonProjects\test_pydoc>python -m pydoc sys

Using the w argument willcreate a HTML file with the documentation.

In this example will be sys.html, because is sys python module.

PythonProjects\test_pydoc>python -m pydoc -w sys
wrote sys.html

Best feature is search by word and show the result as python modules, in this case will show a list ...

PythonProjects\test_pydoc>python -m pydoc -k url
nturl2path - Convert a NT pathname to a file URL and vice versa.
test_sqlite3: testing with SQLite version 3.45.3
test.test_urllib - Regression tests for what was in Python 2's "urllib" module
test.test_urllib2
test.test_urllib2_localnet
test.test_urllib2net

Share the documentation with an server, in this case is set to localhost:

\PythonProjects\test_pydoc>python -m pydoc -p 1234
Server ready at http://localhost:1234/
Server commands: [b]rowser, [q]uit

You can create your python module script named test.py formated and then use pydoc.

"""
my python module
====
This is documentation
"""
def test():
"""
Function test
"""
    print("test")

Use this to show the text from your python source script module:

python -m pydoc test
PythonProjects\test_pydoc>python -m pydoc test
Help on module test:

NAME
    test

FILE
...

Python 3.12.1 : Web server with SQLite database using flask - update.

Update with new URL with params, see the first tutorial:

from flask import Flask, request, jsonify, render_template_string
import sqlite3
from datetime import datetime

app = Flask(__name__)

# Clasa pentru serverul SQL
class SQLiteServer:
    def __init__(self, db_name):
        self.db_name = db_name
        self.init_db()

    def init_db(self):
        conn = sqlite3.connect(self.db_name)
        c = conn.cursor()
        c.execute('''
            CREATE TABLE IF NOT EXISTS users (
                id INTEGER PRIMARY KEY,
                first_name TEXT,
                last_name TEXT,
                occupation TEXT,
                hobby TEXT,
                year_of_birth INTEGER,
                age INTEGER
            )
        ''')
        conn.commit()
        conn.close()

    def calculate_age(self, year_of_birth):
        # Adjust year_of_birth if only two digits are provided
        if len(str(year_of_birth)) == 2:
            if year_of_birth > int(str(datetime.now().year)[-2:]):
                year_of_birth += 1900
            else:
                year_of_birth += 2000
        current_year = datetime.now().year
        return current_year - year_of_birth

    def add_user(self, first_name, last_name, occupation, hobby, year_of_birth):
        age = self.calculate_age(year_of_birth)
        conn = sqlite3.connect(self.db_name)
        c = conn.cursor()
        c.execute('''
            INSERT INTO users (first_name, last_name, occupation, hobby, year_of_birth, age)
            VALUES (?, ?, ?, ?, ?, ?)
        ''', (first_name, last_name, occupation, hobby, year_of_birth, age))
        conn.commit()
        conn.close()

    def get_users(self):
        conn = sqlite3.connect(self.db_name)
        c = conn.cursor()
        c.execute("SELECT * FROM users")
        users = c.fetchall()
        conn.close()
        return users
    def get_users_jsonify():
        conn = sqlite3.connect('sqlite_database.db')
        c = conn.cursor()
        c.execute("SELECT * FROM users")
        users = c.fetchall()
        conn.close()
        return jsonify(users)

# Clasa pentru serverul web
class WebServer:
    def __init__(self, sqlite_server):
        self.sqlite_server = sqlite_server

    def run(self):
        app.run(debug=True)
    #   adauga user si buton de redirect la pagina users
    @app.route('/')
    def index():
        users = sqlite_server.get_users()
        return render_template_string('''
            <!DOCTYPE html>
            <html lang="en">
            <head>
                <meta charset="UTF-8">
                <meta name="viewport" content="width=device-width, initial-scale=1.0">
                <title>Flask website for testing cypress with sqlite</title>
            </head>
            <body>
                <h2>Add User</h2>
                <form action="/add_user" method="post">
                    First Name: <input type="text" name="first_name"><br>
                    Last Name: <input type="text" name="last_name"><br>
                    Occupation: <input type="text" name="occupation"><br>
                    Hobby: <input type="text" name="hobby"><br>
                    Year of Birth: <input type="text" name="year_of_birth"><br>
                    <input type="submit" value="Add User">
                </form>
                <a href="http://127.0.0.1:5000/users"><button type="button">Show Users</button></a>
            </body>
            </html>
        ''', users=users)
    @app.route('/add_user', methods=['POST'])
    def add_user():
        first_name = request.form['first_name']
        last_name = request.form['last_name']
        occupation = request.form['occupation']
        hobby = request.form['hobby']
        year_of_birth = int(request.form['year_of_birth'])
        sqlite_server.add_user(first_name, last_name, occupation, hobby, year_of_birth)
        return 'User added successfully! <a href="/">Go back</a>'
    @app.route('/users', methods=['GET'])
    def get_users():
        query_type = request.args.get('query_type', 'simple')
        
        conn = sqlite3.connect('sqlite_database.db')
        c = conn.cursor()
        
        try:
            c.execute('SELECT name FROM sqlite_master WHERE type="table" AND name="users"')
            if not c.fetchone():
                return jsonify({"error": "Table 'users' does not exist"})

            if query_type == 'advanced':
                # Advanced query logic
                first_name = request.args.get('first_name')
                last_name = request.args.get('last_name')
                occupation = request.args.get('occupation')
                hobby = request.args.get('hobby')
                year_of_birth = request.args.get('year_of_birth')

                query = 'SELECT * FROM users WHERE 1=1'
                params = []
                # Exemple query simple 
                # Basic query: /users
                # Simple query: /users?query_type=simple for simple selection
                # Addvanced query: /users?query_type=advanced&first_name=John&occupation=Engineer for advanced querying
                # Advanced query with name search: /users?query_type=advanced&first_name=John&last_name=Doe
                # Query by occupation: /users?query_type=advanced&occupation=Engineer
                # Query by hobby: /users?query_type=advanced&hobby=Reading
                # Query by year of birth: /users?query_type=advanced&year_of_birth=1990

                if first_name:
                    query += ' AND first_name LIKE ?'
                    params.append(f'%{first_name}%')
                if last_name:
                    query += ' AND last_name LIKE ?'
                    params.append(f'%{last_name}%')
                if occupation:
                    query += ' AND occupation LIKE ?'
                    params.append(f'%{occupation}%')
                if hobby:
                    query += ' AND hobby LIKE ?'
                    params.append(f'%{hobby}%')
                if year_of_birth:
                    query += ' AND year_of_birth = ?'
                    params.append(year_of_birth)

                # Query by minimum age: /users?query_type=advanced&min_age=30
                # Query by maximum age: /users?query_type=advanced&max_age=50
                # Query with ordering: /users?query_type=advanced&order_by=last_name
                # Query with limit: /users?query_type=advanced&limit=10
                # Combined query: /users?query_type=advanced&first_name=John&occupation=Engineer&min_age=25&order_by=year_of_birth&limit=5          
                # Additional advanced query options
                for param, value in request.args.items():
                    match param:
                        case 'min_age':
                            query += ' AND (? - year_of_birth) >= ?'
                            params.extend([datetime.now().year, int(value)])
                        case 'max_age':
                            query += ' AND (? - year_of_birth) <= ?'
                            params.extend([datetime.now().year, int(value)])
                        case 'order_by':
                            query += f' ORDER BY {value}'
                        case 'limit':
                            query += ' LIMIT ?'
                            params.append(int(value))
                c.execute(query, params)
            else:
                # Simple query logic
                c.execute('SELECT * FROM users')

            users = c.fetchall()
        except sqlite3.OperationalError as e:
            return jsonify({"error": str(e)})
        finally:
            conn.close()
        
        return jsonify(users)

# Instanțierea serverului SQL și a serverului web
sqlite_server = SQLiteServer('sqlite_database.db')
web_server = WebServer(sqlite_server)

if __name__ == '__main__':
    web_server.run()

Python 3.12.1 : Web server with SQLite database using flask.

This python surce script can be used to start a web server with an SQLite server.

For example, you can use this to test with javascript on sql server, see next image:

This is the source code:

from flask import Flask, request, jsonify, render_template_string
import sqlite3
from datetime import datetime

app = Flask(__name__)

# Clasa pentru serverul SQL
class SQLServer:
    def __init__(self, db_name):
        self.db_name = db_name
        self.init_db()

    def init_db(self):
        conn = sqlite3.connect(self.db_name)
        c = conn.cursor()
        c.execute('''
            CREATE TABLE IF NOT EXISTS users (
                id INTEGER PRIMARY KEY,
                first_name TEXT,
                last_name TEXT,
                occupation TEXT,
                hobby TEXT,
                year_of_birth INTEGER,
                age INTEGER
            )
        ''')
        conn.commit()
        conn.close()

    def calculate_age(self, year_of_birth):
        # Adjust year_of_birth if only two digits are provided
        if len(str(year_of_birth)) == 2:
            if year_of_birth > int(str(datetime.now().year)[-2:]):
                year_of_birth += 1900
            else:
                year_of_birth += 2000
        current_year = datetime.now().year
        return current_year - year_of_birth

    def add_user(self, first_name, last_name, occupation, hobby, year_of_birth):
        age = self.calculate_age(year_of_birth)
        conn = sqlite3.connect(self.db_name)
        c = conn.cursor()
        c.execute('''
            INSERT INTO users (first_name, last_name, occupation, hobby, year_of_birth, age)
            VALUES (?, ?, ?, ?, ?, ?)
        ''', (first_name, last_name, occupation, hobby, year_of_birth, age))
        conn.commit()
        conn.close()

    def get_users(self):
        conn = sqlite3.connect(self.db_name)
        c = conn.cursor()
        c.execute("SELECT * FROM users")
        users = c.fetchall()
        conn.close()
        return users

# Clasa pentru serverul web
class WebServer:
    def __init__(self, sql_server):
        self.sql_server = sql_server

    def run(self):
        app.run(debug=True)

    @app.route('/')
    def index():
        users = sql_server.get_users()
        return render_template_string('''
            <h1>Users</h1>
            <ul>
                {% for user in users %}
                    <li>{{ user[1] }} {{ user[2] }} - {{ user[3] }} - {{ user[4] }} - {{ user[5] }} ({{ user[6] }} years old)</li>
                {% endfor %}
            </ul>
            <h2>Add User</h2>
            <form action="/add_user" method="post">
                First Name: <input type="text" name="first_name"><br>
                Last Name: <input type="text" name="last_name"><br>
                Occupation: <input type="text" name="occupation"><br>
                Hobby: <input type="text" name="hobby"><br>
                Year of Birth: <input type="text" name="year_of_birth"><br>
                <input type="submit" value="Add User">
            </form>
        ''', users=users)

    @app.route('/add_user', methods=['POST'])
    def add_user():
        first_name = request.form['first_name']
        last_name = request.form['last_name']
        occupation = request.form['occupation']
        hobby = request.form['hobby']
        year_of_birth = int(request.form['year_of_birth'])
        sql_server.add_user(first_name, last_name, occupation, hobby, year_of_birth)
        return 'User added successfully! <a href="/">Go back</a>'

# Instanțierea serverului SQL și a serverului web
sql_server = SQLServer('example.db')
web_server = WebServer(sql_server)

if __name__ == '__main__':
    web_server.run()

Blender 3D and python scripting - part 029.

This is a simple Blender 3D script that render images from myimage_000 to myimage_035 around object named Cube.

The script can be changed with any object and any steps for 0 to 360 degree.

import bpy
import math
# Set the object that the camera will orbit around
#target_object = bpy.data.objects["MyObject"]

# Create a new empty object
empty = bpy.data.objects.new("Empty", None)

# Set the empty object's location to the origin point
empty.location = (0, 0, 0)

# Set the starting position for the camera
camera = bpy.data.objects["Camera"]

# Set the number of degrees to rotate the camera around the object
degrees = 360

# Set the distance that the camera should be from the object
distance = 7.6

# Set the speed at which the camera should orbit
speed = 10

# Set the direction in which the camera should orbit (1 for clockwise, -1 for counter-clockwise)
direction = 1

# Set the camera to track the object
bpy.ops.object.select_all(action="DESELECT")
camera.select_set(True)

# Set the distance to origin point
camera.location = (-distance, 0, 0)
bpy.context.view_layer.objects.active = camera

# Remove all constraints from the object "Cube"
bpy.data.objects['Cube'].select_get()
bpy.context.view_layer.objects.active = bpy.data.objects['Cube']
bpy.ops.object.constraints_clear()

# Add a track to constraint to the object and set it
bpy.ops.object.constraint_add(type="TRACK_TO")
bpy.ops.object.track_set(type="TRACKTO")

# Set the target object as the tracking target
bpy.data.objects['Cube'].select_get()
bpy.context.view_layer.objects.active = bpy.data.objects['Cube']

# Select the file image format
bpy.context.scene.render.image_settings.file_format = 'PNG'

# Animate the camera orbiting around the object
for frame in range(0, 36):
    # Set the current frame
    bpy.context.scene.frame_set(frame)

    # Calculate the new position for the camera based on its distance from the object
    x = distance * math.sin(math.radians(frame*speed*direction))
    y = distance * math.cos(math.radians(frame*speed*direction))
    camera.location = (x,y,0)
    # Set the output path for the rendered image
    bpy.context.scene.render.filepath = "C:\\tmp\\myimage_" + str(frame).zfill(3) + ".png"
    # Render the frame and save it to the output file
    bpy.ops.render.render(write_still=True)

The Zen of Python ...

... see the The Zen of Python, with this source code import this:

python
Python 3.12.4 (tags/v3.12.4:8e8a4ba, Jun  6 2024, 19:30:16) [MSC v.1940 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import this
The Zen of Python, by Tim Peters

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!