PyQt6 : ... management of installations and build python package.

Yesterday I created a small project for managing Python packages and building a new package based on added modules. I only tested the local installations of various Python versions and the creation of a new package, but it worked.

python catafest_build_package_001.py
🔍 Verificare module standard...
[✓] Modul standard 'json' este disponibil.
[✓] Modul standard 'subprocess' este disponibil.
[✓] Modul standard 'platform' este disponibil.
[✓] Modul standard 'datetime' este disponibil.
[✓] Modul standard 'os' este disponibil.
[✓] Modul standard 'sys' este disponibil.

📦 Verificare și instalare module pip...
[✓] Modulul 'PyQt6' este deja instalat.
[✓] Modulul 'build' este deja instalat.
* Creating isolated environment: venv+pip...
* Installing packages in isolated environment:
  - setuptools
  - wheel
...

PyQt6 : Use python with ffmpeg tool ...

If you download a video from youtube with high resolution using a tool as yt-dlp then you can get two files with video and audio content:

... one with be with .f401.mp4 and another with .f251-9.webm and using the ffmpeg tool you can create one .mp4 file with both audio and video content.

Let's see a source code with python and PyQt6 module to search into D:\Software folder and create the mp4 file.

import os
import subprocess
from PyQt6.QtWidgets import (
    QApplication, QWidget, QVBoxLayout, QPushButton,
    QListWidget, QMessageBox
)
# fisier download : yt-dlp.exe -vU https://www.youtube.com/watch?v=xxxxxx -f bestvideo*+bestaudio/best
FOLDER_PATH = r"D:\Software"

class FFmpegMerger(QWidget):
    def __init__(self):
        super().__init__()
        self.setWindowTitle("Combinare Video + Audio cu FFmpeg")
        self.resize(600, 400)

        self.layout = QVBoxLayout()
        self.file_list = QListWidget()
        self.process_button = QPushButton("Prelucrează în MP4")

        self.layout.addWidget(self.file_list)
        self.layout.addWidget(self.process_button)
        self.setLayout(self.layout)

        self.process_button.clicked.connect(self.process_files)

        self.populate_file_list()

    def populate_file_list(self):
        files = os.listdir(FOLDER_PATH)
        video_files = [f for f in files if f.endswith(".f401.mp4")]
        audio_files = [f for f in files if f.endswith(".f251-9.webm")]

        base_names = set(f.split(".f401.mp4")[0] for f in video_files)
        candidates = []

        for base in base_names:
            audio_name = f"{base}.f251-9.webm"
            output_name = f"{base}.mp4"
            if audio_name in audio_files and output_name not in files:
                candidates.append(base)

        for name in candidates:
            self.file_list.addItem(name)

    def process_files(self):
        for i in range(self.file_list.count()):
            base = self.file_list.item(i).text()
            video_path = os.path.join(FOLDER_PATH, f"{base}.f401.mp4")
            audio_path = os.path.join(FOLDER_PATH, f"{base}.f251-9.webm")
            output_path = os.path.join(FOLDER_PATH, f"{base}.mp4")

            cmd = [
                "ffmpeg",
                "-i", video_path,
                "-i", audio_path,
                "-c:v", "copy",
                "-c:a", "aac",
                "-strict", "experimental",
                output_path
            ]

            try:
                subprocess.run(cmd, check=True)
            except subprocess.CalledProcessError as e:
                QMessageBox.critical(self, "Eroare", f"Eroare la procesarea {base}: {e}")
                return

        QMessageBox.information(self, "Succes", "Toate fișierele au fost prelucrate cu succes!")

if __name__ == "__main__":
    app = QApplication([])
    window = FFmpegMerger()
    window.show()
    app.exec()

News : The geoai-py - part 001.

A powerful Python package for integrating Artificial Intelligence with geospatial data analysis and visualization

GeoAI bridges the gap between AI and geospatial analysis, providing tools for processing, analyzing, and visualizing geospatial data using advanced machine learning techniques. Whether you're working with satellite imagery, LiDAR point clouds, or vector data, GeoAI offers intuitive interfaces to apply cutting-edge AI models.

Today , I tested this python package named geoai-py. I used the pip tool:

pip install geoai-py
Successfully installed Flask-Caching-2.3.1 MarkupSafe-3.0.2 PySocks-1.7.1 PyYAML-6.0.2 absl-py-2.3.1 aenum-3.1.16 affine-2.4.0 aiohappyeyeballs-2.6.1 aiohttp-3.12.14 aiosignal-1.4.0 albucore-0.0.24 albumentations-2.0.8 aniso8601-10.0.1 annotated-types-0.7.0 antlr4-python3-runtime-4.9.3 anyio-4.9.0 anywidget-0.9.18 argon2-cffi-25.1.0 argon2-cffi-bindings-21.2.0 arrow-1.3.0 asttokens-3.0.0 beautifulsoup4-4.13.4 bitsandbytes-0.46.1 bleach-6.2.0 blinker-1.9.0 bqplot-0.12.45 branca-0.8.1 buildingregulariser-0.2.2 cachelib-0.13.0 cachetools-6.1.0 cffi-1.17.1 click-8.2.1 click-plugins-1.1.1.2 cligj-0.7.2 color-operations-0.2.0 comm-0.2.2 contextily-1.6.2 contourpy-1.3.2 cycler-0.12.1 datasets-4.0.0 decorator-5.2.1 defusedxml-0.7.1 dill-0.3.8 docstring-parser-0.17.0 duckdb-1.3.2 einops-0.8.1 eval-type-backport-0.2.2 ever-beta-0.5.1 executing-2.2.0 fastjsonschema-2.21.1 filelock-3.18.0 fiona-1.10.1 flask-3.1.1 flask-cors-6.0.1 flask-restx-1.3.0 folium-0.20.0 fonttools-4.59.0 fqdn-1.5.1 frozenlist-1.7.0 fsspec-2025.3.0 gdown-5.2.0 geoai-py-0.9.0 geographiclib-2.0 geojson-3.2.0 geopandas-1.1.1 geopy-2.4.1 gitdb-4.0.12 gitpython-3.1.44 grpcio-1.73.1 h11-0.16.0 httpcore-1.0.9 httpx-0.28.1 huggingface_hub-0.33.4 hydra-core-1.3.2 importlib-resources-6.5.2 ipyevents-2.0.2 ipyfilechooser-0.6.0 ipyleaflet-0.20.0 ipython-9.4.0 ipython-pygments-lexers-1.1.1 ipytree-0.2.2 ipyvue-1.11.2 ipyvuetify-1.11.3 ipywidgets-8.1.7 isoduration-20.11.0 itsdangerous-2.2.0 jedi-0.19.2 jinja2-3.1.6 joblib-1.5.1 jsonargparse-4.40.0 jsonnet-0.21.0 jsonpointer-3.0.0 jupyter-client-8.6.3 jupyter-core-5.8.1 jupyter-events-0.12.0 jupyter-leaflet-0.20.0 jupyter-server-2.16.0 jupyter-server-proxy-4.4.0 jupyter-server-terminals-0.5.3 jupyterlab-pygments-0.3.0 jupyterlab_widgets-3.0.15 kiwisolver-1.4.8 kornia-0.8.1 kornia_rs-0.1.9 leafmap-0.48.6 lightly-1.5.21 lightly_utils-0.0.2 lightning-2.5.2 lightning-utilities-0.14.3 localtileserver-0.10.6 mapclassify-2.10.0 maplibre-0.3.4 markdown-3.8.2 markdown-it-py-3.0.0 matplotlib-3.10.3 matplotlib-inline-0.1.7 mdurl-0.1.2 mercantile-1.2.1 mistune-3.1.3 morecantile-6.2.0 multidict-6.6.3 multiprocess-0.70.16 narwhals-1.48.0 nbclient-0.10.2 nbconvert-7.16.6 nbformat-5.10.4 numexpr-2.11.0 omegaconf-2.3.0 opencv-python-headless-4.12.0.88 overrides-7.7.0 overturemaps-0.15.0 pandas-2.3.1 pandocfilters-1.5.1 parso-0.8.4 planetary-computer-1.0.0 plotly-6.2.0 prettytable-3.16.0 prometheus-client-0.22.1 prompt_toolkit-3.0.51 propcache-0.3.2 psygnal-0.14.0 pure-eval-0.2.3 pyarrow-21.0.0 pycparser-2.22 pydantic-2.11.7 pydantic-core-2.33.2 pygments-2.19.2 pyogrio-0.11.0 pyparsing-3.2.3 pyproj-3.7.1 pystac-1.13.0 pystac-client-0.9.0 python-box-7.3.2 python-dateutil-2.9.0.post0 python-dotenv-1.1.1 python-json-logger-3.3.0 pytorch_lightning-2.5.2 pytz-2025.2 pywin32-311 pywinpty-2.0.15 pyzmq-27.0.0 rasterio-1.4.3 regex-2024.11.6 rfc3339-validator-0.1.4 rfc3986-validator-0.1.1 rich-14.0.0 rio-cogeo-5.4.2 rio-tiler-7.8.1 rioxarray-0.19.0 rtree-1.4.0 safetensors-0.5.3 scikit-learn-1.7.1 scooby-0.10.1 segmentation-models-pytorch-0.5.0 send2trash-1.8.3 sentry-sdk-2.33.0 server-thread-0.3.0 shapely-2.1.1 simpervisor-1.0.0 simsimd-6.5.0 six-1.17.0 smmap-5.0.2 sniffio-1.3.1 soupsieve-2.7 stack_data-0.6.3 stringzilla-3.12.5 tensorboard-2.20.0 tensorboard-data-server-0.7.2 tensorboardX-2.6.4 terminado-0.18.1 threadpoolctl-3.6.0 timm-1.0.17 tinycss2-1.4.0 tokenizers-0.21.2 torch-2.7.1 torchange-0.0.1 torchgeo-0.7.1 torchinfo-1.8.0 torchmetrics-1.7.4 torchvision-0.22.1 tornado-6.5.1 traitlets-5.14.3 traittypes-0.2.1 transformers-4.53.2 types-python-dateutil-2.9.0.20250708 typeshed-client-2.8.2 typing-inspection-0.4.1 tzdata-2025.2 uri-template-1.3.0 uvicorn-0.35.0 wandb-0.21.0 wcwidth-0.2.13 webcolors-24.11.1 webencodings-0.5.1 websocket-client-1.8.0 werkzeug-3.1.3 whitebox-2.3.6 whiteboxgui-2.3.0 widgetsnbextension-4.0.14 xarray-2025.7.1 xxhash-3.5.0 xyzservices-2025.4.0 yarl-1.20.1

You can find some example on the Open Geospatial Solutions - the official youtube channel

Let's see my testing python example:

>>> import geoai
>>> dir(geoai)
['AgricultureFieldDelineator', 'Any', 'AutoConfig', 'AutoModelForMaskGeneration', 

'AutoModelForMaskedImageModeling', 'AutoProcessor', 'BoundingBox', 'BuildingFootprintExtractor',

 'CLIPSegForImageSegmentation', 'CLIPSegProcessor', 'CLIPSegmentation', 'CarDetector', 

'ChangeDetection', 'CustomDataset', 'DetectionResult', 'Dict', 'ET', 'GroundedSAM', 'Image', 

'Iterable', 'List', 'Map', 'MapLibre', 'MultiPolygon', 'NonGeoDataset', 'ObjectDetector', 

'Optional', 'OrderedDict', 'ParkingSplotDetector', 'Path', 'Polygon', 'RandomRotation', 

'ShipDetector', 'SolarPanelDetector', 'Tuple', 'Union', 'Window', '__author__', 

'__builtins__', '__cached__', '__doc__', '__email__', '__file__', '__loader__', '__name__', 

'__package__', '__path__', '__spec__', '__version__', 'adaptive_regularization', 

'add_geometric_properties', 'analyze_vector_attributes', 'batch_vector_to_raster', 'bbox_to_xy',

 'box', 'boxes_to_vector', 'calc_stats', 'change_detection', 'classify', 'classify_image', 

'classify_images', 'clip_raster_by_bbox', 'coords_to_xy', 'create_overview_image', 

'create_split_map', 'create_vector_data', 'csv', 'cv2', 'dataclass', 'deeplabv3_resnet50', 

'dict_to_image', 'dict_to_rioxarray', 'download', 'download_file', 'download_model_from_hf', 

'download_naip', 'download_overture_buildings', 'download_pc_stac_item', 'edit_vector_data', 

'export_geotiff_tiles', 'export_geotiff_tiles_batch', 'export_tiles_to_geojson', 

'export_training_data', 'extract', 'extract_building_stats', 'fasterrcnn_resnet50_fpn_v2', 

'fcn_resnet50', 'features', 'geoai', 'geojson_to_coords', 'geojson_to_xy', 'get_device', 

'get_instance_segmentation_model', 'get_model_config', 'get_model_input_channels', 

'get_overture_data', 'get_raster_info', 'get_raster_info_gdal', 'get_raster_resolution', 

'get_raster_stats', 'get_vector_info', 'get_vector_info_ogr', 'glob', 'gpd', 'hf', 

'hf_hub_download', 'hybrid_regularization', 'image_segmentation', 'inspect_pth_file', 

'install_package', 'instance_segmentation', 'instance_segmentation_batch', 

'instance_segmentation_inference_on_geotiff', 'json', 'leafmap', 'logging', 'maplibregl', 

'mapping', 'mask_generation', 'maskrcnn_resnet50_fpn', 'masks_to_vector', 'math', 

'mosaic_geotiffs', 'ndimage', 'np', 'object_detection', 'object_detection_batch', 'orthogonalize',

 'os', 'pc_collection_list', 'pc_item_asset_list', 'pc_stac_download', 'pc_stac_search', 'pd', 

'pipeline', 'plot_batch', 'plot_images', 'plot_masks', 'plot_performance_metrics', 

'plot_prediction_comparison', 'plt', 'print_raster_info', 'print_vector_info', 'raster_to_vector',

 'raster_to_vector_batch', 'rasterio', 'read_pc_item_asset', 'read_raster', 'read_vector', 

'region_groups', 'regularization', 'regularize', 'requests', 'rotate', 'rowcol_to_xy', 'rxr', 

'segment', 'semantic_segmentation', 'semantic_segmentation_batch', 'set_proj_lib_path', 'shape', 

'show', 'stack_bands', 'subprocess', 'sys', 'temp_file_path', 'time', 'torch', 'torchgeo', 'tqdm',

 'train', 'train_MaskRCNN_model', 'train_classifier', 'train_instance_segmentation_model', 

'train_segmentation_model', 'transform_bounds', 'try_common_architectures', 'utils', 

'vector_to_geojson', 'vector_to_raster', 'view_image', 'view_pc_item', 'view_pc_items', 

'view_raster', 'view_vector', 'view_vector_interactive', 'visualize_vector_by_attribute', 

'warnings', 'write_colormap', 'xr']

Python Qt6 : simple celtic knots tool with SVG file format.

Today, I try to create SVG file with an celtic knot design tool.

I used random values from -360 up to 360 for for Twist 1, Twist 2, and Twist 3 sliders.

The basic function is this, is created by artificial intelligence and not works very well.

        # Generate star polygon vertices
        points_cw = []
        points_ccw = []
        for i in range(steps):
            t = 2 * math.pi * i / steps
            r = outer_radius if i % 2 == 0 else inner_radius
            x_cw = center[0] + r * math.cos(t)
            y_cw = center[1] + r * math.sin(t)
            x_ccw = center[0] + r * math.cos(-t + math.pi / max(lobes, 1))
            y_ccw = center[1] + r * math.sin(-t + math.pi / max(lobes, 1))
            points_cw.append((x_cw, y_cw))
            points_ccw.append((x_ccw, y_ccw))

See one random example with this tool:

Python Qt6 : simple merge sprites images with unittest feature.

Today, I created one python tool script with the artificial intelligence to merge sprites images.

I used the artificial intelligence to add unittest to create default images with PIL to test the result.

You can select your folder , select the align of merge features or test with unittest button.

This is the result and works well:

import os
import unittest
from PIL import Image, ImageDraw, ImageFont, ImageQt
import shutil
from PyQt6.QtWidgets import QApplication, QMainWindow, QPushButton, QFileDialog, QLabel, QVBoxLayout, QWidget, QComboBox
from PyQt6.QtGui import QPixmap
from PyQt6.QtCore import Qt
import sys

def create_test_image(path, size, number):
    img = Image.new('RGBA', size, (255, 255, 255, 255))
    draw = ImageDraw.Draw(img)
    # Simplified to just draw the number with a basic color background
    draw.rectangle((0, 0, size[0], size[1]), fill=(0, 100 * number % 255, 0, 255))
    try:
        font = ImageFont.load_default()
    except:
        font = None
    draw.text((size[0]//2-5, size[1]//2-5), str(number), fill=(255, 255, 255, 255), font=font)
    img.save(path, 'PNG')

def merge_sprites(folder_path, output_horizontal, output_vertical):
    images = [Image.open(os.path.join(folder_path, f)) for f in os.listdir(folder_path) if f.endswith(('.png', '.jpg', '.jpeg'))]
    
    if not images:
        return None, None
    
    width, height = images[0].size
    
    # Horizontal merge
    total_width = width * len(images)
    horizontal_image = Image.new('RGBA', (total_width, height))
    for i, img in enumerate(images):
        horizontal_image.paste(img, (i * width, 0))
    horizontal_image.save(output_horizontal, 'PNG')
    
    # Vertical merge
    total_height = height * len(images)
    vertical_image = Image.new('RGBA', (width, total_height))
    for i, img in enumerate(images):
        vertical_image.paste(img, (0, i * height))
    vertical_image.save(output_vertical, 'PNG')
    
    return horizontal_image, vertical_image

class TestSpriteMerger(unittest.TestCase):
    def setUp(self):
        self.test_folder = 'test_images'
        self.size = (50, 20)
        os.makedirs(self.test_folder, exist_ok=True)
        for i in range(3):
            create_test_image(os.path.join(self.test_folder, f'test_{i+1}.png'), self.size, i+1)
    
    def test_merge_horizontal(self):
        output_h = 'test_merged_horizontal.png'
        output_v = 'test_merged_vertical.png'
        h_img, _ = merge_sprites(self.test_folder, output_h, output_v)
        
        self.assertIsNotNone(h_img, "Horizontal merge failed")
        self.assertEqual(h_img.size, (self.size[0] * 3, self.size[1]))
    
    def test_merge_vertical(self):
        output_h = 'test_merged_horizontal.png'
        output_v = 'test_merged_vertical.png'
        _, v_img = merge_sprites(self.test_folder, output_h, output_v)
        
        self.assertIsNotNone(v_img, "Vertical merge failed")
        self.assertEqual(v_img.size, (self.size[0], self.size[1] * 3))
    
    def tearDown(self):
        if os.path.exists(self.test_folder):
            shutil.rmtree(self.test_folder)
        for f in ['test_merged_horizontal.png', 'test_merged_vertical.png']:
            if os.path.exists(f):
                os.remove(f)

class SpriteMergerApp(QMainWindow):
    def __init__(self):
        super().__init__()
        self.setWindowTitle("Sprite Merger")
        self.setGeometry(100, 100, 800, 600)
        
        self.folder_path = ""
        
        layout = QVBoxLayout()
        
        self.select_button = QPushButton("Select Folder")
        self.select_button.clicked.connect(self.select_folder)
        layout.addWidget(self.select_button)
        
        self.merge_type = QComboBox()
        self.merge_type.addItems(["Horizontal", "Vertical"])
        layout.addWidget(self.merge_type)
        
        self.process_button = QPushButton("Process Selected Folder")
        self.process_button.clicked.connect(self.process_folder)
        layout.addWidget(self.process_button)
        
        self.test_button = QPushButton("Run Unit Test")
        self.test_button.clicked.connect(self.run_unit_test)
        layout.addWidget(self.test_button)
        
        self.result_label = QLabel("No image processed")
        layout.addWidget(self.result_label)
        
        self.image_label = QLabel()
        layout.addWidget(self.image_label)
        
        container = QWidget()
        container.setLayout(layout)
        self.setCentralWidget(container)
    
    def select_folder(self):
        self.folder_path = QFileDialog.getExistingDirectory(self, "Select Sprite Folder")
        self.result_label.setText(f"Selected: {self.folder_path}")
    
    def process_folder(self):
        if not self.folder_path:
            self.result_label.setText("Please select a folder first")
            return
        h_img, v_img = merge_sprites(self.folder_path, 'merged_horizontal.png', 'merged_vertical.png')
        selected_type = self.merge_type.currentText()
        
        img = h_img if selected_type == "Horizontal" else v_img
        if img:
            pixmap = QPixmap.fromImage(ImageQt.ImageQt(img))
            self.image_label.setPixmap(pixmap.scaled(700, 500, aspectRatioMode=Qt.AspectRatioMode.KeepAspectRatio))
            self.result_label.setText(f"{selected_type} merge completed")
        else:
            self.result_label.setText(f"{selected_type} merge failed")
    
    def run_unit_test(self):
        suite = unittest.TestLoader().loadTestsFromTestCase(TestSpriteMerger)
        result = unittest.TextTestRunner().run(suite)
        
        test_folder = 'test_images'
        os.makedirs(test_folder, exist_ok=True)
        for i in range(3):
            create_test_image(os.path.join(test_folder, f'test_{i+1}.png'), (50, 20), i+1)
        
        h_img, v_img = merge_sprites(test_folder, 'test_merged_horizontal.png', 'test_merged_vertical.png')
        selected_type = self.merge_type.currentText()
        
        img = h_img if selected_type == "Horizontal" else v_img
        if img:
            pixmap = QPixmap.fromImage(ImageQt.ImageQt(img))
            self.image_label.setPixmap(pixmap.scaled(700, 500, aspectRatioMode=Qt.AspectRatioMode.KeepAspectRatio))
            self.result_label.setText(f"Unit tests: {result.testsRun} run, {len(result.failures)} failed, showing {selected_type.lower()} merge")
        else:
            self.result_label.setText(f"Unit tests: {result.testsRun} run, {len(result.failures)} failed, merge failed")

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

Python 3.13.5 : keras and torch and tensorflow on python version 3.13.5 !

I am not very satisfied with the security of the system in this area, I have noticed intrusions when I was at the Vodafone provider and now I am on mobile and they persist. I should improve my software and hardware protection and restart the system, but I have the impression that it won't help much considering the hacking capabilities that exist.

For now, I'm sticking with this solution, because it's quite good for simple tests with the Python language.

Today I will show you that the involvement of developers is somewhat lagging behind, and this can be seen from the analysis of the development progression across versions of the Python language, as it is not easy to implement in newer versions. Some packages, although important, are not available in newer versions.Today I will show you that the involvement of developers is somewhat lagging behind, and this can be seen from the analysis of the development progression across versions of the Python language, as it is not easy to implement in newer versions. Some packages, although important, are not available in newer versions. Let's see these python packages:

Keras is a deep learning API designed for human beings, not machines. Keras focuses on debugging speed, code elegance & conciseness, maintainability, and deployability. When you choose Keras, your codebase is smaller, more readable, easier to iterate on.

... read more on the official website.

pip install --upgrade keras
Collecting keras
  Downloading keras-3.10.0-py3-none-any.whl.metadata (6.0 kB)
...
Successfully installed absl-py-2.3.0 h5py-3.14.0 keras-3.10.0 ml-dtypes-0.5.1 namex-0.1.0 optree-0.16.0

TensorFlow does not support Python 3.13 as of July 2025; it supports Python 3.9–3.11. To use Keras with TensorFlow, downgrade to Python 3.11, and this install will comes with:

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

You can use the torch python package:

pip install torch
Collecting torch
...
Successfully installed filelock-3.18.0 fsspec-2025.5.1 mpmath-1.3.0 sympy-1.14.0 torch-2.7.1

... during the test with these packages in running it seems that I have errors. I believe that those who develop Python didn't really have a strategy regarding the protection of installed packages because I've found all sorts of junk packages that can be installed with pip or from GitHub.

Python 3.13.5 : the groq tested with basic example !

About groq you can find on the official Grok website .

Today I tested the groq A.P.I. with the basic example :

import os

from groq import Groq

client = Groq(
    api_key="gsk_..."
)

chat_completion = client.chat.completions.create(
    messages=[
        {
            "role": "user",
            "content": "explain what groq is",
        }
    ],
    model="llama-3.3-70b-versatile",
)

print(chat_completion.choices[0].message.content)

The result of : "explain what groq is" is that :

Groq is a relatively new and innovative technology company that focuses on developing high-performance, artificial intelligence (AI) computing hardware and software solutions. Founded in 2016 by Jonathan Ross, a former Google engineer, Groq aims to provide faster, more efficient, and scalable AI computing capabilities to various industries. Groq's primary product is a tensor processing unit (TPU) chip designed specifically for machine learning (ML) and deep learning (DL) workloads. This TPU is optimized for high-performance, low-latency, and low-power consumption, making it suitable for applications that require rapid processing of vast amounts of data, such as: 1. **Computer Vision**: Image and video recognition, object detection, and tracking. 2. **Natural Language Processing (NLP)**: Text analysis, sentiment analysis, and language translation. 3. **Speech Recognition**: Voice command processing and speech-to-text applications. Groq's innovative architecture and design philosophy are centered around the following key aspects: 1. **High-Bandwidth Memory**: Groq's TPU features high-bandwidth memory, which enables fast data transfer and processing. 2. **Scalable Architecture**: The TPU is designed to scale horizontally, allowing for easy expansion to meet growing computational demands. 3. **Low-Latency**: Groq's architecture minimizes latency, ensuring fast response times and real-time processing capabilities. 4. **Software-Defined**: The TPU is software-defined, allowing for flexibility and customization to support a wide range of AI applications and frameworks. Groq's technology has the potential to accelerate AI adoption in various industries, including: 1. **Autonomous Vehicles**: Enhanced computer vision and sensor processing for safer and more efficient autonomous driving. 2. **Healthcare**: Faster medical image analysis and diagnosis, as well as improved personalized medicine and treatment planning. 3. **Financial Services**: Enhanced risk analysis, portfolio optimization, and fraud detection using AI-powered systems. While Groq is still a relatively new company, its innovative approach to AI computing has garnered significant attention and interest from the tech industry, investors, and potential customers. As AI continues to transform various aspects of our lives, Groq's technology is poised to play a significant role in shaping the future of artificial intelligence and machine learning.

Python Qt6 : ... simple resize image files.

I like the combination of Python development and the inclusion of the PyQt6 module. It is very fast and stable and allows me to create all sorts of tools to use.

Today I will show you another handy script that allows you to read all the image files from a folder and, depending on the selections: height, length, and/or aspect ratio, resize them and then place them in a folder created specifically for the resulting images.

Here is how the script looks, I clearly used artificial intelligence and it didn't take more than a few minutes, my evaluation, testing, and rearranging the interface took longer ...

import sys
import os
from datetime import datetime
from PyQt6.QtWidgets import QApplication, QMainWindow, QWidget, QVBoxLayout, QPushButton, QFileDialog, QLineEdit, QCheckBox, QLabel, QMessageBox
from PyQt6.QtCore import Qt
from PIL import Image

class ResizeApp(QMainWindow):
    def __init__(self):
        super().__init__()
        self.setWindowTitle("Image Resizer")
        self.setGeometry(100, 100, 400, 200)

        layout = QVBoxLayout()
        central_widget = QWidget()
        central_widget.setLayout(layout)
        self.setCentralWidget(central_widget)

        self.folder_button = QPushButton("Select Folder")
        self.folder_button.clicked.connect(self.select_folder)
        layout.addWidget(self.folder_button)

        self.width_edit = QLineEdit("800")
        self.width_edit.setPlaceholderText("Width (px)")
        layout.addWidget(QLabel("Width:"))
        layout.addWidget(self.width_edit)

        self.height_edit = QLineEdit("600")
        self.height_edit.setPlaceholderText("Height (px)")
        layout.addWidget(QLabel("Height:"))
        layout.addWidget(self.height_edit)

        self.aspect_ratio = QCheckBox("Maintain Aspect Ratio")
        self.aspect_ratio.setChecked(True)
        layout.addWidget(self.aspect_ratio)

        self.resize_button = QPushButton("Resize Images")
        self.resize_button.clicked.connect(self.resize_images)
        layout.addWidget(self.resize_button)

        self.folder_path = ""

    def select_folder(self):
        self.folder_path = QFileDialog.getExistingDirectory(self, "Select Image Folder")
        if self.folder_path:
            self.folder_button.setText(f"Selected: {os.path.basename(self.folder_path)}")

    def resize_images(self):
        if not self.folder_path:
            QMessageBox.warning(self, "Error", "Please select a folder.")
            return

        try:
            width = int(self.width_edit.text())
            height = int(self.height_edit.text())
        except ValueError:
            QMessageBox.warning(self, "Error", "Please enter valid width and height.")
            return

        if width <= 0 or height <= 0:
            QMessageBox.warning(self, "Error", "Width and height must be positive.")
            return

        date_str = datetime.now().strftime("%d%m%y_%H%M")
        aspect_str = "asp_on" if self.aspect_ratio.isChecked() else "asp_off"
        output_folder = os.path.join(self.folder_path, f"resized_{date_str}_{height}_{aspect_str}")
        os.makedirs(output_folder, exist_ok=True)

        for file_name in os.listdir(self.folder_path):
            if file_name.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif')):
                image_path = os.path.join(self.folder_path, file_name)
                try:
                    with Image.open(image_path) as img:
                        if self.aspect_ratio.isChecked():
                            img.thumbnail((width, height), Image.Resampling.LANCZOS)
                        else:
                            img = img.resize((width, height), Image.Resampling.LANCZOS)
                        output_path = os.path.join(output_folder, f"resized_{date_str}_{height}_{aspect_str}_{file_name}")
                        img.save(output_path)
                except Exception as e:
                    QMessageBox.warning(self, "Error", f"Failed to process {file_name}: {str(e)}")

        QMessageBox.information(self, "Success", f"Images resized and saved to {output_folder}!")

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

Python 3.13.5 : use the jupyterlab, notebook and voila - part 001.

JupyterLab is the latest web-based interactive development environment for notebooks, code, and data. Its flexible interface allows users to configure and arrange workflows in data science, scientific computing, computational journalism, and machine learning. A modular design invites extensions to expand and enrich functionality.

Let's test with these python modules: jupyterlab, notebook and voila.

First, I install with pip tool the jupyterlab python module:

pip install jupyterlab
Collecting jupyterlab
...
Successfully installed anyio-4.9.0 argon2-cffi-25.1.0 argon2-cffi-bindings-21.2.0 arrow-1.3.0 asttokens-3.0.0 async-lru-2.0.5
attrs-25.3.0 babel-2.17.0 bleach-6.2.0 cffi-1.17.1 comm-0.2.2 debugpy-1.8.14 defusedxml-0.7.1 executing-2.2.0 
fastjsonschema-2.21.1 fqdn-1.5.1 h11-0.16.0 httpcore-1.0.9 httpx-0.28.1 ipykernel-6.29.5 ipython-9.4.0 
ipython-pygments-lexers-1.1.1 isoduration-20.11.0 jedi-0.19.2 json5-0.12.0 jsonpointer-3.0.0 jsonschema-4.24.0 
jsonschema-specifications-2025.4.1 jupyter-client-8.6.3 jupyter-core-5.8.1 jupyter-events-0.12.0 jupyter-lsp-2.2.5 
jupyter-server-2.16.0 jupyter-server-terminals-0.5.3 jupyterlab-4.4.4 jupyterlab-pygments-0.3.0 jupyterlab-server-2.27.3 
matplotlib-inline-0.1.7 mistune-3.1.3 nbclient-0.10.2 nbconvert-7.16.6 nbformat-5.10.4 nest-asyncio-1.6.0 notebook-shim-0.2.4
overrides-7.7.0 pandocfilters-1.5.1 parso-0.8.4 platformdirs-4.3.8 prometheus-client-0.22.1 prompt_toolkit-3.0.51 
psutil-7.0.0 pure-eval-0.2.3 pycparser-2.22 python-json-logger-3.3.0 pywin32-310 pywinpty-2.0.15 pyyaml-6.0.2 pyzmq-27.0.0
referencing-0.36.2 rfc3339-validator-0.1.4 rfc3986-validator-0.1.1 rpds-py-0.26.0 send2trash-1.8.3 sniffio-1.3.1 
stack_data-0.6.3 terminado-0.18.1 tinycss2-1.4.0 tornado-6.5.1 traitlets-5.14.3 types-python-dateutil-2.9.0.20250516 
uri-template-1.3.0 wcwidth-0.2.13 webcolors-24.11.1 webencodings-0.5.1 websocket-client-1.8.0

Next, the install of the notebook python module

pip install notebook
Collecting notebook
...
Installing collected packages: notebook
Successfully installed notebook-7.4.4

This python package named voila will help us to use online graphic user interfaces:

pip install voila
Collecting voila
...
Successfully installed voila-0.5.8 websockets-15.0.1

The voila package need to work with ipywidgets python package:

pip install ipywidgets
Collecting ipywidgets
...
Successfully installed ipywidgets-8.1.7 jupyterlab_widgets-3.0.15 widgetsnbextension-4.0.14

Let's start the jupiter tool with this command:

jupyter notebook

I used an default python example with a slider:

import ipywidgets as widgets
from IPython.display import display

slider = widgets.IntSlider(value=5, min=0, max=10)
display(slider)

This command will start the web with the slider using the voila command:

voila test.ipynb

The result is this:

Python 3.13.5 : the manim python module - part 001.

I used this package few days ago and now I wrote about how can used it.

Update the new release of pip is available: 25.0.1 -> 25.1.1 , run this command:

python.exe -m pip install --upgrade pip

The documentation can be found on the official website.

pip install manim
Collecting manim
  Downloading manim-0.19.0-py3-none-any.whl.metadata (11 kB)
...
Successfully installed Pillow-11.2.1 Pygments-2.19.1 audioop-lts-0.2.1 av-13.1.0 beautifulsoup4-4.13.4 click-8.2.1 cloup-3.0.7 colorama-0.4.6 decorator-5.2.1 glcontext-3.0.0 isosurfaces-0.1.2 manim-0.19.0 manimpango-0.6.0 mapbox-earcut-1.0.3 markdown-it-py-3.0.0 mdurl-0.1.2 moderngl-5.12.0 moderngl-window-3.1.1 networkx-3.5 numpy-2.3.0 pycairo-1.28.0 pydub-0.25.1 pyglet-2.1.6 pyglm-2.8.2 rich-14.0.0 scipy-1.15.3 screeninfo-0.8.1 skia-pathops-0.8.0.post2 soupsieve-2.7 srt-3.5.3 svgelements-1.9.6 tqdm-4.67.1 typing-extensions-4.14.0 watchdog-6.0.0

Let's see how can be used to see the help area:

python.exe -m manim render --help
Manim Community v0.19.0

Usage: python -m manim render ...

Let's use this source code:

from manim import *

class AdvancedAnimation(Scene):
    def construct(self):
        # Scene 1: Introduction
        title = Text("Advanced Animation with Manim").scale(0.76)
        self.play(FadeIn(title))
        self.wait(2)

        # Scene 2: Custom Animation
        circle = Circle().set_fill(color=BLUE, opacity=0.5)
        square = Square().set_fill(color=RED, opacity=0.5)
        self.add(circle, square)
        self.play(
            Rotate(circle, angle=TAU),
            Rotate(square, angle=-TAU),
            run_time=2,
            rate_func=linear
        )
        self.wait()

        # Scene 3: Text Animation
        text = Text("This is a custom text animation", font_size=40).to_edge(UP)
        self.play(Write(text), run_time=2)
        self.wait()

        # Scene 4: Shapes Manipulation
        triangle = Triangle().shift(RIGHT * 2)
        self.play(GrowFromCenter(triangle), run_time=1.5)
        self.wait()

        # Scene 5: Transition to next scene
        self.play(Uncreate(triangle), FadeOut(text))

        # Scene 6: Final Animation
        final_text = Text("This is the end of our animation", font_size=50).to_edge(DOWN)
        self.play(FadeIn(final_text), run_time=1.5)
        self.wait(2)

# Run the animation
AdvancedAnimation()

Use this command to render:

python.exe -m manim render manim_test_001.py AdvancedAnimation -p
AdvancedAnimation -p
Manim Community v0.19.0

[06/27/25 19:52:43] INFO     Animation 0 : Partial movie file      scene_file_writer.py:588
                             written in
                             'D:\PythonProjects\manim_projects\med
                             ia\videos\manim_test_001\1080p60\part
                             ial_movie_files\AdvancedAnimation\397
                             7891868_355746014_223132457.mp4'
...
[06/27/25 19:53:56] INFO     Previewed File at:                             file_ops.py:237
                             'D:\PythonProjects\manim_projects\media\videos
                             \manim_test_001\1080p60\AdvancedAnimation.mp4'

The result comes with many files, see this 1080p60 video result:

Python Qt6 : ... simple processing file.

Today I will show you an simple python script with PyQt6.

This script ai build using the artificial inteligence and I tested will process your files by slections : copy to another folder , zip all selected and delete all selected.

import sys
import os
import re
import shutil
import zipfile
from PyQt6.QtWidgets import (QApplication, QMainWindow, QWidget, QVBoxLayout, QHBoxLayout, 
                            QPushButton, QListWidget, QFileDialog, QMessageBox, QDialog, QLabel)
from PyQt6.QtCore import Qt

class CriteriaDialog(QDialog):
    def __init__(self, folder, parent=None):
        super().__init__(parent)
        self.setWindowTitle(f"Processing Folder: {folder}")
        self.layout = QVBoxLayout(self)
        self.layout.addWidget(QLabel(f"Selected folder: {folder}"))
        self.ok_button = QPushButton("OK")
        self.ok_button.clicked.connect(self.accept)
        self.layout.addWidget(self.ok_button)

class DuplicateFinder(QMainWindow):
    def __init__(self):
        super().__init__()
        self.setWindowTitle("Duplicate File Finder")
        self.setGeometry(100, 100, 600, 400)
        
        self.central_widget = QWidget()
        self.setCentralWidget(self.central_widget)
        self.layout = QVBoxLayout(self.central_widget)
        
        self.file_list = QListWidget()
        self.file_list.setSelectionMode(QListWidget.SelectionMode.MultiSelection)
        self.layout.addWidget(self.file_list)
        
        button_layout = QHBoxLayout()
        self.select_button = QPushButton("Select Folder")
        self.select_button.clicked.connect(self.select_folder)
        button_layout.addWidget(self.select_button)
        
        self.copy_button = QPushButton("Copy To")
        self.copy_button.clicked.connect(self.copy_files)
        button_layout.addWidget(self.copy_button)
        
        self.zip_button = QPushButton("Zip All")
        self.zip_button.clicked.connect(self.zip_files)
        button_layout.addWidget(self.zip_button)
        
        self.delete_button = QPushButton("Delete All")
        self.delete_button.clicked.connect(self.delete_files)
        button_layout.addWidget(self.delete_button)
        
        self.layout.addLayout(button_layout)
        
        self.files = []
        self.selected_folder = ""
        
    def select_folder(self):
        folder = QFileDialog.getExistingDirectory(self, "Select Folder")
        if folder:
            self.selected_folder = folder
            dialog = CriteriaDialog(folder, self)
            if dialog.exec():
                self.files = []
                self.file_list.clear()
                self.scan_folder(folder)
                self.find_duplicates()
            
    def scan_folder(self, folder):
        for root, _, files in os.walk(folder):
            for file in files:
                file_path = os.path.join(root, file)
                self.files.append({
                    'path': file_path,
                    'name': os.path.basename(file_path),
                    'size': os.path.getsize(file_path),
                    'extension': os.path.splitext(file_path)[1]
                })
                
    def find_duplicates(self):
        duplicates = self.find_by_similar_name()
        self.display_duplicates(duplicates)
        
    def find_by_similar_name(self):
        duplicates = []
        name_groups = {}
        pattern = r'(.+?)(?:[\s_-]*\d{3,}|[\s_-]*\d{1,2}|_)?(?:\.\w+)?$'
        
        for file in self.files:
            match = re.match(pattern, file['name'])
            if match:
                base_name = match.group(1)
                if base_name in name_groups:
                    name_groups[base_name].append(file)
                else:
                    name_groups[base_name] = [file]
        
        for base_name, files in name_groups.items():
            if len(files) > 1:
                duplicates.extend(files)
                
        return duplicates
    
    def display_duplicates(self, duplicates):
        self.file_list.clear()
        for file in duplicates:
            self.file_list.addItem(file['path'])
            
    def copy_files(self):
        if not self.file_list.selectedItems():
            QMessageBox.warning(self, "Warning", "No files selected!")
            return
        dest_folder = QFileDialog.getExistingDirectory(self, "Select Destination Folder")
        if dest_folder:
            for item in self.file_list.selectedItems():
                file_path = item.text()
                dest_path = os.path.join(dest_folder, os.path.basename(file_path))
                shutil.copy2(file_path, dest_path)
            QMessageBox.information(self, "Success", "Files copied!")
            
    def zip_files(self):
        if not self.file_list.selectedItems():
            QMessageBox.warning(self, "Warning", "No files selected!")
            return
        zip_path = QFileDialog.getSaveFileName(self, "Save Zip File", "", "Zip Files (*.zip)")[0]
        if zip_path:
            with zipfile.ZipFile(zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
                for item in self.file_list.selectedItems():
                    file_path = item.text()
                    zipf.write(file_path, os.path.basename(file_path))
            QMessageBox.information(self, "Success", "Files zipped!")
        
    def delete_files(self):
        if not self.file_list.selectedItems():
            QMessageBox.warning(self, "Warning", "No files selected!")
            return
        reply = QMessageBox.question(self, "Confirm", "Delete selected files?",
                                  QMessageBox.StandardButton.Yes | QMessageBox.StandardButton.No)
        if reply == QMessageBox.StandardButton.Yes:
            for item in self.file_list.selectedItems():
                os.remove(item.text())
            self.file_list.clear()
            QMessageBox.information(self, "Success", "Files deleted!")

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

Python 3.13.5 : Get bookmarks from Edge browser with python.

Today I tested with these python modules json and pathlib.

This python script will get all bookmarks from Edge browser:

import json
from pathlib import Path

bookmark_path = Path.home() / "AppData/Local/Microsoft/Edge/User Data/Default/Bookmarks"

with open(bookmark_path, "r", encoding="utf-8") as f:
    data = json.load(f)

# Exemplu: listăm toate titlurile bookmark-urilor
def extract_bookmarks(bookmark_node):
    bookmarks = []
    if "children" in bookmark_node:
        for child in bookmark_node["children"]:
            bookmarks.extend(extract_bookmarks(child))
    elif bookmark_node.get("type") == "url":
        bookmarks.append((bookmark_node["name"], bookmark_node["url"]))
    return bookmarks

all_bookmarks = extract_bookmarks(data["roots"]["bookmark_bar"])
for name, url in all_bookmarks:
    print(f"{name}: {url}")

Python 3.13.5 : testing with flask, request and playwright python module.

Today some testing with these python modules: flask, request and playwright.

I used pip to install flask python package:

pip install flask
Collecting flask
  Downloading flask-3.1.1-py3-none-any.whl.metadata (3.0 kB)
...
Installing collected packages: markupsafe, itsdangerous, blinker, werkzeug, jinja2, flask
Successfully installed blinker-1.9.0 flask-3.1.1 itsdangerous-2.2.0 jinja2-3.1.6 markupsafe-3.0.2 werkzeug-3.1.3

pip install requests
...
Installing collected packages: urllib3, idna, charset_normalizer, certifi, requests
Successfully installed certifi-2025.6.15 charset_normalizer-3.4.2 idna-3.10 requests-2.32.4 urllib3-2.5.0

pip install playwright
Collecting playwright
...
Installing collected packages: pyee, greenlet, playwright
Successfully installed greenlet-3.2.3 playwright-1.52.0 pyee-13.0.0
...
playwright install
Downloading Chromium 136.0.7103.25 ...

This will download a lot fo files and the will install the playwright tool.

First script is simple one will try to get cloudflare header on default ip:

from flask import Flask, request

app = Flask(__name__)

@app.route("/")
def detecteaza_ipuri():
    ip_client = request.headers.get('CF-Connecting-IP', 'Necunoscut')
    ip_cloudflare = request.remote_addr
    return (
        f"IP real vizitator: {ip_client}
"
        f"IP Cloudflare (vizibil de server): {ip_cloudflare}"
    )

if __name__ == "__main__":
    app.run(debug=True)

The next one will check more ...

from flask import Flask, request
import requests
import ipaddress

app = Flask(__name__)

def este_ip_cloudflare(ip):
    try:
        raspuns = requests.get("https://www.cloudflare.com/ips-v4")
        raspuns.raise_for_status()
        subneturi = raspuns.text.splitlines()

        for subnet in subneturi:
            if ipaddress.ip_address(ip) in ipaddress.ip_network(subnet):
                return True
        return False
    except Exception as e:
        return f"Eroare la verificarea IP-ului Cloudflare: {e}"

@app.route("/")
def detecteaza_ipuri():
    ip_client = request.headers.get('CF-Connecting-IP', 'Necunoscut')
    ip_cloudflare = request.remote_addr
    rezultat = este_ip_cloudflare(ip_cloudflare)

    return (
        f"IP real vizitator: {ip_client}
"
        f"IP Cloudflare (forwarder): {ip_cloudflare}
"
        f"Este IP-ul din rețeaua Cloudflare? {'DA' if rezultat == True else 'NU' if rezultat == False else rezultat}"
    )

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=5000)

Now, the script with the request python module:

import requests

url = "https://cobalt.tools"
headers = {
    "User-Agent": "Mozilla/5.0",  # Simulează un browser real
}

try:
    r = requests.get(url, headers=headers, timeout=10)
    content = r.text.lower()

    print(f"Cod răspuns HTTP: {r.status_code}")

    if "cloudflare" in content or "cf-ray" in content or "attention required" in content:
        print("Cloudflare a intermediat cererea sau a blocat-o cu o pagină specială.")
    else:
        print("Cererea a fost servită normal.")
except Exception as e:
    print(f"Eroare la conexiune: {e}")

The last one will use the playwright python module:

import sys
import re
from urllib.parse import urlparse
from pathlib import Path
from playwright.sync_api import sync_playwright

def converteste_url_in_nume_fisier(url):
    parsed = urlparse(url)
    host = parsed.netloc.replace('.', '_')
    path = parsed.path.strip('/').replace('/', '_')
    if not path:
        path = 'index'
    return f"{host}_{path}.txt"

if len(sys.argv) != 2:
    print("Utilizare: python script.py https://exemplu.com")
    sys.exit(1)

url = sys.argv[1]
fisier_output = converteste_url_in_nume_fisier(url)

with sync_playwright() as p:
    browser = p.chromium.launch(headless=True)
    pagina = browser.new_page()
    pagina.goto(url, wait_until='networkidle')
    continut = pagina.content()
    Path(fisier_output).write_text(continut, encoding='utf-8')
    browser.close()

print(f"Conținutul a fost salvat în: {fisier_output}")

This will create a file with the source code of web page.

News : UV - fast Python package and project manager.

An extremely fast Python package and project manager, written in Rust.

See the official website

cd uv_projects

uv_projects>uv init hello-world
Initialized project `hello-world` at `D:\PythonProjects\uv_projects\hello-world`

uv_projects>cd hello-world

uv_projects\hello-world>uv run main.py
Using CPython 3.13.5 interpreter at: C:\Python3135\python.exe
Creating virtual environment at: .venv
Hello from hello-world!

Python Qt6 : simple animation with sprites.

Today I created with addon for Blender 3D and result is an image with sprites ...

I used that image with sprites and PyQt6 to animate my desktop screen, see the result:

This is the source code I used:

import sys
from PyQt6.QtWidgets import QApplication, QLabel, QWidget, QVBoxLayout, QMenu

# diff PyQt6 versus old PyQt
from PyQt6.QtGui import QAction

from PyQt6.QtGui import QPixmap, QIcon
from PyQt6.QtCore import QTimer, Qt

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

        # set window
        self.setWindowFlags(Qt.WindowType.FramelessWindowHint | Qt.WindowType.WindowStaysOnTopHint)
        self.setAttribute(Qt.WidgetAttribute.WA_TranslucentBackground)

        # build layout 
        layout = QVBoxLayout()
        self.label = QLabel(self)
        layout.addWidget(self.label)
        self.setLayout(layout)

        # load sprite sheet from Camera_256px.png file name
        sprite_sheet = QPixmap("Camera_256px.png")  
        self.frame_width = sprite_sheet.width() // 11  # because I have 11 sprite on image
        self.sprites = [sprite_sheet.copy(i * self.frame_width, 0, self.frame_width, sprite_sheet.height()) for i in range(11)]
        self.current_frame = 0

        # 
        self.timer = QTimer()
        self.timer.timeout.connect(self.update_animation)
        self.timer.start(150)  # Schimbă frame-ul la fiecare 150 ms

        # 
        self.resize(self.frame_width, sprite_sheet.height())

        # left down on screen 
        screen = QApplication.primaryScreen().geometry()
        self.move(10, screen.height() - self.height() - 10)

    def update_animation(self):
        """Actualizează sprite-ul în QLabel"""
        self.label.setPixmap(self.sprites[self.current_frame])
        self.current_frame = (self.current_frame + 1) % len(self.sprites)

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

Python 3.13.3 : ... Nuitka package works with python 3.12 and MinGW.

Nuitka is licensed under the Apache License, Version 2.0; you may not use it except in compliance with the License.

Nuitka is the Python compiler. It is written in Python. It is a seamless replacement or extension to the Python interpreter and compiles every construct that Python 2 (2.6, 2.7) and Python 3 (3.4 - 3.13) have, when itself run with that Python version.

Nuitka translates the Python modules into a C level program that then uses libpython and static C files of its own to execute in the same way as CPython does.

I used the pip command:

python -m pip install -U nuitka
Collecting nuitka
  Downloading Nuitka-2.7.tar.gz (3.9 MB)
...
Successfully built nuitka
Installing collected packages: zstandard, ordered-set, nuitka
Successfully installed nuitka-2.7 ordered-set-4.1.0 zstandard-0.23.0

[notice] A new release of pip is available: 25.0.1 -> 25.1.1
[notice] To update, run: python.exe -m pip install --upgrade pip

This version of python : 3.13.0rc1 not work !!!

I need to upgrade my version to 3.13.3 version today after I open an issue on github repo!

python.exe -m pip install --upgrade pip
...
Successfully installed pip-25.1.1

python -m nuitka --version
2.7
Commercial: None
Python: 3.13.0rc1 (tags/v3.13.0rc1:e4a3e78, Jul 31 2024, 20:58:38) [MSC v.1940 64 bit (AMD64)]
Flavor: CPython Official
GIL: yes
Executable: C:\Python313\python.exe
OS: Windows
Arch: x86_64
WindowsRelease: 10
Nuitka-Scons:WARNING: Windows SDK must be installed in Visual Studio for it to be usable
Nuitka-Scons:WARNING: with Nuitka. Use the Visual Studio installer for adding it.
Version C compiler: ~\AppData\Local\Nuitka\Nuitka\Cache\downloads\gcc\x86_64\14.2.0posix-19.1.1-12.0.0-msvcrt-r2\mingw64\bin\gcc.exe (gcc 14.2.0).

After upgrade the nuitka show me these results:

python -m nuitka --version
2.7
Commercial: None
Python: 3.13.3 (tags/v3.13.3:6280bb5, Apr  8 2025, 14:47:33) [MSC v.1943 64 bit (AMD64)]
Flavor: CPython Official
GIL: yes
Executable: C:\Python313\python.exe
OS: Windows
Arch: x86_64
WindowsRelease: 10
Nuitka-Scons:WARNING: Windows SDK must be installed in Visual Studio for it to be usable
Nuitka-Scons:WARNING: with Nuitka. Use the Visual Studio installer for adding it.
Version C compiler: ~\AppData\Local\Nuitka\Nuitka\Cache\downloads\gcc\x86_64\14.2.0posix-19.1.1-12.0.0-msvcrt-r2\mingw64\bin\gcc.exe (gcc 14.2.0).

Same error, I uninstall the Python: 3.13.3 version and I install the python version 3.13.0 and use the pip again to install this python package.

python -m pip install -U nuitka
Collecting nuitka
...
Installing collected packages: zstandard, ordered-set, nuitka
Successfully installed nuitka-2.7 ordered-set-4.1.0 zstandard-0.23.0

[notice] A new release of pip is available: 24.2 -> 25.1.1
[notice] To update, run: python.exe -m pip install --upgrade pip
python.exe -m pip install --upgrade pip
Requirement already satisfied: pip in c:\python_3_13_0\lib\site-packages (24.2)
...
Successfully installed pip-25.1.1

Using this version tell me same error with Windows and Visual Studio, but the MinGW is install from the first version.

The solution from artificial intelligence is to use another python version.

I used these commands:

py -3.12 -m pip install -U nuitka
Collecting nuitka
  Using cached Nuitka-2.7.tar.gz (3.9 MB)
  Installing build dependencies ... done
  ...
  Installing collected packages: zstandard, ordered-set, nuitka
Successfully installed nuitka-2.7 ordered-set-4.1.0 zstandard-0.23.0

[notice] A new release of pip is available: 24.2 -> 25.1.1
[notice] To update, run: C:\Python312\python.exe -m pip install --upgrade pip
py -0
 -V:3.13 *        Python 3.13 (64-bit)
 -V:3.12          Python 3.12 (64-bit)
py -3.12 -m nuitka --mingw64 hello.py
Nuitka-Options: Used command line options:
Nuitka-Options:   --mingw64 hello.py
Nuitka-Options:WARNING: You did not specify to follow or include anything but main
Nuitka-Options:WARNING: program. Check options and make sure that is intended.
Nuitka: Starting Python compilation with:
Nuitka:   Version '2.7' on Python 3.12 (flavor 'CPython Official')
Nuitka:   commercial grade 'not installed'.
Nuitka: Completed Python level compilation and optimization.
Nuitka: Generating source code for C backend compiler.
Nuitka: Running data composer tool for optimal constant value handling.
Nuitka: Running C compilation via Scons.
Nuitka-Scons: Backend C compiler: gcc (gcc 14.2.0).
Nuitka-Scons: Backend C linking with 6 files (no progress information available for
Nuitka-Scons: this stage).
Nuitka-Scons: Compiled 6 C files using ccache.
Nuitka-Scons: Cached C files (using ccache) with result 'cache miss': 6
Nuitka: Keeping build directory 'hello.build'.
Nuitka: Successfully created 'D:\PythonProjects\hello.exe'.
Nuitka: Execute it by launching 'hello.cmd', the batch file needs to set environment.

The test is a simple python script from the official website:

def talk(message):
    return "Talk " + message

def main():
    print(talk("Hello World"))

if __name__ == "__main__":
    main()

... and this python version works well with MinGW, the artificial intelligence used to fix these errors was ChatGPT.

hello.exe
Talk Hello World

Python 3.13.0rc1 : ... fal artificial intelligence and python test.

We have the most-popular models implemented and available as API endpoints for you to start crafting your own AI-powered app today. From the fal.ai website !

You need to set your A.P.I. key from this url.

system32>setx.exe FAL_KEY "e6fd708c-8065-4c73-ac2a-e3c73c6ff0fe:f70e0adb08362a3073993efa31b6acee"

SUCCESS: Specified value was saved.

Open a new terminal and with your editor create this simple example ...

import fal_client

response = fal_client.run("fal-ai/fast-sdxl", arguments={"prompt": "a cute cat, realistic, orange"})
print(response["images"][0]["url"])

Into the terminal run the python script and you will find the url of the image :

python test_fal_client_001.py
https://v3.fal.media/files/rabbit/kY2MZG6LLkzjyIT8J3oiI.jpe

This is the result output of the running source code as 1024px image, see the resize 112px I created:

Python Qt6 : Simple tool to convert HTML.

This is based on old tutorial from this post.

I add a class AgentPY class with all features for processing input and HtmlEditor class for .

Maybe I will use the agentpy module , but now works well without agents.

This is the source code:

from PyQt6.QtWidgets import QApplication, QMainWindow, QTextEdit, QMenu
from bs4 import BeautifulSoup

class AgentPy:
    """Clasă pentru procesarea și curățarea HTML-ului."""
    @staticmethod
    def clean_all_styles(html_content):
        soup = BeautifulSoup(html_content, 'html.parser')
        for tag in soup.find_all(True):
            if tag.name == "a":
                attrs_to_keep = {"href": tag.attrs.get("href")} if "href" in tag.attrs else {}
                tag.attrs = attrs_to_keep
            else:
                tag.attrs = {}
        return str(soup)

    @staticmethod
    def clean_empty_tags(html_content):
        soup = BeautifulSoup(html_content, 'html.parser')
        for tag in soup.find_all(True):
            if not tag.contents or all(str(content).strip() == "" for content in tag.contents):
                tag.decompose()
        return str(soup)

    @staticmethod
    def clean_duplicate_tags(html_content):
        soup = BeautifulSoup(html_content, 'html.parser')
        unique_tags = {}
        for tag in soup.find_all(True):
            tag_key = (tag.name, str(tag.attrs))
            if tag_key in unique_tags:
                tag.decompose()
            else:
                unique_tags[tag_key] = tag
        return str(soup)

    @staticmethod
    def convert_to_html(source_code):
        """Convertim caractere speciale din cod sursă în entități HTML."""
        # Creăm un dicționar pentru conversia caracterelor
        html_entities = {
            '<': '<',
            '>': '>',
            '&': '&',
            '"': '"',
            "'": ''',
            '[': '[',
            ']': ']',
        }
        # Înlocuim caracterele în codul sursă
        for char, entity in html_entities.items():
            source_code = source_code.replace(char, entity)
        return source_code

class HtmlEditor(QMainWindow):
    def __init__(self):
        super().__init__()
        self.setWindowTitle("catafest-cleaner-HTML")
        self.setGeometry(100, 100, 800, 600)

        # Editor de text
        self.editor = QTextEdit(self)
        self.setCentralWidget(self.editor)

        # Meniu contextual
        self.editor.setContextMenuPolicy(Qt.ContextMenuPolicy.CustomContextMenu)
        self.editor.customContextMenuRequested.connect(self.show_context_menu)

    def show_context_menu(self, position):
        menu = QMenu(self)
        clean_styles_action = menu.addAction("Clean basic HTML")
        clean_styles_action.triggered.connect(self.clean_all_styles)
        clean_empty_tags_action = menu.addAction("Clean Empty Tags")
        clean_empty_tags_action.triggered.connect(self.clean_empty_tags)
        clean_agentpy_action = menu.addAction("Clean AgentPy")
        clean_agentpy_action.triggered.connect(self.clean_duplicate_tags)
        convert_to_html_action = menu.addAction("Convert to HTML")  # Noua opțiune
        convert_to_html_action.triggered.connect(self.convert_to_html)
        menu.exec(self.editor.mapToGlobal(position))

    def clean_all_styles(self):
        html_content = self.editor.toPlainText()
        clean_html = AgentPy.clean_all_styles(html_content)
        self.editor.setPlainText(clean_html)

    def clean_empty_tags(self):
        html_content = self.editor.toPlainText()
        clean_html = AgentPy.clean_empty_tags(html_content)
        self.editor.setPlainText(clean_html)

    def clean_duplicate_tags(self):
        html_content = self.editor.toPlainText()
        clean_html = AgentPy.clean_duplicate_tags(html_content)
        self.editor.setPlainText(clean_html)

    def convert_to_html(self):
        source_code = self.editor.toPlainText()
        html_content = AgentPy.convert_to_html(source_code)
        self.editor.setPlainText(html_content)

if __name__ == "__main__":
    import sys
    from PyQt6.QtCore import Qt
    app = QApplication(sys.argv)
    window = HtmlEditor()
    window.show()
    sys.exit(app.exec())

Python 3.11.11 : Colab fixed catafest_0059 with NVIDIA models - part 051.

Fixed the colab notebook for test models from NVIDIA for waveglow and tacotron2.

Python Qt6 : Simple tool for clean HTML.

Today I make a simple tool to clean the HTML from style and more. I used artificial inteligence from copilot.

This is the result of this simple tool.

from PyQt6.QtWidgets import QApplication, QMainWindow, QTextEdit, QMenu
from bs4 import BeautifulSoup

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

        self.setWindowTitle("catafest-cleaner-HTML")  # Titlu actualizat
        self.setGeometry(100, 100, 800, 600)

        # Editor de text
        self.editor = QTextEdit(self)
        self.setCentralWidget(self.editor)

        # Meniu contextual
        self.editor.setContextMenuPolicy(Qt.ContextMenuPolicy.CustomContextMenu)
        self.editor.customContextMenuRequested.connect(self.show_context_menu)

    def show_context_menu(self, position):
        menu = QMenu(self)
        clean_styles_action = menu.addAction("Clean basic HTML")
        clean_styles_action.triggered.connect(self.clean_all_styles)
        clean_empty_tags_action = menu.addAction("Clean Empty Tags")
        clean_empty_tags_action.triggered.connect(self.clean_empty_tags)
        menu.exec(self.editor.mapToGlobal(position))

    def clean_all_styles(self):
        # Obține conținutul HTML din editor
        html_content = self.editor.toPlainText()

        # Utilizează BeautifulSoup pentru a procesa HTML-ul
        soup = BeautifulSoup(html_content, 'html.parser')

        # Elimină toate atributele, cu excepția celor din ancorele <a>
        for tag in soup.find_all(True):
            if tag.name == "a":  # Păstrează doar atributul 'href' pentru <a>
                attrs_to_keep = {"href": tag.attrs.get("href")} if "href" in tag.attrs else {}
                tag.attrs = attrs_to_keep
            else:
                tag.attrs = {}  # Elimină toate atributele pentru celelalte tag-uri

        # Actualizează conținutul editorului
        clean_html = str(soup)
        self.editor.setPlainText(clean_html)

    def clean_empty_tags(self):
        # Obține conținutul HTML din editor
        html_content = self.editor.toPlainText()

        # Utilizează BeautifulSoup pentru a procesa HTML-ul
        soup = BeautifulSoup(html_content, 'html.parser')

        # Elimină tag-urile goale
        for tag in soup.find_all(True):
            # Verifică tag-uri goale
            if not tag.contents or all(str(content).strip() == "" for content in tag.contents):  
                tag.decompose()  # Elimină tag-ul complet

        # Actualizează conținutul editorului
        clean_html = str(soup)
        self.editor.setPlainText(clean_html)

if __name__ == "__main__":
    import sys
    from PyQt6.QtCore import Qt
    app = QApplication(sys.argv)
    window = HtmlEditor()
    window.show()
    sys.exit(app.exec())