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Showing posts with label tutorials. Show all posts
Showing posts with label tutorials. Show all posts

Tuesday, January 6, 2026

Python 3.13.0 : PyWin32 is full compatible with Python 3.13 .

Today I tried to use these python packages:
import win32serviceutil
import win32service
import win32event
import servicemanager
The works , but python -m pywin32_postinstall -install comes with:
python.exe: No module named pywin32_postinstall
NOTE : The copilot artificial intelligence, search and give me an old answer , but is wrong ...
PyWin32 is updated slowly, and at this moment there are no wheels for Python 3.13.
The pip tool cannot install pywin32 does not install anything usable, and pywin32_postinstall does not exist
Possible solutions
PyWin32 works perfectly on:
  • Python 3.12
  • Python 3.11
  • Python 3.10
If you need win32service, win32api, win32com, etc., you must use a supported version.
Need to see the last tutorial from my blogger.
I tested on admin with simple service and works:
python service_test_001.py install
Installing service MyPythonService
Service installed
This is the source code:
import win32serviceutil
import win32service
import win32event
import servicemanager
import time

class MyService(win32serviceutil.ServiceFramework):
    _svc_name_ = "MyPythonService"
    _svc_display_name_ = "My Python Windows Service"
    _svc_description_ = "A minimal Windows service example written in Python."

    def __init__(self, args):
        win32serviceutil.ServiceFramework.__init__(self, args)
        self.stop_event = win32event.CreateEvent(None, 0, 0, None)
        self.running = True

    def SvcStop(self):
        self.ReportServiceStatus(win32service.SERVICE_STOP_PENDING)
        win32event.SetEvent(self.stop_event)
        self.running = False

    def SvcDoRun(self):
        servicemanager.LogInfoMsg("MyPythonService is starting.")
        self.main()

    def main(self):
        while self.running:
            # Your service logic goes here
            time.sleep(5)
            servicemanager.LogInfoMsg("MyPythonService heartbeat.")


if __name__ == '__main__':
    win32serviceutil.HandleCommandLine(MyService)

Sunday, January 4, 2026

Python 3.13.0 : how to install pywin32_postinstall.

Today a tutorial on how to install pywin32_postinstall.
This package is essential for accessing Windows-specific functionalities in Python.
The pywin32_postinstall missing python error typically occurs when the pywin32 package is not properly installed or the post-installation script is not executed correctly.
Fisrt install the pywin32 python package.
pip install pywin32
The next step is to run this command on the path with Script folder.
python C:\Python313\Scripts\pywin32_postinstall.py -install
Parsed arguments are: Namespace(install=True, remove=False, wait=None, silent=False, quiet=False, destination= ...
The next step is to run this command on the path with Script folder.
D:\Python313_64bit>python
Python 3.13.0 (tags/v3.13.0:60403a5, Oct  7 2024, 09:38:07) [MSC v.1941 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import win32api
>>> print(win32api.GetVersion())

Friday, January 2, 2026

Python Qt6 : script for impact on your development workflow using scans features.

Impact on development workflows that rely on Language Server Protocol (LSP) features.
1. Editor Limitations
Your editor (VS Code, Neovim, Qt Creator, etc.) attempts to send a file to the Language Server, but the file is not accessible through the file:// protocol.
When this happens, the LSP rejects the request, and you lose essential features such as:
  • IntelliSense
  • Autocomplete
  • Hover information
  • Diagnostics
  • Jump‑to‑definition
  • Refactoring tools
2. Issues in Non‑Standard Projects
This limitation becomes more severe when working with:
  • dynamically generated files
  • files inside containers
  • remote workspaces
  • build systems that create temporary or virtual files
Since the LSP cannot process these resources, you lose intelligent code support.
3. Toolchain Breakdowns
If you rely on an automated workflow (analysis, diagnostics, UI integration, etc.), an LSP restricted to file:// can break:
  • static analysis
  • code validation
  • report generation
  • plugin integrations
Real Risks in Development
1. False or Incomplete Diagnostics
The LSP may not see the actual files, leading to:
  • false errors
  • missed real errors
2. Dangerous Refactoring
If the LSP cannot access all files, automated refactoring may:
  • fail to update all references
  • introduce new bugs
3. Reduced Productivity
Without full LSP support, you lose:
  • intelligent completion
  • fast navigation
  • real‑time validation
4. Incompatibility With Modern Tooling
Many modern IDEs rely on virtual or remote workspaces. An LSP limited to file:// becomes outdated quickly.
5. Indirect Security Risks
Not a vulnerability by itself, but:
  • if the LSP cannot analyze remote files, you may miss security issues in generated or synchronized code.
I tested with a simple python source code to detect how bad is running on I.D.E. The script continuously scans your Windows system to detect, analyze, and report the real‑time behavior, resource usage, crashes, leaks, ports, and child processes of all VS Code, LSP, and Antigravity components, showing their impact on your development workflow through a live PyQt6 dashboard.
The result after runnig is:

Thursday, January 1, 2026

Python 3.12.12 : simple example with CompVis/stable-diffusion-v1-4 model on colab.

Because this year we need to start it as advanced and more prepared as we know and can do ...
Today I tested a simple source code with an interactive interface for text-to-image generation based on the CompVis/stable-diffusion-v1-4 model.
This is not an advanced model and you will have some dizzy images, but the learnning idea is the base of these colabs notebooks.
See the default example on my colab github project.
The colab notebook use this python version:
Python 3.12.12 (main, Oct 10 2025, 08:52:57) [GCC 11.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
I'm mode advanced with some models like SDXL, image generation is not a priority at the moment ...
... and first image result is this:

Wednesday, December 10, 2025

Python 3.13.0 : ... simple script for copilot history.

NOTES: I have been using artificial intelligence since it appeared, it is obviously faster and more accurate, I recommend using testing on larger projects.
This python script will take the database and use to get copilot history and save to file copilot_conversations.txt :
import os
import sqlite3
import datetime
import requests
from bs4 import BeautifulSoup
import shutil

# Locația tipică pentru istoricul Edge (Windows)
edge_history_path = os.path.expanduser(
    r"~\\AppData\\Local\\Microsoft\\Edge\\User Data\\Default\\History"
)

# Copiem fișierul History în folderul curent
def copy_history_file(src_path, dst_name="edge_history_copy.db"):
    if not os.path.exists(src_path):
        print("Nu am găsit istoricul Edge.")
        return None
    dst_path = os.path.join(os.getcwd(), dst_name)
    try:
        shutil.copy(src_path, dst_path)
        print(f"Am copiat baza de date în {dst_path}")
        return dst_path
    except Exception as e:
        print(f"Eroare la copiere: {e}")
        return None

def extract_copilot_links(db_path):
    conn = sqlite3.connect(db_path)
    cursor = conn.cursor()

    cursor.execute("""
        SELECT url, title, last_visit_time
        FROM urls
        WHERE url LIKE '%copilot%'
    """)

    results = []
    for url, title, last_visit_time in cursor.fetchall():
        ts = datetime.datetime(1601, 1, 1) + datetime.timedelta(microseconds=last_visit_time)
        results.append({
            "url": url,
            "title": title,
            "last_visit": ts.strftime("%Y-%m-%d %H:%M:%S")
        })

    conn.close()
    return results

def fetch_conversation(url):
    try:
        resp = requests.get(url)
        if resp.status_code == 200:
            soup = BeautifulSoup(resp.text, "html.parser")
            texts = soup.get_text(separator="\n", strip=True)
            return texts
        else:
            return f"Eroare acces {url}: {resp.status_code}"
    except Exception as e:
        return f"Eroare acces {url}: {e}"

if __name__ == "__main__":
    copy_path = copy_history_file(edge_history_path)
    if copy_path:
        chats = extract_copilot_links(copy_path)
        if chats:
            with open("copilot_conversations.txt", "w", encoding="utf-8") as f:
                for chat in chats:
                    content = fetch_conversation(chat["url"])
                    f.write(f"=== Conversație: {chat['title']} ({chat['last_visit']}) ===\n")
                    f.write(content)
                    f.write("\n\n")
            print("Am salvat conversațiile în copilot_conversations.txt")
        else:
            print("Nu am găsit conversații Copilot în istoricul Edge.")

Saturday, December 6, 2025

News : Python 3.14.1 and Python 3.13.10 are now available!

... these are good news from 2 december 2025:
Python 3.14.1 is the first maintenance release of 3.14, containing around 558 bugfixes, build improvements and documentation changes since 3.14.0.
Python 3.13.10 is the tenth maintenance release of 3.13, containing around 300 bugfixes, build improvements and documentation changes since 3.13.9.
Read more on the official blogger.

Wednesday, December 3, 2025

Python 3.13.0 : ... playwright - part 001.

Playwright for Python is a modern automation library that allows developers to control browsers like Chromium, Firefox, and WebKit. It is widely used for testing, scraping, and simulating real user interactions.
The package provides an asynchronous API, enabling fast and reliable automation. Developers can launch browsers, navigate to pages, fill forms, click buttons, and capture results with minimal code.
In practice, Playwright is useful for tasks such as automated testing, repetitive searches, data collection, and simulating human-like browsing behavior across multiple browsers.
The example script demonstrates how to open Firefox, navigate to Google, perform a series of searches, scroll the page, and pause between actions to mimic natural user activity.
Additionally, the script saves each search query into a text file, creating a simple log of performed searches. This shows how Playwright can combine browser automation with file handling for practical workflows.
I used the pip tool then I install the playwright:
pip install playwright
playwright install
Let's see the script:
import asyncio
from playwright.async_api import async_playwright

async def main():
    async with async_playwright() as p:
        browser = await p.firefox.launch(headless=False)
        context = await browser.new_context()
        page = await context.new_page()

        await page.goto("https://www.google.com")

        queries = [
            "python automation",
            "playwright tutorial",
            "google search automation"
        ]

        with open("results.txt", "w", encoding="utf-8") as f:
            for q in queries:
                # Fill search box
                await page.fill("textarea[name='q']", q)
                await page.press("textarea[name='q']", "Enter")
                await page.wait_for_load_state("domcontentloaded")

                # Scroll + pause
                await page.evaluate("window.scrollBy(0, document.body.scrollHeight)")
                await page.wait_for_timeout(3000)

                # Extract search results (titles + links)
                results = await page.query_selector_all("h3")
                f.write(f"\nResults for: {q}\n")
                for r in results[:5]:  # primele 5 rezultate
                    title = await r.inner_text()
                    link_el = await r.evaluate_handle("node => node.parentElement")
                    link = await link_el.get_attribute("href")
                    f.write(f"- {title} ({link})\n")

                print(f"Saved results for: {q}")

        await browser.close()

asyncio.run(main())
Then I run with this command:
python google_search_test_001.py
Saved results for: python automation
Saved results for: playwright tutorial
Saved results for: google search automation
Need to click to accept on browser ... , and some basic result on results.txt file:

Results for: python automation

Results for: playwright tutorial
- Playwright: Fast and reliable end-to-end testing for modern ... 

Sunday, November 30, 2025

News : the xonsh shell language and command prompt.

Xonsh is a modern, full-featured and cross-platform python shell. The language is a superset of Python 3.6+ with additional shell primitives that you are used to from Bash and IPython. It works on all major systems including Linux, OSX, and Windows. Xonsh is meant for the daily use of experts and novices.
The install is easy with pip tool:
python -m pip install 'xonsh[full]'

Python 3.13.0 : mitmproxy - part 001.

Mitmproxy is an interactive, open‑source proxy tool that lets you intercept, inspect, and modify HTTP and HTTPS traffic in real time. It acts as a "man‑in‑the‑middle" between your computer and the internet, making it possible to debug, test, or analyze how applications communicate online.
Why Python?
  • Mitmproxy is built in Python and exposes a powerful addon API
  • You can write custom scripts to automate tasks and traffic manipulation
  • Block or rewrite requests and responses with flexible logic
  • Inject headers or simulate server responses for testing
  • Integrate with other Python tools for advanced automation
  • Intercept and inspect HTTP and HTTPS traffic in real time
  • Modify requests and responses dynamically with Python scripts
  • Block specific hosts or URLs to prevent unwanted connections
  • Inject custom headers into outgoing requests for debugging or control
  • Rewrite response bodies (HTML, JSON, text) using regex or custom logic
  • Log and save traffic flows for later analysis and replay
  • Simulate server responses to test client behavior offline
  • Automate testing of web applications and APIs with scripted rules
  • Monitor performance metrics such as latency and payload size
  • Integrate with other Python tools for advanced automation and analysis
  • Use a trusted root certificate to decrypt and modify HTTPS traffic securely
Let's install:
pip install mitmproxy
Let's see the python script:
# addon.py
from mitmproxy import http
from mitmproxy import ctx
import re

BLOCKED_HOSTS = {
    "hyte.com",
    "ads.example.org",
}

REWRITE_RULES = [
    # Each rule: (pattern, replacement, content_type_substring)
    (re.compile(rb"Hello World"), b"Salut lume", "text/html"),
    (re.compile(rb"tracking", re.IGNORECASE), b"observare", "text"),
]

ADD_HEADERS = {
    "X-Debug-Proxy": "mitm",
    "X-George-Tool": "true",
}

class GeorgeProxy:
    def __init__(self):
        self.rewrite_count = 0

    def load(self, loader):
        ctx.log.info("GeorgeProxy addon loaded.")

    def request(self, flow: http.HTTPFlow):
        # Block specific hosts early
        host = flow.request.host
        if host in BLOCKED_HOSTS:
            flow.response = http.Response.make(
                403,
                b"Blocked by GeorgeProxy",
                {"Content-Type": "text/plain"}
            )
            ctx.log.warn(f"Blocked request to {host}")
            return

        # Add custom headers to outgoing requests
        for k, v in ADD_HEADERS.items():
            flow.request.headers[k] = v

        ctx.log.info(f"REQ {flow.request.method} {flow.request.url}")

    def response(self, flow: http.HTTPFlow):
        # Only process text-like contents
        ctype = flow.response.headers.get("Content-Type", "").lower()
        raw = flow.response.raw_content

        if raw and any(t in ctype for t in ["text", "html", "json"]):
            new_content = raw
            for pattern, repl, t in REWRITE_RULES:
                if t in ctype:
                    new_content, n = pattern.subn(repl, new_content)
                    self.rewrite_count += n

            if new_content != raw:
                flow.response.raw_content = new_content
                # Update Content-Length only if present
                if "Content-Length" in flow.response.headers:
                    flow.response.headers["Content-Length"] = str(len(new_content))
                ctx.log.info(f"Rewrote content ({ctype}); total matches: {self.rewrite_count}")

        ctx.log.info(f"RESP {flow.response.status_code} {flow.request.url}")

addons = [GeorgeProxy()]
Let's run it:
mitmdump -s addon.py
[21:46:04.435] Loading script addon.py
[21:46:04.504] GeorgeProxy addon loaded.
[21:46:04.506] HTTP(S) proxy listening at *:8080.
[21:46:18.547][127.0.0.1:52128] client connect
[21:46:18.593] REQ GET http://httpbin.org/get
[21:46:18.768][127.0.0.1:52128] server connect httpbin.org:80 (52.44.182.178:80)
[21:46:18.910] RESP 200 http://httpbin.org/get
127.0.0.1:52128: GET http://httpbin.org/get
              << 200 OK 353b
[21:46:19.019][127.0.0.1:52128] client disconnect
[21:46:19.021][127.0.0.1:52128] server disconnect httpbin.org:80 (52.44.182.178:80)
Let's see the result:
curl -x http://127.0.0.1:8080 http://httpbin.org/get
{
  "args": {},
  "headers": {
    "Accept": "*/*",
    "Host": "httpbin.org",
    "Proxy-Connection": "Keep-Alive",
    "User-Agent": "curl/8.13.0",
    "X-Amzn-Trace-Id": "Root=1-692c9f0b-7eaf43e61f276ee62b089933",
    "X-Debug-Proxy": "mitm",
    "X-George-Tool": "true"
  },
  "origin": "84.117.220.94",
  "url": "http://httpbin.org/get"
}
This means
The request successfully went through mitmproxy running on 127.0.0.1:8080. Your addon worked: it injected the custom headers (X-Debug-Proxy, X-George-Tool). The httpbin.org echoed back the request details, showing exactly what the server received.

Python 3.13.0 : Tornado - part 001.

Python Tornado is a high‑performance web framework and asynchronous networking library designed for extreme scalability and real‑time applications. Its standout capability is handling tens of thousands of simultaneous connections efficiently, thanks to non‑blocking I/O.
This is an open source project actively maintained and available on tornadoweb.org.

Python Tornado – Key Capabilities

  • Massive Concurrency: Tornado can scale to tens of thousands of open connections without requiring huge numbers of threads.
  • Non‑blocking I/O: Its asynchronous design makes it ideal for apps that need to stay responsive under heavy load.
  • WebSockets Support: Built‑in support for WebSockets enables real‑time communication between clients and servers.
  • Long‑lived Connections: Perfect for long polling, streaming, or chat applications where connections remain open for extended periods.
  • Coroutines & Async/Await: Tornado integrates tightly with Python’s asyncio, allowing developers to write clean asynchronous code using coroutines.
  • Versatile Use Cases: Beyond web apps, Tornado can act as an HTTP client/server, handle background tasks, or integrate with other services.
Tornado setup: The script creates a web server using the Tornado framework, listening on port 8888.
Route definition: A single route /form is registered, handled by the FormHandler class.
GET request: When you visit http://localhost:8888/form, the server responds with an HTML page (form.html) that contains a simple input form.
POST request: When the form is submitted, the post() method retrieves the value of the name field using self.get_argument("name").
Response: The server then sends back a personalized message
Let's see the script:
import tornado.ioloop
import tornado.web
import os

class FormHandler(tornado.web.RequestHandler):
    def get(self):
        self.render("form.html")  # Render an HTML form

    def post(self):
        name = self.get_argument("name")
        self.write(f"Hello, {name}!")

def make_app():
    return tornado.web.Application([
        (r"/form", FormHandler),
    ],
    template_path=os.path.join(os.path.dirname(__file__), "templates")  # <-- aici
    )

if __name__ == "__main__":
    app = make_app()
    app.listen(8888)
    print("Server pornit pe http://localhost:8888/form")
    tornado.ioloop.IOLoop.current().start()

Thursday, October 30, 2025

Python 3.13.0 : xAI A.P.I. with regional endpoint on xai_sdk python package.

Grok is a family of Large Language Models (LLMs) developed by xAI.
Inspired by the Hitchhiker's Guide to the Galaxy, Grok is a maximally truth-seeking AI that provides insightful, unfiltered truths about the universe.
xAI offers an API for developers to programmatically interact with our Grok models. The same models power our consumer facing services such as Grok.com, the iOS and Android apps, as well as Grok in X experience.
If you want to use a regional endpoint, you need to specify the endpoint url when making request with SDK. In xAI SDK, this is specified through the api_host parameter.
Is not free models available for xAI A.P.I.
See this example from the official website:
import os

from xai_sdk import Client
from xai_sdk.chat import user

client = Client(
api_key=os.getenv("XAI_API_KEY"),
api_host="us-east-1.api.x.ai" # Without the https://
)

chat = client.chat.create(model="grok-4")
chat.append(user("What is the meaning of life?"))

completion = chat.sample()

Monday, October 20, 2025

Python Qt6 : tool for remove duplicate files ...

Today I created a Python script with PyQt6 that allows me to remove duplicate files based on three ways of selecting the type of duplicate.
The script also makes an estimate of the execution time...
Because the source code is relatively simple and can be very easily reconstructed with the help of artificial intelligence, I am not adding it to the posts.
Here is what the application looks like with PyQt6.

Saturday, October 18, 2025

Python Qt6 : tool for cutting images ...

Today I made a script that allows adding custom horizontal and vertical sliders to an image and, depending on the custom distance between them, cuts the image into squares of different sizes.

Python Qt6 : tool for renaming files with creation date .

Since this hacking and the crashes... I've always taken screenshots... Today I created a small script that takes files from a folder and renames them with the creation date in this format...yyyyMMdd_HHmmss .
... obviously artificial intelligence helped me.
This is the source code :
import sys
import os
import shutil
from PyQt6.QtWidgets import QApplication, QWidget, QPushButton, QVBoxLayout, QFileDialog, QMessageBox
from PyQt6.QtCore import QDateTime

class FileRenamer(QWidget):
    def __init__(self):
        super().__init__()
        self.setWindowTitle("Redenumire fișiere cu dată și index")
        self.setGeometry(100, 100, 400, 150)

        layout = QVBoxLayout()

        self.button = QPushButton("Selectează folderul și redenumește fișierele")
        self.button.clicked.connect(self.rename_files)
        layout.addWidget(self.button)

        self.setLayout(layout)

    def rename_files(self):
        folder = QFileDialog.getExistingDirectory(self, "Selectează folderul")
        if not folder:
            return

        files = [f for f in os.listdir(folder) if os.path.isfile(os.path.join(folder, f))]
        files.sort()  # Sortează pentru consistență

        for index, filename in enumerate(files, start=1):
            old_path = os.path.join(folder, filename)
            try:
                creation_time = os.path.getctime(old_path)
                dt = QDateTime.fromSecsSinceEpoch(int(creation_time))
                date_str = dt.toString("yyyyMMdd_HHmmss")
                ext = os.path.splitext(filename)[1]
                new_name = f"{date_str}_{index:03d}{ext}"
                new_path = os.path.join(folder, new_name)

                # Evită suprascrierea fișierelor existente
                if not os.path.exists(new_path):
                    shutil.move(old_path, new_path)
            except Exception as e:
                QMessageBox.critical(self, "Eroare", f"Eroare la fișierul {filename}:\n{str(e)}")
                continue

        QMessageBox.information(self, "Succes", "Fișierele au fost redenumite cu succes!")

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

Saturday, October 4, 2025

Friday, September 26, 2025

Python Qt6 : tool for game development with PNG images.

Today, I worked with art artificial intelligence, to create tool for my game development.
I used python and PyQt6 and this tool help me to remove border, resize, split, rename and save images as PNG file type for Godot game engine.

Saturday, August 30, 2025

Python Qt6 : ... 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
...

Thursday, August 21, 2025

Python Qt6 : 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()

Monday, July 21, 2025

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
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']

Sunday, July 13, 2025

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: